Overcoming challenges Capturing the value from gen AI is not just about technology. While gen AI leaders have addressed technological infrastructure, adoption, and scaling challenges, issues such as gen AI strategy (47 percent), operating model (37 percent), and AI models/machine learning operations tools (30 percent) remain roadblocks. Laggards still struggle with foundational issues like infrastructure (81 percent) and adoption (65 percent) (Exhibit 17). To catch up, gen AI laggards can address foundational gaps such as data infrastructure, governance, and integration into existing workflows. Without these building blocks, gen AI efforts risk being confined to piecemeal pilots that deliver limited value. The real opportunity lies in systematically establishing these foundations to enable marketing transformations at scale, rather than fragmenting efforts through isolated experiments. In B2C contexts, this means prioritizing high-impact, customer-facing applications, which we are already seeing across industries (such as Kraft Heinz’s Tastemaker). In B2B settings, it requires bold investments in end-to-end process automation and role redesigns. Small bets are unlikely to drive big gains—closing the gap depends on committed, scalable investments in high-value use cases that jointly constitute a full transformation of the marketing domain. Areas with the largest potential for gen AI in marketing,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: For which of the following gen AI marketing use cases do you see the largest potential for your company? (Multiple selections). Source: State of Marketing Europe Report 2026, McKinsey, n = 500 senior marketing leaders across France, Germany, Italy, Spain, and the United Kingdom CMOs see the highest potential from gen AI for media optimization, personalized content creation at scale, and market research. McKinsey & Company 100 Total Market research, customer insights and trend spotting Personalized content creation at scale Media optimization Product discovery Creative efficiency 46 45 Automation of noncreative tasks 38 47 54 60 100 Gen AI laggards 32 19 62 43 22 54 100 Gen AI leaders 57 47 37 33 80 60 Exhibit 16 41 Past forward: The modern rethinking of marketing’s core