By Joanna Levesque
Artificial intelligence is often discussed in extremes: either as an existential threat to creative industries or a miracle productivity tool that will replace half the workforce. In reality, for media, information and events companies, AI is neither. It is a profound shift in how value is created, distributed and captured – a golden opportunity to realise near-term efficiency and reach while laying the foundations for business models that can evolve and sustain growth in a new discovery landscape.
Over the past decade, publishers and information providers have spent much of their time playing catch-up with platform dynamics. The rise of search and social media gave unprecedented reach but gradually eroded control. Today’s AI revolution brings both a reckoning and a reset. While generative systems are changing how people find and consume information, they also open new routes to differentiation, efficiency and growth. AI is already proving its worth inside organisations. The greater opportunity lies in how it reshapes business models– from ownership of discovery to the creation of entirely new forms of value.
Where AI really adds Value
The most meaningful impact of AI in publishing today is not about replacing journalists or analysts with machines. Itlies in extending human capability to improve clarity, depth and speed.
Expanding reach
Translation tools have evolved far beyond literal conversion. Modern AI systems can adapt tone, context and even cultural references. For publishers and events businesses, this means the ability to localise stories, reports or session summaries for specific regions or professional communities without proportionally increasing staff. A single piece of journalism or event content can now travel across markets with minimal friction, opening new audiences and revenuepotential. The opportunity for many publications to access a diaspora audience is one example of how we are seeing publishers leverage this, and this is being grasped by south asian publishers already.
Deepening insight and analysis
AI also accelerates investigative and analytical work. Publishers are using machine learning to extract insights from complex datasets – satellite imagery, blockchain transactions, environmental data – where manual analysis would be prohibitively slow. The human layer remains essential: judgment, editorial sense and ethical framing. But the time saved on collection and structuring allows teams to focus on interpretation and storytelling. Recently the Financial Times published a series of stories on MPs’ interests based on the publicly available material in the Register of Members’interests. Bringing the diverse formats within the register together was possible faster and more accurately than previously releasing time to bring the stories together.
For information and research providers, similar methods are turning raw data into decision-ready intelligence. Structured extraction, summarisation and anomaly detection can reveal commercial or policy patterns far faster than traditional methods.
Innovating in format and storytelling
AI is also unlocking new forms of storytelling and audience engagement. Voice synthesis and dynamic visualisation enable journalists or analysts to produce explainers and interactive summaries that match changing consumptionhabits. Conversational interfaces – where audiences ask questions and receive verified, contextual answers – are beginning to bridge the gap between news, knowledge and utility. For the Financial Times, Ask FT has been delivering quality summaries of information from our archives for many months now and is a clear tool for engaging readers.
For event organisers, generative AI can extend the life of a conference or panel by transforming recorded sessions into searchable transcripts, highlight reels or thematic summaries. The line between live experience and knowledge productis starting to blur.
Unlocking internal efficiency
The less glamorous side of AI is often the most valuable. Automation of routine tasks – from meeting summarisation to knowledge retrieval – saves hours of unproductive work. In organisations where time is the scarcest resource, thesesmall gains accumulate into cultural change. Teams become faster, better informed and more confident using AI in their day-to-day work. One colleague described to me that they measured AI Return on Investment as “painful hours saved”.Surely we all have tasks that we’d like to have automated.
This combination of audience reach, analytical depth and operational efficiency explains why AI is already improving margins and morale in leading media companies. But the story does not end there. These short-term efficiencies are also building the foundations for a more profound shift in how discovery, trust and value will operate in the decade ahead.
Inflection Point: Discovery with AI
AI is already proving its worth inside organisations. The greater opportunity lies in how it reshapes business models– from ownership of discovery to the creation of entirely new forms of value. If the first wave of digital transformation was about distribution, the next is about discovery. For two decades, the web’sdiscovery layer – search engines and social platforms – defined how audiences found content. Publishers produced; algorithms delivered. That model is now breaking.
AI-generated “answers” in search engines are reducing click-through traffic across the industry. Consumers areincreasingly satisfied with summaries or conversational responses. Fewer users reach the original sources; more staywithin AI interfaces. Similar dynamics are emerging in research, education and event discovery, where generative tools surface insights without crediting or compensating the original provider.
From the user’s perspective, this represents convenience. From the publisher’s, it is a structural shock. Discovery no longer guarantees engagement, and reach no longer guarantees revenue. The behaviour of audiences – and algorithms– is fragmenting across a widening set of touchpoints: AI chatbots, messaging apps, short-form video, and emerging multimodal platforms. This fragmentation forces companies to decide how and where they wish to be discovered. The question is no longersimply how to grow traffic, but what kind of audience relationships are worth owning.
FT Strategies frames this as a two-axis choice:
- Distribution – whether a company retains direct access to audiences or relies on intermediaries.
- Audience need – whether it primarily serves utility (information) or identity (entertainment and community).
The resulting four archetypes – Niche Specialist, Intelligence Provider, Voice-led Brand and Mass-Reach Publisher – each imply different capabilities and risks. A subscription-based business might thrive through direct relationships andhabit-forming products. A data-driven information provider could license structured feeds into AI ecosystems. Voice-ledfranchises rely on personality and community. Mass-reach players chase scale across platform environments.
The critical point is that AI discovery collapses the old hierarchy. No single model dominates. The winners will be those who diversify intelligently across these positions, balancing owned control with selective embedding in third-party ecosystems.
From efficiency to advantage
Operational gains from AI – the faster workflows, the improved reach – are only the beginning. They are steppingstones towards more defensible, higher-value business models.
Building the foundations
Capabilities such as prompt fluency, data literacy and safe experimentation are not peripheral; they are prerequisites. Organisations that treat early AI pilots as learning investments, rather than isolated projects, accumulate reusableassets: clean data, shared tools and experienced teams. These become the platform for strategic differentiation later.
Owning trust and distinctiveness
For those operating in the Niche Specialist quadrant, the opportunity lies in doubling down on depth and habit. As AI systems summarise surface-level information, human expertise and reliability grow in value. Trusted brands that provideverification, context and consistent tone will retain audiences seeking assurance rather than novelty.
Meanwhile, Voice-led Brands can lean into personality. In a world of synthetic sameness, human perspective is thepremium product. Podcasts, newsletters and community-driven formats can turn affinity into membership or sponsorship revenue.
Becoming the infrastructure
For Intelligence Providers, the real breakthrough is becoming part of the information infrastructure that underpins AI ecosystems. Structured, high-quality data – enriched with metadata and provenance – can be licensed to aggregators, research tools or generative models under transparent agreements. As retrieval-based licensing evolves, publishers and event businesses that can measure and monetise where their content surfaces will gain recurring, scalable income.
Events companies, for example, could transform session transcripts and delegate interactions into structuredknowledge feeds for professional databases. This turns ephemeral experiences into enduring data assets.
Balancing reach with resilience
Mass-reach players – or anyone dependent on advertising and platform distribution – face the greatest volatility. Yet even here, AI offers options: better content tagging, smarter contextual ad placement, and improved prediction of what drives attention. The long-term challenge is converting transient visibility into repeat engagement within owned channels, where brands control the experience and the data.
A unified lesson
Across all quadrants, the strategic logic is the same: use today’s efficiency gains to invest in tomorrow’s defensible advantage. AI shortens cycles, but it also raises the bar for differentiation. The organisations that win will be those that convert automation into time – time to understand their audiences better, experiment more, and design business models aligned with new patterns of discovery.
What readiness looks like
The technical barriers to AI adoption are falling; the cultural ones remain. Many media organisations recognise the potential of AI yet struggle to allocate time and focus for meaningful experimentation. Leadership therefore matters more than technology. Executives must set a clear vision of why AI matters, definemeasurable goals, and empower teams to test and learn. Early pilots will fail – sometimes because the technology is immature, sometimes because the real problem lies elsewhere. What distinguishes successful adopters is their ability to extract insight from those missteps and redeploy lessons at scale.
Investment in foundational skills is equally critical. The Financial Times’ own success with tools such as Ask FT, which combines large language models with earlier vectorisation techniques, reflects years of quiet work on data governance and shared infrastructure.
These enablers made subsequent innovation cheaper, safer and faster. For smaller organisations or event businesses, readiness means identifying reusable processes – from content taggingto metadata standards – that can support future AI use. Culture, capability and clarity of purpose are the real competitive moats.
Time to reimagine value
AI is not a passing trend or a marginal tool. It is an accelerant that exposes where value truly resides. For media, information and events companies, that value lies not in volume or virality, but in trust, context and the ability to turn knowledge into action. The industry is entering a decisive phase. Companies that treat AI merely as automation will see diminishing returns. Those that integrate it into their strategic fabric – aligning experimentation with clear business objectives – will capture the upside.
This requires executives to make deliberate choices about where to play: to own their distribution or embed within ecosystems; to focus on depth or breadth; to invest in infrastructure or identity. Each path carries risk, but inaction carries more.
AI can, and should, be the catalyst for rebuilding control, trust and value across the information economy. The realgolden opportunity is not in using AI faster, but in using it smarter – to redefine what makes your organisation essential in an AI-shaped world.
FT Strategies report : “The Future of Discovery, Strategic business model choices for Publishers“. November 2025
Joanna Levesque is managing director of FT Strategies
