AI Adoption Hinges on Employee Readiness Not Technology

Stop chasing manager actions plans from employee surveys, instead try this: 1) Explain why it matters: If managers understand how survey results (really the employee experience) connect to their goals and performance, they’re far more likely to act. 2) Let consequences be consequences: If a manager still doesn't act, the performance review cycle will surface it as their teams underperform and KPIs don't do well. In 2026, let's stop propping up managers who don't care. If this doesn't apply, and employee experience doesn't impact outcomes in a given part of the organisation, I'd question whether the tasks there should be being done by humans at all.

AI is reshaping work faster than many organisations are redesigning the systems that support it. While investment in AI tools continues to accelerate, many job architectures, skills frameworks, career paths and performance models remain rooted in a pre-AI world. Our latest insight explores why organisations need to look beyond technology adoption and focus on redesigning work itself. From redefining roles and responsibilities to building AI-enabled skills and rethinking career progression, leaders have an opportunity to create a workforce model built for the future.

For people and business leaders, an engagement score can feel like clarity - a single number, simple to track. The tension is that this simplicity hides a messy truth, that engagement is only a proxy for a more complex relationship between a person, their work and their employer. No matter how well it’s measured, 'engagement' isn’t the relationship itself. It’s a compressed signal - by design - an oversimplification of a dynamic too intricate to capture fully. That makes it incomplete, even inadequate. So, yesterday's conversation with Jordan Saxby naturally led to: 𝐖𝐡𝐲 𝐦𝐞𝐚𝐬𝐮𝐫𝐞 𝐢𝐭 𝐚𝐭 𝐚𝐥𝐥? Because in employee listening, the goal isn’t to measure engagement. The goal is to understand what we can improve and how to prioritise our response. Improved employee engagement comes from improving the conditions that drive it: manager support, communication, growth opportunities, inclusion. That’s where interventions live. But to know what to go after, you need an anchor, and the engagement score provides that reference point. It 𝐡𝐞𝐥𝐩𝐬 frame where to put limited time, effort and resources. In that sense, the engagement score is a means to an end: a conversation starter with an executive team, not a definitive list of actions. And certainly not a target to chase. The real value isn’t in the outcome measure itself but in the predictors of that outcome. So a relatively simple engagement index - with intention to stay, advocacy (eNPS), motivation - can be ‘good enough’, provided those outcomes matter in your context. Because when survey space is limited, every extra question spent on the outcome is one less question on what actually drives change. Which leads to this question: 𝐇𝐨𝐰 𝐝𝐨 𝐰𝐞 𝐤𝐞𝐞𝐩 𝐞𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐬𝐜𝐨𝐫𝐞𝐬 𝐮𝐬𝐞𝐟𝐮𝐥 𝐚𝐬 𝐚𝐧𝐜𝐡𝐨𝐫𝐬 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐥𝐞𝐭𝐭𝐢𝐧𝐠 𝐭𝐡𝐞𝐦 𝐝𝐨𝐦𝐢𝐧𝐚𝐭𝐞 𝐭𝐡𝐞 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧, 𝐚𝐬 𝐭𝐡𝐞𝐲 𝐬𝐨 𝐨𝐟𝐭𝐞𝐧 𝐝𝐨?

AI is reshaping work faster than many organisations are redesigning the systems that support it. While investment in AI tools continues to accelerate, many job architectures, skills frameworks, career paths and performance models remain rooted in a pre-AI world. Our latest insight explores why organisations need to look beyond technology adoption and focus on redesigning work itself. From redefining roles and responsibilities to building AI-enabled skills and rethinking career progression, leaders have an opportunity to create a workforce model built for the future.

"Are your employee surveys a system of measurement or a stimulus for change?" There should always be something from an employee survey that creates change, even if it is movement of a strategy by degrees, or alteration of some positioning on a piece of internal comms. By the end of my latest gig running employee listening in-house, we had stakeholders from far-flung parts of the business banging on our door for insights from employee listening and I think that's due to the compounding changes well-run employee listening brings. Would love to see what people think on Rob's original post:

I think we may be teaching AI backwards. For the past few years, much of the conversation about AI readiness has focused on tools. Learn prompting. Learn agents. Learn automation. All useful. But I'm increasingly convinced that: Learning AI is not the same as redesigning work for AI. Boston Consulting Group (BCG)'s AI at Work 2025 study surveyed more than 10,600 workers across 11 countries. 72% said they were regularly using AI. But only 13% said AI agents were broadly integrated into workflows. Think about that gap. The technology is spreading much faster than the work itself is changing. And that's the part I find most interesting. Imagine giving someone an incredibly powerful AI assistant while leaving everything else untouched: The same process. The same approvals. The same handoffs. The same meetings. The same job description. The same measures of performance. We may make individual tasks faster. But have we transformed the work? Probably not. BCG reached a similar conclusion: organizations realizing greater value from AI aren't simply deploying tools. They're reshaping workflows around them. I think we need to start one level earlier. Not: “Where can I use AI?” But: “What are we actually trying to accomplish, and how should this work be designed now that AI exists?” Then we can look at the work itself: → What should disappear entirely? → What should be simplified? → What should AI augment? → What can be automated? → What needs to be redesigned? → What should remain intentionally human? That last question matters just as much as all the others. Because the #futureofwork isn't simply about putting AI into today's jobs. It's about redesigning work around the capabilities of both humans and machines. This is the question I've become increasingly obsessed with, and over the next few weeks I'm going to unpack what Work Redesign actually looks like in practice. I'm curious: If you looked at your own job today (not your AI tools, but the actual work) what would you redesign first? Source: Boston Consulting Group, AI at Work 2025: Momentum Builds, but Gaps Remain — global survey of 10,600+ workers across 11 countries. https://lnkd.in/gP6w_sFP

LOUDER FOR THOSE AT THE BACK: You can't fix what you haven’t understood. And you can’t coach what you’ve misdiagnosed. Love this view. I've never really worked with anyone that doesn't want to do a good (or at least good-enough) job. It's about identifying where the blockers are, or in the worst cases identifying where job fit isn't right, rather than getting caught in vibes-based person bashing.

AI is reshaping how work gets done. Organizations create the most value when employees have the confidence and capability to use AI effectively. Learn how to turn AI spending into measurable business results https://ow.ly/LG7Q50ZP7vw #EmployeeExperience #ChangeManagement #AIstrategy

AI is reshaping how work gets done. Organizations create the most value when employees have the confidence and capability to use AI effectively. Learn how to turn AI spending into measurable business results https://ow.ly/681v50ZQb7G #EmployeeExperience #ChangeManagement #AIstrategy