TL;DR: AI will create more analysts, more firms and more authority. As research becomes cheaper to produce and easier to distribute, authority will concentrate around analysts with trusted expertise, strong networks and access to proprietary evidence. Analyst firms will need new commercial models to fund independent research, while AR teams must understand analyst influence on LLMs and look beyond firm size to map the people, communities, events and channels that actually shape buyer decisions.
AI is breaking the analyst research business model.
AI makes it easier than ever to become an analyst and harder than ever to make money as one. The barriers to analyst work are collapsing, the previous model of information asymmetry where analysts were the gatekeeper no longer exists. Research is easier to produce, information is easier to interrogate and distribution no longer depends on a large firm’s website or subscription base. While this could create more analyst voices, buyer attention remains finite and it’s harder than ever to cut through the noise of AI slop. The result? A flatter, more fragmented analyst market where far more people can participate, while only some build enough authority to sustain a business.
More analysts means a new distribution of influence.
AI lowers the barrier to entry, but not the barrier to relevance. Anybody with expertise, access to public information and the right AI tools can now produce credible-looking research quickly. Independent analysts also have LinkedIn, newsletters, podcasts and communities to distribute content without needing a large firm’s distribution model or formal research subscription behind them.
This creates the analyst equivalent of the podcaster economy. AI is the research equivalent of an Amazon microphone, making content production cheap. But earning enough attention and trust to influence technology buying decisions remains difficult. And just like the podcast industry, there will be many more voices than commercially successful ones.
B2B influence may become even more specialised.
Big audiences are not automatically valuable audiences. B2C influencer marketing has already moved beyond follower counts towards relevance, engagement and identifiable communities, allowing microinfluencers to sustain a brand. Analyst influence could move in the same direction.
The important analyst may be the biggest voice in a very small room. An expert who reaches a few hundred relevant enterprise buyers or a highly specific audience, like Dean Bubley for telco regulators, can matter more than somebody with tens of thousands of generic followers. We should therefore expect influential analysts to emerge around increasingly specific technologies, industries and buyer groups.
That creates opportunities for specialist firms as well as individuals. BARC in data, Fosway in HR tech, Dresner Advisory in BI, KuppingerCole in security and others already demonstrate that analysts do not need FIG (Forrester, IDC & Gartner) scale reach to become respected within a niche market. HFS and Constellation offer other models built around thought leadership, peer interaction and experience. There is a long list of analyst firms beyond the FIGs, and AI makes that wider market easier for buyers to discover.
Analyst firms will have to manufacture authority differently.
Analysts continue to have value that an LLM-generated report cannot manufacture: market authority. Proprietary evidence, end-user relationships, research methodology, communities, events and institutional trust are precisely what make analysts VIPs –very influential persons. The firm’s job becomes creating the environment in which individual analysts can build defensible authority.
Gartner shows that the established model can evolve rather than disappear. It combines research with peer reviews, advisory, major destination events and increasingly AI-enabled research access with AskGartner. The interesting point is not that Gartner represents the past. It is that even the largest incumbent is changing how its expertise reaches people.
AI is already Napster, now the analyst industry needs its Spotify.
AI has created a Napster moment for analyst research. Research that once sat behind subscriptions can increasingly be searched, summarised and surfaced through LLMs and MCP connectors. That potentially exposes analysts to a much wider audience. We have written about the Napster analogy before, so we will not labour it here.
But the industry still needs its Spotify. Music streaming massively expanded distribution without making music worthless, but it changed what artists could monetise. Analyst firms face a similar shift towards advisory, consulting, events, peer communities and other experiences around the research. The precise mix will vary by firm and by market.
Research still needs somebody to pay for it. If end-user subscription revenue falls, analyst firms need another way to fund serious, independent research agendas. Vendor revenue can form part of a healthy mix, but over-reliance creates an obvious tension between commercial incentives and independence. The winning model must expand reach without undermining the trust that made analyst influence valuable in the first place.
Analyst expertise becomes the authority.
The report is no longer necessarily the destination. It can establish expertise, train an AI interface, support an inquiry, inform a keynote and give a peer community something substantive to debate. One piece of open source research can travel much further than the PDF reprint ever did, and substantially further than the physical ones of the early days. That makes research potentially more influential even as it becomes harder to sell on its own.
The experience around the research becomes more important. Buyers can ask an LLM for a market summary in seconds, but they still value access to somebody who has spoken to dozens of customers, challenged competing vendors and watched the category evolve. Inquiries, peer groups, advisory days and analyst firm events turn static knowledge into judgement applied to a specific decision. That is much harder to commoditise.
Events are particularly well suited to this new model. A research report may reach hundreds of relevant readers while a major keynote, webinar or destination event can put an analyst in front of thousands. Events also create something AI cannot reproduce particularly well: proximity, debate and relationships. As digital research becomes easier to consume, those live experiences become more rather than less valuable.
AR needs to map authority, not analyst firms.
For AR teams, the analyst market becoming more open is good news. The FIGs remain enormously important, but they are no longer the only routes through which analyst thinking reaches buyers. Specialist firms, independents, communities, events and LLMs all add new paths into the sales spaghetti monster. Your analyst strategy needs to reflect that wider reality.
Stop assuming firm size is a proxy for influence. Ask which analysts your actual buyers encounter, whose frameworks they repeat and whose events they attend. A niche analyst with extraordinary authority among 300 relevant buyers may matter more to you than a famous name with a much broader audience. The right analyst for the job becomes an even more important principle when distribution is fragmented, so don’t tier with prejudice.
And continue the conversation beyond the research calendar. Analyst influence increasingly happens through conference stages, webinars, social channels, peer groups and AI-powered discovery as well as formal reports. Marketing and AR should work together to create content and experiences that reinforce credible market authority across those touchpoints. The objective is not to manufacture noise, but to remain present wherever serious buyers are trying to make sense of the market.
Read the latest Starsight Transmissions.
- What is the future of analyst research in the age of AI & GEO authority?
- Why is your content failing? And how B2B tech industry analysts can help.
- Analyst relations: the discipline investors now mandate for their B2B tech startups portfolio.
