Part of our guide: AI transformation for COOs
BCG's well-known rule of thumb puts the split at roughly 10 per cent algorithms, 20 per cent technology and 70 per cent people and process. That figure is about where the effort goes rather than the cost, and it predates generative AI, but the direction has held: the hard part of AI transformation is the people and the process, not the model.
And yet most AI initiatives are led by the technology team with the people team brought in as an afterthought, usually when someone realises that the workforce is anxious and engagement scores are dropping.
If you are a Chief People Officer or HR Director, you are probably seeing this play out already, and the CEO is keen on AI. The CTO is building a roadmap and your team is fielding questions from employees who want to know if their job is safe.
The fear is real, and ignoring it makes everything harder
AI will change roles, and some tasks that people currently do will be automated, some roles will evolve significantly and in some cases roles will be reduced. Pretending otherwise is not kind, and it is a fiction that your people know.
The research consistently shows that the businesses that handle this well do not lose their best people, and what they lose instead is their worst processes. The talent stays because the work gets better: less repetitive data entry, less manual reconciliation and less copying and pasting between systems. The people who were drowning in mundane work get to focus on the parts of their job that actually use their expertise.
The businesses that handle it badly announce "AI transformation" without explaining what it means for individuals, and they watch their best performers leave for competitors who feel more stable. They then end up with an AI programme that technically works and that cannot be adopted because nobody trusts it.
Your people strategy is the main track and not a side-track.
What the CPO needs to own in an AI programme
The people team needs to shape the programme from day one, and the people dimension needs to be designed in rather than bolted on after the technology decisions have been made:
Before a single AI tool is deployed, you need a role impact assessment that maps the roles affected, how they are affected and what the transition looks like. That mapping happens role by role and process by process as each initiative is planned rather than all at once, giving people time to prepare and the business time to reskill.
Communication that's straight about change and optimistic about opportunity. The worst thing you can do is say "nobody's job is at risk" when people can see that some tasks are being automated. The best thing you can do is say "these tasks are going to be done differently, here's what your role looks like after the change, and here's how we'll support you through it."
If a claims handler's role shifts from manual document review to exception management and customer interaction, they need different skills, and that is where skills gap analysis and reskilling plans matter early. Identify those gaps early and invest in development, because this is cheaper than redundancy and recruitment and it sends a powerful signal about how the business values its people.
Retention risk monitoring. During any change programme, your best performers are the ones most likely to leave, because they are the ones with the most options. Monitor engagement, have direct conversations and make sure the people you cannot afford to lose understand their place in the future operating model.
Change readiness as a gate on deployment. Do not deploy AI capabilities to teams that have not been prepared, because technology that is ready while the people are not ready is technology that will fail. If the communication has not happened, the training is not in place and the managers are not equipped to support their teams through the transition, the deployment should wait.
The "AI anxiety" conversation
Every organisation going through this will face a period where employees are uncertain, and that is normal, so the question that matters is whether you manage that uncertainty or let it manage you.
Managed well, it looks like: clear communication about what is changing and what is not, individual conversations about role evolution, visible investment in reskilling and a frank acknowledgement that the business needs to operate differently to stay competitive. Managed badly, it looks like the opposite: vague announcements about "digital transformation", no clarity about individual impact and a perception that AI is being done to people rather than for the business. It also looks like a steady drip of resignations from people who decide that the uncertainty is not worth it.
What a good process looks like
The businesses that get this right start with a capability assessment that explicitly includes workforce impact. For each process being considered for AI-assisted automation, they ask what happens to the people who currently do this work and whether those people move to higher-value tasks. They also ask whether those people need new skills, whether there is a transition period and who manages the communication.
This is essential work (not extra work) and it needs to happen at the same time as the technology assessment rather than after it.
At Oxygen Bubbles, workforce impact is built into our Breathe engagement from day one, and when we map capabilities and score AI opportunities, workforce impact is one of the considerations we weigh rather than an afterthought. That covers which roles are affected, what the transition looks like and what the people team needs to plan for, so you do not get a technology roadmap that ignores the humans.
A practical first step
If your business is starting to talk about AI and nobody has consulted the people team, now is the time to get involved rather than waiting to be invited. The decisions being made now about which processes to automate will directly affect your workforce, your culture and your retention for the next three years.
If you want the structured framework, get in touch and we will share it.
If your CEO is driving the AI conversation, share this with them: The Blockbuster Question: Is Your Business Model Ready for the AI Era?
If your COO is looking at process automation, share this: 5 Signs Your Operations Won't Scale