AI Is Outpacing Corporate Playbooks
PwC's chief commercial officer Kathryn Kaminsky argues that AI is disrupting corporate decision-making faster than traditional playbooks can accommodate, forcing leaders across the C-suite to rethink investment criteria, organizational ownership, and workforce planning simultaneously. Unlike previous technology cycles that affected single business functions, AI touches every executive role, from CIOs to CHROs, creating ambiguity about who owns transformation and how to measure success. Companies are responding by testing multiple AI models at once and reframing ROI calculations to emphasize the risk of inaction rather than immediate returns, while simultaneously reshaping talent strategies to prioritize uniquely human skills.
TL;DR
- →AI adoption is outpacing traditional change management processes, leaving companies uncertain about decision rights and ROI frameworks across the entire C-suite
- →CIOs are forced to evaluate and deploy multiple frontier models simultaneously rather than following historical single-vendor selection processes, complicating cost management
- →Business leaders are reconsidering how they present AI investments to boards, blurring lines between operating expenses and long-term strategic bets to justify spending without clear near-term returns
- →Companies are hiring new technical roles like engineers and data scientists while emphasizing human-led skills like critical thinking and relatability that machines cannot easily replicate
Why it matters
AI's pervasive impact across all business functions represents a fundamental departure from how companies have historically managed technology adoption. The speed of AI capability evolution is forcing executives to make high-stakes decisions without stable frameworks or clear accountability structures, creating organizational friction that traditional governance models were not designed to handle.
Business relevance
Operators and founders need to understand that AI investment decisions are no longer purely technical or financial matters but strategic bets that require board-level framing and cross-functional ownership. Companies that delay decisions waiting for clear ROI may face existential risk, while those that move forward without coherent playbooks risk misallocating resources and creating organizational confusion about who owns outcomes.
Key implications
- →Traditional CIO authority over technology selection is eroding as business units demand input on AI model choices, requiring new governance structures and decision-making protocols
- →ROI frameworks designed for incremental technology improvements are inadequate for AI, forcing CFOs and boards to accept strategic optionality and scenario-based planning instead of predictable returns
- →Workforce planning must account for simultaneous demand for new technical talent and heightened value for distinctly human skills, creating a bifurcated hiring strategy that most companies are still learning to execute
What to watch
Monitor how public companies communicate AI spending to investors and whether board-level framing shifts from ROI to risk mitigation language. Track whether CIO-business unit tensions over model selection lead to new organizational structures like dedicated AI governance committees, and observe whether companies successfully retain and deploy human-centric skills as AI capabilities expand.
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