KPMG says CEOs are racing to cut costs and adopt AI

The new client brief is efficiency with an AI deadline

KPMG’s latest CEO outlook points to the same message landing in boardrooms across industries: cut friction, protect margins, and do not miss the AI shift. That combination matters because it changes the kind of work clients will buy next. Instead of treating AI as a side experiment, CEOs are pushing it into the core operating model, where it has to deliver measurable savings, clearer decision-making, and faster execution.

For KPMG professionals, that creates a very specific kind of demand. Clients are likely to ask for help redesigning how work gets done, not just how to deploy new tools. That means more pressure on consulting, audit, and advisory teams to connect technology decisions to operating outcomes, risk controls, and workforce readiness all at once.

Why this is not just a cost-cutting story

The bigger signal in the outlook is that cost pressure and AI adoption are moving together, not separately. CEOs are aggressively tackling supply-chain and operating-cost pressure, but they also see that they need to meet the AI moment to stay competitive over the next three years. That is a transformation agenda, not a narrow expense exercise.

In practice, that means executives are likely to spend where AI can simplify operations, cut cycle times, or improve forecasting, while trimming work that looks redundant, manual, or too slow to scale. The result is a familiar but more intense corporate pattern: more investment in automation, more scrutiny on headcount, and more pressure on teams to show where human effort still adds value.

Where the work will go inside KPMG

The most immediate client demand sits at the intersection of strategy and execution. Supply-chain cost pressure creates room for diagnostics, process simplification, sourcing analysis, and change management. AI pressure creates a parallel need for governance, controls, use-case prioritization, and workforce upskilling. Those are not separate opportunities; they are increasingly the same engagement.

That matters in a firm like KPMG, where industry specialization and cross-functional collaboration are central to how work gets delivered. A single client conversation can now pull in multiple service lines: a team diagnosing operating inefficiencies, another helping define where AI can be used safely, and another looking at control design or workforce impact. For employees, that means the most useful people will be the ones who can move between transformation language and operational detail without losing either.

What clients are likely to buy next

• Operating-model redesign that strips out redundant steps and manual handoffs
• Supply-chain and sourcing analysis tied directly to cost relief
• AI governance and controls that show how tools will be used, monitored, and tested
• Use-case prioritization so companies do not waste time on low-value experimentation
• Change management and training that help employees actually adopt new workflows

The important shift is that these are not “AI projects” in isolation. They are business redesign projects in which AI is one of the levers. That should keep demand high for people who can translate technical capability into measurable process gains, because that is what clients will need when they are under pressure to do more with less.

What this means for audit teams

Audit and assurance work is unlikely to stay neatly separated from the AI conversation. As companies automate more of their operations, they create new questions about data quality, controls, documentation, and oversight. That is especially true if management is using AI to make decisions faster or to reduce labor in core functions.

For KPMG auditors, the practical implication is that AI fluency matters, but it is not enough on its own. The more valuable skill is understanding how AI changes the risk profile of a business: where controls need to be tightened, where judgment is still required, and how to test systems that are producing faster, more opaque outputs. That is where audit becomes a business conversation, not just a compliance exercise.

What this means for consulting and advisory teams

Consulting teams are likely to feel the strongest pull from clients who want visible efficiency gains without a messy transformation program. CEOs under cost pressure usually want something more concrete than a slide deck: shorter turnaround times, lower operating expense, fewer bottlenecks, and a clearer plan for how people will work once automation is introduced. That creates room for practical advisory work, especially when the client wants to move quickly but not recklessly.

Advisory teams also have a clearer lane in workforce upskilling. If CEOs are trying to adopt AI over the next three years, they have to decide who learns what, how quickly, and with what safeguards. That opens work around role redesign, skills mapping, training strategy, and governance. In other words, the AI conversation is no longer just about tools. It is about how the firm organizes people around those tools.

How this changes the career picture inside KPMG

For consultants, auditors, and advisory professionals, the message is less about a single hot skill and more about a new combination of skills. AI knowledge will help, but the people who stand out will be the ones who can pair it with process knowledge, risk judgment, and change leadership. A person who can explain where automation fits into an operating model will be more valuable than someone who can only describe the tool itself.

That has real implications for promotion cycles and the partner track. The firm will reward people who can speak to both efficiency and control, both transformation and execution. In busy season and beyond, that likely means more pressure on managers and senior associates to translate broad CEO priorities into concrete deliverables that clients can use quickly.

The bottom line for the next phase of work

The CEO outlook points to a workplace reality that many professionals are already feeling: companies want AI, but they want savings too, and they want both now. That combination will keep pushing KPMG teams toward projects that promise cleaner operations, tighter controls, and a more disciplined use of data and automation.

The winners in that environment will not be the people selling AI as a buzzword. They will be the ones who can show how it cuts cost, changes workflows, and reshapes the workforce without creating new chaos.