Laroze Partners · Sector Analysis · Tech & Digital Services · June 2026

VivaTech 2026 set a clear watchword: impact, not illusion. At the same time, the IT services market (ESN) shrank for the first time in fifteen years. Behind these two signals lies the same question: what kind of leader is needed to shift a model from volume to value, and where can we find the rare profiles that will drive this transition.

The sector in a few figures

VivaTech 2026: the end of talk, time for proof

For its tenth edition, held from June 17 to 20 in Paris, VivaTech surpassed 200,000 visitors and brought together 15,000 startups around a deliberately direct theme: "Artificial Intelligence: impact, not illusion". The message is addressed to the entire industry. After years of spectacular announcements and demonstrations, AI is no longer judged on its promise, but on its measurable results.

This shift is not just exhibition shorthand. It describes a market status. According to Bpifrance Le Lab, 55% of French VSEs and SMEs were using generative AI at the end of 2025, up from 31% a year earlier. AI has entered operations. And once it is expected to deliver results, it changes the game for those whose job is precisely to sell technical expertise: IT services companies.

The ESN model, struck to the core

The economic model of an ESN relies on a simple equation: revenue equals the number of consultants multiplied by a utilization rate, a daily rate, and days worked. Time & materials billing, i.e., invoicing by time spent, is its foundation. This model sustained a decade of continuous growth.

Two forces are disrupting it simultaneously.

• The first is cyclical, but of unprecedented magnitude. According to Numeum, the ESN market in France contracted by about 1.8% in 2025, to 34.3 billion euros. This is the first contraction in more than fifteen years. The digital sector had already lost nearly 7,000 jobs in 2024, bringing workforce levels back to where they were in 2022.

• The second is structural, and it is the deepest. Generative AI is compressing the very unit that ESNs bill: the consultant's day. Productivity gains related to generative AI are estimated at 12.5% on average in 2025, with an expected increase of up to 17% in 2026 according to the Numeum and PAC observatory. At the same time, IT departments no longer want lengthy, highly customized, resource-intensive services. They want clear, packaged, result-oriented, and quickly operational offerings.

In other words, the market is demanding value where the legacy model sold volume. Selling fewer days, but more results. This shift is not just a margin adjustment. It is a fundamental change of nature.

Added to this internal pressure is a new threat from the top of the chain. In 2026, the major artificial intelligence laboratories themselves entered the services arena. According to CIO and Reuters, OpenAI and Anthropic have created dedicated deployment divisions, embedding their own engineers with clients and intelligence-driven outcomes. OpenAI has funded its division with several billion dollars and is acquiring service companies to accelerate. These players are imposing a tighter delivery model, outcome-oriented, capable of delivering in weeks what used to take months. They are no longer content with just providing technology; they are targeting client value directly. The pressure on the time-and-materials model, based on headcount, is stronger than ever.

From volume to value: a leadership shift before a tool shift

This is where the blind spot lies. Most analyses treat this transformation as a technological topic: adopting AI, industrializing offerings, upskilling. All of this is necessary. But none of these initiatives can be carried out without a leader capable of driving them.

Yet the executive who grew an ESN for fifteen years built their success on a specific logic: managing capacity, optimizing utilization rates, handling bench time, and securing contract renewals. These are real, demanding skills. They are not, however, the ones required to make the turn toward value.

Shifting a model toward outcomes, productized offerings, and an AI-native value proposition requires a different leadership mindset. An ability to rethink the business model, not just optimize it. A sufficient understanding of AI to pilot its transformation without being its engineer. An aptitude for bringing along teams accustomed to a model that has sustained them, toward a model that makes them anxious.

This profile exists. It is rare. And it looks nothing like the executive who succeeded in the previous model.

Field Observation

I supported executive recruitment within the team of a female transformation leader at a major digital services player. Her background, on paper, was not the one the market would have bet on: strategy consulting and high-level public service, with no operational track record in IT services.

Yet in operations, her thinking proved visionary. She viewed human capital and AI training as tools to facilitate daily tasks, not as threats to the teams. She integrated sustainability and energy sobriety as a strategic baseline in an industry known to be polluting and energy-intensive. She anticipated the arrival of new entrants with colossal resources—including AI laboratories within the services space—and built a resilient economic model designed to endure in a hyper-competitive environment.

This ability to foresee tomorrow, in a profile that conventional screening criteria would have ruled out, is precisely what makes the difference. And this is not an isolated case: major groups in the sector are today steering in a similar direction.

The talent war, all the way to the top

The tech talent shortage is not new. The sector estimates a shortfall of about 60,000 engineers per year. What is new is that the strain has climbed all the way to the executive suite.

The Chief AI Officer is the clearest symbol of this. According to the IBM study of May 2026, 76% of organizations now have one, compared to 26% a year earlier. Job listings for CAIO roles have grown by about 400% since 2023, while the supply of qualified candidates has struggled to keep pace. Technical and data leadership roles are no exception: packages for CTOs, CDOs, and CPOs are skyrocketing, and profiles capable of aligning technological strategy with business challenges, ROI, and time-to-market are being actively headhunted with compensation packages that often include equity.

The AI market in France is worth about 5 billion euros and is growing by more than 30% annually. Job offers mentioning AI, machine learning, or data science jumped by 45% between 2024 and 2026, according to Apec and France Travail, with recruitment times often exceeding six months for senior hires. AI skills command a 15% to 25% premium at hire over other IT engineering roles.

This overheating does not just affect software vendors and startups. It hits ESNs head-on, as they must simultaneously recruit these rare profiles for their clients and equip themselves internally with leaders capable of steering their own transformation.

Why this is a recruitment issue, not a technology issue

The CAIO perfectly illustrates the nature of the challenge. This is not a technical role. According to industry practitioners, the title matters less than the ability to connect technical, business, and human challenges. The CAIO defines an AI strategy, ensures its governance and compliance—particularly with regard to AI Act obligations applicable from August 2026—and translates the potential of AI into business results. They typically report directly to the CEO or the board.

Evaluating this type of profile does not fall under standard recruitment practices. Over years spent at the heart of the digital services ecosystem, supporting major accounts and placing high-level executives and experts, I have seen three key realities confirmed that organizations consistently underestimate.

• First: these profiles are passive and invisible. The best transformation leaders and AI executives do not apply to job ads. They are in office, rarely looking, and can only be reached through direct search and in-depth knowledge of the ecosystem. This is the very definition of the hidden market.

• Second: technical competence is not a predictor of success. An excellent AI profile can fail if they do not know how to bring an executive committee onboard, unify teams, or translate a vision into measurable results. Conversely, a leader capable of driving the shift from volume to value is not necessarily the most technical one. Assessment must focus on the intersection of technical, business, and human leadership, which cannot be read on a resume.

• Third: the cost of a hiring mistake is massive. For these foundational, high-demand, and expensive roles, a bad hire is not just paid for in search fees. It is paid for in lost months during a critical market window, and in disoriented teams.

What VivaTech 2026 really says about Tech recruitment

The event's theme was clear: impact, not illusion. For the digital services sector, this impact will not come from technology alone. AI does not deploy itself. It requires leaders capable of turning it into strategy, governing it, and translating it into value, all while shifting an entire economic model.

The IT services companies that succeed in this transition will not be those with the most consultants. They will be those that recruited, at the right time, the leaders capable of driving the change from volume to value. Identifying these profiles, evaluating them on the right blend of competencies, and reaching out to find them where they are—which is rarely on the visible job market—is where much of the sector's future will be decided.

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Sources: VivaTech 2026 (organizers, June 2026) · Numeum and Numeum-PAC observatory · IBM CEO Study, May 2026 · CIO and Reuters (OpenAI and Anthropic services, May 2026) · Apec and France Travail · Bpifrance Le Lab · IT and AI salary benchmarks 2026.