The Chardonnay of AI

<h2><b><span class="h6">New data reveals a striking gap between the AI companies enterprise leaders recognize and the ones they trust to help them transform.</span></b></h2>

<p>Today's technology landscape is awash in IPO announcements, model launches, benchmark wars, and hyperscaler campaigns. The industry has collectively decided that the companies building the models are the companies that matter. Enterprise buyers are absorbing that message.</p> <h3><span style="font-weight: normal;" class="h4">AI builders in name and in practice</span></h3> <p>We suspected something was being lost in translation, so we tested it. When asked to identify &quot;AI builders,&quot; enterprise leaders gravitate first toward Google, OpenAI, and Microsoft. Each registers at roughly 40 to 49% recognition, and the association is intuitive: these are the companies that built the technology that started the conversation.</p> <p>But when you ask how AI is actually adopted and integrated inside enterprise, perception and reality begin to diverge. That is where the real story starts.</p> <p>We asked enterprise leaders, directors and above at companies with $100M or more in revenue, to rank which types of organizations are best positioned to help them adopt AI. IT services firms came out on top: 55% ranked them in their top three, trailed by cloud providers, SaaS companies, and management consultancies. The companies dominating every AI headline — the model companies — ranked fifth, just ahead of AI startups.</p> <p>So what does it mean to consistently rank in the top three? Since it's Cannes Lions week, let's use French wine to explain. Ask people to name their three favorite French wines and some will choose Champagne, Bordeaux, and Chardonnay. Others choose Pinot Noir, Chardonnay, and Sauvignon Blanc. Still others land on Côtes du Rhône, Merlot, and Chardonnay. By now you see the common thread. Chardonnay shows up on every list. IT services exists in the same space, where trust determines purchase decisions. We are the Chardonnay of AI—not always the first name out of someone's mouth, but reliably present wherever the decisions that matter actually get made.</p> <h3><span style="font-weight: normal;" class="h4">The gap between ambition and capability</span></h3> <p>That trust reflects a very real need. Our research found that only 13% of enterprise leaders believe their current AI capabilities fully match their AI ambitions, and nearly two-thirds (62%) admit they need meaningful additional capabilities to meet their own goals. The gap between what organizations have committed to and what they can actually deliver is significant, and it is growing.</p> <p>Despite that gap, and perhaps because of it, investment is accelerating. Ninety-seven percent of enterprises expect to grow their AI spending, with more than half planning increases of 10% or more over the next two years. That is real budget, moving fast, in search of partners who can close the capability gap. The data is clear about where enterprise leaders are looking: not to the companies that built the models, but to the companies that know how to put them to work.</p> <h3><span style="font-weight: normal;" class="h4">AI brand recognition vs. AI builder trust</span></h3> <p>There is a meaningful difference between which organizations enterprise buyers associate with AI and which they trust to help them transform, and right now those two things are pointing in different directions. Model companies and hyperscalers have captured the awareness, but IT services firms are quietly earning the confidence, and when it comes to purchase decisions, confidence is what closes deals.</p> <p>The challenges enterprise leaders describe make the case plainly. Ninety-seven percent report facing significant AI adoption barriers, with data security topping the list at 40%, followed by difficulty demonstrating ROI at 32% and lack of clear AI strategy at 31%. These are implementation and governance challenges, not questions of which model to buy. Our survey reinforces this: only 36% of enterprise leaders believe off-the-shelf AI solutions deliver substantial value. The majority needs something more tailored, more embedded, and more accountable to actual outcomes.</p> <h3><span style="font-weight: normal;" class="h4">What this means for how the industry needs to tell its story</span></h3> <p>The IT services category has been underselling itself at exactly the moment the market is most ready to listen. The question enterprise buyers are asking has shifted: no longer which model is best, but who can help close the gap between what they have committed to and what they can actually deliver. That is a different brief, and it requires a different kind of marketing — not capability claims or benchmark comparisons, but evidence of outcomes, storytelling grounded in proof rather than promise that meets buyers where their real concerns live.</p> <p>The companies in this space that learn to position themselves as trusted transformation partners, rather than technology vendors, will define how this category is understood for the next decade.</p> <h3><span style="font-weight: normal;" class="h4">The real AI race</span></h3> <p>Enterprise transformation is no longer about finding the best model; that challenge has largely been solved. The hard work is deployment, integration, change management, and governance, and the buyers already understand this. The AI brand race and the AI value race are running on different tracks, and the data suggests the window to close that gap is open right now. The companies that show up as builders in the way enterprises actually need them will earn something more durable than recognition. They will win the continued trust of the leaders building the future alongside them.</p>