The Human Side of AI

Why Bringing Your Team Along Isn't Optional

Hi there,

I've been a project manager for years. Completed the transformation projects, received the certificates, and managed the change resistance. The experience of seeing what AI tools can do and their potential to do things better, faster, and cheaper drove a significant part of my decision to focus on AI from earlier in this journey.

However, here's what keeps me up at night: most business leaders are still treating this shift like they're upgrading their CRM, when in fact, they're actually restructuring how work happens at the most fundamental level.

The numbers are stark. The World Economic Forum predicts that 44% of workers will need reskilling by 2027. Russell Reynolds found that 42% of executives view workforce transformation as a significant threat, but only 38% believe they're ready. That gap isn't just a statistic. It's where businesses fail or succeed.

The 52% Problem

Microsoft discovered something disturbing: 52% of employees using AI won't admit it. They're scared of looking replaceable. Currently, half of your workforce is secretly experimenting with these tools, likely yielding inconsistent results and working in fear.

BCG's research makes it worse. While 89% of companies recognise that their employees need AI skills, only 6% have taken meaningful action to address this need. The rest are expecting their people to figure it out themselves while maintaining normal performance. Meanwhile, experienced workers who genuinely understand your business and its edge cases are evaluating their retirement options and planning their exits.

This isn't just dysfunction. It's a massive missed opportunity.

Your Best Ideas Are Hiding

Those fearful workers aren't just hiding - they're innovating in secret. They're solving real problems you don't even know exist. They understand the daily frustrations, the workarounds, the places where current processes break down.

They're experimenting with fixes, but won't share them because sharing means admitting they're using AI or that your culture disincentivises sharing new ideas.

Think about what that means. Your customer service team may have developed a more efficient way to handle complex queries. Your finance team might have automated that report everyone hates. Your salespeople might have found ways to personalise at scale. But fear keeps them quiet.

Deloitte's research confirms employees are often more ready for AI than leaders assume - many already use it independently. The innovation you need is already happening. You're just not seeing it because you've made it dangerous to share.

Why They Don't Trust You

McKinsey found 79% of leaders say AI adoption is essential to compete, but 60% admit they don't have a clear plan. Your people see this. They hear "transformation" in the all-hands meeting, then watch leadership fumble with intern-level questions about what that means.

Russell Reynolds found that 89% of leaders admit leadership itself needs to change. One in five think their entire leadership team needs substantial changes. You can't guide people through something you don't understand. When you talk about "exciting opportunities" while clearly not knowing what those opportunities are, people see through it.

Traditional change management assumed you moved from one stable state to another. With AI, there is no stable state. The tools evolve monthly. The roles you're creating now will look different next year. But instead of acknowledging this uncertainty, most leaders pretend they have it figured out. Your people know you don't.

The Real Cost of Doing Nothing

Expecting ordinary people to learn AI skills at home while maintaining their work responsibilities isn't only unrealistic but also impractical. You're asking them to invest their own time preparing for a future you haven't guaranteed them. They're supposed to maintain performance, manage their fear about job security, and somehow become AI experts on weekends.

Workers with options are already making plans. The talented ones are building portfolios at night, taking recruiter calls, or realising self-employment is the “next best option” for the times ahead.

The experienced ones - the people who know why that one client needs special handling, who remember what happened last time you tried to change that process - they're calculating whether they can make it to retirement without dealing with this.

When they leave, they take with them decades of context. New hires might know the technology, but they don't know your business. Successful and lasting business transformation requires real investment in strategy, communication, and learning infrastructure. Most companies offer lunch sessions and article links instead. And you’re forced to use CoPilot, which is worse than what you have on your iPhone.

Partnership, Not Replacement

The wrong question: "What can we automate?" The right question: "How can technology make our people more effective?"

Deloitte identifies four key opportunities for human-AI integration: effective human-machine teaming, experimenting with autonomous systems while keeping humans in the loop, leveraging AI to enhance skill development, and improving knowledge transfer. But this requires intentional design.

Let machines handle data processing while your team determines its implications for your specific context. Have AI draft the report while humans add the insight that actually influences decisions. Use automated systems for routine queries while humans handle the relationships that keep customers from leaving.

Every role has genuinely routine aspects that require human judgment and discretion. Companies that succeed will combine machine consistency with human adaptability. But a partnership only works if people feel safe enough to engage.

Making It Safe to Experiment

Creating an environment where experimentation is encouraged rather than suspected requires more than words. Run sessions where people share what they're actually doing, including failures and unexpected outputs. Not presentations about best practices. Real stories about what worked and what didn't.

Set clear guidelines about acceptable use. Protect jobs for a defined period while people adapt. Not vague promises - specific commitments with timelines. When people understand they have time to learn without risking their mortgage, they stop hiding and start innovating.

Microsoft's finding that 52% hide their AI use represents massive lost potential. Your teams understand problems that leadership doesn't even know exist. They could be finding applications worth far more than any top-down initiative, but only if fear stops driving their behaviour.

Support That Actually Works

IBM's research is clear about what successful transformation needs: lasting strategy, clear communication, and genuine investment in learning infrastructure. Not token efforts. Real support.

This means professional guidance for individuals whose careers are undergoing a shift. Clear pathways from current roles to future ones. Protected time for learning - actual scheduled hours, not "when you get a chance." Adjustment periods where you accept lower productivity because people are learning.

Most companies won't do this. They'll run workshops and send emails about opportunities, then wonder why their best people left. They’ll try AI and claim it failed when the real reason was leadership skill issues or data quality problems. Companies that invest properly will have a significant advantage.

The 4% Advantage

Russell Reynolds found that only 4% of leaders felt their workforce was well-adapted for the future. Those companies aren't just slightly ahead - they're positioned to dominate.

Not because they have better technology. Everyone has access to similar tools. But because they have people who understand both the technology and the business. They have innovation from people who feel secure enough to take risks and experiment. They have business knowledge preserved and enhanced rather than lost.

While your competitors scramble to hire scarce talent at whatever price the market demands, these companies have teams that deeply understand their specific context and how to apply new tools within it. That's an advantage you can't put a price on. You have to build it.

Six Months to Choose

By mid-2026, the talent market is expected to shift. Those with AI skills will have a wide range of opportunities to choose from. Those without will face increasingly limited options. The companies that started early will be scaling their transformed teams. Those who waited will be competing for scraps.

The World Economic Forum's projection that 44% of workers need reskilling by 2027 isn't abstract. It's your workforce. The executives and business owners worried about transformation - that might include you. The gap between threat and readiness is closing fast.

Your people are watching. They know transformation is coming. They're waiting to see if you're serious about bringing them along or if this is just another efficiency drive with a technology label.

By this time next year, you'll either have a team that's been learning with you or a talent crisis you can't recruit your way out of. Your people have already started making their choice.

Time to make yours.

How Can I Help?

If you’re ready to move from an AI transformation idea to executing on an AI transformation in your business, but need help working through the challenges you face, book a complimentary 30 minute call with me.

I’m putting together some more detailed playbooks and guides. If there’s a specific AI transformation topic you’d be interested in reading my take on, please comment below or reply to this email.

Regards,

Brennan