Artificial intelligence has already achieved near-universal adoption among technology leaders, yet just 27% report their organizations are seeing substantial return on investment, according to a May 2026 survey by Futurum Research. The disconnect between widespread use and measurable value could shape the channel's next phase of AI opportunity as managed service providers shift from helping customers deploy the technology to proving it actually works. Futurum's chief strategy and research officer, Tiffani Bova, compared the current AI cycle to cloud adoption but noted the timeline has condensed dramatically—cloud took 15 to 20 years, while AI is moving in 12 to 18 months or even six to 12 months.
Futurum surveyed 775 technology leaders and discovered AI use is already nearly universal among respondents, though only 27% said their organizations were realizing substantial ROI from AI. Thirty percent reported pressure from leadership to overstate the success of AI initiatives, while one-quarter said their organizations prioritize moving quickly on AI over ensuring deployments are safe, governed, or compliant. More than half of respondents reported moderate to transformative productivity gains, but nearly one in five also cited meaningful negative effects, including time spent fact-checking AI output, managing tools and workflows, and reworking generated content. On the workforce front, 58% of respondents expect their organizations to employ fewer technology workers within three years because of AI, though the near-term picture centers more on role restructuring than widespread layoffs—43% have restructured roles to incorporate AI responsibilities, while 37% have increased AI-related hiring and 14% have reported AI-driven workforce reductions.
According to Bova, the tension reflects both AI's extraordinary pace and a familiar technology adoption problem. "I really, really do believe that it is pressure around the visibility AI has at the top of the organization," she told Channel Insider. The report emphasizes that MSPs should resist the immediate urge to turn customer requests for AI into a discussion of products or infrastructure, and instead stop to ask what the customer is trying to accomplish with their business—whether that's reducing the time required to close financial books, improving inventory processes, speeding up product development, or changing call center operations. Bova characterized this as moving from the infrastructure conversation to the intelligence conversation, a shift that becomes more important as customers struggle with what Futurum calls AI's "productivity paradox."
The report warns that the tension around enterprise AI adoption won't ease as organizations move into 2027—Bova expects the anxiety won't lessen, the uncertainty won't go away, and the friction and tension will remain. The channel needs to think about pivoting toward the intelligence layer and then the business consulting layer, she said. Customers may still come to partners asking which model, platform, or infrastructure they should deploy, but the more valuable role will increasingly be helping them determine where AI fits into the business, how employees and workflows need to change, and whether those investments are producing measurable outcomes. Notably, AI-specific skills ranked behind traditional technical skills, soft skills, domain expertise, and leadership in Futurum's hiring data, with critical thinking and problem-solving ranking as the most valuable soft skills—meaning MSP leaders heading into 2027 should evaluate whether they're hiring people who can connect technology capabilities to business outcomes rather than simply adding another layer of product certifications. That consulting pivot may soon separate partners who sell AI from those who make it work, especially as the gap between adoption and results forces organizations to justify investments they've already made under executive pressure.