Deloitte AI Institute

The Future of Publishing in the Age of Generative AI

Strategically leverage AI in content production and secure intellectual property rights to avoid publisher extinction

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Generative AI is potentially an extinction-level event for publishers who do not move quickly to strategically use AI in content production and secure intellectual property rights

Generative AI is expected to disrupt the publishing industry on multiple fronts, and survival will likely require executives to adapt with a transformational mindset. Because Generative AI can create unique content with computer speed, it is poised to drive a tectonic shift in market forces underlying the traditional publishing ecosystem of advertisers, strategic partners, and core business functions.

Publishers should reconsider fundamental questions regarding their business, including:

  1. How are the economics of intellectual property and archival content changing?
  2. What is the outlook for web traffic and ad revenue when information is increasingly sourced from the search engine itself?
  3. How can a publisher maintain its brand and value differentiators as AI-generated content floods the market with increasing quality, depth, and breadth?

While Generative AI is just emerging, it is clear it will likely impact publishing in these three key areas, and companies should move now to seize opportunities and plan for risks.

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Increased access to content archives enhances value

Publishers face critical decisions regarding the use of their archives, offering high-value experiences to readers while protecting the value and security of their intellectual property. AI models trained on archival data unlock new capabilities for readers and writers to rapidly access, summarize, personalize, and query the institution’s historical knowledge. Some publishers are currently negotiating deals with Generative AI model providers for mutual gain around usage of archived stories to further expand the knowledge sources of Generative AI-based applications such as ChatGPT.

An example of an archive-search use case that can be enabled with Generative AI is when a subscriber can prompt an application trained on the publisher's archives to retrieve specific historical context to a story they are writing on a local issue previously covered by the publisher (e.g., school board policy changes).

As Generative AI enables enhanced reader experiences with new interactive capabilities including archive content summarization personalized reader Q&A functionality to drill deeper into stories, publishers can solidify their position as the “content discovery”

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Key questions for publishers to consider include:

  • How can archives be used to serve more relevant and personalized content?
  • How can Generative AI enhance reader experiences and drive new subscriptions/renewals?
  • How can archives be used to train and product-ize Generative AI models?
  • What is the right balance between public archive availability for readers and proprietary knowledge?
  • Are there partnership opportunities with non-competing publishers to enhance archival value?
  • What agreements should be made with Generative AI ecosystem vendors to share/sell archives?
  • How can these deals be structured for publishers to maintain the value of their archives?

Search behavior shifts from clicking-out to in-platform experiences

Even prior to Generative AI’s influence, search engines returned responses tailored to the user’s query intent and altered the impact of Search Engine Optimization (SEO) tactics on gaining clickthrough (e.g., 47.4% of all internet traffic in 2022 came from bots). Today, half of all search queries result in no clickthrough to the host site’s information, and evolving capabilities are pushing the trend further forcing publishers to seek legal retribution from search providers.

Generative AI is expected to accelerate the quality and accessibility of information available in the search platform, evidenced by a nearly 16% increase in page visits following one search provider’s ChatGPT integration. Plug-ins such as ChatGPT Web Browser enable chatbots to browse the web and access current news stories in conversational dialogue, providing a single web platform for the user to interact with. In their current form, these solutions present significant risk to publishers’ revenue streams.

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Publishers should consider new ways to reach and monetize their readerships to maintain relevancy

Consider these crucial questions:

  • As user search behavior shifts towards interactive search bots, how can we drive more website traffic?
  • How can we monetize content, given fewer opportunities to show digital ads?
  • How might we tailor content to be featured by Generative AI-powered search engines?
  • How will advertisers partnering with Generative AI vendors to build AI-enabled advertising content engines affect the digital advertising landscape (e.g., WPP & NVIDIA)?

To address these challenges, publishers could explore partnerships with chatbot platforms to help ensure compensation for intellectual property and seek innovative ways to deliver ads alongside generated content.

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An AI-augmented, next-generation journalist can drive productivity and quality in content creation

The explosion of AI-generated content presents opportunities and challenges for publishers, including new technology ecosystem partners (e.g., Google Tests A.I. Tool That Is Able to Write News Articles). With Generative AI capabilities, such as writing first draft of content based on approved news sources, archive-search capabilities, or aggregating information from thousands of sources in a personalized and meaningful way considering the tone and style most appropriate to a target audience, publishers can increase journalists’ productivity by automating portions of the content lifecycle.

As research and writing become increasingly augmented by Generative AI models, journalists can evaluate the generated content for accuracy, style, and comprehensiveness before finalizing the article for publication. Once finalized, Generative AI models can additionally be trained on regional data to hyper-localize the message for readers through language translation, dialect intricacies, latest news integration, and more.


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The maturity of Generative AI tools will likely continue to improve as publishers developing working relationships with model providers to license archival material in model training, and journalists from new and established players adapt their working styles to the technology. We expect a flood of content as competitors look to disrupt the industry by targeting reading attention with speed and cost advantages, and consequently amplifying the risk of misinformation.

As content volume and misinformation increase, a trusted information provider becomes more valuable and empowered to drive subscriber loyalty.

Leading publishers should establish a Generative AI nerve center to institute trustworthy policies around the technology, assess vendor Generative AI model vulnerability and risk, and optimize their publishing processes with new Generative AI capabilities while maintaining humans-in-the-loop.

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Winning in a Generative AI world requires a strategy refresh

To prosper in a Generative AI era, publishers must adopt a strategic approach rather than relying on short-term tactics or a wait and see mentality. Without a thoughtful strategy, the following challenges will likely only intensify and narrow the window of opportunity. Publishers could experience:

  • Tradeoffs of providing increased archival access to readers while protecting IP
  • Loss of advertising revenue from decreased traffic
  • Value differentiation given rapid content creation capabilities and new market entrants
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The publishing industry is recognizing the transformative power of Generative AI and embracing its potential to enhance productivity, experiences, and intellectual property value. Now is the time to formulate and execute comprehensive strategies, including:

  • Offering and content creation process transformation and tooling
  • Archive usage and new content monetization strategies
  • Strategic content and technology partnerships with Generative AI vendors and other publishers
  • Generative AI technology design, implementation, and operational requirements
  • Governance and usage policies to reinforce brand trust and minimize liabilities

Doing so can help publishers secure their future in this rapidly evolving landscape.

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