Content licensing has long been an important revenue stream for digital media companies. For decades, it allowed publishers to monetize their content by granting rights for others to republish or repurpose their material, evolving from licensing to aggregators, databases, social platforms, to streaming video services.  Now, content licensing faces another evolution: artificial intelligence (AI).

Digital media publishers are finding themselves in a unique position in that they possess decades worth of quality content AI companies crave. “Over the next few years, content creators and AI companies will deepen their relationships,” predicts Yulia Petrossian Boyle, founder and principal of YPB Global LLC and FIPP chair. “However, as AI players try to secure more original content, those relationships will need to transition from one-off deals to well-structured, ethical partnerships with strict IP protection and meaningful ongoing revenue for publishers.”

TIME’s COO Mark Howard believes that publishers currently have three ways they can approach the AI dilemma: “You can do nothing. That’s just not something we would consider, to sit on the sidelines and just let everybody else figure it out. The other two options are to litigate and negotiate. Litigation is a very, very large commitment… So, that leaves negotiation.”

For some media companies, AI licensing agreements offer an alluring mix of copyright protection and monetization opportunities as DCN contributor Damian Radcliffe points out. And, as they negotiate these deals, publishers are discovering they must balance the potential for monetization with the need to protect intellectual property rights, navigate complex legal challenges, and ensure responsible AI usage. 

Fair value in AI content licensing

According to a recent INMA report, executives considering licensing deals need to understand the value of their content in an AI-driven market. Then they have to negotiate attribution and compensation models that align with business goals. The report recommends collaborating with industry peers to create standardized agreements. It emphasizes the importance of advocating for responsible AI practices, including transparency in data usage. 

The report also highlights emerging licensing models, which include direct licensing, value-in-kind partnerships, training fees, bundled partnerships, and per-use compensation. Boyle notes promising approaches, like “data-as-currency” deals, where AI companies offer analytics in exchange for access to their platforms and services (in some cases in addition to some smaller flat fees). 

“Revenue-sharing is on the rise, where publishers earn a portion of subscription revenue or performance-based compensation (based on lead-gen, or engagement analytics),” she says. “For example, Perplexity AI’s Publishing Program launched in July 2024 offers revenue share based on the number of a publisher’s web pages cited in AI-generated responses to user queries. Those in the program earn a variable percentage of ad revenue generated per cited page.”  

Boyle says that, while compensation models are improving, she worries that AI companies do not adequately compensate for content that has higher production costs, such as investigative journalism. She points to pushback from publishers like Forbes, who rejected the Perplexity proposal.

Negotiating with AI companies on behalf of her consultancy, Boyle has observed that offers by some AI companies for training datasets are insufficient. “Since agreements are not indefinite, it is unclear to me how publishers will be compensated in future when AI companies may no longer need training data for their data sets.”

In her opinion, current compensation models between major AI companies and publishers do not adequately reflect the significant investments that publishers make in creating original content. She believes compared to the substantial amounts AI companies invest in technology, such as chips, their expenditure on content seems disproportionately low. This disparity highlights a need for a more balanced financial recognition of the value that original content creators bring to these partnerships, she says.

However, striking these deals isn’t simple. Howard notes that each one is different, each has different monetization models and philosophies on revenue sharing. 

“Some of them are flat fee for training, some of them are variable based on user adoption of their own products, and some of them are based on future ad models that haven’t even launched yet,” Howard says. “Many of them have some form of value-in-kind around technology or technology resources, which makes me very excited. I think that that may end up being where most of the value is derived in the long term.”

TIME for an active role in AI negotiations

Over the last year, TIME has struck deals with six AI companies, including OpenAI, Perplexity and ProRata.ai among others. The 101-year-old global media brand also launched TIME AI in December, an innovative platform developed in collaboration with Scale AI, that tailors content to individual readers. 

A few of TIME’s AI partnerships are infrastructure-based, like Fox Verify, which uses their blockchain-based technology to verify all of the content TIME publishes in the CMS. This provides them with a ledger of all of their intellectual property going forward. After that, according to Howard, they worked with Tollbit and Scalepost to track and monitor all of the AI bots on TIME’s site any given day and see what they’re doing. 

Access to technology is a key benefit of TIME’s AI partnerships for Howard. “We’re partners of theirs. I have direct access to their CTO and their senior leadership team. We get to hear what… they’re thinking about the market, that’s a really valuable conversation for us to have.”

“We brought money in as a result of these deals,” he says. “I’m happy about what we brought in. Some of it is fixed, a lot of it is variable and a lot of it is access to product resources and technology.” 

Factiva puts trust first in its AI licensing

Dow Jones launched Factiva Smart Summary in November, a groundbreaking feature in its business intelligence platform engineered with Google’s Gemini models on Google Cloud. Smart Summary leverages generative AI technology to create concise summaries for Factiva users that are fully transparent and traceable, utilizing licensed content from each of their publishing partners.

To do so, Factiva approached every one of its nearly 4,000 sources in 160 countries with licensing agreements. “We did this because we are a publisher first and arbiter for publishers… We won’t ask any of our publishing partners to do anything that we’re not prepared to do ourselves,” explains Traci Mabrey, general manager of Factiva. “As such, we have elected and will continue to elect, to reach out to publishing entities and request additional licensing permissions and actual rights for generative AI use.” Today, its marketplace includes more than 5,000 partners. 

Dow Jones emphasizes the importance of respecting and compensating intellectual property and content creation. Mabrey outlines four key criteria guiding their AI partnerships: trust, transparency, segmentation, and compliance. 

“We believe that trust is imperative. We believe there needs to be transparency in terms of content being created, used, surfaced and attributed,” Mabrey says. “There also needs to be relative segmentation in terms of use cases across different solutions. And there needs to be compliance and governance to adherence to the first three, of trust, transparency and segmentation.”

Deal points when licensing content for AI training

There’s no one-size-fits-all model for licensing deals, and the best approach depends on a publisher’s specific goals, content, and resources. Some determine how easily an LLM can integrate into their existing systems and CMS. Some choose LLMs based on those they already deal with.

But, data privacy and security are central concerns in these agreements. Vadim Supitskiy, chief digital and information officer at Forbes, told Digiday that ensuring interactions with AI products remain safe and protected is a key priority.

Mabrey echoes this sentiment, emphasizing that privacy and security are integral components to negotiations with AI partners. “As we’re looking at responsible delivery of AI, responsible usage of content and privacy and security in terms of technical infrastructure, that is our leading indicator.”

Publishers must have review rights over AI-generated outputs, ability to see proof of usage logs, and be able to enforce brand guidelines, according to Boyle. “All those things have to be clearly defined in the licensing agreements. Tracking metrics of engagement, attribution, and demographic insights is also important for publishers to receive, to be able to see how valuable their licensed content is,” she says.

Essential safeguards in the agreements themselves ought to include strong, sophisticated clauses to protect publishers’ IP, says Boyle, “including mechanisms to prevent unauthorized reproduction, clear ownership definitions, restrictions on data usage, well defined termination provisions, attribution and fair compensation.”

Howard emphasizes that no two content licensing deals with AI companies are the same, and each comes with significant legal and technical hurdles. “First, there’s the legal aspect and every company needs to come up with their own legal terms and what is acceptable to them and what is not. What do they have the rights to? What do they not have the rights to?” he says. 

“Once you’ve determined all of that, you need a technology solution to be able to deliver the content to them… All of the delivery mechanisms are quite different and require some form of customization.”

These complexities point to why AI companies have slowed the pace of new licensing agreements after an initial rush. Negotiating unique terms and building tailored tech solutions for each partner has proven difficult to scale, Howard notes.

Where AI licensing is headed

AI is reshaping how content is distributed, discovered, and monetized. For media companies, the choice is clear: engage in legal battles or proactively negotiate terms that ensure fair compensation. The market is rapidly evolving with new players, technologies and partnership models. 

For companies currently negotiating content licensing deals with AI, Howard says to move forward. He points out that, while there are benchmarks based on what other companies have secured, the initial rush of deals has likely passed. He doesn’t expect future deals to improve; in fact, he thinks they’ll probably get worse.

Mabrey believes that the industry has reached a unique inflection point, where generative AI gives it the chance to assert that content is intellectual property and requires compensation. “We, as a media community around the world, should be coming together to assure that all of us are asserting our rights in the same manner.”

In light of these shifts, there’s a clear message for media executives: the future of content licensing is in their hands. Instead of letting the industry define them, publishers can shape the future of the industry by hammering out a windfall through litigation and the courts, negotiating partnerships, and advocating for fair treatment.