AI Insights
KPMG AI Quarterly Pulse Survey
AI questions facing every leader
As organizations shift from AI experimentation to adoption at scale, key considerations are coming into focus. Explore these actionable insights grounded in data and real-world experience—addressing what’s top of mind for leaders today.
1
What new organizational roles are emerging in the agentic AI era?
As organizations move to agentic AI systems, new roles that span strategy, operations, governance and oversight are taking shape, such as: workforce planning architects focused on AI, orchestration engineers, AI performance managers, and AI governance and risk specialists. These positions help organizations responsibly and effectively design, deploy, and manage digital teammates.
Dive deeper in Agents of change: New organizational roles in the age of AI.
2
What is shadow AI, and what risks does it pose to organizations?
Shadow AI occurs when employees use unapproved AI tools or models without oversight. While it may boost speed, it can introduce risks like data leakage, regulatory non-compliance, fragmented workflows, and inconsistent outputs. Effective mitigation includes clear policies, approved tooling, training, and centralized governance.
Learn more in Shadow AI is already here.
3
How should leaders decide whether to build, buy, or borrow AI agents?
As agentic AI moves from pilots to enterprise‑scale deployment, leaders face a critical decision: whether to build custom agents, buy off‑the‑shelf solutions, or borrow capabilities through partnerships. The right answer is rarely one‑size‑fits‑all. Research shows many organizations are adopting a blended approach, balancing speed, differentiation, cost, and risk. Success depends on aligning the choice to business value, organizational readiness, data and trust foundations, and the ability to orchestrate and govern a growing AI workforce at scale.
Dive deeper in Agentic AI untangled: Navigating the build, buy, or borrow decision.
4
How can leaders tell whether employees are using AI effectively?
As organizations accelerate AI adoption, usage alone is no longer a reliable signal of value. Research based on real AI workplace interactions shows that the most effective users treat AI as a reasoning partner—routinely delegating complex tasks with clear objectives, choosing the right tools, and refining outputs. The shift to high-impact AI capability can be achieved when leaders deliberately create the conditions for these behaviors to take hold at scale.
Read more in Sophisticated AI collaboration: An inside look at high-impact use.
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