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AI is no longer a trend of the future. It is already embedded in newsrooms, integrated into news products and asking strategic questions about value, trust and differentiation. Yet many organizations still ask themselves: what is AI really good for?
The answer depends not on the technology itself, but on how clearly organizations define their problems and structure their responses. Where AI is really providing value is not replacing journalism: it is enabling humans to tell important stories more effectively.
Where AI is really helping: depth, reach and engagement
The most promising uses of AI in publishing are not about speed or volume of content production, but about insight, clarity, and accessibility.
For example, publishers are using AI to extend the reach of their content to new and more diverse audiences. Translation tools are evolving from word-for-word engines to systems that can adapt to tone, style, and local context – or at least prepare a draft for human review. This allows publishers to localize stories for specific markets or diaspora communities, without the need to linearly grow their newsroom footprint.
Publishers are also applying AI to external or unstructured datasets – provided they can be safely brought in-house – opening up new possibilities for deeper reporting. Some of the most impactful stories from the Financial Times involve applying AI to satellite imagery, or building the right technical infrastructure to organize massive datasets related to blockchain transactions. The human layer remains essential for interpreting results, but AI can accelerate the acquisition as well as analysis of this data.
New formats are another area of innovation. Whether it’s dynamic visualizations, sound synthesis or real-time explainers using conversational AI, AI can support more interactive and accessible storytelling. These reflect changing expectations about news consumption, particularly among younger or more mobile-first audiences.
Less glamorous but higher-value use cases
Some of the most impactful uses of AI are internal and often overlooked. At FT Strategies, we use AI for everyday tasks like summarizing meeting notes and sharing knowledge. These aren’t groundbreaking innovations, but they reduce conflicts and save valuable time between teams.
This type of enablement is often where media companies see clear, measurable returns. Instead of focusing solely on audience-facing tools, they benefit from improved workflow, documentation, and access to insights. This also builds confidence and capability throughout the organization.
Investing in the right foundational skills and infrastructure is essential. At the Financial Times, building in-house prompting flows and strengthening AI procurement processes (for example, identifying opportunities for different teams to share common tools) helped the team win Generative AI Initiative of the Year at the 2025 British Data Awards.
Capabilities exceed hype: what readiness really looks like
Adoption of AI is not only a technical challenge. It is a question of leadership and culture. The FT Strategies attitudinal survey, covering nearly 2,000 professionals across 20 media companies in EMEA, revealed a persistent gap between the amount of time available for training with AI tools and the attitudes set by senior management. Many journalists see the potential but lack the support to make meaningful use of it.
Leaders don’t need to solve everything at once. But they need to foster experimentation, empower their teams, and prioritize reusable capabilities, even if the immediate payoff isn’t obvious. For example, investing in technologies like vectorization could later unlock a whole range of AI tools. Ask FT – FT’s generative AI tool for answering readers’ questions, which combines new large language models with older vectorization techniques (in a so-called “RAG” approach) – benefits from such forward planning.
It’s also important to know when not to scale. Early experiments may fail for perfectly good reasons: the technology is not ready; The business model doesn’t support it; Or the real problem is different from how it first appeared. Teams that define clear goals and evaluation methods recover value even from missteps.
Rethinking value in an AI-shaped landscape
AI forces media organizations to rethink fundamental strategic questions. What makes your journalism worth paying for? What sets your newsroom apart from a world where content can be produced on the fly? Answers will vary. Some may grow into trusted brands focused on curation and verification. Others may specialize in formats, specialties or services that AI cannot easily replicate.
Whether you’re experimenting with content formats, integrating LLM into your workflow, or reevaluating your data capabilities, the goal isn’t to automate journalism. This is to protect its value while increasing its impact.
For all publishers, the emerging question is not just “how do we use AI,” but “how do we remain valuable and trusted in a world that uses AI?”
As publishers grapple with the promises and pitfalls of AI, the challenge is not only to adopt new tools, but to do so with purpose. At FT Strategies, we help organizations build the strategies, skills and structures to use AI responsibly, and in ways that strengthen their journalistic and commercial value.