For media companies investigating how to incorporate AI into their operations, open chatbots like ChatGPT, Claude, or Google Bard are often a natural starting point. Thanks to OpenAI’s game-changing launch of ChatGPT for public use in 2022, AI has essentially become synonymous with chatbots in the public mind, so it’s unsurprising that’s where many media companies turn first when experimenting with AI.
Open chatbots certainly have useful applications, but they also have some serious limitations. The user experience for these chatbots varies widely. They place a burden on the user to know how to engineer prompts that will generate good results, which can lead to significant user fatigue. Media companies will get more value from AI by going beyond basic chatbots to build capabilities that will deliver better results and a better experience for users.
Creating a better chatbot
The success of any AI-powered chatbot comes down to what’s underneath. The Washington Post has launched an excellent climate chatbot, which works well because they invested in building the underlying functionality from the ground up. They also emphasized providing trustworthy responses because the underlying large-language model synthesizes information from Washington Post articles published since 2016 in their Climate & Environment and Weather sections. The chatbot is also highly controlled and tightly framed to focus on climate coverage, which delivers a better experience than open chatbots.
Building a good chatbot requires many different technologies. First, a chatbot needs to have a solid system prompt behind it that defines what it is and is not supposed to do. Second, the chatbot needs to be based on a fast, performant model, which could include OpenAI’s GPT-4, Google’s BERT, or other large-language models. The platform needs to be quick in order to deliver answers in real time. And finally, the chatbot model needs to be trained to ensure it does what you want it to do.
It’s also important to remember that AI doesn’t have to be synonymous with a chat- or prompt-based interface. Based on the use case, a button, an automated feature, or a call to another application might be more appropriate.
Leveling up with fine tuning and vectors
To truly deliver meaningful applications of AI with significant business value, media organizations should look to fine tuning and vector databases. These advanced capabilities allow chatbots and other AI applications to be customized to meet an organization’s specific needs and operate with a deep understanding of its content base.
Fine tuning trains an AI model to deliver results that are tailored to your requirements. It essentially tells the model to read all of your content and learn exactly what you want it to do and what the results should be. For example, with fine tuning, an AI model can learn to generate headlines in a specific length or style. This can be done even down to the author level, with the model learning how to detect who the content creator is and return a headline or summary in their tone of voice.
Vector databases go a step further by building a knowledge map of all of your content— you could even think of a vector database as a miniature brain that serves as the “memory” for your AI applications. At a basic level, a vector database stores data or content in various formats (a single word, a story, a photo, a video, etc.) and creates a numerical representation of that content. The numbers assigned to each piece of content are used to calculate its distance from other content in terms of relevance. Mapping content relationships in this way enables powerful search and recommendation applications.
To understand fine tuning and vector databases in practical terms, we can look at the example of using AI for content tagging. A general-purpose AI model like GPT can look at a story and identify keywords or topics that could be used for tagging, but it doesn’t understand your specific tagging requirements.
Fine tuning the model will incorporate your tagging requirements. For example, if you have a specific set of approved tags, it will return a result that’s tailored to those needs. A vector database will not only know your whole tag library but will also understand the relationships between tags and identify overlaps that will help with powering search and content recommendations.
It’s an exciting time for AI in the media industry, with new developments emerging every month. Building your own AI capabilities can be daunting, and software vendor offerings for AI vary widely. If you spend some time learning about the possibilities for AI, including chatbots and beyond, you’ll be well positioned to create your AI strategy and identify the technologies and vendors that can help you achieve your goals.
Creativity fuels innovation and expression across various media disciplines. With the advent of generative artificial intelligence (AI) and large language models (LLMs), many question how these technologies will influence human creativity. While generative AI may effectively enhance productivity across sectors, its impact on creative processes remains questioned. New research, Generative AI enhances individual creativity but reduces the collective diversity of novel content, investigates AI’s effect on the creative output of short (or micro) fiction. While the research focuses on short stories, the study examines how generative AI influences the production of creative expression, which has larger implications.
Creative assessment
The study evaluates creativity based on two main dimensions: novelty and usefulness. Novelty refers to the story’s originality and uniqueness. Usefulness relates to its potential to develop into a publishable piece. The study randomly assigns participants to one of three experimental conditions for writing a short story: Human-only, Human with one Generative AI idea, and Human with five Generative AI ideas.
The AI-assisted conditions include three-sentence story ideas to inspire creative narratives. This design allows the researchers to assess how AI-generated prompts affect the creativity, quality, and enjoyment of the stories produced. Both writers and 600 independent evaluators assessed these dimensions, providing a comprehensive view of the stories’ creative merit across different conditions.
Usage and creativity
In the two generative AI conditions, 88.4% of participants used AI to generate an initial story idea. In the “Human with one Gen AI idea” group, 82 out of 100 writers did this, while in the “Human with five Gen AI ideas” group, 93 out of 98 writers did the same. When given the option to use AI multiple times in the “Human with five GenAI ideas” group, participants averaged 2.55 requests, with 24.5% asking for a maximum of five ideas.
The findings from the independent evaluators show that access to generative AI significantly enhances the creativity and quality of short stories. Writers who use AI-generated ideas to produce stories consistently rate higher in creativity and writing quality than those written without AI assistance. This effect was particularly noticeable in the Human with five GenAI ideas condition, suggesting that increasing exposure to AI-generated prompts leads to greater creative output.
However, the study also uncovers notable similarities among stories generated with AI assistance. This suggests that while AI can enhance individual creativity, it also homogenizes creative outputs, diminishing the diversity of innovative elements and perspectives. The benefits of generative AI for individual writers may come at the cost of reduced collective novelty in creative outputs.
Implications for stakeholders
Despite several limitations, the research highlights the complex interplay between AI and creativity across different artistic domains. These limitations restrict the creative task by length (eight sentences), medium (writing), and type of output (short story). Additionally, there is no interaction with the LLM or variation in prompts. Future studies should explore longer and more varied creative tasks, different AI models, and the ethical considerations surrounding AI’s role in creative text and video production. Examining the cultural and economic implications in creative media sectors and balancing innovation with preserving artistic diversity is essential.
Generative AI can enhance human creativity by providing novel ideas and streamlining the creative processes. However, its integration into creative media processes must be thoughtful to safeguard the richness and diversity of artistic expression. This study sets the stage for further exploration into generative AI’s evolving capabilities and ethical implications in fostering creativity across diverse artistic domains. As AI technologies evolve, understanding their impact on human creativity is crucial for harnessing their full potential while preserving the essence of human innovation and expression.
To stand out in the “AI-age,” media companies are emphasizing direct relationships with the audience. We’re also seeing the resurgence of the homepage, the emergence of AI-powered editorial workflows, and an increased need for strong data management. As we wrote last month, this is being driven by the fact that quality is of utmost importance as generative AI drives the cost to produce generic content down to zero and Google search shifts to focus on offering “answers” instead of driving traffic.
Now, we’ll walk through trends we’re seeing in media product management, and how teams are aligning to drive results in this new paradigm.
The ascendancy of product management
As media organizations refocus on delivering content of the highest quality, combined with an excellent user experience (that people want to pay for), the role of the product manager is changing somewhat as various teams try to institute changes on the digital experience.
These changes might be editorial teams creating new workflows, revenue teams adding more ads and popups, engineering teams building fancy bespoke front ends—normal stuff that has been part of media forever. What’s changed somewhat is product management’s share of voice. Do product managers just take orders and make it happen, or can they say no? Who is speaking for the user? Who is advocating for a clean content experience? What makes your subscription stand out?
As direct relationships and the homepage get more important, product management is finding itself in a more strategic position. The challenge is in balancing the needs of discrete teams with the needs of their audience—and the needs of everyone with the needs of the business.
Focus on innovation and fundamentals
Organizations are taking an extremely hard look at where they spend their engineering dollars. These organizations are assessing how much of their team’s work is dedicated to maintenance versus creating new revenue-generating features.
For example, the ability to handle traffic spikes. If they’re doing all the maintenance of keeping the site up for traffic spikes and similar occurrences, leadership are thinking about whether that can be outsourced to a managed platform that specializes in that work and can thus do it more cost-effectively.
This focus on innovation introduces the drive towards open-source. With open source, you can let the community maintain the software, for free. You just customize on top of it.
Those not using open source are burning money and missing out
If the engineering team is celebrating introducing something like Authors and Permissions to the tech stack, it’s time to ask critical questions. These features have been available in open-source CMSes for more than a decade. Why is anyone reinventing the wheel? “We’ll make it ourselves and it’ll be better” is a common trap. Couldn’t something more productive have been done with those engineering hours?
Besides embracing open source, we’re also seeing more consolidation in tech stacks—a broad organization with many distinct properties might be moving from having four CMSes down to just one. This reduces friction from new feature releases and enhances learnings across publications or business units.
The most interesting thing we are seeing in this area is a major spike in contribution back to the open source community in terms of code, best practices, and more. This is perhaps a tacit acknowledgement that content, not technology, is the real differentiator for media organizations.
Headless architecture is losing steam
Headless was all the hotness in engineering for a while. Now we’re seeing media organizations choose monolithic (or “full stack”) implementations. Simply put, the bet on headless hasn’t paid off for many media use cases.
Frequently, the needs of these sites are pretty simple—serving written content to the end user. Most open-source CMSes can power both the front end and the back end. Choosing to develop their own headless front end is choosing to create costly tech debt—and most media engineering teams don’t have money to spare. This change opens up all the time they spent creating and maintaining basic front-end technology for reprioritization towards revenue-generating engineering.
The “desire line” we’re walking
A desire line is an “unplanned route or path (such as one worn into a grassy surface by repeated foot traffic) that is used by pedestrians in preference to or in the absence of a designated alternative (such as a paved pathway).” Frequently it’s because this path is simply the most efficient path between points A and B.
With media products, the desire line is straightforward: the platforms are unreliable sources of traffic, and there isn’t enough money to fund anything but the most efficient paths forward. This is why we are seeing organizations across the industry align on direct, subscriber-based relationships. And, to support these efforts, media organizations are focused on the efficient use of engineering resources via open-source technology. The most exciting part here is that—because we are not all just producers but also consumers of news and media—the reader experience itself is getting better. It has to be better, in order to justify a subscription.
In the fast-paced world of digital publishing, the latest wave of developments in Artificial Intelligence (AI) has emerged as a welcome solution to the organized chaos of ad operations. Yet, despite its transformative potential, many media companies struggle with the adoption of AI technology. Costly implementation, complex integrations, and a shortage of AI-savvy professionals are hurdles slowing adoption to a snail’s pace.
For media executives looking to move faster, the answer is simple: purpose-built AI solutions. Forget everything you know about generic AI technology. The real magic happens with AI solutions specifically built – for a very specific purpose. By embracing a tailored approach, media executives can accelerate AI adoption with purpose-built solutions that deliver immediate value and growth.
But to harness AI’s power, understanding the strategic advantage of purpose-built AI solutions is crucial. These specialized tools can help media companies reduce implementation issues and offer tangible benefits. Let’s explore the common challenges in media operations that custom AI tools can address.
Unpacking the challenges in digital media operations
Operationally, digital publishers have their work cut out for them in today’s digital media ecosystem. Fragmented data, inefficient, manual workflows, and complexity management in ad operations create significant challenges. These issues slow down processes and hinder the ability to quickly adapt to market changes.
This is where a purpose-built AI solution can deliver a strategic advantage over a generic AI tool. Think of a generic AI tool as a Swiss Army knife – versatile but not specialized for any one task. In contrast, a purpose-built AI solution is like a precision scalpel, expertly designed for a specific function, ensuring optimal performance and efficiency in that area. Now, let’s explore how these tailored solutions can specifically address implementation challenges.
Finding and implementing AI solutions involves extensive testing and high costs. However, purpose-built AI sidesteps these challenges with pre-designed functionalities that can be implemented quickly and efficiently. Here’s how these tailored solutions address common implementation hurdles.
Lower implementation costs
The initial investment in AI technology, including hardware, software, and skilled personnel, can be prohibitively expensive. However, purpose-built AI solutions are pre-designed for specific tasks, reducing the need for extensive custom development. This lowers both initial investment and ongoing costs.
Simplified integrations
Integrating AI systems with existing workflows often proves difficult, requiring significant time and resources. But purpose-built solutions are designed to integrate seamlessly with existing workflows and technologies, minimizing the complexity and time required for setup. They offer specific capabilities that streamline the integration process.
Unified data management
Disparate data sources and poor data quality hinder AI performance. According to Theorem’s research, 33% of ad professionals cite a lack of centralized tools as a major pain point. Purpose-built AI solutions consolidate data sources, improving quality and consistency. This unified approach enables more accurate insights, better decision-making, and more effective ad targeting.
User-friendly
There is often a shortage of professionals with the expertise needed to develop, implement, and maintain AI systems. With user-friendly interfaces and automated features, purpose-built AI solutions reduce the dependency on specialized AI talent. This makes it easier for existing staff to utilize and manage the AI system.
Faster deployment
These solutions are designed for specific workflows and processes, which reduces the development cycle, while accelerating deployment, and team training. Organizations can rapidly implement the solution and hit the ground running.
With implementation challenges out of the way, more on the tangible benefits and rapid results purpose-built AI solutions have to offer.
Benefits and strategic growth opportunities
Purpose-built, custom AI solutions offer a number of benefits and opportunities for growth, including:
Immediate value
With an AI solution specifically designed to automate ad operations, implementation and adoption shift from labor-intensive to quick and easy. This allows media companies to quickly realize productivity gains by tapping into ready-to-launch solutions almost instantly.
Scalability
These solutions are built to scale seamlessly with the company’s growth. As your business expands and evolves, purpose-built AI solutions can adapt to new requirements and increased workloads. This flexibility ensures sustained performance and supports long-term success without the need for constant reinvestment in new technologies.
Cost-effectiveness
Purpose-built AI solutions offer significant cost benefits. Processes are streamlined, makegoods and errors decrease. And, as a result, implementation and operational costs are reduced.
New revenue generation
Purpose-built AI solutions can identify new revenue streams and optimize existing ones. For example, an AI solution built specifically to increase engagement through more targeted, personalized advertising can generate more ad revenue. Or consider the impact of a solution designed to predict what type of content will be popular in the future. This solution would allow publishers to focus on creating content that is more likely to attract and retain users, driving more revenue.
Maintaining a competitive edge in digital media’s turbulent ecosystem today requires the ability to act swiftly and strategically. Understanding the benefits is just the beginning, now it’s time to take action.
Practical steps to drive quick adoption of purpose-built AI solutions
Implementing purpose-built AI solutions can be streamlined with the right approach. By following these steps, your organization can swiftly integrate AI technology and start reaping the benefits.
Start by identifying key areas where AI can have the most impact with a thorough assessment of current processes.
Prioritize those that promise the quickest wins and greatest value. Next, research and select AI solutions with capabilities that align with your business goals and workflow challenges.
Measure the potential impact on data, infrastructure and governance to ensure smoother AI adoption.
Identify training needs and assess any ethical considerations.
Carefully evaluate vendors based on functionality, ease of integration, and proven success.
Begin with a pilot implementation, test the solution in a controlled environment, gather feedback, and make necessary adjustments before a full rollout.
Investing in a purpose-built AI solution is a long-term strategy that yields ongoing benefits as the technology evolves. Much like choosing a tailored suit that fits perfectly vs a suit off the rack, it offers the precise fit and functionality needed to drive strategic growth. Those who embrace it now stand to reap immediate productivity gains, scalability, and cost-effectiveness.
The data is clear: a chasm exists between what traditional news offers and what younger audiences crave. Decades of research haven’t bridged this gap, and proposed solutions often fall short. Blumler and McQuail’s (1970) Need for Gratification Theory suggests people use media to fulfill specific desires. You do have to wonder if the problem a mismatch in needs. Perhaps traditional news fails to satisfy younger generations’ hunger for in-depth analysis or a more positive outlook, driving them to seek information elsewhere. This disconnect demands a fresh approach – one that bridges the gap and fosters genuine connection.
A Spring 2023 Harvard Youth Poll reveals that young Americans prioritize economic concerns like inflation, healthcare, housing, and job availability, alongside social justice and environmental issues like reproductive rights, climate change, and immigration. This focus mirrors global trends. However, traditional media coverage often falls short on these topics. The rise of “alternative platforms” and the demand for short, relatable, and authentic content signals a broader shift in news consumption. Furthermore, Gen X’s declining interest and the perception of traditional media content as distant, pedantic, and delivered on outdated platforms underscore the need to completely rethink how we deliver news.
Despite the challenges, a bright future awaits news media built on growth and audience engagement. The key lies in a shift towards hyper-local coverage. This doesn’t mean abandoning national and global news. Rather, it means prioritizing content that resonates with the local audience. Imagine relatable journalists delivering stories on local issues through engaging formats like social media posts, listicles, explainers, and high-quality video content. This focus has demonstrably built loyal readership and increased audience size for news organizations around the country.
A decline in news interest among Gen X and Millennials, as reported by the Pew Research Center, and a growing preference for authenticity in news presenters, according to Reuters 2022 Digital News Report, paint a clear picture of the current news consumption landscape. Addressing these audience preferences and tailoring content to local issues can foster greater trust and engagement with news media.
The solution seems straightforward: connect the dots between state or regional events and their impact on local communities. However doing this effectively is harder than it seems. News outlets must transition from high-level reporting to a more responsible and objective approach. This means translating complex issues into clear, concise explanations that highlight the specific impact on people’s daily lives. For example, a national story on rising gas prices might be tailored locally to show how much transportation costs have increased in your city and how residents are coping.
Take, for instance, the Miami Herald’s recent spring climate change article on sea levels rising. This article uses multimedia storytelling to explore the rising sea level’s impact on Miami, a city particularly vulnerable to coastal flooding. The article features data insights from local scientists and researchers and explains how climate change is affecting the city’s infrastructure and communities. By connecting the global threat of climate change to the specific challenges faced by Miami, this article highlights the urgency of addressing sea level rise. This focus on local impacts can potentially empower younger audiences to engage with the issue in their city, and “actionability” is something that is particularly resonant with this group.
As we navigate the evolving media landscape and changing news consumption habits, traditional media must redefine its role. It should not only inform, but also serve as a vital resource for today’s and tomorrow’s generations. This shift is crucial for both local and national news outlets as they strive to bridge the generational gap and earn trust.
Younger audiences increasingly seek news that offers practical and useful information for their daily lives. This demand highlights the need for journalism to evolve beyond reporting. News organizations must provide guidance and resources on various topics, offering actionable insights that empower readers.
The challenge lies in transforming news into actionable resources that not only inform but also empower and engage audiences. Organizations like NPR have shown the way by expanding their coverage to include comprehensive guides and interactive tools on topics like financial planning and mental health resources. These resources equip readers to make informed decisions and take meaningful action based on factual reporting.
By providing practical resources alongside factual reporting, news organizations can empower readers with deeper understanding and the tools they need to take action. This ensures content remains informative while upholding journalistic integrity. In an era where accessible knowledge and meaningful impact are highly valued, this approach fosters informed decision-making and strengthens audience engagement.
Embracing hyper-local coverage and authentic storytelling will enable news organizations to bridge the chasm that separates them from Gen X and Millennials. Focusing on issues that directly impact these audiences’ daily lives fosters a sense of relevance and connection. Authentic voices, relatable formats, and clear explanations that empower readers with actionable insights will cultivate trust and engagement. This also translates to a more valuable audience for advertisers, potentially leading to increased revenue streams.
In essence, a focus on local issues and a commitment to genuine storytelling that makes issues personally relevant represents a strategic investment in the future of news. By prioritizing content that resonates with younger generations, news organizations can not only ensure their long-term sustainability but also cultivate a more engaged and informed citizenry. A future where news is relevant, sustainable, and fosters meaningful connections between audiences and journalists is entirely within reach.
The Tokyo 2020 Olympics heralded the digital transformation of Games coverage. Fans no longer need to stay glued to the TV to see what they want. Nor do they have to or solely rely on news titles to keep them up to speed on the big picture. Younger audiences in particular consumed highlight clips rather than watching linear coverage and followed their favorite athletes on social media to gain a more in-depth, behind-the-scenes insights. In fact, the IOC clocked6.1 billion digital engagements on Olympic social media channels during the competition.
Four years later, as we approach the Paris event, these trends are again set to influence international consumption of Olympic content. News and sports organizations have already learned from these new social media-inspired audience dynamics, with live blogs offering a valuable means of competing with social channels for mainstream media share of voice. The delivery of real-time, snackable content that enables interactivity will continue to be essential in 2024 Olympics coverage. Still, there are also new, broader issues to address to capture audience share – particularly among Gen Z, or ‘the purpose generation‘.
Beyond the sport
Olympics coverage is no longer simply about sport. Athletes and governments have always used the Games to spotlightpertinent social and political issues, from Black Power and anti-apartheid to LGBTQI. Now, younger generations increasingly see the potential for activism from the sidelines. Environmental sustainability and the participation of transgender athletes have emerged as important topics for Paris 2024. There’s also likely to be an impact from the substantial political tension caused by the Russia-Ukraine and Israel-Hamas conflicts on the event. Newsrooms will need to have one eye on the sport, and one eye on the bigger picture to ensure audience engagement.
News providers covering the Olympics must, therefore, up their game (pun intended), adopting audience-first strategies that cater to theneeds of Gen Z and beyond to ensure they compete in the race against social media for audience share. They must deliver authentic, personalized, and interactive content that addresses both the event and the wider issues surrounding it.
Incorporating multiple, intertwined storylines to provide greater depth and insight and encourage engagement will be vital. By doing so, they can boost traffic, dwell time or subscription conversions and encourage brands keen for Olympics association to spend money on advertising.
Prepare for the marathon, not the sprint
However, with the Games lasting two weeks and spanning 320 different competitions across 32 sports, it’s no easy feat to keep audiences up to date on the sports that interest them, provide athlete and behind-the-scenes insights and tune into the wider news stories that intersect with the Olympics. Newsrooms must, therefore, box clever when it comes to delivering on audience expectations.
Live blogs offer an important starting block to help reach this goal. They allow newsrooms to create an engaging and responsive experience tailored to the audience’s preferences by offering real-time updates, encouraging active participation, and enabling a multimedia-rich format. But live blogs can also go beyond real-time news to deliver much more.
Curated content to meet multiple audience needs
The beauty of the live blog format for long events such as the Olympics is that it allows content to be curated, drawing on a range of mixed media to tell the wider story and showcasing numerous perspectives in easily digestible snippets. From integrating Q&As with athletes and coaches for greater depth of insight to fans’ social media posts, multimedia clips of key moments or retrospective and contextual news bits relating to the environmental, political and social issues surrounding the games, live blogs can effectively serve a wide range of audience expectations.
The 2022 European Championships ably demonstrated how live blogs can communicate complex event information in simple terms for spectators, volunteers and employees. From rain delays and available transportation to coverage of medal winners, funny anecdotes and heart-wrenching athlete stories, reporters delivered both range and depth of coverage, harnessing the live blog’s visual storytelling power to share close to 600 photos of what made the event so unique. Custom tags allowed each post to be categorized so that users could easily search for and access the information they wanted.
User-generated content (UGC) creates a more engaging and inclusive narrative beyond just text. Surveys, polls, unique social media hashtags, and live comment blocks all enable a two-way flow of information. Stufffrequently uses this to good effect in their live blog coverage, giving its passionate sports community the chance to engage on topics such as the All Blacks World Cup Squad Announcement, and the team’s return home. This involves audiences in the reporting process and establishes a sense of community to strengthen the media-audience relationship.
Live blogs also allow individual journalist and editorial styles to shine through, creating further audience bonds. We see many young journalists creating social-style videos to tell stories, with their personalities influencing how viewers consume content. DER SPIEGEL’s reporters demonstrated the power of personality intheir coverage of the FIFA Women’s World Cup in 2023, expressing personal opinions, cracking jokes and reacting with emojis in a lively dialogue. This gives the audience a deeper understanding of the people behind the content, injecting personality and making it more relatable and authentic.
On your mark, get set, go!
The evolution of Olympics coverage reflects the changing preferences of audiences, particularly younger generations. As we look forward to the Paris 2024 Olympics, it’s clear that news and sports organizations must continue to adapt to digital and social media consumption to compete. In order to capture and maintain audience engagement, a focus on delivering real-time, interactive, and curated content that addresses both the sporting events and the broader social, political, and environmental issues surrounding the Games is crucial.
Live blogs have emerged as a valuable tool for providing both real-time and in-depth coverage while catering to diverse audience needs and preferences. As newsrooms prepare for the marathon-like coverage of the two-week event, prioritizing audience-first strategies will be essential to ensure a meaningful and immersive Olympic experience for all. Leveraging live blogs during the Games enables publishers to inform, educate, engage, and connect with audiences on a new level.
Last month, I co-led a week-long journalism program during which we visited 16 newsrooms, media outlets and tech companies in New York. This study tour provided an in-depth snapshot of the biggest issues facing the media today and offered insights into some of the potential solutions publishers are exploring to address them.
We met with everyone from traditional media players – like The New York Times, Associated Press, CBS and Hearst – to digital providers such as Complex Media and ProPublica, as well as conversations with academics and policy experts. Based upon these visits and conversations, here are four key takeaways about the state of media and content publishing today.
1. Hands-on AI experience matters
Not surprisingly, AI dominated many conversations. Although recent research shows the American public is both skeptical and surprisingly unaware of these tools, the emergence of Generative AI – and the discussions around it – are impossible to ignore.
One mantra oft repeated throughout the week was that everyone in the media will need to be conversant with AI. Despite this, research has shown that many newsrooms are hesitant about adopting these technologies. Others, however, are taking a more proactive approach. “I like playing offense, not defense, Aimee Rinehart, Senior Product Manager AI Strategy at the Associated Press, told us. “Figure out how the tools work and your limits.”
With many media companies having to do more with less, AI can help improve workflows, support labor-intensive work like investigative journalism, as well as streamline and diversify content creation and distribution. By harnessing these AI-powered functions, smaller outlets may benefit the most, given the efficiencies these resource-strapped players may be able to unlock.
Reporting on AI is also an emerging journalistic beat. This is an area more newsrooms are likely to invest in, given AI’s potential to radically reshape our lives. As Hilke Schellmann, an Emmy‑award winning investigative reporter and journalism professor at NYU, told us “we used to hold powerful people to account, now we have to add holding AI accountable.”
Echoing Schellmann’s sentiments, “every journalist should be experimenting with AI,” one ProPublica journalist said. “We owe it to our audience to know what this is capable of.”
2. Demonstrating distinctiveness and value is imperative
One fear of an AI-driven world is that traffic to publishers will tank as Generative Search, and tools like ChatGPT, remove the need for users to visit the sites of creators and information providers. In that environment, distinctiveness, trustworthy and fresh content becomes more valuable than ever. “You need to produce journalism that gives people a reason to show up,” says Ryan Knutson, co-host of The Wall Street Journal’s daily news podcast, The Journal.
In response, publishers will need to demonstrate their expertise and unique voice. That means leaning more into service journalism, exclusives, and formats like explainers, analysis, newsletters, and podcasts.
Bloomberg’s John Authers, exemplifies this in his daily Points of Return newsletter. With more than three decades of experience covering markets and investments, he brings a longitudinal and distinctive human perspective to his reporting. Alongside this, scoops still matter, Authers suggests. After all, “journalism is about finding out something other people don’t know,” he says.
Media players also need to make a more effective case as to why original content needs to be supported and paid for. As Gaetane Michelle Lewis, SEO leader at the Associated Press, put it, “part of our job is communicating to the audience what we have and that you need it.”
For a non-profit like ProPublica that means demonstrating impact. They publish three impact reports a year, and their Annual Report highlights how their work has led to change at a time when “many newsrooms can no longer afford to take on this kind of deep-dive reporting.”
“Our North Star is the potential to make a positive change through impact,” Communications Director, Alexis Stephens, said. And she emphasized how “this form of journalism is critical to democracy.”
The New York Times’ business model is very different but its publisher, A.G. Sulzberger, has similarly advocated for the need for independent journalism. As he put it, “a fully informed society not only makes better decisions but operates with more trust, more empathy, and greater care.”
Given the competition from AI, streaming services, and other sources of attention, media outlets will increasingly need to advocate more forcefully for support through subscriptions, donations, sponsorships, and advertising. In doing this, they’ll need to address what sets them apart from the competition, and why this matters on a wider societal level.
“This is a perilous time for the free press,” Sulzberger told The New Yorker last year. “That reality should animate anyone who understands its central importance in a healthy democracy.”
3. Analytics and accessibility go hand in hand
Against this backdrop, finding and retaining audiences is more important than ever. However, keeping their attention is a major challenge. Data from Chartbeat revealed that half the audiences visiting outlets in their network stay on a site for fewer than 15 seconds.
This has multiple implications. From a revenue perspective, this may mean users aren’t on a page long enough for ad impressions to count. It also challenges outlets to look at how content is produced and presented.
In a world where media providers continue to emphasize growing reader revenues, getting audiences to dig deeper and stay for longer, is essential. “The longer someone reads, the more likely they are to return,” explained Chartbeat’s CMO Jill Nicolson.
There isn’t a magic wand to fix this. Tools for publishers to explore include compelling headlines, effective formats, layout, and linking strategies. Sometimes, Nicolson said, even small modifications can make all the difference.
These efforts don’t just apply to your website. They apply to every medium you use. Brendan Dunne of Complex Media referred to the need for “spicy titles” for episodes of their podcasts and YouTube videos. Julia D’Apolito, Associate Social Editor at Hearst Magazines, shared how their approach to content might be reversed. “We’ve been starting to do social-first projects… and then turning them into an article,” she said, rather than the other way round.
Staff at The New York Times also spoke about the potential for counter-programing. One way to combat news fatigue and avoidance is to shine a light on your non-news content. The success of NYT verticals such as Cooking, Wirecutter, and Games shows how diversifying content can create a more compelling and immersive proposition, making audiences return more often.
Lastly, language and tone matters. As one ProPublica journalist put it, “My editor always says pretend like you’re writing for Sesame Steet. Make things accurate, but simple.” Reflecting on their podcasts, Dunne also stresses the need for accessibility. “People want to feel like they’re part of a group chat, not a lecture,” he said.
Fundamentally, this also means being more audience-centric in the way that stories are approached and told. “Is the angle that’s interesting to us as editors the same as our audiences?” Nicolson asked us. Too often, the data would suggest, it is not.
4. Continued concern about the state of local news
Finally, the challenges faced by local news media, particularly newspapers, emerged in several discussions. Steven Waldman, the Founder and CEO of Rebuild Local News, reminded us that advertising revenue at local newspapers had dropped 82% in two decades. The issue is not “that the readers left the papers,” he said, “it’s that the advertisers did.”
For Waldman, the current crisis is an opportunity not just to “revive local news,” but also to “make better local news.” This means creating a more equitable landscape with content serving a wider range of audiences and making newsrooms more diverse. “Local news is a service profession,” he noted. “You’re serving the community, not the newsroom.”
According to new analysis, the number of partisan-funded outlets designed to appear like impartial news sources (so-called “pink slime” sites) now surpasses the number of genuine local daily newspapers in the USA. This significantly impacts the news and information communities receive, shaping their worldviews and decision-making.
Into this mix, AI is also rearing its ugly head. While it can be hugely beneficial for some media companies—“AI is the assistant I prayed for,” saysParis Brown, associate editor of The Baltimore Times. However, it can also be used to fuel misinformation, accelerating pink slime efforts.
“AI is supercharging lies,” one journalist at ProPublica told us, pointing to the emergence of “cheap fakes” alongside “deep fakes,” as content which can confirm existing biases. The absence of boots on the ground makes it harder for these efforts to be countered. Yet, as Hilke Schellmann, reminded us “in a world where we are going to be swimming in generative text, fact-checking is more important [than ever].”
This emerging battleground makes it all the more important for increased funding for local news. Legislative efforts, increased support from philanthropy, and other mechanisms can all play a role in helping grow and diversify this sector. Steven Waldman puts it plainly: “We have to solve the business model and the trust model at the same time,” he said.
All eyes on the future
The future of media is being written today, and our visit to New York provided a detailed insight into the principles and mindsets that will shape these next few chapters.
From the transformative potential of AI, to the urgent need to demonstrate distinctiveness and value, it is clear that sustainability has to be rooted in adaptability and innovation.
Using tools like AI and Analytics to inform decisions, while balancing this with a commitment to quality and community engagement is crucial. Media companies who fail to harness these technologies are likely to get left behind.
In an AI-driven world, more than ever, publishers need to stand out or risk fading away. Original content, unique voices, counter-programming, being “audience first,” and other strategies can all play a role in this. Simultaneously, media players must also actively advocate for why their original content needs to be funded and paid for.
Our week-long journey through the heart of New York’s media landscape challenged the narrative that news media and journalism are dying. It isn’t. It’s just evolving. And fast.
The fediverse buzz continues to grow, with articles highlighting the potential to revolutionize the digital landscape. Proponents say it’s similar to the Internet’s early days, before Big Tech platforms built their algorithmic fiefdoms. Instead, the fediverse is about interoperability and flexibility.
Media companies are always on the lookout for ways to attract new audiences and engage more meaningfully with their readers. And – given Google’s experimentation with AI answers and social sites “distancing themselves from news” – finding new routes to audience development has become an increasing imperative.
The decentralized nature of the fediverse offers a compelling alternative to traditional search and social. Importantly, this approach allows media companies to retain their direct relationship with audiences, which removes the dependency on social and big-tech platforms for reaching new people.
Unlike traditional social media platforms that operate within closed ecosystems, fediverse represents a decentralized network of interconnected servers and platforms. It comprises a federation of independent servers, each hosting its social media platform.
These platforms, which range from microblogging to image sharing to video hosting, communicate using standard protocols. Their interoperability allows people on different servers to interact seamlessly. The fediverse decentralizes media companies by enabling them to distribute their content across interconnected servers and platforms rather than relying on a single, centralized platform.
Emphasis on choice and control
Unlike centralized platforms, where a single server owned by the platform provider stores user data and content, fediverse lets people choose their server. This server is selected based on individual preferences regarding privacy, content moderation, and community guidelines. This decentralized approach empowers audiences by putting them in charge of their online experience. It also mitigates concerns about data ownership and platform censorship. For media companies, this translates into an environment where people are more likely to engage with content they trust and have control over.
Encouraging diversity and inclusivity
The fediverse enables people to connect across different platforms and communities within the federation. For example, a user on a microblogging platform can follow and interact with users on a video hosting platform. This functionality breaks down the barriers that typically separate content and conversations on traditional social media platforms. This cross-platform interaction fosters a rich tapestry of ideas, perspectives, and content, creating a more vibrant and dynamic online ecosystem. Media companies can leverage this aspect of fediverse to reach diverse audiences actively seeking varied content.
Organic and community-driven engagement
In contrast to the centralized model, where platform algorithms often dictate content visibility and user interactions, fediverse promotes a more organic and community-driven approach. Users have greater control over their timelines and content visibility, allowing for a more personalized and authentic online experience.
This user-centric design aligns with evolving expectations of digital privacy and autonomy, resonating with individuals seeking alternatives to mainstream social media platforms. Media companies can benefit from this by creating content that naturally finds its way to interested audiences without algorithmic interference.
Media companies test the fediverse
At least two digital media companies are exploring the fediverse to gain more control over their referral traffic and onsite audience engagement. The Verge and 404 Media are building new functions that allow them to simultaneously distribute posts on their sites and federated platforms like Threads, Mastodon, and Bluesky. Replies to those posts on those platforms become comments on their sites.
This functionality means people from different platforms can interact with the content without creating individual accounts for each platform. For media companies, this interoperability can significantly enhance audience reach and engagement.
Advantages for media companies using the fediverse
Usability and interoperability are ideal for enhancing user experience. This approach enables seamless communication between platforms, ensuring autonomy, and providing robust content control.
Interoperability ensures that different platforms can communicate using common protocols like ActivityPub. This allows people to interact with content across various platforms seamlessly, thus creating a unified and interconnected ecosystem.
User autonomy empowers people to select their servers (instances) based on their preferences for privacy, moderation, and community guidelines, offering greater freedom and reducing the dominance of any single platform.
Content control enables media companies to host their servers or collaborate with trusted ones, giving them direct control over content distribution and audience engagement. Therefore, it mitigates risks associated with algorithm changes or policy shifts on major social media platforms.
Cross-platform interaction allows content like a media company’s article shared on one platform to receive comments, likes, and shares from users on other platforms, broadening reach and engagement without being confined to a single platform.
Community-driven moderation decentralizes content moderation, allowing it to occur at the community or server level. Media companies can set moderation policies to ensure their content meets their standards and audience expectations.
Enhanced privacy through decentralization gives media companies more control over their data and privacy settings, protecting user data from being exploited by large platforms.
Although federated platforms have smaller user bases than the larger walled gardens like Facebook and X, they offer significant audiences for media companies. Federating sites allow media companies to tap into the growing demand for decentralized, user-centric platforms, attracting new audiences and fostering a more loyal and engaged user base.
Federated platforms offers the potential for a fundamental shift in how media companies interact with their audiences. Media companies that experiment with the fediverse can initiate engagement and have an opportunity to build stronger, more direct connections with their audiences.
These days, digital media companies are all trying to figure out how to best incorporate AI into their products, services and capabilities, via partnerships or by building their own. The goal is to gain a competitive edge as they tailor AI capabilities to their audiences, subscribers and clients’ specific needs.
By leveraging proprietary Large Language Models (LLMs) digital media companies have a new tool in their toolboxes. These offerings offer differentiation and added value, enhanced audience engagement and user experience. These proprietary LLMs also set them apart from companies that are opting for licensing partnerships with other LLMs, which offer more generalized knowledge bases and draw from a wide range of sources in terms of subject matter and quality.
A growing number of digital media companies are rolling out their own LLM-based generative AI features for search and data-based purposes to enhance user experience and create fine-tuned solutions. In addition to looking at several of the offerings media companies are bringing to market, we spoke to Dow Jones, Financial Times and Outside Inc. about the generative AI tools they’ve built and explore the strategies behind them.
Media companies fuel generative AI for better solutions
Digital media companies are harnessing the power of generative AI to unlock the full potential of their own – sometimes vast amounts – of proprietary information. These new products allow them to offer valuable, personalized, and accessible content to their audiences, subscribers, customers and clients.
Take for example, Bloomberg, which released a research paper in March detailing the development of its new large-scale generative AI model called BloombergGPT. The LLM was trained on a wide range of financial data to assist Bloomberg in improving existing financial natural language processing (NLP) tasks, such as sentiment analysis, named entity recognition, news classification, and question answering, among others. In addition, the tool will help Bloomberg customers organize the vast quantities of data available on the Bloomberg Terminal in ways that suit their specific needs.
Launched in beta June 4, Fortune partnered with Accenture to create a generative AI product called Fortune Analytics. The tool delivers ChatGPT-style responses based on 20 years of financial data from the Fortune 500 and Global 500 lists, as well as related articles, and helps customers build graphic visualizations.
Generative AI helps customers speed up processes
A deeper discussion of how digital media companies are using AI provides insights to help others understand the potential to leverage the technology for their own needs. Dow Jones, for example uses Generative AI for a platform that helps customers meet compliance requirements.
Dow Jones Risk Compliance is a global provider of risk and compliance solutions across banks and corporations which helps organizations perform checks on their counterparties. They do that from the perspective of complying with anti-money laundering regulation, anti-corruption regulation, looking to also mitigate supply chain risk and reputational issues. Dow Jones Risk Compliance provides tools that allow customers to search data sets and help manage regulatory and reputational risk.
In April, Dow Jones Risk & Compliance launched an AI-powered research platform for clients that enables organizations to build an investigative due diligence report covering multiple sources in as little as five minutes. Called Dow Jones Integrity Check, the research platform is a fully automated solution that goes beyond screening to identify risks and red flags from thousands of data sources.
The planning for Dow Jones Integrity Check goes back a few years, as the company sought to provide its customers with a quicker way to do due diligence on their counterparties, Joel Lange, executive Vice President and General Manager, Risk and Research at Dow Jones explained.
Lange said that Dow Jones effectively built a platform which automatically creates a report for customers on a person or company, using technology from AI firm Xapien. It brings together Dow Jones’ data that is plugged into other data sets, corporate registrar information, and wider web content. It then leverages the platform’s Generative AI capability to produce a piece of analysis or a report.
Dow Jones Risk & Compliance customers use their technology to make critical, often complex, business decisions. Often the data collection process can be incredibly time consuming, taking days if not weeks.
The new tool “provides investigations, teams, banks and corporations with initial due diligence. Essentially it’s a starting point for them to conduct their due diligence, effectively automating a lot of that data collection process,” according to Lange.
Lange points out that the compliance field is always in need of increased efficiency. However, it carries with it great risk to reputation. Dow Jones Integrity Check was designed to reshape compliance workflows, creating an additional layer of investigation that can be deployed at scale. “What we’re doing here is enabling them to more rapidly and efficiently aggregate, consolidate, and bring information to the fore, which they can then analyze and then take that investigation further to finalize an outcome,” Lange said.
Regardless of the quality of the generated results, most experts believe that it is important to have a human in the loop in order to maintain content accuracy, mitigate bias, and enhance the credibility of the content. Lange also said that it’s critical to have “that human in the loop to evaluate the information and then to make a decision in relation to the action that the customer wants to take.”
In recent months, digital media companies have been launching their own generative AI tools that allow users to ask questions in natural language and receive accurate and relevant results.
The Associated Press created Merlin, an AI-generated search tool that makes searching the AP archive more accurate. “Merlin pinpoints key moments in our videos to exact second and can be used for older archive material that lacks modern keywords or metadata,” explained AP Editor in Chief Julie Pace at The International Journalism Festival in Perugia in April.
Outside’s Scout: AI search with useful results
Chatbots have become a popular form of search. Originally pre-programmed and only able to answer select questions included in their programming, chatbots have evolved and increased engagement by providing a conversational interface. Used for everything from organizing schedules and news updates to customer service inquiries, Generative AI-based chatbots assist users in finding information more efficiently across a wide range of industries.
Much like The Guardian, The Washington Post, The New York Times and other digital media organizations that blocked OpenAI from using their content to power artificial intelligence, Outside CEO Robin Thurston explained that Outside Inc. wasn’t going to let third parties scrape their platforms to train LLM models.
Instead, they looked at leveraging their own content and data. “We had a lot of proprietary content that we felt was not easily accessible. It’s almost what I’d call the front page problem, which is you put something on the front page and then it kind of disappears into the ether,” Thurston said.
“We asked ourselves: How do we create something leveraging all this proprietary data? How do we leverage that in a way that really brings value to our user?” Thurston said. The answer was Scout, Outside Inc.’s AI search assistant. Scout is a custom-developed chatbot.
The company could see that generative AI offered a way to make that content accessible and even more useful to its readers. Outside had a lot of evergreen content that wasn’t adding value once it left the front page. Their brands inspire and inform audiences about outdoor adventures, new destinations and gear – a lot of which is evergreen and proprietary content that still had value if it could easily be surfaced by its audience. The chat interface allows their content to continue to be accessible to readers after it is no longer front and center on the website.
Scout gives users a summary answer to their question, leveraging Outside Inc’s proprietary data, and surfaces articles that it references. “It’s just a much more advanced search mechanism than our old tool was. Not only does it summarize, but it then returns the things that are most relevant,” he explained.
Additionally, Outside Inc’s old search function worked by each individual brand. Scout searches across the 20+ properties owned by the parent company which include Backpacker, Climbing, SKI Magazine, and Yoga Journal, among others. Scout brings all of the results together, from the 20+ different Outside brands, from the best camping destinations, to the best trails, outdoor activities for the family, gear, equipment and food all in one result.
One aspect that sets Outside Inc.’s model apart is their customer base, which differs from general news media customers. Outside’s customers engage in a different type of interaction, not just a quick transactional skim of a news story. “We have a bit of a different relationship in that they’re not only getting inspiration from us, which trip should I take? What gear should I buy? But then because of our portfolio, they’re kind of looking at what’s next,” Thurston said.
It was important to Thurston to use the LLM in a number of different ways, so Outside Inc launched a local newsletter initiative with the help of AI. “On Monday mornings we do a local running, cycling and outdoor newsletter that goes to people that sign up for it, and it uses that same LLM to pick what types of routes and content for that local newsletter that we’re now delivering in 64,000 ZIP codes in the U.S.”
Thurston said they had a team working on Scout and it took about six months. “Luckily, we had already built a lot of infrastructure in preparation for this in terms of how we were going to leverage our data. Even for something like traditional search, we were building a backend so that we could do that across the board. But this is obviously a much more complicated model that allows us to do it in a completely new way,” he said.
Connecting AI search to a real subscriber need
In late March, The Financial Times released its first generative AI feature for subscribers called Ask FT. Like Scout, the chat-based search tool allows users to ask any question and receive a response using FT content published over the last two decades. The feature is currently available to approximately 500 FT Professional subscribers. It is powered by the FT’s own internal search capabilities, combined with a third-party LLM.
The tool is designed to help users understand complicated issues or topics, like Ireland’s offshore energy policy, rather than just searching for specific information. Ask FT searches through Financial Times (FT) content, generates a summary and cites the sources.
“It works particularly well for people who are trying to understand quite complex issues that might have been going on over time or have lots of different elements,” explained Lindsey Jayne, the chief product officer of the Financial Times.
Jayne explained that they spend a lot of time understanding why people choose the FT and how they use it. People read the FT to understand the world around them, to have a deep background knowledge of emerging events and affairs. “With any kind of technology, it’s always important to look at how technology is evolving to see what it can do. But I think it’s really important to connect that back to a real need that your customers have, something they’re trying to get done. Otherwise it’s just tech for the sake of tech and people might play with it, but not stick with it,” she said.
Trusted sources and GenAI attribution
Solutions like those from Dow Jones, FT and Outside Inc. highlight the power of a brand with a trusted audience relationship to create deep, authentic relationships built on reliability and credibility. Trusted media brands are considered authoritative because their content is based on credible sources and facts, which ensures accuracy.
Currently, generative AI has demonstrated low accuracy and poses challenges to sourcing and attribution. Attribution is a central feature for digital media companies who roll out their own generative AI solutions. For Dow Jones compliance customers, attribution is critical to customers, to know if they’re going to make a decision based on information that is available in the media, according to Lange.
“They need to have that attributed to within the solution so that if it’s flowing into their audit trails or they have to present that in a court of law, or if they would need to present it to our internal audit, the attribution is really key. (Attribution) is going to be critical for a lot of the solutions that will come to market,” he said. “The attribution has to be there in order to rely on it for a compliance use case or really any other use case. You really need to know where that fact or that piece of information or data actually came from and be able to source it back to the underlying article.”
The Financial Times’ generative AI tool also offers attribution to FT articles in all of its answers. Ask FT pulls together lots of different source material, generates an answer, and attributes it to various FT articles. “What we ask the large language model to do is to read those segments of the articles and to turn them into a summary that explains the things you need to know and then to also cite them so that you have the opportunity to check it,” Jayne said.
They also ask the FT model to infer from people’s questions when it should be searching from. “Maybe you’re really interested in what’s happened in the last year or so, and we also get the model to reread the answer, reread all of the segments and check that, as kind of a guard against hallucination. You can never get rid of hallucination totally, but you can do lots to mitigate it.”
The Financial Times is also asking for feedback from the subscribers using the tool. “We’re literally reading all of the feedback to help understand what kinds of questions work, where it falls down, where it doesn’t, and who’s using it, why and when.”
Leaning into media strengths and adding a superpower
Generative AI seems to have created unlimited opportunities and also considerable challenges, questions and concerns. However it is clear that an asset many media companies possess is a deep reservoir of quality content and it is good for business to extract the most value from the investment in its creation. Leveraging their own content to train and program generative AI tools that serve readers seems like a very promising application.
In fact, generative AI can give trustworthy sources a bit of a super power. Jayne from the FT offered the example of scientists using the technology to read through hundreds of thousands of research papers and find patterns in a process that would otherwise take years to read in an effort to make important connections.
While scraped-content LLMs pose risks to authenticity, accuracy and attribution, proprietary learning models offer a promising alternative.
As Jayne put it, “The media has “an opportunity to harness what AI could mean for the user experience, what it could mean for journalism, in a way that’s very thoughtful, very clear and in line with our values and principles.” At the same time, she cautions that we shouldn’t be “getting overly excited because it’s not the answer to everything – even though we can’t escape the buzz at the moment.”
We are seeing many efforts bump up against the limits of what generative AI is able to do right now. However, media companies can avoid some of generative AI’s current pitfalls by employing the technology’s powerful language prediction, data processing and summarization capabilities while leaning into their own strengths of authenticity and accuracy.
When aspiring journalists ask me whether the media is dead, I always say no.
I remind them that while the menu might change, the hunger for news and information never vanishes. To stick with the food analogy, news these days is like UberEats: far more options are available at your fingertips.
Here’s the thing: evolution in the media is constant and ongoing.
Historically, the delivery method has evolved in this industry, from horseback to telegraph and radio to television. Cable news, the internet and social media caused disruptive waves over time. These days, news is on a 24-hour cycle that is no longer limited to cable news. And, now, Artificial Intelligence has entered the chat. (And they are here whether we like it or not.)
Newsrooms ignore the emergence of AI at their peril, as history shows that transformative technologies don’t disappear simply because they’re ignored. Remember in 1995 when Newsweek predicted the Internet would fail? It was already decades into its inevitable march to dominate media consumption.
Technology usually gets better in time, and it has only improved in my 22 years in this industry. We have a greater reach than we could have imagined. I can instantly read what’s happening in any part of this country—or the world. All from a device that fits in my pocket.
Technology and journalism will always travel hand-in-hand. However right now, a lot about the relationship is toxic. It’s not serving us and we need to do some soul searching to fix what’s not working.
Change can be a painful experience
News and information is everywhere, and everyone can share their perception of news. It’s transforming in real time and the growing pains are unrelenting.
The year started with over 500 journalists losing their jobs, according to Challenger, Gray & Christmas, Inc. About 2,681 journalism jobs were eliminated in 2023 alone. That’s a 48% increase from 2022 and a staggering 77% increase from 2021.
Circulation, viewership and listeners have steadily declined for newspapers, broadcast TV news, and public radio. Major online news outlets are trying to stave off website traffic and engagement decreases. The shift to social media platforms for news consumption is particularly noticeable among younger generations. All this before we get to the fallout from tarnished community trust and news avoidance.
Everyone is looking for sustainability.
Same old traffic metrics
Meanwhile, social media referral traffic has plummeted globally over the past two years.
The big picture: News organizations invested heavily in social media for two decades, relying on platforms like Facebook and Twitter/X, but the algorithms were not in our favor. They never loved us half as much as we loved them. We infiltrated these platforms, but social media prioritized advertising over truth and accountability.
Now, logic tells us that AI search could be a death knell for search traffic. Search has served as a major entry point for metrics that have helped newsrooms drive advertising revenue. Audiences have grown accustomed to using Google searches to find links to information. AI, however, can directly answer most questions, and it’s getting smarter by the hour.
The WSJ has reported that publishers might lose 20-40% of their website traffic when Google’s AI products are fully implemented. The loss of traffic from social media and search will likely have devastating effects on this industry.
Some local shops still rely on the same old metrics – the volume of web traffic and the value of a click or pageview – because that’s what we’ve always done. But given how much the landscape has changed, that well is drying up and we need to find a new source.
Rather than wait and see and react to the technological changes coming at us, the industry must redefine its relationship with technology and take some control. Some news organizations have come to terms with this, and others see the value in creating new revenue streams. Diversifying revenue sources is key.
But beyond that, the industry has to be more entrepreneurial and less traditional. Doubling down on the old models is simply not enough.
When we think about rebuilding the infrastructure for news, we should ask ourselves: Could we build our own pipeline to traffic? Is there a way we can empower audiences to share content by building a trusted social media platform for distribution? That’s the thing: We – the news and media industry – have to take responsibility and build the infrastructure we need to create new habits for readers.
Provide audiences with utility
The reality is that news organizations have done a decent job building brand presence across platforms, but there’s no measurement for the value of that. Unfortunately, our success is housed under decaying pillars of success. The entire model must be flipped on its ear. We must reimagine everything. That mindset is why some startups have done more than survive and become a new breed of media success story. There’s a there there.
We spend a lot of time curating audiences we already have and need to spend more of our days figuring out how to capture the ones we don’t. Live events, office hours and panel discussions center the news and make it accessible to more people. It’s a way to expand your brand in a three-dimensional way. Lean into your personalities and their subject matter expertise to establish a more potent value proposition. And recognize that not all change is bad. The trick is harnessing it in ways that attract and satisfy audiences.
We must pay closer attention to evolving media consumption habits. Some people do have shorter attention spans and want brevity. However, that’s not absolute; there’s room for it all.
We use our phones to do everything and email is a new form of currency. Delivering news to a consumer’s inbox via newsletters just makes sense. We have to develop content creation and delivery strategies that fit today’s lifestyles. And then be ready to do it again as things inevitably change.
Newspapers are going the way of the tablet—not the ones Apple makes, but the ones Moses carried when he descended from Mount Sinai. Hieroglyphics, papyrus and wood had a place in history, as did quill pens. We can appreciate Johannes Gutenberg’s contribution and still embrace all the waves of technology that followed.
Diverse perspectives
The pandemic showed us that people need the expertise journalists wield. However, at the same time we see that people increasingly value the perspectives of social media influencers over journalists. We may not like it, but this needs to teach us something. Rather than ask our journalists to be invisible or unobtrusive, perhaps we need to re-examine ways to humanize them for audiences.
The plethora of free options suggests that every media outlet needs to focus on offering more distinctive coverage. No, it shouldn’t be harmful or polarizing. But it has to be inclusive, reflecting more communities that demand to be heard. That’s why so many niche and local publishers have cropped up; to fill a void that was created by arrogance, neglect and an unwillingness to change – a poisonous recipe.
Media has to marry new technology, develop a trustworthy infrastructure for news distribution and create a steady diet of distinctive coverage mixed with utility and expertise and get back into communities.
The media landscape will look different by the end of this year (and the next, and the one after that), but you can’t point to a time in history when information didn’t matter. And you cannot point to a time in civilization when news – no matter its platform – didn’t make a difference.
If we haven’t learned anything else, history tells us we should pay attention.
New technologies will be critical to the media landscape in 2024, converging with trends towards immersive, personalized experiences and the increased impact of the creator economy, according to Arthur D. Little’s State of the Media Market 2024. The report is subtitled “Back to Balance: A Year of Prudent Economic Expectations,” reflecting the authors’ belief in the sector’s recovery and stabilization following a rocky 2023. Read on for a few takeaways from this extensive report.
The media embraces new technologies
A persistent theme in the ADL report is the need to employ new technologies to improve operations, engage new audiences, and customize experiences.
Artificial Intelligence (AI) and Machine Learning (ML) continue to transform the media landscape, helping to automate manual processes, personalize content and experiences, and enable data-driven decision-making to power industry growth. However, for all its utility and potential, AI is a powder keg of potentially explosive issues, as seen during the WGA strikes (which resulted in greater protections and compensation for writers). The ADL report maintains that early adopters will benefit from AI innovations, even as the regulatory and ethical landscape around AI continues to evolve.
VR and AR add dimension to immersive experiences for customers and will increasingly merge with other new technologies in the development of cutting-edge user experiences.
Cloud computing facilitates agility and reduces costs. Cloud gaming continues to expand globally, driven in part by immersive experience.
Big data and analytics should be wisely employed to discover customer preferences and behavior and inform industry decision-making.
Social media continues to be vital to the overall media industry, with huge capacity to engage audiences, build brand awareness, and boost content discovery. Platforms such as Twitch, Reddit, Discord, and TikTok are enticing content creators with AI tools that facilitate video and music editing, while also developing tools to label AI-generated content.
Audio is a big opportunity
Perhaps it’s a sign of multitasking culture, but the public’s appetite for music, podcasts, and audiobooks has remained robust and is forecast to remain strong.
Music streaming saw almost double-digit growth globally during the pandemic, and that growth is forecast to continue at a somewhat slower but still steady rate. The U.S. was the main driver, contributing about 40% of the growth in the global music streaming market in 2024. Spotify continues to dominate as a platform. Most streaming services increased consumer prices in 2023 but also expanded options such as audiobooks and podcasts.
Podcasts are still climbing in popularity and attracting advertisers. A significant portion of the public are tuning in to news podcasts, especially in the U.S. 19% of U.S. residents surveyed have tuned into a news podcast in the last month, compared to an average of 12% globally. Sweden is just behind the U.S. in news podcast use at 17%, with the UK lagging at only 8%, according to the ADL study.
Audiobooks continue in popularity overall and will benefit from a boom in education publishing (which is expected to achieve double-digit growth between 2020 to 2025), and in self-publishing. Spotify has moved into the audiobooks business, offering 15 free hours of audiobook listening to paid subscribers in the U.S., UK, and Australia.
Traditional news vs. the “creator” economy
Creator culture and the resulting creator economy have grown, and AI tools are making even it easier for individuals to create and edit content. Brands are recognizing the power of influencer marketing and giving creators more leeway to put forth fresh, albeit less polished, content.
A flipside of the enthusiasm for interactivity and user creation is declining interest in newsprint and linear television. Younger generations are driving this change. In the UK, only people aged 55 and older cited television as their primary source of news (42%). Those under age 45 showed a strong preference for online sites and apps as news sources, followed by social media. People under 25 relied on social media above all, with 41% of people in that age group citing it as their main source of news, according to the survey.
A concerning aspect of this trend is the lack of regulation, which makes misinformation much easier to launch and spread. Print news struggles to compete with free but often less reliable digital news platforms. Only a small minority of all age groups (ranging from 6% of people 55+ to 0% of those 45-54) in the ADL’s UK survey cited print as their primary source of news. Bundling and partnerships may be one path to combine more traditional linear media sources with more fluid and creator-friendly platforms.
Recommendations for media companies
In addition to the key theme of embracing and leveraging new technologies, the report’s authors offer a few more recommendations.
Forge strategic partnerships to reach new audiences, pool resources, and share expertise.
Balance user privacy with data-driven decision-making.
Invest in customer relationships, using new technologies to better understand and communicate with users and tailor content accordingly.
Deliver excellent content and experiences. There’s no substitute for outstanding content. Audiences seek high quality, engaging, unique experiences, so media leaders must invest in content that rises above that of competitors.
News has long relied on the power of visuals to tell stories: first through illustrations and more recently through photography and video. The recent rise in access to generative AI tools for making and editing images offers photojournalists, video producers and other journalists exciting new possibilities. However, it also poses unique challenges at each stage of the planning, production, editing, and publication process.
As an example, AI-generated assets can suffer from algorithmic bias. Therefore, organizations that use AI carelessly run the risk of reputational damage.
AI-generated images can suffer from algorithmic biases. As examples, without specifying any demographic or environmental attributes, text-to-image AI generator Midjourney returned four images—all of light-skinned men and all in seemingly urban environments—for the prompt, “wide-angle shot of journalist with camera.
However, despite the risks, a recent Associated Press report found that one in five journalists uses generative AI to make or edit multimedia. But how are journalists using these tools, specifically, and what should other journalists and media managers look out for?
I recently undertook a study of how newsroom workers perceived and used generative visual AI in their organizations with Ryan J. Thomson and Phoebe Matich. That study, “Generative Visual AI in News Organizations: Challenges, Opportunities, Perceptions, and Policies,” uses interviews with newsroom personnel at 16 leading news organizations in seven countries, including the U.S. It reveals how newsroom leaders can protect their organizations from the dangers of careless generative visual AI use while also harnessing its possibilities.
Challenges for deploying AI visuals in newsrooms
Mis/disinformation
Those interviewed were most worried about the way in which generative AI tools or outputs can be used to mislead or deceive. This can happen even without ill intent. In the words of one of the editors interviewed:
When it comes to AI-generated photos, regardless of if we go the extra mile and tell everyone, “Hey, this is an AI-generated image” in the caption and things like that, there will still be a shockingly large amount of people who won’t see that part and will only see the image and will assume that it’s real and I would hate for that to be the risk that we put in every time we decide to use that technology.
The World Economic Forum has named the threat of AI-fuelled mis/disinformation as the world’s greatest short-term risk. They rank it above other pressing issues, such as armed conflict and climate change.
Labor concerns
The second biggest challenge, interviewees said, was the threat that generative AI posed to lens-based workers and other visual practitioners within news organizations. AI-generated visual content is much cheaper to produce than paying for bespoke content but the interviewees noted that quality is, of course, different.
An editor in Europe said he didn’t think AI tools would take peoples’ jobs. Instead, he felt it would be others who apply these tools well who would be hired instead, as the newsroom can thus be more efficient by using them.
Copyright
The third biggest challenge, according to the interviewees, was copyright concerns around AI-generated visual content. In the words of one of the editors interviewed:
“Programs like Midjourney and DALL-E are essentially stealing images and stealing ideas and stealing the creative labor of these illustrators and they’re not getting anything in return.”
Many text-to-image generators, including Stable Diffusion, Midjourney, and DALL-E, have been accused of training their models on vast swathes of copyrighted content online. The two biggest players in the market that said they are taking a different approach are Adobe (with its generative AI offering, Firefly) and Getty (with its offering, Generative AI by Getty Images).
Both of these claim they’re only training their generators with proprietary content or with content they have license to use, which makes using them less legally risky. (Although Adobe was later discovered to have trained its model partially on Midjourney images.)
The downside of not indiscriminately scraping the web for training data is that this affects the outputs that are possible. Firefly, for example, wasn’t able to fully render the prompt: “Donald Trump on the Steps of the Supreme Court.” It returned four images of the building itself sans Trump along with the error message: “One of more words may not meet User Guidelines and were removed.”
Adobe Firefly wasn’t able to fully render the prompt “Donald Trump on the Steps of the Supreme Court.” It returned this image of the building itself, instead.
On its help center, Adobe notes, “Firefly only generates images of public figures available for commercial use on the Stock website, excluding editorial content. It shouldn’t generate public figures unavailable in the Stock data.”
Detection issues
The fourth biggest challenge was that journalists themselves didn’t always know when AI had been used to make or edit visual assets. Some of the traditional ways to fact-check images don’t always work for those made by or edited with AI.
Some participants mentioned the Content Authenticity Initiative and its Content Credentials, a kind of tamper-evident metadata used to show the history of an image. However, they also lamented significant barriers to implementation. These included having to buy new cameras equipped with the content credentials technology and also re-develop their digital asset management systems and websites to work with and display the credentials. Considering that at least half of all Americans get at least some news from social media platforms, content credentials will only be effective if they are adopted widely across the industry and by big tech giants, alike.
Despite these significant risks and challenges, newsroom workers also imagined ways that the technology could be used in productive and beneficial ways.
Opportunities for deploying AI tools and visuals in newsrooms
Creating illustrations
This is how text-to-image generator Midjourney responded to a prompt about visualizing generative AI. Journalists said they could see the potential for using generative AI to show difficult-to-visualize topics, such as AI itself.
The newsroom employees interviewed were most comfortable with using generative AI to create illustrations that were not photorealistic. AI can be helpful to illustrate hard-to-visualize stories, like those dealing with bitcoin or with AI itself.
Brainstorming and idea generation
Those interviewed also thought generative AI could be used for story research and inspiration. Instead of just looking at Pinterest boards or conducting a Google Image search, journalists imagined asking a chatbot for help with how to show challenging topics, like visualizing the depth of the Mariana Trench. Interviewees also thought generative AI could be used to create mood boards to quickly and concretely communicate an editor’s vision to a freelancer.
Visualizing the past or future
Journalists also thought the potential existed to help them show the past or future. In one editor’s words:
“We always talk about how like it’s really hard to photograph the past. There’s only so much that you can do in terms of pulling archival images and things like that.”
This editor thought AI could be used in close consultation with relevant sources to narrate and then visualize how something looked in the past. Image-to-video AI tools like Runway can allow you to bring a historical still image to life or to describe a historical scene and receive a video in return.
Image-to-video AI tool Runway allows a user to bring life to a still image from history.
More guidance (and research) needed
From our research, which also discusses principles and policies that newsrooms have in place to guide the responsible use of AI within news organizations, it is clear that the media industry finds itself at another major crossroads. As with each evolution of the craft, there are opportunities to explore and risks to be evaluated. But from what we saw, journalists need more guardrails to guide their use and allow for experimentation and innovation in ethically sound and responsible ways.
