AI is commanding unprecedented levels of investment across the enterprise. But according to Jeff Baker, Technology Managed Services Lead at PwC, many organizations are still struggling to translate that investment into measurable business results.
Speaking at a recent CIO event in Atlanta, Baker pointed to the PwC’s 2026 Global CEO Survey, which found that only 12% of companies investing heavily in AI are seeing returns they can clearly attribute to those efforts.
For Baker, the issue is not a lack of activity, but a lack of impact. “I think the answer is we still are treating AI a little bit like an experiment,” he says.
Many organizations, he explains, are focusing on incremental or isolated use cases, often in back-office environments or on individual productivity gains. While those efforts may demonstrate technical capability, they rarely translate into meaningful business outcomes.
That disconnect, Baker argues, reflects a broader failure to think strategically about where AI can drive real value. “You’re not thinking big enough, in other words, right? Just disrupt yourself is kind of where I head with this.”
This challenge becomes even more pronounced as AI begins to reshape managed services and outsourcing models. Baker described the industry as sitting in a transitional phase, moving from traditional, technology-enabled services toward more advanced, AI-driven approaches, with fully AI-native models still emerging.
What is changing most is not just the technology itself, but how organizations structure work around it.
One of the immediate barriers is the disconnect between technical teams building AI systems and the business units expected to use them. Baker described scenarios where both sides engage in discussions but leave without a shared understanding of either the problem or the solution.
To address this, organizations should rethink how teams collaborate. Embedding technical talent directly within business functions provides the context to move beyond theoretical use cases and into practical, outcome-driven agentic solutions.
But even when alignment improves, new challenges can quickly surface, particularly in outsourced environments.
As service providers invest heavily in AI tools and agents, fundamental questions around ownership, integration, and value realization often remain unresolved. Organizations should determine how these assets are deployed, how they integrate with existing environments, and how their value is measured over time.
At the same time, the workforce implications of AI are becoming increasingly visible. Yet Baker emphasized that the shift is not solely about workforce. Instead, many organizations are using AI to dramatically increase productivity, expecting the same teams to deliver significantly more output. In that sense, AI functions less as a replacement and more as a force multiplier, amplifying what existing teams can achieve.
For CIOs, the takeaway is clear. The challenge is no longer whether to invest in AI, but how to help drive those investments lead to sustained business impact. That requires more than deploying new tools. It demands structural change, closer alignment between technology and business teams, and a willingness to rethink long-standing operating models.
PwC’s research shows just 20% of companies are capturing 74% of all AI-driven value. “The organizations that lean into that uncertainty — rather than wait for it to resolve — will be the ones who define what this industry looks like on the other side,” says Baker.