There continue to be widespread discussions about the future of digital media and what shape it will take. There is consensus, however, that continued revenue diversification beyond free content funded by advertising is a must and that offering differentiated value to audiences – something they can’t get elsewhere – is critical to survival. 

Delivering a diversified strategy with reduced staff and less revenue requires efficiency and no one can argue that AI promises that! If 2023 was about considering and understanding AI’s capabilities, ethical implications and potential impact, 2024 will be the year companies implement. For more on how digital media companies integrate it into their strategies, check out our ‘AI in digital publishing’ report.

Digital media today

It’s been widely reported that it’s been a tough twelve months for digital media. Buzzfeed shut its Pulitzer prize-winning news desk; Vice has ceased to publish on Vice.com, and widespread efforts to reduce overheads have resulted in thousands of layoffs globally. Vox Media, the owner of The Verge and New York Magazine, cited uncertainty in the ad marketplace and readership as its reasons, which Condé Nast echoed as it made cuts across its portfolio, including at the normally bulletproof New Yorker Magazine. 

It’s no secret that referral traffic from search and social is either declining or flatlining – digital media has long been at the whim of social and search engines’ algorithmic changes – and the end of third-party cookies is in the process of dealing another blow to the digital advertising revenue that was long the primary source of media companies' income.

On top of all that, there has been a massive shift in consumer attention. Millennials who would faithfully return to their favourite sites for trusted information, hot takes and irreverent listicles could now find those on social media platforms. Gen Zers never thought of finding it anywhere else.

The digital media companies left serving discreet audiences are the legacy publishers that remain trusted because they offer high-quality journalism like the New York Times and those with smaller, niche but engaged returning audiences – Vittles, Copa90, etc. At both ends of the spectrum, they're focused on offering something unsubstitutable to their audiences instead of joining a race to the middle as in the 2010s when similar sites vied to sweep up traffic by publishing news first and creating clickable lists with in-built social shareability.

Digital media differentiation and diversification

In a world of increasing media consumption, where digital publishers are no longer solely competing against each other for audiences but against social and streaming platforms too, there is consensus that differentiation and diversification may save the industry. 

Differentiation in this context is a byword for branding: digital publishers must have a clear modus operandi informed by the value they offer their audiences, and they have to ensure this runs through all of their touchpoints. Once established, building diversified revenue streams becomes a case of delivering on that promise in the formats their audiences want to consume – video, events, FAST channels, paywalled personalized content, and branded partnerships.

AI will be one of the ways digital publishers and media companies drive efficiency as they look to overcome the challenges of their shifting business model. However, companies are still in the process of considering how and where AI should be applied.

Journalists remain concerned about what AI means for the future of unbiased journalism and the rise of identikit content designed for algorithms rather than readers. In the era of fake news and low audience trust, finding a balance between AI that increases efficiency without jeopardizing media companies' editorial proposition is at the top of publishers’ minds. Its application in journalism is predominantly within content distribution and repurposing, as opposed to its wholesale creation.  AI for content creation remains an ethically tricky topic that many media companies are still grappling with.

The first overarching benefit of AI in the media industry is its ability to streamline internal processes and declutter complex workflows, freeing employees to focus on high-value work that requires human analytical and creative skills. 

According to this hypothesis, it makes sense that AI tools and services are most easily implemented, and their impact is measured within content distribution, that is, to ensure human-created work reaches the widest audiences. For example, it is used to adapt existing content for multiple social media platforms across various devices, tailor content to users' preferences, or dub existing content for audiences abroad that have engaged with content in its original language. Where and how companies interact with audiences to highlight their differentiated offering will ultimately drive engagement and increase audience loyalty. 

AI to evolve content creation

While there is scepticism around using AI in the wholesale creation of content, it enables publishers to streamline the processes. Tools like AI chatbots for research, speech-to-text applications for transcription and AI dubbing tools to create voiceovers for content that would otherwise be subtitled are all examples of how AI is optimizing the creative process. 

It’s common for these tools to be used individually, but their power arguably lies in their integration to reduce content’s time to market. Tools like Zapier and Make connect tools to automate repetitive, time-consuming tasks 

AI in content distribution: growing audiences

Declining search and social traffic has necessitated a shift in strategic approach to content distribution. Publishers increasingly rely on AI to personalize content recommendations based on first-party data and enhance content discovery via customized AI search tools. 

With the imminent end of third-party cookies, growing the reach of content and deepening engagement are crucial to publishers’ ability to monetize. For example, Hearst uses its digital membership model to grow its e-commerce marketplace. Insider and Bloomberg use Papercup’s AI dubbing technology to expand their global audience by making content accessible in multiple languages. Not only does dubbing existing content drive non-English speaking engagement, but it also allows these publishers to expand the total addressable market willing to buy into their other offerings – events, e-commerce, ads, etc.

Monetizing content with AI

AI tools are instrumental in optimizing monetization by creating a more efficient and lucrative publishing model: AI improves ad conversion rates through dynamic ad placement based on first-party data. Still, successful monetization also relies heavily on driving brand affinity and engagement with global audiences that can buy into media companies’ various offerings.

Summary

Figuring out a differentiated media offering and producing content based on that playbook relies on the creativity of humans informed by data. In 2024, ensuring that content is curated based on audience preferences, delivered in the formats they are most likely to consume, and in the language they prefer will be the thing that drives affinity and engagement. When audiences already value a brand, revenue diversification becomes an exercise in content adaptation, which should be AI-assisted for efficiency. 

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