Observed Signal · Sep 30, 2026 · Market Analysis · Source: Tech.eu (European Tech & Deals) · Impact: 2/5 · Sentiment: Positive
AI Adoption Gap: Only 6% Deliver Significant EBIT Impact
McKinsey's 'State of AI in 2026' reveals that while nearly 90% of companies use AI in at least one function, only 37% report measurable EBIT impact. Only 6% are 'high performers' attributing at least 5% of EBIT to AI. The article argues that closing this gap depends on fixing data silos, assigning clear accountability, and redesigning workflows, not just adopting better models. DMEXCO 2026 in Cologne, themed 'Scaling Intelligence', echoed these themes. The piece also highlights a shift in digital visibility where AI assistants and social platforms become entry points, requiring products to be machine-understandable.
Provides industry insights into AI adoption challenges and success factors, but lacks a specific corporate event or announcement.
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Key Takeaways & Evidence Grounding
- Nearly 90% of companies use AI in at least one business function, but only 37% report measurable EBIT impact.
- Only about 6% of companies qualify as 'high performers' attributing at least 5% of their EBIT to AI.
- McKinsey's 'State of AI in 2026' was released in late August, showing little change from the previous year.
- Nearly three-quarters of high performers have redesigned workflows around AI, up from 55% a year earlier.
- DMEXCO 2026 in Cologne attracted over 40,000 attendees and around 1,000 speakers.
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AI Adoption Rarely Shows on Balance Sheets
This analysis argues that while many companies claim to use AI, fewer than 40% report measurable profit or cost savings tied to those efforts. Citing the Stanford AI Index (2026) and a Gartner projection, the piece highlights a gap between technical adoption (models, agents, inferences) and business outcomes (reduced churn, cost savings). It warns that without clear, dollar-based success metrics and cross-functional alignment between engineering, product, and finance, AI projects risk ballooning costs, model drift, and being shelved despite deployment.
AI's Biggest Opportunity: Creating New Value
The article argues that while most organisations use AI (88% per McKinsey), only a small share (6%) see significant enterprise-wide impact because companies mainly apply AI to existing tasks rather than rethinking business models. Only 23% of generative-AI users have redesigned workflows for the technology. The author contrasts a 'factory' (efficiency) mindset with a 'laboratory' (experimentation and effectiveness) mindset and recommends marketing operations lead experimentation to discover new revenue models. Examples include Pieter Levels' portfolio of experiments generating sizable monthly revenue and IKEA’s chatbot 'Billie', which resolved 47% of inquiries, triggered reskilling of call-centre staff into design advisers and produced €1.3 billion in new revenue in 2022. The piece emphasises deliberate, low-cost experimentation to move organisations into higher-value AI stages.
McKinsey: German companies scale AI but lack ROI
According to the Germany edition of McKinsey's 'State of AI in 2026: On the Road to ROI' report, German companies are scaling AI broadly across their operations, but many struggle to quantify its financial return. 49% of surveyed organizations report that AI is scaled or fully rolled out, while 43% cannot quantify its contribution to operating results. On average, German companies use AI regularly in 4.3 business functions, higher than the global average of 3.5. While 63% report at least moderate benefits, only 14% see significant impact. AI is seen to improve productivity and reduce costs more than driving revenue growth. 36% of respondents have foregone purchasing a software product or feature because they could build it internally using AI coding tools. 24% have limited AI usage due to ongoing costs, yet 64% plan to increase AI investment next year. Looking at workforce impact, 46% expect AI to contribute to headcount reductions in the coming year, up from 17% who reported such reductions last year.
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