Consulting and IT Services Firms: Get Recommended by AI

Before sending a request for proposal to three IT services firms or consultancies, a growing share of B2B buyers now ask ChatGPT or Perplexity to draw up a shortlist first. According to a Gartner survey of 645 B2B buyers (fielded August-September 2025, released May 20, 2026), 45% used generative AI during a recent purchase, mainly to gather information on vendors and products, and buyers now rely on an average of seven information sources before deciding.

For a consulting firm or an IT services company, that informal shortlist plays out on different ground than it does for software: no product page, no listed price, no feature comparison table. What the AI synthesizes is what the web says about your credibility to run a project. Here is what shapes that answer, why the brand name alone is not enough, and what a firm can actually do about it.

Why consulting and IT services firms are a special case for AI

A buyer comparing CRMs gets a list of named products from ChatGPT, with strengths and limits; we cover that mechanism for software vendors in our guide on B2B SaaS recommended by ChatGPT. A buyer looking for an IT services partner for a cloud migration, or a consultancy for a digital transformation, does not get the same thing: there is no catalog to compare, only providers whose relevance depends on the industry, the project's scale and the technology involved.

The AI therefore has to judge credibility rather than read a spec sheet. It does so the same way it handles any brand: by searching the web, picking the fragments it judges reliable, then synthesizing an answer. We describe this mechanism in detail in how ChatGPT chooses its sources. For consulting and IT services firms, the fragments that matter most are almost never an "our expertise" page — they are a case study, a trade-press article, or a dated client review.

What AI engines actually read to judge a provider

Content a firm publishes about itself carries less weight than what others say about it. According to the May 2026 edition of Muck Rack's "What Is AI Reading?" report (more than 25 million links analyzed across ChatGPT, Claude and Gemini answers, in 17 industries), about 84% of citations come from earned media: news coverage, research, institutional sites, encyclopedic sources. Journalism alone accounts for 27% of cited sources, and paid or advertorial content shows up in just 0.3% of citations.

That pattern matches what our own calibration study found (317 pages on major French websites): 79 to 89% of citations go to third-party sites, not to the brands' own sites. For a consulting firm or an IT services company, that means a case study published on an industry outlet, an interview in the trade press, or a verified client review carries more weight than a polished "about us" page. It is the same principle we detail for sourcing content in sources and AI citations, and for reviews in customer reviews and AI visibility.

A French market growing slowly, where visibility becomes a way to stand out

This citation pattern matters even more because France's technology consulting and IT services market is struggling to rebound. According to the Numeum-Xerfi semi-annual observatory, reported by Blog du Modérateur, the French digital market is returning to growth of about 3% for 2026 (up from +1.8% in 2025), but the rebound mainly benefits software publishers (+6.2%, on a €30.9 billion market): IT services companies (+1%, on a €34.6 billion market) and technology consulting (+0.2%, on a €7.7 billion market) are growing much more slowly, and the recovery has not yet shown up in the sector's profitability.

In a market that is barely growing, every tender matters more, and a shortlist built by an AI before the first sales call even happens becomes a filter whose rules are worth understanding rather than enduring.

Why your firm's name matters less than answering a precise need

This is where the classic B2B marketing instinct — build a recognized brand — stops being enough on its own. According to a Semrush study of 643 US B2B professionals surveyed in March-April 2026 (519 of whom use AI at work), only 7% of B2B buyers say brand recognition is what makes them notice a vendor named in an AI-generated answer. What captures their attention, per the study, is how precisely the answer matches the need described in the prompt.

In practice: a buyer asking "which IT services firm for an Azure migration in the insurance sector" is more likely to see a firm cited whose published case study speaks to exactly that topic, than a better-known firm whose content stays generic. The same Semrush study shows that trust in an AI recommendation is not blind: B2B buyers largely verify what the AI tells them before committing, which lines up with the Gartner figure above: 69% of B2B buyers check with a human sales rep to validate AI-generated information. Being cited by an AI opens a door; what a human buyer finds next (case study, verifiable references, reviews) has to confirm that first impression.

What this means in practice for a consulting firm or IT services company

Getting cited on a vendor question does not happen through a generic "our expertise" page. Four levers carry most of the impact.

• Case studies with numbers, organized by industry and technology. Starting problem, approach, measurable result, project duration. It is the same format comparison sites already use in other sectors; we describe it for e-commerce in how AI engines choose which products to recommend, and the principle holds for a consulting engagement: the more specific the content is to a real need, the more likely it is to be extracted.
• Pages organized by expertise or technical stack, not by service line. A page on "SAP S/4HANA migration for manufacturers" directly answers a question a buyer puts to an AI; a page titled "our ERP services" much less so.
• Press mentions and expert commentary. Interviews in the trade press, contributions to industry studies, speaking at events covered by media: earned media is the register that dominates citations, not a press release published on your own site.
• Recent, verifiable references and client reviews. How long the relationship has run, on what kind of project, with what result. A dated proof point carries more weight than a logo wall with no context; see our article on demonstrated expertise (E-E-A-T) and AI visibility.

For a broader measurement that compares your firm against your direct competitors on the questions your prospects actually ask, Beeleven's AI visibility audit, from the agency behind Detekia, asks ChatGPT, Gemini, Claude and Perplexity about those precise needs (migration, cybersecurity, transformation), and measures who gets cited, in what position, and against which competitors.

What should you actually do?

1. List your prospects' typical needs, phrased the way they would type them into an AI: "which IT services firm for [technology] in [industry]", "consulting firm for [type of engagement]". Test these questions on ChatGPT and Perplexity and note who gets cited.
2. Publish a case study with numbers for each key expertise, with a measurable result, instead of relying on a single general overview page.
3. Restructure your expertise pages around precise needs (technology, industry, project type) rather than around your internal service org chart.
4. Pursue press mentions and public speaking: a byline, a cited study, a talk covered by a trade outlet carries more weight than a press release on your own site.
5. Keep your references and client reviews current, with the length of the relationship and the type of project, even without naming a client who wants to stay confidential.
6. Measure regularly what AI engines say about you against your direct competitors, using the same method each time: our guide to measuring AI visibility compares the available approaches.

Frequently asked questions

Can AI really recommend a consulting firm or IT services company by name?

Yes, when a case study, a press article or a sufficiently specific client review exists on the topic asked about. Without that specific content, the AI stays general (types of providers, selection criteria) without naming a particular firm, for lack of a source relevant enough to cite.

Does an AI-drafted RFP replace the traditional tender process?

No. Per the Gartner survey cited above, B2B buyers use generative AI early on, to research and build a first list of vendors, but 69% then check with a human sales rep to validate that information. AI shortens the scouting phase, not the selection process itself.

Do case studies matter more than the firm's website?

The available data strongly suggests so: most AI citations come from third-party content (media, studies), not from the brand's own site. The site is still needed to spell out the case study in detail, but a mention or pickup by an independent third party carries more weight in the generated answer.

How do you find out whether ChatGPT cites your firm over your competitors?

By asking your typical prospect needs directly to ChatGPT, Perplexity, Gemini and Claude, and noting who is cited, in what position, and with what supporting evidence. For a complete, repeated measurement, Beeleven's AI visibility audit does this work across all four AI engines and weights it by their actual usage in France.

Sources

• Gartner, "Gartner Survey Finds 69% of B2B Buyers Turn to Sales Reps to Validate AI-Generated Insights," May 20, 2026 (survey of 645 B2B buyers, August-September 2025).
• Semrush, "How AI Tools Shape the B2B Buying Process," survey of 643 US B2B professionals, March-April 2026.
• Muck Rack / Generative Pulse, "What Is AI Reading?," May 2026 (more than 25 million links analyzed across ChatGPT, Claude and Gemini).
• Blog du Modérateur, on why the digital sector's rebound has not yet reached profitability (Numeum-Xerfi observatory, in French).

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