AI is more than just a trendy buzzword; it’s a transformative force that will shape the future of media. From content creation to personalization and automation, AI is on the brink of revolutionizing how we both produce and consume news, and media organizations that are prepared to embrace AI stand to benefit significantly. In a recent webinar, I spoke with Arc XP Chief Technology Officer, Matt Monahan, to learn how the emergent technology of generative AI is unlocking new workflows, presenting and solving unique business challenges, and creating opportunities for growth within the digital media industry.  

Understanding generative AI 

Today, when we talk about AI, we often mean generative AI, a subset of deep learning, which teaches computers to think like humans, recognizing complex patterns in data. “Generative AI is really a transformer model and the models behind them, or what we call large language models (LLMs),” says Monahan. These models, such as Chat GPT, can handle tasks ranging from text generation to code creation, image generation, and even 3D modeling.  

The AI industry is currently in a hype cycle, marked by high expectations and significant investments. However, a growing awareness of the limitations of LLMs like Chat GPT, particularly within the media industry, has emerged. AI is not a magic wand capable of creating content from scratch with flawless accuracy. Automated story publication, without human oversight, presents significant challenges because these models are not designed for fact-checking or the introduction of new content; their core competency lies in predicting language.  

Despite these limitations, experimenting with generative AI provides invaluable insights into the evolving media landscape. Monahan stated, “The companies that spend time in experimentation today are going to be the ones who accrue benefit when they are ready to take advantage of it as the technology matures.” AI is a journey, and its potential is unlocked gradually as teams experiment, learn, and build competency.  

While integrating generative AI may initially feel like stepping through a one-way door, there are experiments that allow for exploration without irreversible commitments. By integrating human review processes alongside AI, companies can achieve a harmonious blend of efficiency and accuracy. Human editors bring essential elements such as context, fact-checking and ethical judgment to the table — qualities that AI lacks.  

Adopting AI in the newsroom  

Recognizing AI as not a distant future technology but a viable solution right now, many news organizations have already embraced LLMs in their newsrooms. With human review processes, they utilize AI for tasks including creating AI-assisted graphics and diagrams, drafting written content, and even generating turnkey content at scale, such as translations, financial reporting, sports coverage, and large dataset analysis. This integration of AI enhances their capabilities while preserving the integrity of their news reporting.  

One example of AI in action is its role in translation. Some media companies are already using AI to quickly create high-quality translations, needing little to no editing. This has allowed journalists to reach global audiences more efficiently by tailoring the same story to different readers. By implementing AI into their workflows, journalists are able to minimize their time spent on repetitive and time-consuming tasks, enabling them to focus on what matters – producing compelling and meaningful content that resonates with their readers.  

What to expect by 2030 

As news organizations take their first steps into the realm of AI, Monahan envisions a future where AI becomes the standard. “If you examine the pace of LLM development over the past three to four years, it becomes quite evident that the quality will improve at a rate beyond most people’s imagination,” he says.

Today, less than 1% of online content is AI-generated. However, he predicts that within a decade, at least 50% of online content will be generated by AI. This raises important questions: What does it mean for content to be 50% AI-generated? Does it represent content created entirely from scratch, content edited by AI, or content that has received AI assistance? These are questions that the media industry will need to address and define in the coming years.  

Looking ahead to 2030, Monahan anticipates several key developments: 

• AI will significantly cut the costs of content creation, encompassing written content, graphics, and video explainers. However, this shift won’t eliminate the need for human involvement, especially in crucial areas like fact-checking and quality assurance. 
• Content formats and user experiences will shift significantly, with personalized content becoming the norm. Media companies will need to adapt and innovate to meet these new demands. 
• Sports content will gain immense value as one of the few remaining sources of “original content” resistant to full automation. 
• Advertising will become hyper-personalized, delivering unique ads and commercials tailored to individual users.  
• With automated workflows and most of the code being generated by AI tools, every developer is expected to become an AI-assisted developer.  

Monahan emphasizes that embracing AI isn’t just about staying ahead; it’s about spearheading a future where AI elevates content creation, enriches user experiences, and reshapes the media landscape. By automating tasks in the newsroom, such as content creation and translation, AI empowers journalists to concentrate on their core mission: crafting engaging and meaningful content for their readers. The future of media is powered by AI, and those who harness its capabilities will lead the way in this transformative journey.