AI is already changing work faster than many organisations are redesigning around it.
The early evidence does not point to a simple story of mass job replacement. The more immediate shift is happening at task level. Work is being drafted faster, researched differently, reviewed differently and, in some cases, quietly redesigned before any formal workforce decision has been made.
For CPOs and senior People leaders, that creates a leadership challenge that goes beyond tool approval, usage metrics or prompt training.
The harder question is whether AI has already started changing how work gets done before the organisation has fully understood the implications.
Employees may be making informal decisions about how work is produced and handed off. Managers may be setting different standards across teams without realising it. Junior learning pathways may be affected before anyone has redesigned how capability should be built. Headcount plans may still be based on task volumes that AI is beginning to reduce.
This is where AI becomes a People leadership issue, not just a technology issue.
Our discussion guide sets out 10 questions for the CPO agenda, designed to help senior People leaders move the conversation from AI adoption into work redesign, capability, governance and strategic workforce planning.
It is grounded in recent AI-at-work research, 2026 workplace adoption evidence, and live conversations with senior People and Technology leaders.
Use it as a prompt for conversations with the CEO, CTO, Legal, Finance, HRLT or the board.
What the guide explores
The guide focuses on the questions that matter once AI moves beyond individual productivity and into how work is actually produced, reviewed, delegated and governed.
- What new capability, ownership and control model does AI-enabled work create?
- What decisions about how work gets done have already been made, without anyone realising they were decisions?
- Which headcount requests are solving workflow problems that AI or automation could reduce?
- Where has AI created capacity, and is that time being reinvested deliberately or just filled?
- Which human capabilities become more important when AI makes output faster but judgement more exposed?
- Which junior tasks are at risk of being removed before organisations understand what they were teaching?
- If two teams use the same AI tool on the same task, who is responsible for the gap in output quality?
- Where has AI moved from helping people produce work to shaping decisions?
Download our discussion guide here to learn more.
