A study by KPMG and Numeum, titled Grand Angle ESN & ICT 2026, suggests that artificial intelligence (AI) is significantly reshaping the business models of companies that provide digital services and information and communication technology (ICT) consulting. Based on responses from nearly 200 firms in France of various sizes, the research shows that 58% of leaders in these sectors expect generative and agentive AI—types of AI that can create content or make decisions—to have a strong or even disruptive effect on their operations. The study reveals that 37% of respondents have seen project productivity increase by more than 20% due to AI. Currently, AI is mostly used to support tasks like generating code, content, or project deliverables, with only 11% of companies allowing AI to produce certain deliverables on its own. Clients are increasingly expecting productivity gains from AI, with 75% of ESN and ICT companies noting this pressure, 62% citing a demand for pre-project advice, and 33% experiencing pressure on pricing. The way companies are responding to AI varies depending on their size. Over half of large companies (52%) have made strategic changes in response to AI, compared to 38% of mid-sized companies, 32% of small and medium-sized enterprises (SMEs), and 30% of very small businesses. Most of these categories are currently in an adaptation phase, with between 57% and 60% of companies adjusting their strategies. The impact on company margins is partially measured, with 36% of large companies and mid-sized firms reporting slight improvements due to AI, and 6% reporting significant improvements. However, 27% of these companies do not track this effect. SMEs and very small businesses show a net improvement in 21% of cases, but 42% do not measure it. Margins have worsened for 8% of large companies and mid-sized firms, and 7% of SMEs and very small businesses, where AI investments have outpaced the gains. Charles Mauclair, director general of SII France and president of the ESN and ICT college for Numeum, notes that the industry has traditionally relied on mobilizing skilled personnel, but AI now demands creating more value with less human effort. Pricing models are being rethought due to pressure from "AI-native" companies, which are businesses that have built their operations around AI. Two-thirds of companies are already updating their pricing policies, using models such as billing by unit of work or flat rate (59%), subscription models (42%), and value-based or outcome-based billing (33%). Thirty percent of companies are not significantly changing their pricing at this stage. In the short term, 37% of industry actors believe a shift to value-based billing is the most likely development. Monetizing platforms and AI agents ranks second, followed by reducing average daily rates and increasing operational activities. New competitors are emerging in the market, with 80% of respondents citing low-cost "AI-native" companies as a risk to their business models. Other concerns include clients who use AI tools to handle projects internally (53%) and those who design their own AI agents (48%). These new actors are introducing innovative billing methods, such as compensation based on project success. Xavier Niffle, associate in the technology sector and head of Digital Audit & Innovation at KPMG France, warns that the real risk for ESN and ICT companies is not just losing competitiveness but becoming irrelevant in the market. Recruitment practices are also evolving as the demand for pre-project advice increases. Sixty-two percent of ESN and ICT companies report that AI is influencing their hiring policies. For 32% of respondents, this means higher selectivity and greater expectations for AI skills, while 19% report reducing hiring for certain roles, and 11% are compensating by enhancing internal skills. Looking ahead, companies expect to prioritize hiring AI specialists (43%), followed by candidates who can bridge technical and business aspects (42%) and experienced professionals (39%). The most experienced profiles, such as architects and technical leaders, are also in demand (31%), while hiring for junior roles supported by AI is less common (18%). The most sought-after skills include critical thinking, validation, and responsibility for AI-generated results (39%), high-level business framing and advice (22%), and mastery of AI tools (17%). Nearly half of respondents (47%) expect AI mastery to be a requirement for entry-level positions. Forty-seven percent of companies describe the impact of AI on junior hiring as stable, 22% report a significant decline, and 9% report an increase. The remaining 22% have not yet decided, as their hiring models are being redefined. Team composition is also expected to change. Thirty-nine percent of ESN and ICT companies do not anticipate changes to their staffing models, while 24% expect fewer junior employees and a higher average skill level. Sixteen percent expect a polarization between highly experienced professionals and AI tools or agents. Only 5% expect to hire more junior employees through AI. Training initiatives vary, with 20% of ESN and ICT companies having more than 80% of employees familiar with generative AI. Most often, this familiarity affects between 10% and 30% of employees, which is the case in 28% of companies. Advanced training on AI systems such as large language models (LLMs), retrieval-augmented generation (RAG), and agentive systems concerns only 6% of large companies and mid-sized firms, and 8% of SMEs and very small businesses. The content of training programs depends on company size, with large firms and mid-sized companies focusing on intermediate-level training (62%), covering use cases, security, and methods. In SMEs and very small businesses, basic-level training (tools and best practices) affects 43% of companies, and 16% limit themselves to a half-day to one-day awareness session.