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Mid-market businesses stumble in rush to AI

Avanade survey finds rollouts are slowed by workforce readiness, data governance, and tech infrastructure.

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Mid-marketorganizations are confident that adopting AI applications can deliver up to fourfold returns within 12 months, but first they have to get over obstacles like gaps in workforce readiness, data governance, and tech infrastructure, according to a study from British consulting firm Avanade.

The report found that 85% of businesses are expressing concern over losing competitive ground without rapid AI adoption, and 53% of them expect to increase their budgets for gen AI projects by up to 25%. But despite that enthusiasm, nearly half are stuck at business case (48%) or proof of concept (44%) stage.


The results come from “Avanade Trendlines: AI Value Report 2025,” which includes two surveys conducted by the market research firms McGuire Research Services and Vanson Bourne. Conducted in in August and September 2024, they encompass responses from a total of 4,100 IT decision makers and senior business decision makers across Australia, Brazil, France, Germany, Italy, Japan, Netherlands, Spain, UK, and US.

Additional results showed that 76% of respondents state that poor data quality and governance inhibits their AI progress. To overcome that, companies are stepping up investments in that area, with 44% planning to implement new data platforms and 41% setting governance standards. And to support the scaling of AI, budgets will focus on data and analytics (27%), automation (17%), and security and cyber resilience (15%).

"Mid-market leaders are at a defining moment with AI—where investments must not only boost efficiency but ignite future innovation and sustainable growth," Rodrigo Caserta, CEO of Avanade, said in a release. "The tension between cost-cutting and growth ambitions shows the AI value equation is still being worked out. Productivity with AI isn't just about doing things faster; it's about reimagining work itself. People are central to this shift, requiring workforce alignment, clear communication, and new training. Leaders must rethink how they support collaboration, measure productivity, and ultimately, assess the true value AI brings to their organizations."

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