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-chess king to show credibility is king in AI search-
AI | Supporter Spotlight

AI is rewriting search and credibility is king

For 25+ years, the open web ran on links. You typed a question into Google, got ten blue link results, and clicked on the one that resonated most with you. 

Not anymore. Generative AI is shifting user behavior, from querying and clicking to asking and consuming inside tools like ChatGPT, Gemini, and Perplexity. Google’s AI Overviews rewrite results into ready-made answers, turning what used to be a page of links into a single, synthesized suggestion. In its place, we’re entering a recommendation web—a world where every surviving link must have strong context and credibility.

In the wake of AI overviews, search isn’t dying, but the link economy is. 

At Raptive, we see this shift firsthand across 6,000+ publisher partners generating billions of monthly sessions. The data reveals a re-ordering of trust. The winners will be those who modernize for this “answer-first” landscape without abandoning the fundamentals.

Search is no longer a traffic channel; it’s a reputation test. 

Here’s what we’re learning about staying visible and resilient in this new era of search, and what digital media leaders should prioritize. 

1. Traffic patterns are fragmenting

Searches are growing, but click-through rates are declining. Similarweb data shows that zero-click searches have climbed from 56% to 69% year-over-year as Google’s AI Overviews increasingly answer questions directly on the page. Search behavior is being redistributed and discovery is flowing across new channels: AI assistants, social algorithms, recommendation engines, and Google Discover. 

-AI search charts showing AI overview growth and AI overview keywords-
Source: Ahrefs

Executive takeaway: Continue investing in high-quality, differentiated content that strengthens brand reputation. Move away from lightweight informational content that can be commoditized by AI. In a world of algorithmic discovery, originality and authority are the only currencies that hold value.

2. Quality and authorship signals are non-negotiable

Google’s June 2025 Core Update reaffirmed that expertise and trust win. In our analysis, sites with clear bylines, full author names, and robust About pages outperformed those without. Those signals are key ranking factors tied to credibility.

Executive takeaway: Audit your trust signals. Every article should clearly identify who wrote it, when it was last updated, and why readers should trust it. Invest in author pages, structured data, and visible expertise across verticals. “Real names, real voices” is the new SEO.

-chart showing content activity and pageview outcomes from AI search-
Source: Raptive

3. Consistent content activity drives resilience

In a study across independent creators, we found that sites publishing one new post and updating at least five existing ones monthly were far more likely to gain traffic after the June update. We saw the same correlation among larger publishers: steady, consistent activity signals both relevance and reliability.

Executive takeaway: Operationalize content cadence. Build processes for regular updates to evergreen content, and treat publishing frequency as a core SEO health metric, not just an editorial one.

4. Engagement metrics are rising in importance

Across our network, URLs that gained traffic after Google’s June update had 3x more comments and 3x more engagement than those that declined. AI and Google’s algorithms alike are rewarding proof of reader value.

Executive takeaway: Design for engagement and invite readers to interact. Encourage user reviews, comments, and feedback loops. Treat engagement as a credibility metric.

5. Discoverability is shifting toward recommendations

As AI search becomes more personalized, Google Discover is growing as a key traffic source. Discover rewards relevance and freshness, often outperforming traditional search in volume and conversion.

Executive takeaway: Optimize for recommendation ecosystems. Publish consistently, pair content with strong visuals, and prioritize depth and originality. These factors correlate directly with Discover visibility.

-Chart showing Google's AI search and Discover impact on traffic-
Source: Press Gazette

Why “modern SEO” still wins

Despite the hype around “GEO” (Generative Engine Optimization), “AEO” (Answer Engine Optimization), and a growing alphabet soup of new acronyms, the fundamentals of optimization haven’t changed. Today’s AI search is just a bunch of classical searches in a trench coat. Modern SEO—writing for readers, demonstrating expertise, and maintaining technical excellence—is what allows your content to surface in both traditional and AI-driven results.

And while the conversation around AI traffic grows louder, it’s important to remember that AI surfaces account for just 0.02% of total traffic today. In fact, our research found that pages ranking in Google’s top three positions are twice as likely to appear in AI Overviews as those outside the top three. 

Good SEO is good GEO.

And good GEO begins with genuine expertise. 

What to prioritize next

For digital media executives guiding strategy in 2025 and beyond:

  • Diversify traffic sources: Balance your reliance on Google with growth in newsletters, Discover, and direct audiences.
  • Double down on quality and cadence: Content activity and freshness are measurable, defensible advantages.
  • Audit trust and transparency: Author identity, About pages, and schema markup now influence both human perception and algorithmic ranking.
  • Invest in engaged communities: Reader interaction and loyalty protect against volatility in algorithms and AI tools.
  • Stay pragmatic: Don’t chase new acronyms or “AI hacks.” Track changes, test cautiously, and keep your team focused on fundamentals.

The bottom line

The future belongs to those worth recommending. 

People still want what they’ve always wanted: answers they can trust, ideas that make sense, and trustworthy sources. That’s where publishers matter most—not as content factories, but as champions of quality and original content that real people can count on. 

At Raptive, our mission is to ensure that independent voices remain discoverable, trusted, and economically viable in an AI-mediated web. Because the end of links doesn’t have to mean the end of independence—it can mark the beginning of a new era of credibility.

That’s not just good SEO; it’s good business. And, more than that, it’s good humanity.

-concept art to show a checklist for an ethical AI framework-
AI | Supporter Spotlight

Eight pillars of ethical AI: framework for responsible use

As media companies expand the use of AI to drive efficiency, many are seeking best practices to ensure AI is implemented responsibly and with minimal risk. A recent IAB study found that only one-third of publishers, brands and agencies have adopted formal AI governance tools, which underscores the need for greater accountability and transparency when AI is used.

But where should publishers start? An ethical AI framework provides a blueprint for how organizations can manage risk, protect data and demonstrate compliance when integrating AI into their operations.

Here are examples of each of the eight pillars of ethical AI. When implemented together, these best practices create a strong foundation to help media companies strengthen trust with audiences and partners.

1. Ethical AI Policies

Establishing clear policies that define how AI is being implemented provides the foundation for responsible AI governance. These policies should reflect a commitment to trans­parency, accountability, minimizing bias and protecting user privacy, and should be reviewed regularly to ensure they evolve with industry developments and regulatory changes.

Example: The Associated Press created a comprehensive policy around its use of generative AI, including who is responsible for monitoring the accuracy of AI output.

2. Transparency and Disclosures

Transparency helps establish greater trust in media. In addition to having an AI policy, publishers should make these policies publicly available and include disclosures when AI is used. A consistent communication strategy, supported by public-facing AI policies, strengthens accountability and promotes confidence among readers, advertisers and partners.

Example: Bay City News, a San Francisco Bay area nonprofit news organization, publicly shares how the team uses AI and adds in-depth context about the process behind each project.

3. Rights and Permissions

It’s also important that media companies secure applicable rights and permissions and the appropriate level of consent to use the information powering AI solutions. This might include establishing internal safeguards to prevent the misuse of proprietary or third-party content. This helps protect media companies from legal challenges and reinforces ethical content development practices.

Example: The New York Times provides guidelines for its staff that copyrighted material should not be input into AI tools, which prevents potential misuse of third-party content in AI training.

4. Accountability and Human Oversight

Since hallucinations and biases in AI exist, human oversight is essential. A “human-in-the-loop” approach ensures that AI outputs have been reviewed before being published. Organizations should assign clear roles for managing AI tools and outputs, and make sure qualified individuals are accountable for how these systems are used.

Example: The USA TODAY Network adds disclaimers to AI-generated article summaries that explain how key points were created and discloses that they were reviewed by a journalist prior to publication.

5. Bias and Fairness

AI models train on existing data, which can include biases that are then amplified. Media companies must implement strategies to identify and mitigate AI bias such as monitoring AI outputs for fairness and inclusivity. Developing a bias mitigation strategy strengthens credibility and supports fair representation across content and audiences.

Example: The Reuters Institute shared several examples from media leaders on identifying AI bias including how The Financial Times’ teams use internal checklists to assess whether AI-generated output from its content recommender system is unbiased and fair across demographics.

6. Privacy and Data Protection

Responsible AI also means demonstrating a strong commitment to protecting data privacy. Companies must ensure that AI systems comply with privacy regulations such as GDPR and CCPA and protect user data. Prioritizing data privacy can reduce legal risk and reinforce a company’s commitment to responsible use of technology.

Example: Graham Media Group, a Detroit-based media company, prioritizes reader privacy and security and shares its compliance with data privacy laws on its disclosure page and in its privacy policy.

7. Training and Education

Training and education are essential to implementing AI responsibly. Ongoing training ensures that staff understand the capabilities and limitations of AI tools and are made aware of any policy updates as the technology evolves. This includes both general training for all staff as well as proficiency training for individuals responsible for developing, deploying and monitoring AI systems.

Example: Radio-Canada launched a comprehensive AI literacy program to help staff better understand AI and how it should be used. The program includes a foundational training session to provide an overview of AI concepts and ethical considerations as well as follow-up workshops focused on practical applications.

8. Governance and Risk Management

Effective AI governance requires a structured approach to identifying and managing risk. Organizations should embed ethical AI principles into existing policies, ensure legal and regulatory requirements are met and assign clear accountability for oversight. Regular reviews and feedback loops help detect and address emerging risks, allowing companies to adapt as technology evolves.

Example: Gannett’s AI council brings together members from various departments to discuss ideas and assess risk when using AI in new ways.

Responsible AI isn’t about slowing progress but creating a foundation that supports innovation, transparency and trust. Media companies that integrate an ethical AI framework into processes will increase transparency, minimize risk and maintain the credibility that defines trusted media.

- Media executives looking at streaming video strategy -
Advertising | Supporter Spotlight | Video

The streaming shift in media strategy

The video market is fragmenting — but the prize is bigger than ever. According to MediaRadar analysis, U.S. ad spend will surpass $500 billion by 2028, with video alone accounting for $220 billion.  The question for media leaders isn’t if those dollars will flow, but who will capture them.

Sports, social video, and AI-driven targeting are rewriting the rules of engagement. For executives, the opportunity is clear: act now to secure share, or risk losing ground to platforms and competitors who move faster.

Sports and streaming: a new business lever

Live sports remain the most valuable premium video inventory, commanding CPMs north of $14, according to MediaRadar 1H 2025 estimates. Yet the structure of rights is rapidly shifting. In the 2025–26 NFL season, MediaRadar projects:

  • 46% of games will be simulcast across linear and streaming
  • 46% will be linear-only.
  • 8% of games (20 total) will stream exclusively.

This fragmentation isn’t chaos. It’s leverage. Publishers are using it to their advantage by bundling across platforms and segmenting audiences more precisely, tapping into the 11% year-over-year growth in digital channels and the projected $220 billion in video ad spend by 2028, according to MediaRadar analysis.  With Amazon, YouTube, and Netflix expanding coverage, publishers positioned across both linear and streaming can bundle inventory, maximize yield, and deliver addressable audiences at scale.

Case in Point: In 2024, live sports streaming alone neared $6 billion in ad spend according to MediaRadar analysis. Platforms like Amazon and Peacock benefited most. However, publishers who can sell across channels stand to capture premium demand.

Social and user-generated video: the budget shift

Scripted content once accounted for 70% of U.S. viewing; today, it’s closer to 30%. User-generated content (UGC) now represents nearly half of all viewing according to MediaRadar 1H 2025 estimates. While CPMs average just $4, the scale is undeniable – and advertisers and media executives alike are chasing it.

Automotive, finance, and CPG brands are redirecting budgets from scripted into YouTube, Instagram, and TikTok. For publishers, the strategic question is no longer whether to invest in these ecosystems, but how – via influencer collaborations, branded content, and social partnerships that extend reach and diversify revenue.

AI: from wild card to margin engine

AI is often positioned as experimental, but for publishers it’s becoming a margin mandate. According to MediaRadar’s analysis, AI is reshaping three critical areas:

  • Search & discovery: AI helps audiences cut through fragmentation to find premium content — and helps publishers surface it more efficiently, compressing the cost of audience acquisition while expanding the yield from discovery.
  • Information management: By automating insights and replacing armies of analysts with real-time optimization, AI dramatically compresses operational costs and expands yield through faster, smarter decisioning.
  • Content generation: In creative and bidding workflows, AI streamlines production and media planning, compressing content development costs and expanding yield by scaling personalization and campaign throughput.

For media executives, the implication is simple: AI compresses cost and expands yield. Integrating AI into targeting and personalization is no longer optional; it’s the difference between competing on price versus competing on value.

What publishers need to do now

The next 24 months will determine market leaders. Here’s how to protect and grow share:

  • Align with sports: Premium live events still command the highest CPMs. NFL streaming rights on Amazon, YouTube, and Netflix open fresh monetization channels.
  • Leverage social and UGC: Nearly half of viewing happens here. Automotive and finance brands are already investing heavily in YouTube and Instagram. Publishers need to meet them where spend is flowing.
  • Invest in AI-driven targeting: Precision targeting turns fragmented inventory into measurable, ROI-driven campaigns. Dynamic ad personalization increases yield.
  • Double down on data: First-party insights are pricing power. Even in a soft ad market, MediaRadar analysis found digital channels grew 11% YoY in H1 2025.

Looking ahead

The path forward is clear: streaming, sports, and AI will define the next era of video advertising. Together, they represent the pillars of a new video economy—one where reach, relevance, and rights management will determine who thrives and who fades.  

As we said in our recent webinar from the State of the Industry Series: “In times of change, data is your greatest advantage.” Executives who act now—before platforms consolidate power again—will set the pace for the industry.

About the Author

Matt Krepsik, CEO of MediaRadar, is an experienced media executive with a demonstrated history of working across the media and information technology industries. Skilled in big data, artificial intelligence, technology, marketing, and market research, he is a seasoned business development professional with global leadership experience.

-broken chain link concept to show that audience links are broken because of AI search -
Audiences | Supporter Spotlight

What smart media leaders are doing now that search is broken

Let’s get one thing out of the way: search can no longer be your primary audience strategy. But the real shock is how fast it’s become nearly useless for audience growth.

Google’s turning into a closed loop. Over half of all searches now end with zero clicks, and when AI-generated summaries appear, organic links lose a third of their clicks on the spot. If your site traffic is down, it’s not your SEO team’s fault — it’s because search as we’ve known it is dead.

“Your headline is your homepage.” In other words, your content has to earn attention without the click. You can’t rely on users landing on your site anymore, because most of them never will.

So where does that leave media brands? Smack in the middle of a reset. Here’s what the smartest operators are doing now to adapt and why the rest risk falling further behind.

1. Stop chasing traffic. Start earning intent.

Sure, you can still try to play the volume game. Crank out more articles. Cast a wider net. Cross your fingers. But the volume game won’t work like it used to.

The collapse of passive search traffic is shrinking your top of funnel. However, that’s not necessarily a bad thing. Much of that traffic was never your real audience. It was noise. Window shoppers. Bots. AI-generated detours.

Now’s the time to trade quantity for quality. Every impression, every email capture, every form fill has to work harder. That means media professionals need to focus on:

  • Sharper conversion paths
  • Smarter segmentation
  • Personalized nurture tracks that actually lead somewhere

When the funnel’s narrower, your optimization game has to be stronger. Period.

2. Clean up your data because the bots are winning

Let’s talk email. You may think your open and click rates look solid. But there’s a good chance those numbers are lying to you.

According to our research, up to 80% of email clicks across the industry are generated by security bots, not people.1 That’s not just a rounding error. That’s full-on performance distortion at scale.

And it’s getting worse. These new “data center” bots mimic human behavior well enough to slip through basic detection. If you’re not using advanced bot filtering, you’re likely reporting inflated engagement, overvaluing underperforming content, and misleading your advertisers.

The takeaway: If you’re not scrubbing your metrics, you’re not measuring engagement. You’re measuring noise.

3. Your first-party data is your only real moat

Let’s stop romanticizing platform reach. You don’t own your audience on LinkedIn, Facebook, or YouTube. You rent it. And the rent keeps going up.

The only data that can’t be taken away, throttled, or repriced is the data you collect yourself. That means:

  • Known user identities
  • Email addresses
  • Preference data
  • Behavioral signals
  • Demographics tied to intent

This isn’t just marketing hygiene — it’s strategic infrastructure. Without it, you’re building on sand.

4. If you can’t see the growth, you’re looking in the wrong place

Here’s the part most brands miss: the best audience growth isn’t visible in your dashboard. It’s happening in dark social such as Slack groups, Discord threads, iMessage chains, and private communities.

You won’t see referral traffic from these places. You can’t boost a post into them. The only way in is to be so useful someone decides to share your content voluntarily.

And no, that doesn’t mean slapping another CTA at the end of your article. It means surfacing real insights. Speak human. Create content that solves a problem or starts a conversation.

In dark social, trust is the algorithm. If your brand doesn’t have it, you won’t grow.

5. The economics matter more than the volume.

Executives who can’t answer two questions are flying blind:

  • “What does it cost to acquire a user?”
  • “What’s that user worth over time?”

User acquisition costs vary wildly by channel. So does LTV. The most sophisticated operators treat audience like a supply chain:

  • Tracking acquisition by source
  • Measuring velocity and retention
  • Monitoring value creation over time

It’s not just a marketing metric. It’s a P&L strategy. And this strategy should shape every audience investment you make.

6. Audience operations is your most strategic hire

It’s not campaign management. It’s orchestration.

The best audience teams sit at the intersection of data, content, marketing, tech, and revenue. They’re translators. Strategists. Connectors.

And yes — they’re expensive. But they’re also your best shot at future-proofing your business.

If you don’t understand the role, you’ll under-resource it. If you undervalue it, you’ll fall behind.

Final Thought

The audience playbook has been rewritten. Again.

Search is evaporating. Bots are faking engagement. Social algorithms are tightening their grip. And the platforms aren’t coming to save you.

But if you know your audience — truly know them — you’re not just surviving this shift. You’re building something no algorithm can take away.

So ask yourself: Are you still chasing traffic? Or are you building something that lasts?

About the author

Tony Napoleone is VP of Client Experience at Omeda, where he helps media brands turn audience data into revenue. With deep expertise in audience development, marketing tech, and lifecycle strategy, he leads high-touch client partnerships that drive growth, engagement, and innovation.

1 Omeda Email Engagement Report Q1 2025.
-people designing human centered AI workflow as part of strategy-
AI | Supporter Spotlight

WSJ’s AI strategy: urgency, clarity, and human-centered reporting

After devastating floods claimed over 100 lives in Kerr County, Texas, our newsroom started investigating: could this tragedy have been prevented? The team narrowed in on public records of meetings by the Kerry County commissioners. The sheer volume of transcripts and a legacy filing system made a manual search impractical. But we quickly realized that AI could help. Using in-house built AI tools, we were able to uncover critical pieces of information central to the creation of  a landmark piece, published within days of the disaster.

To be clear, this was not a story written by AI. However, it was a story made possible by it. And it’s a perfect example of how we’re deliberately approaching AI at The Wall Street Journal – always to enhance journalism, not replace it. We spent the summer honing that deliberate approach with the goal of building knowledge, solutions, and a vision for AI’s newsroom role. 

⇒ Takeaway: Given generative AI’s transformative impact and the industry’s rapid change, newsroom leaders must address short-, mid- and long-term strategies all at once. 

NOW: Building a strong AI foundation

In the short term, we’re focused on ensuring our journalists know how to leverage AI and can do so in alignment with our newsroom AI guidelines. 

We rolled out enterprise AI tools and provided the standard company-wide “AI 101” training earlier this year. Yet even after months of effort, many reporters remained unsure how to use these tools effectively. I frequently heard questions like “How should I apply this in my job?” and “Where do I even start?” 

To address those concerns, we launched a summer series of lunch and learn sessions with the Newsroom AI task force to demonstrate how reporters and editors are already using AI in their work. Reporters walked away with role-specific tip sheets and more visibility on who is the AI evangelist in each department. Better yet, with the editor in chief in attendance, the sessions delivered a clear endorsement that the newsroom can and should be using these tools. 

 ⇒ Takeaway: We found that reporters need clear examples that demonstrate the return on investment for learning this new technology, especially as caution and uncertainty remain high. 

NEXT: Identify opportunities and embrace transformation

We scheduled brainstorming sessions with teams to identify elements of typical workflows that are rote and repetitive, more chore than creative. The key question we wanted to address was how can we free up time for journalists to focus on stuff only they can do? 

Concrete takeaways from these meetings are a prioritized list of workflow challenges. We identify places where new tooling or AI agents might help. We’ve now got a list of projects to prototype in the newsroom and to collaborate on with our tech and engineering colleagues.

Zooming even further out, we hosted a series of sessions with each coverage area that focused on how our newsroom can evolve to anticipate changes in reader behavior and expectations. The goal was to think big: Given what ChatGPT, Gemini and Claude can already do, how do our workflows evolve? How should our coverage change?

The industry is at a massive inflection point in the way audiences discover, digest and manage information – and that’s our business. While we won’t always get it exactly right, we do need to anticipate audience behavioral changes to stay ahead. Those conversations have never felt more urgent. Our future-proofing sessions clarified the need to focus on direct relationships with readers and creating unique, human-centered storytelling experiences that AI can’t replicate. 

⇒ Takeaway: Executive-led sessions reinforced that AI is a top priority – and every journalist should treat it with the same level of urgency. 

Our AI roadmap

As we shape our strategy and roadmap, we’re actively harnessing AI to deliver impactful journalism. AI continues to be a force multiplier for our newsroom, increasing speed and discoverability in areas and formats that have historically been hard to cover by a single reporter. 

Our data journalism team built a tool that does just that. Nicknamed “Orca,” this tool helps reporters digest and summarize conversations happening in podcasts. Where previously a reporter would have to listen to every episode, tallying hundreds of hours on a particular topic or show, now Orca leverages AI to transcribe conversations into text that can be searched, summarized or quantified. Orca was the engine behind this piece, which analyzed how conservative podcasters have discussed the Jeffrey Epstein case. Orca listened to more than 22,100 episodes from 148 podcasts, obviously a feat previously unfathomable by even a large team of reporters. 

⇒ Takeaway: Roadmaps and cross team alignment can take time. Let’s not keep that from holding back areas where AI can move at speed and make a real impact— our journalism.  

Embracing AI wisely means moving with both urgency and care – deploying it where it can supercharge reporting today, while building the culture and strategy to guide its long-term role. At The Wall Street Journal, our guiding principle is clear: using AI to enhance our journalism, not to replace it. By investing in training, rethinking workflows and pushing ourselves to imagine what’s next, we’re ensuring that our distinctive, exclusive and human-led journalism remains at the heart of every story we publish.

-hands typing on keyboard showing AI search-
AI | Supporter Spotlight

How publishers can survive the AI search shift

Artificial intelligence is rewriting the rules of discovery. Search results are no longer a simple list of blue links. With tools like Google’s AI Mode delivering instant summaries, audiences often get what they need without clicking through to the original source. For publishers, this shift is already visible in their analytics. Mail Online reported click-through rates dropping by more than 50% when AI overviews appeared, even when the site ranked first in traditional search results.

For digital media executives, the implications are serious. Fewer visits mean fewer opportunities to monetize, weaker brand authority and a growing disconnect between audiences and the trusted outlets that produce the content. Readers develop loyalty to the aggregator, not the publisher. The challenge now is to reclaim direct relationships and remind audiences why visiting a publisher’s own site matters.

Strengthening the core

The first priority is to reinforce the value of a publisher’s own destination. Strong editorial identity and a clear brand voice give readers a reason to come back. Investigative reporting, live coverage and deeply reported opinion pieces resist machine-generated simplification and highlight a publisher’s expertise. Investing in these formats makes the brand indispensable and difficult for AI to replicate.

Loyalty programs can also deepen ties. Offering exclusive access, community recognition or tangible perks encourages habitual engagement without relying on restrictive paywalls. The goal is voluntary, not coerced, return visits. Readers should want to come back because the experience is worth it., rather than being pressured through paywalls, aggressive pop-ups, or other forms of friction that limit genuine choice.

Expanding discovery and engagement

Relying on search alone is no longer viable. Audience acquisition needs to extend across a wider ecosystem: partnerships with other respected outlets, distributed content on reliable platforms, curated newsletter growth and smart syndication. Each step reduces dependence on any single traffic source and introduces the brand to new readers. Some publishers have shown how effective this can be, with audience acquisition programs generating hundreds of millions of additional monthly page views across participating outlets, helping to fill gaps left by declining search traffic.

Discovery must also go beyond distribution. Publishers can build intentional paths into their ecosystems by embracing products like curated apps, podcasts, and social channels that are designed to funnel audiences back to their owned platforms. The goal is to make discovery a two-way street: audiences find the publisher, but the publisher also actively guides them toward deeper engagement.

Once visitors arrive, their time must count. Interactive storytelling, immersive explainers and vertical video feeds keep users exploring. Research shows vertical video can generate more than triple the time spent compared with high-impact display ads. Formats that encourage longer sessions strengthen the relationship and increase the value of every visit.

Using AI as an ally

Avoiding AI altogether is not the answer. Publishers can harness machine learning to improve personalization and relevance. AI-powered recommendation engines surface content tailored to individual preferences, reinforcing the brand’s value through context and depth. The key is to integrate AI as a tool for engagement while maintaining control of the narrative.

AI can also automate low-value newsroom tasks such as headline testing, tagging, or formatting, freeing journalists to focus on reporting that machines cannot replicate. At the same time, it strengthens the use of first-party data, helping publishers uncover patterns that drive more relevant content and advertising while respecting privacy. Used in this way, AI becomes less a threat and more a tool to deepen engagement, improve efficiency, and support the distinctive editorial voice that sets publishers apart.

Search and AI: navigating the road ahead

The next five years will determine which digital media companies maintain authority and revenue. Those that cultivate direct relationships, amplify unique editorial strengths and create richer on-site experiences will weather the volatility of platform-driven traffic. Those that don’t risk fading behind a layer of algorithms.

What is unfolding is not just a shift in referral traffic but a structural reordering of how information is discovered, trusted, and monetized. Search is no longer the dependable gateway it once was, and AI is accelerating the pace of change. Publishers that thrive will be those who see discovery as an ecosystem rather than a single channel, who treat loyalty as a relationship rather than a transaction, and who use technology to enhance — not replace — their editorial identity.

The future of publishing will not be decided by algorithms alone. It will be shaped by the ability of publishers to assert their value, claim their place in the open internet, and remind audiences that real journalism and original voices are worth seeking out.

---unlock ad sales growth through pre-sales ---
Advertising | Supporter Spotlight

Unlocking growth through pre-sales in ad ops

For media revenue leaders working in ad operations, the pressure is constant: grow revenue, protect margins, and capture opportunities faster in a crowded marketplace. Yet those goals are often undermined at the very start of the process:  pre-sales.

Often an overlooked part of the Order-to-Cash (OTC) process, pre-sales is a critical phase that shapes pricing, product fit, feasibility, and advertiser expectations, which influence revenue outcomes long before an IO is signed. But it’s also where RFPs, media plans, contracts, and approvals are still handled through manual, disconnected workflows that hinder campaign performance.

That’s beginning to change. Ad Operations teams are rethinking the day-to-day workflows in pre-sales. They’re replacing manual effort with automation that delivers consistency, accuracy, and momentum. This shift is building healthier pipelines, stronger margins, and a clearer link between operations and profit.

For media industry revenue leaders, this is more than a workflow issue. The tangible benefits highlight the upside of change. However, they also underscore why pre-sales can’t remain manual. Left untouched, it drags on margins, delays responses, and weakens advertiser trust.

Why pre-sales can’t stay manual

Despite its critical role, advertising pre-sales is still weighed down by outdated processes. RFPs bounce between inboxes, media plans are rebuilt in multiple spreadsheets, and contracts move only when someone manually follows up. Each step slows the deal cycle and multiplies the risk of errors.

The result isn’t just wasted time. It’s missed opportunities, inconsistent pricing, and proposals that reach advertisers too late. Proposals are often prolonged and require repeated rework. And in some cases, deals are lost outright when responses arrive too late. Errors slip in, deals drag out, and the credibility of the entire sales process takes a hit.

For revenue leaders, that’s more than an operational nuisance. Manual pre-sales creates revenue leakage: slow responses mean lost deals, mismatched proposals squeeze margins, and rework inflates delivery costs. In a marketplace where speed and accuracy are decisive, manual workflows put growth goals at risk before a single campaign even launches.

When pre-sales shifts away from manual effort, it doesn’t just remove inefficiencies – it highlights just how much revenue is left on the table until automation takes hold.

The revenue upside of fixing pre-sales

Automation in pre-sales does more than streamline workflows – it creates a stronger engine for revenue. Automated intake, planning, and approvals move proposals to advertisers faster and with greater accuracy. Connected systems eliminate duplicate entry, giving sales and ops teams a single source of truth from the very first step.

Yet tools alone are not enough. Inconsistent use of CRMs and planning systems often leaves downstream teams working from incomplete or inaccurate information.

Structured automation closes those gaps by ensuring proposals are built on reliable inputs and aligned across functions from the start.

Instead of delays and rework, sales teams see deals advance with fewer obstacles and greater predictability. Advertisers receive timely proposals aligned to inventory and pricing, reducing the risk of mismatched expectations. For advertisers, this translates into faster, more accurate proposals that align with their objectives and build trust from the first interaction. Internally, ad ops teams spend less energy on corrections and more time on activities that drive growth – from refining strategy to deepening client relationships.

For revenue leaders, these improvements are operational wins that translate into measurable outcomes: higher proposal acceptance rates, healthier pipelines, stronger margins, and a clearer connection between operational execution and financial performance.

And those gains don’t stop once the IO is signed. The strength of pre-sales sets the tone for everything that follows – from campaign delivery to long-term client relationships.

Pre-sales as the foundation for long-term success

The value of optimizing pre-sales sets the tone for the entire OTC process. Campaign teams inherit cleaner plans, delivery starts with fewer corrections, and client service teams avoid the frustration of resetting advertiser expectations.

Without that consistency, delivery teams often find themselves having to resell deals internally. That means that must translate proposals into what can realistically be executed. Over time, these inefficiencies compound, which inflates delivery costs and weakens advertiser confidence. Renewal opportunities are lost when campaigns fail to meet objectives, and long-term revenue suffers.

By contrast, when proposals are execution-ready from the start, disputes are minimized, renewals are stronger, and organizations can scale without proportional increases in headcount. That’s because growth is built on reliable, repeatable processes rather than manual workarounds.

For revenue leaders in the media industry, the takeaway is simple: pre-sales is more than process. It’s the foundation for stronger margins, lasting client loyalty, and a business built to scale.

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Advertising | Supporter Spotlight | Video

Programmatic confusion is holding CTV back – can we fix it?

If you read the latest analyst forecasts or industry headlines, a clear narrative emerges: programmatic is taking over connected TV. The reality is more complex. While automated deliveries are indeed growing, programmatic’s role in CTV remains widely misunderstood – and sometimes overstated.

This matters for media owners. Confusion around definitions and measurement can distort investment decisions, complicate yield strategies, and cloud how some publishers position their ad inventory in a rapidly evolving market. Understanding where programmatic fits, and where it doesn’t, is essential for anyone making decisions about CTV monetization.

The latest FreeWheel Video Marketplace Report (VMR) found that over 70% of streaming ad views are still delivered directly, outside of programmatic channels. At the same time, some industry forecasts suggest that over 80% of CTV spend is already programmatic. The gap between these figures highlights a deeper problem: the industry still lacks a shared way of defining and measuring programmatic in CTV.

Why the disconnect exists

Programmatic, at its simplest, is about automation. Yet in everyday use, the term has stretched so far that it now covers almost everything. This can include everything from open exchange bidding and private marketplaces to programmatic guaranteed deals, and even digitized versions of old-style insertion orders.

This broad application muddies the waters. For example, guaranteed CTV buys executed through programmatic channels may be classified as programmatic, even though they behave more like direct transactions. At the same time, some forecasts group together very different formats, such as in-stream, outstream, and social video. all under the CTV umbrella. The result is an inflated picture of programmatic’s footprint in premium CTV environments, which has resulted in a narrative that does not always reflect the actual transactions taking place.

For media owners, the problem isn’t just about definitions. It directly affects how buyers perceive value, how inventory is packaged, and how technology investments are prioritised. When “programmatic” can have four or five different meanings, publishers risk being evaluated against expectations that do not align with the real economics of their supply.

CTV is not display, and not linear

Part of the challenge is that CTV doesn’t fit neatly into existing categories. It isn’t digital display, and it isn’t traditional TV. Instead, it combines TV living-room style viewing with digital-style automation.

That in-between status has consequences. Budgets often get split between TV and digital teams, leading to competing KPIs and conflicting expectations. Agencies with more established brand clients may prioritize guaranteed premium placements, while performance-led advertisers may lean towards real-time optimization. Both want automation, but they mean very different things when they use the word “programmatic.”

And then there are publisher realities. Premium inventory is finite. Direct deals remain the backbone when it comes to revenue and they allow tighter control over both supply and the viewing experience. Adding programmatic layers can introduce extra costs and unnecessary operational complexity. Not to mention ongoing issues with signal loss, fraud, lack of transparency, and inventory duplication which all make it harder to trust the open exchange. The idea of pushing all CTV into this model simply doesn’t reflect how premium video is bought and sold today.

The impact of language and alignment

A serious stumbling block for the industry is not the technology but the terminology. “programmatic” is being used to describe multiple, fundamentally different transaction models. Without clearer definitions, buyers and sellers risk building toward different futures. That leaves publishers in a difficult position. Do they double down on auction-based infrastructure, channel resources into tools that support direct guarantees, or try to straddle both? Without greater industry alignment, even the most carefully designed strategies can end up misfiring.

Buyers, too, grow wary when CTV is labelled as “programmatic” but still depends on direct negotiation. The result is a disconnect between expectation and reality. That, in turn, can hold back spend, despite CTV’s growing share of consumer attention. The confusion makes it harder for publishers to position their inventory correctly, and for buyers to evaluate its true value.

A more grounded future

A large share of premium CTV deals still happen within closed publisher ecosystems, using formats and configurations that escape conventional measurement tools. The real challenge isn’t just automation – with the risk of mirroring the display advertising model – it’s figuring out how to make programmatic truly fit CTV without reinforcing the fragmentation that already limits transparency and scale.

This will mean new models that reflect the economics of television, rather than forcing CTV into frameworks designed for other channels. It will also mean new tools that allow publishers to maintain supply control while offering buyers efficiency, better transparency, and the ability to tailor how they transact.

For media owners, progress requires pressing for greater alignment on terminology, more transparency in measurement, and continued investment in infrastructure that supports both efficiency and control. The challenges are real. But so are the opportunities.

-concept shows programmatic ad and revenue squeeze-
Advertising | Supporter Spotlight

How smart publishers are winning in a squeezed media economy

Publishers are under siege. Platforms and AI are siphoning off traffic, ad dollars are consolidating, and the rules of digital media are being rewritten in real time. According to a recent forecast by eMarketer, 85% of programmatic display ad dollars will transact via programmatic direct and PMP in 2026, leaving smaller players fighting for scraps. This isn’t a passing storm. It’s a structural reset of the media economy that threatens to push many publishers to the margins.

Yet moments of disruption can be moments of reinvention. Publishers that once relied on stability must now build resilience. They need to diversify revenue streams, cultivate loyal audiences, and lean on partners who can shoulder the heavy lift of technology, brand safety, and optimization. Survival in this market doesn’t come from standing still. It comes from adapting with speed and purpose.

What’s causing the squeeze

Advertisers are consolidating spending on fewer, trusted partners—supply sources that deliver quality, brand safety, performance, and scale. For independent publishers, that means competing against much larger players with deeper pockets and more sophisticated technology.

Meanwhile, running an in-house programmatic stack has become unsustainable. Effective yield management requires continuous testing, demand path optimization, identity and brand safety investments, dynamic pricing strategies, and strong demand partner relationships. 

The result? Media companies are being crowded out. Without adapting, many publishers risk losing visibility and revenue in a marketplace dominated by scale.

The power of programmatic scale

The growth of sales houses isn’t accidental; it’s structural. As the dedicated monetization partner for multiple publishers and a one-stop shop for advertisers, sales houses combine diverse ad inventory in a single channel. The model rests on significant fixed-cost investments in technology, teams, and innovation beyond what a single publisher can rationalize. 

By aggregating supply, sales houses can unlock efficiencies and command more attractive demand relationships. At Raptive, we run over 750 optimization experiments annually across 6,000 sites, generating insights no single publisher could replicate. We believe that, by tapping into that level of learning, publishers can turn programmatic into a resilient engine of sustainable growth.

This explains why the sales house category has grown by 31% in three years: many publishers are tapping into those benefits rather than going it alone. 

The bottom line: ad management is a strategic advantage. It allows publishers to increase revenue, cut costs, compete with scaled players, and adapt to the changing flow of ad dollars. 

Four strategies for surviving the squeeze

What can publishers do in the face of so much change? The rules of digital media are shifting fast, but with the right programmatic approach, audience focus, and monetization plan, there are clear ways to stay competitive. Here are four smart moves to help publishers grow stronger and smarter in today’s disrupted media landscape.

Build your brand

Brand is the ultimate differentiator—and the most reliable antidote to platform volatility. As Gen Z matures beyond its “TikTok generation” reputation, it seeks trusted sources to guide decisions around home ownership, careers, and finances. They value authenticity and expertise, not clickbait or surface-level content. 

Advertisers follow the same logic. They value publishers whose audiences already see them as credible. And strong brands don’t just win loyalty; they also drive more direct traffic, as readers bypass intermediaries and head straight to the publisher’s front door. That kind of audience relationship is invaluable in an era of shrinking search referrals and shifting algorithms. The risk of inaction is steep: our research shows trust drops by nearly 50% when readers suspect content is AI-generated. Publishers who invest in building strong brands now will secure resilience. This results in reader loyalty, advertiser trust, and a steady stream of front-door traffic.

Diversify traffic sources

AI-generated results and the rise of zero-click searches mean that search is an increasingly unreliable source of traffic—an existential threat for publishers who lean too heavily on SEO. Expanding reach through alternatives like Google Discover—already rivaling search in some categories—along with emerging platforms such as Newsbreak, opens new pathways to audience acquisition. 

Social referrals have declined but remain a vital offset to search dependency. For lean teams, subject-matter expertise and dedicated resources are critical to uncovering and executing creative strategies that balance traffic sources and protecting long-term growth.

Prioritize direct sales

Programmatic may be gobbling up advertising budgets, but that doesn’t mean publishers should completely abandon direct sales. The 20% of ad spend not going to programmatic is worth fighting for. In fact, combining private marketplace sales with direct sales can boost inventory value to 2-3x that of the open market. For media companies, the challenge is scale: partnering with the right sales house extends your reach, unlocking premium demand without adding overhead.

Invest in identity solutions

Google hasn’t killed cookies, but that doesn’t mean publishers can afford to sleep on authenticated traffic. The pressure is still mounting—from regulators, from savvier users demanding privacy, and from the nearly one billion people worldwide now invisible to advertisers due to ad blockers. Maximizing email-identified traffic and leveraging the right technology can deliver 30–90% more revenue in cookieless environments. The challenge is scale: no single publisher can match the reach of major platforms alone. But by tapping into networks that have invested in ID solutions for years, publishers can benefit from identity matching across thousands of sites—unlocking richer data, stronger advertiser demand, and long-term competitive strength.

Gain power through partnerships

Sales houses provide access to expertise, technology, and scale that individual publishers can’t easily build on their own, reducing operational strain, unlocking competitive advantages, and freeing up resources to focus on what matters most—delivering the kind of authentic, trusted content that keeps audiences coming back.

In an era defined by shifting algorithms, rising privacy expectations, and tighter resources, resilience won’t come from going it alone. Resilience, and success, are built by combining authentic brands with smart strategies and the right partners.

-Calibrated Signal Concept Art-
Advertising | Supporter Spotlight

Calibrated Signal: audience data yield without audience data leakage

There isn’t a premium content company on the planet that isn’t feeling the combined effects of several significant shifts reshaping how publishers reach and monetize audiences. Google’s AI Overviews now answers more user queries directly on the search results page, reducing click-throughs to original content and reporting. Brand safety systems have long filtered out legitimate journalism when stories touch on sensitive topics, further shrinking the monetizable audience on the open Internet. And since Apple began tightening the screws on third-party identity, high-value audience budgets have been steadily consolidating inside walled gardens, where targeting and measurement are easy, and results are immediate.

It’s tempting to frame publisher revenue as a traffic problem or an audience targeting problem. In reality, it’s a control problem. Walled gardens win because they own the most useful audience data, control the environment in which it’s applied, and make performance measurement effortless for buyers. The open Internet, by contrast, has allowed too much of its most valuable audience signal to slip away. Publishers have an incredibly valuable asset, which they have failed to surface to advertisers in usable ways without giving away the farm. The result is a performance gap that premium publishers can’t afford to ignore.

The way forward isn’t to hand over more raw data in the hopes of winning a larger share of your clients’ ad budgets. It’s to calibrate the signal you share. It needs to offer enough to make your media competitive on targeting, measurement and optimization, while keeping control of the underlying data.

At Symitri, we call this approach Calibrated Signal.

Defining Calibrated Signal

Calibrated Signal is the deliberate practice of exposing just enough information about your audience and content to drive advertiser performance, without revealing personal identifiers or relinquishing ownership of the data. It’s a middle ground between “lock it all down” and “let it all out,” designed to satisfy privacy requirements, protect competitive advantage and give buyers the clarity they need to plan, measure and optimize with confidence. Publishers who calibrate signal stay in control of their valuable audience data while giving buyers everything they need to justify premium CPMs.

This isn’t theoretical. Calibrated Signal can take the form of aggregated intent cohorts, recency-based engagement tiers, deterministic privacy-safe audiences, affinity-oriented contextual signals and privacy-safe conversion reporting. Each element is designed for one purpose: to make it easy for an advertiser to plan, buy, measure and optimize against your audience as effectively – or more effectively – than they can inside a walled garden.

A publisher playbook for Calibrated Signal

Premium content publishers are at an advantage because they tend to attract repeat, engaged audiences. This regularity is a built-in differentiator that distinguishes premium publishers from the rest of the transactional open Internet. For publishers in this category, creating value from Calibrated Signal requires a modest effort and investment that will yield significant returns.

1. Own your data spine

Start with consented, first-party data and a durable identity framework you control. If you can motivate your audience to log in, that’s gold. But even without explicit authentication, commercial identity solutions can help you uniquely recognize repeat visitors in a privacy-compliant fashion. Whatever your approach, standardize the way you capture and categorize signal – content taxonomies, intent cohorts, engagement tiers – so it maps cleanly to advertiser needs. Share the schema (not the identifiers) so buyers or their technology partners can act on it without taking custody of the underlying data.

2. Federate signal to create reach

Even the largest premium publishers rarely have enough audience scale to fulfill most campaign objectives on their own. That’s why Calibrated Signal works best when it can be activated across a network of trusted publishers with a consistent taxonomy and governance model. When buyers can plan, target and measure against a unified signal set that spans multiple properties – without the underlying audience data ever leaving publisher control – it becomes a true alternative to walled-garden scale.

3. Measure results in real-time

Performance budgets follow proof. Programmatic performance budgets follow proof in real time.

While closed-loop measurement and optimization are standard in walled gardens, achieving real-time performance on the open Internet has become far more challenging. Why? Because underlying audience identity signals have largely disappeared from publisher inventory. Premium publishers need to own the work of restoring the signals that make fast, consistent outcome validation possible across trusted inventory – without giving away the farm. When that happens, the results will speak for themselves. Research strongly suggests that the premium open Internet will easily match – and likely exceed – platform benchmarks.

4. Give buyers the confidence to trust what they’re buying

All this focus on audience data and measurement would be meaningless without the valuable, high-quality inventory to which Calibrated Signal is attached. Buyers need to know they’re reaching real audiences in brand-safe environments that have a high propensity to perform. That means eliminating MFA inventory, ensuring direct, cost-efficient supply paths and consistently operating with verifiable supply-chain transparency. With these quality promises – and a consistent level of Calibrated Signal – buyers are likely to shift their big budget bets from the walled gardens to the trusted and transparent environments that premium open Internet publishers can uniquely offer.

5. Anchor everything in outcomes

Structure every campaign with clear KPIs – incremental reach, CPA improvement, conversions and lift – and fixed timelines. Make it easy for buyers to prove value quickly and justify scaling spend.

Why this is different from legacy data deals

Legacy audience data-driven deals often handed over audiences with limited controls or offered broad contextual targeting with no performance accountability. Calibrated Signal is different in three ways:

  • Value is intentional: you share only what improves outcomes, nothing more.
  • Measurement is integral: buyers don’t just trust; they test and see results.
  • Privacy is by design: you always own and control your valuable consumer data assets.

This reframes the open Internet’s so-called “signal loss.” No individual publisher needs the same identity resolution scale as a walled garden. Instead, you and your premium open Internet publishing peers need consistent, privacy-safe signals that outperform on cost per outcome.

A premium publisher call to action

Traffic patterns will continue to shift as AI captures more queries on the results page. Brand safety systems will still misclassify legitimate journalism. Don’t fight these headwinds by creating more commodity inventory or compromising with looser data practices. Win with Calibrated Signal that gives you the power to stay in control of your data while proving you can generate outcomes for advertisers that matter. When you do, brands will discover what many already suspect – that the open Internet can outperform walled gardens when premium publishers make signal a product, not a by-product.

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Revenue | Supporter Spotlight

Why publishers are embracing tech consolidation

For years, publishers have relied on a patchwork of point solutions to manage subscriptions, consent, adblock recovery, newsletters, and more. Each solved a problem, but together they created inefficiencies, siloed data, and disjointed visitor experiences. This results in sites weighed down by multiple tags, overwhelmed teams, and insights lost between systems.

On publisher websites, this shows up as tag bloat. Scripts and widgets accumulate, dragging down performance and complicating analytics. An analysis of the top 200 marketing websites found an average of 12 tags per site. Some publishers reported 60–80 tags as typical, and in extreme cases the number of tags ran into the hundreds. Each additional tag adds latency, increases vendor management overhead, and compounds compliance risk.

The Reuters Institute’s Journalism, Media, and Technology Trends 2025 warns that technical debt is a growing concern. Site quality and personalization are “difficult, expensive, and time-consuming” when stacks are bloated. For publishers on lean margins, these inefficiencies are unsustainable. The solution, increasingly, is consolidation—streamlining vendors and functions into unified platforms that bring data, workflows, and visitor journeys together.

Why consolidation is gaining momentum

Economic pressures

The downturn in digital advertising and ongoing cost-cutting in media have forced publishers to scrutinize every contract. Across industries, SaaS spending shrank by 11% in 2023, with companies cutting their tool counts by an average of 8%. Redundant vendors are something few can afford.

Integration and compliance

Marketers report that after cost, integration is the top reason they replace tools—cited by 51% of respondents. Fragmented data not only limits insights but also complicates compliance with GDPR and CCPA. Larger, integrated platforms are often better equipped with consent management and privacy features built in.

Industry consolidation

The adtech ecosystem itself is shrinking. Publishers use an average of 19 SSPs. However, the ANA recommends cutting that number to about seven for efficiency. At the same time, standalone ad exchanges have been absorbed into broader supply-side platforms, leaving publishers to navigate fewer, but larger, partners. 

As Admiral CEO Dan Rua observes, “We’re seeing top publishers actively moving from six separate tags and vendors to a single consolidated stack, not just to cut costs, but to speed page loads, simplify vendor management, and optimize the entire visitor journey.”

Benefits of a consolidated ad tech stack

Cost savings

Eliminating overlapping licenses and contracts delivers immediate savings. HubSpot customer Liquidity Services cut software costs by 50% after replacing eight different tools with one platform, while also improving pipeline visibility by 80% and boosting email deliverability by 70%. Salesforce’s Total Economic Impact study found companies that consolidated saw more than $13M in net benefits, from lower tech costs to productivity gains.

Revenue growth

Ultimately, cohesion drives monetization. HubSpot clients reported 36% more deals closed after moving to the platform. In publishing, integrated content packages across consolidated media groups generate 30% higher audience engagement than siloed campaigns.

Admiral’s CEO emphasizes the performance angle. He says that, “Turning five or six disparate tags into one doesn’t just simplify operations—it directly improves site performance. That speed boost translates into higher conversions and more revenue opportunities for publishers.”

Unified data and analytics

Consolidation creates a single source of truth for audience interactions. Publishers can connect data from consent, engagement, and monetization touchpoints to see the full visitor journey. That kind of holistic view is impossible when data lives across half a dozen systems.

User experience

Fragmented stacks create jarring, redundant prompts—a consent banner from one vendor, a newsletter pop-up from another, a separate subscription wall later. Operating in silos, these tools often trigger targeting conflicts, overlapping pop-ups, and inconsistent styling—borders, fonts, and formats that don’t match, resulting in a disjointed, unprofessional user experience.

A consolidated platform coordinates these touchpoints into a seamless journey, where consent flows into registration and then subscription offers, all timed and styled consistently. The result is smoother interactions that reduce annoyance, build trust, and lift engagement and conversion.

Compliance, security, and vendor management

Fewer vendors mean fewer vulnerabilities and simpler consent recordkeeping, reducing the compliance burden for publishers under constant regulatory pressure. Just as important, consolidation streamlines vendor management: instead of juggling multiple contracts, account managers, dashboards, and data exchanges, publishers work with a single point of contact and unified support team. That efficiency saves time, cuts administrative overhead, and frees lean teams to shift focus from maintenance to innovation.

Challenges to Consider

However, consolidation isn’t without challenges. Publishers must weigh:

  • Vendor lock-in: Fewer vendors can mean greater reliance on one. Choosing platforms with open APIs and strong data portability is key.
  • Transition costs: Migrating off legacy systems takes planning. A phased approach, starting with a tech stack audit, helps minimize disruption.
  • Team adoption: Departments may resist losing familiar tools. Leaders need to frame consolidation as a win for everyone. Focus on the advantages of faster work, better insights, and less manual effort.
  • Publisher focus: Not every vendor understands the nuances of digital media. Some platforms are built for ecommerce or generic websites, but publishers need partners who know the demands of ad operations, audience engagement, subscriptions, and consent.
  • Customer service. A consolidated partner takes on more responsibility. Great customer support is essential when one vendor is handling multiple critical parts of the stack.

As one adtech executive told Campaign Asia: “Layered technology, by all means, presents a sustainability issue, and publishers are under pressure to streamline.”

Cohesion as the future

Consolidation has evolved beyond a cost-cutting exercise. It’s how publishers combat digital debt, improve agility, and build stronger relationships with audiences. 

Catherine Beattie, then Director of Digital Ad Operations at Encyclopaedia Britannica, summed up the operational need for consolidation:

“My dev team’s involvement has practically become a critical KPI these days. If they can do something once and be done, then I can iterate, work with product teams, and make adjustments without going back to that queue to beg for resources. That makes everything so much more efficient.”

In a competitive environment where margins are thin and complexity is rising, publishers that simplify and consolidate today will be better equipped to innovate tomorrow.

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AI | Supporter Spotlight

The year of now: an AI turning point for publishers

In the media industry, AI’s hype cycle has officially entered its hard reality era. As Arc XP’s Chief Technology Officer Joe Croney put it during our recent webinar Real Automation, Real Agents, Real Impact, 2023 was “the year of wow,” 2024 “the year of how,” and 2025 is “the year of now.”

AI in media has matured beyond experimental pilots and workflow quick wins. The question is no longer if you will use AI. It’s how you’ll use it to stand out in a marketplace where speed, volume, and even exclusivity are no longer differentiators.

Arc XP’s latest report with Digiday, surveying 108 publishers and broadcasters to understand how media organizations are incorporating AI into their newsrooms, confirms the stakes:

  • 97% of publishers are investing in AI.
  • 88% are prioritizing AI to elevate content quality, not just efficiency.
  • Yet only 1% have scaled AI across their organizations.

For the rest, the gap between AI experimentation and AI transformation is the opportunity and the risk.

Beyond automation: the rise of agentic workflows

The first wave of AI in the newsroom focused on automation by reducing labor time, accelerating production, and streamlining repetitive tasks. Those gains are real: 86% of publishers report reduced labor time and 85% report faster creation.

But the next wave, already underway, is about agentic workflows. Here, AI-powered assistants work in the background or are embedded in storytelling. They are designed to support journalists, not replace them.

Arc XP’s vision, as described by VP of Arc Intelligence Joey Marburger, is clear: “AI is like a junior reporter. Train it, guide it, but never expect it to replace your newsroom.”

In practice, this means agents that:

  • Check style guides automatically.
  • Suggest metadata and keywords in real time.
  • Surface relevant video, photo, and archival content instantly.
  • Summarize research while keeping humans in the editorial driver’s seat.

This “human-in-the-loop” approach is essential to maintaining trust, brand integrity, and editorial judgment, qualities AI cannot replicate.

Content has been commoditized. Insight has not.

Generative AI can repackage, summarize, and distribute stories faster than any newsroom. That means the old competitive advantages—speed, volume, and exclusivity—no longer guarantee audience loyalty.

What AI can’t replicate are journalistic instincts, mission, and audience. That’s why leading publishers are using AI to free up time for original reporting, local engagement, and audience-driven experimentation.

By pairing AI tools with secure, flexible, media-focused workflows, news organizations can focus on what machines can’t create: voice, context, originality, and trust.

Multi-modal storytelling for audience 3.0

Our State of AI in the newsroom report revealed AI is accelerating multimedia production—82% of publishers use it for video editing, 87% for image optimization. However, many remain dissatisfied with quality and consistency.

Arc XP’s AI roadmap tackles this head-on with a vector-based asset database, enabling instant retrieval of relevant photos, video clips, and audio. This makes it possible to reformat content across modalities, turning a text story into a video or podcast, or transforming audio interviews into publish-ready text, without sacrificing editorial quality.

This is critical for “Audience 3.0,” where engagement is immersive, adaptive, and co-created. In this environment, text-only strategies aren’t enough; audiences expect stories that move, speak, and adapt to their preferences.

An AI business imperative

AI isn’t just an editorial tool. It’s a business weapon. Our research shows forward-looking publishers are using AI to:

  • Personalize content delivery
  • Improve accessibility
  • Unlock new revenue streams by protecting and monetizing premium content from AI crawlers and bots

These capabilities are also part of a broader shift toward strengthening direct audience relationships. This is particularly important at a time when referrals are declining and chat-based AI platforms are changing how people discover content.

The clock is ticking

In 2025, the divide is clear: publishers who treat AI as a strategic advantage are redefining their markets. Those who don’t risk irrelevance.

The winning formula is already visible:

  • Treat AI as a platform, not a plug-in.
  • Align editorial, product, and engineering around shared goals.
  • Protect and monetize your intellectual property.
  • Prioritize originality, insight, and human voice over scale alone.

The transformation window is open now. But it will not stay open forever. The choice is stark: lead the market by building intelligent, human-centered AI systems that multiply your newsroom’s impact, or watch from the sidelines as competitors redefine the media business without you.

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