In the intricate dance of media evolution, 2024 marks a pivotal moment, when generative artificial intelligence steps into the spotlight, simultaneously leading and following in the rhythm of innovation.

This dance is not new. It echoes past transformations in social media where pioneers like BuzzFeed and Vice once led, challenging legacy media to adapt or fall behind.

The music, however, has changed, and with it, the steps. Here are three things we should keep in mind to start 2024.

The pendulum swings: paywalls and niche subscriptions

The business interests of media organizations are in a constant ebb-and-flow. The current dominant waltz has seen the steady rise of paywalls and regards subscription-based models as having ultimate value. This trend is a reaction to the social media years, with its pivots to video and audience attention as the ultimate key performance indicator.

As Sam Cholke, the manager of distribution and audience growth at the Institute for Nonprofit News, writes, “The last year has reminded many news organizations how brittle online audiences can be. Facebook traffic declined sharply in 2023, dashing publishers’ hopes that a long fall in referral traffic had finally plateaued.”

The social media epoch brought Vice, Mic, BuzzFeed, and others who promised investors they would master all social media trends and elbow out the competition for the kind of scale hitherto unimaginable to media companies. We’ve seen the results of that overreach. Eventually, a platform comes along that requires too much retooling, or monetization needs to happen further down the business funnel (such as subscriptions) and business leaders realize short-term audience attention isn’t fit for a cause. This cycle will rinse and repeat.

Now, as the pendulum swings towards exclusivity, a gap will eventually emerge for media organizations to again leverage mass audiences for a business advantage. However, this return to a mass audience won’t happen for a few years. The social years from 2008 to 2016 gave way to our current era. When the tide does turn again back to upstarts making a name for themselves by amassing large audiences it will look different from the aughts, as the technological emphasis will shift from social to generative AI.

The rarity of the human touch: AI-generated vs. unique content

As generative AI takes the stage in the production of content — from punchy headlines to tailored audience segments — it inadvertently elevates the value of human-created content.

I wrote about this in Poynter as a “proof of trust” premium that will be associated with provably bylined or printed content. Media analyst Mauricio Cabrera and others are also coming to this conclusion. “It might sound paradoxical,” Cabrera wrote, “but the future will require the media to be like magazines and print newspapers tend to be: with less content, but of better quality.”

Technology leader Ben Werdmuller used similar terms: “Newsrooms that commit to AI-driven storytelling as a way to cut costs while increasing output will be lost in a sea of similarly bland content and spammy marketing. Newsrooms that cling to traditional SEO and social media tactics will find that they become less and less effective in the face of more and more noise.”

The uniqueness of personally crafted bylines and narratives will become akin to rare art in a world of replicas. This will not diminish AI’s role in the future of content production, but rather complement it. Generative AI is not a panacea for content, but a new paradigm that will put value and emphasis on the human touch.

The next era of engagement journalism

Engagement journalism, a branch of journalism with a long and evolving tradition, will also find new life through generative AI. At its most basic, engagement journalism is about making the process of journalism more transparent and participatory.

While the first blush of generative AI applications is around producing traditional articles, it can also help to sift through public input, separating the wheat from the chaff, and revive old engagement tools like comment sections and tip lines.

Even more interesting would be the scalability of an AI editor that can craft narratives from a mosaic of public input. A question such as, “What do you think about the mayor’s proposal?” can go from “leave a comment” to “see what the public thinks en-masse” with relative ease. This evolution speaks not of AI as a creator in solitude, but as a collaborator and community builder, fostering deeper connections between the media and its audience.

In 2024, we stand at the cusp of a media renaissance, in which AI’s role is not just as a tool but as a partner in the journalistic process. This partnership calls for a delicate balance, ensuring that while we embrace the efficiencies and insights AI offers, we also preserve the irreplaceable value of human perspective and creativity.

As we navigate these waters, questions arise: How do we best integrate AI without losing the soul of journalism? Can AI be taught to understand the nuances of human experience that are often the heart of impactful storytelling? And most importantly, how do we maintain the trust of our audience in an era where the line between machine-generated and human-crafted content blurs?