Top 3 challenges in capturing value from gen AI in marketing for gen AI leaders and laggards,¹ % of respondents Note: Gen AI leaders and laggards determined based on self-assessment of maturity along 9 dimensions: internal capabilities to define and lead gen AI strategy, strategy and guardrails for gen AI in marketing, data quality, technological infrastructure, pilots and proof of concept, deployment in production, process and operating model redesign, change management and training, efficiency gains through gen AI implementations. Gen AI leaders = maturity rating of 5.4 or higher (4/9 or more questions answered with 6). Gen AI laggards = maturity rating of 1 or 2 (1 = very immature, 6 = very mature). 1 Question: What are the main challenges preventing your company from capturing value through gen AI in marketing? (Up to 3 selections.) 2 Machine learning operations. Source: State of Marketing Europe Report 2026, McKinsey, n = 500 senior marketing leaders across France, Germany, Italy, Spain, and the United Kingdom Gen AI leaders see an inadequate operating model and lack of a coherent strategy as the main challenges for capturing value from gen AI. McKinsey & Company Operating model Technological infrastructure Adoption and scaling Strategy Budget Legal and reputational risk Talent AI models and MLOps² tools Data foundations Top management support 35 81 65 51 43 32 19 11 100 100 Gen AI laggards Gen AI leaders 43 35 37 20 7 47 17 30 27 7 3 17 Exhibit 17 “ One of the biggest challenges is rethinking our processes to fully integrate gen AI. For example, while we have experts working on AI-driven tools, we often struggle to quantify their impact or scale their use across the organization. Another challenge is ensuring that these initiatives don’t remain isolated pilots. We need to “rewire” our processes to make AI a core part of how we operate, rather than a side project.” — Benjamin Faveris, CMO, Orange France 42 State of Marketing Europe 2026