Microsoft released research showing that in 2025, global adoption of artificial intelligence (AI) saw a significant increase, rising to 16.3 percent of the world’s population, up from 15.1 percent earlier in the year. Notably, approximately one in six people are now utilizing generative AI tools, marking a noteworthy advancement for a technology that has only recently gained mainstream traction. According to the Microsoft AI Economy Institute, this growth reveals a widening divide, with the Global North experiencing nearly double the adoption rate of the Global South—24.7 percent compared to 14.1 percent among the working-age population. Early infrastructure and policy investment continues to correlate strongly with adoption, with a small number of countries pulling far ahead.
Nearly half of U.S. workers now report using artificial intelligence tools at work at least a few times per year, with usage steadily increasing through 2025, according to a Gallup report. While 37% of employees believe their employers have implemented AI to enhance productivity and efficiency, 40% disagree, and 23% are uncertain about their organization’s AI strategy. Despite the rising adoption of AI, a significant “trust gap” persists; workers desire transparency about AI usage in their workplaces. While 45% of employees use AI tools at least annually, only about 10% engage daily, largely concentrated in knowledge-based roles. Workers express a preference for viewing AI as an empowering tool rather than a replacement, highlighting the importance of supportive managerial strategies for broader AI integration.
Why do we care?
AI isn’t being adopted as a strategy. It’s being adopted as a workaround.
Employees are using AI because it helps them get work done—not because their organization has told them how, when, or why to use it. Leadership often can’t explain their AI posture, and workers notice. That’s where the trust gap comes from.
The global numbers reinforce this. High adoption follows infrastructure and policy maturity. Where those are missing, AI use is sporadic and opportunistic. That doesn’t scale. It fragments.
The dangerous MSP behavior here is equating “more usage” with “more value” and giving away governance as an implied part of tool deployment. If responsibility is increasing and revenue is not, MSPs are subsidizing risk without pricing it
If you help a client roll out AI tools without defining governance, you’re not enabling productivity—you’re enabling inconsistency and risk. When something goes wrong, the question won’t be “who approved this tool?” It’ll be “why didn’t IT stop it?”
This matters now because AI is already embedded in day-to-day work, just not in a way anyone fully owns. The next phase isn’t about convincing people to use AI. It’s about deciding who is responsible for its outcomes.
If MSPs don’t claim that role deliberately, they’ll inherit it accidentally. And that’s a bad place to be.