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AI in the middle market: High satisfaction, limited enterprise adoption

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Driving AI impact with governance, measurement, workforce readiness and integration
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July 21, 2026
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Download the 2026 AI survey report
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AI in the middle market: High satisfaction, limited enterprise adoption

Key takeaways

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Middle market AI adoption is high, but enterprise-scale impact remains limited.
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Data quality, governance and integration are the biggest barriers to scale.
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AI investment is rising, but spending alone will not deliver lasting value.
  • Artificial intelligence
  • Agentic AI
  • Generative AI
  • Machine learning
  • Predictive analytics
  • Business applications
  • Business tax
  • Data & digital services
  • Managed cloud and IT
  • Management consulting
  • Risk consulting
  • Tax technology
  • Application development
  • Business intelligence
  • Data infrastructure
  • IT infrastructure
  • Business transformation
  • Strategy and planning
  • Business risk consulting
  • Technology risk consulting
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Key findings of the RSM Middle Market AI Survey 2026

86%

of respondents said AI is integrated into operations, yet only 36% have it fully embedded across core processes.

97%

reported satisfaction with AI’s business value, but many organizations are measuring early wins instead of enterprise-wide outcomes.

34%

cited data quality as a top barrier to AI deployment, followed by security and privacy concerns (30%) and legacy systems integration (28%).

85%

said leadership is more enthusiastic than employees are about AI, highlighting the need for effective change management and workforce readiness.

AI impact in the middle market

Middle market organizations are investing in artificial intelligence and reporting strong satisfaction with the technology. However, organizations still face challenges scaling AI to achieve measurable business impact. AI isn’t failing in the middle market, but scaling it requires governance, measurement, workforce readiness, integration and change management.

The challenge is how to operationalize AI beyond isolated wins. That means prioritizing issues, figuring out how AI can solve them and then executing on those ideas.

Ana Minter, Consulting AI Go-to-Market Leader, RSM US

Although middle market firms have made great progress with AI, the next phase requires more than tools and pilots. It requires an operating model that connects strategy, technology and talent.

Download the report to understand where middle market firms stand on AI—and what leaders can do now to move from productivity enhancements to accelerate scaling and create repeatable, enterprise-wide value.

Inside the report

The RSM Middle Market AI Survey 2026: U.S. and Canada aggregated the responses of 827 U.S. and 203 Canadian middle market executives across a variety of industries.

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Snapshots: Industry, tax and finance

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  • /insights/industries/manufacturing/manufacturers-using-ai-2026
  • /insights/services/audit/ai-financial-reporting-risk
  • /insights/industries/financial-services/ai-for-financial-services-organizations-in-2026
  • /insights/industries/health-care/ai-healthcare-wide-adoption-operational-accountability
  • /insights/services/business-tax/ai-is-working-in-tax-scaling-it-is-the-hard-part
  • /insights/industries/technology-companies/ai-adoption-integration-challenges-tech-companies
  • /insights/industries/professional-services/professional-services-firms-focusing-ais-practical-uses
  • /insights/industries/real-estate/real-estate-and-construction-firms
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