Operations, Strategy, and AI-Enabled Systems

For more than a decade at IKEA, I led digital transformation initiatives across the U.S., introducing new enterprise systems and the operational changes that came with them. Whether it was a CRM, ERP, or OMS, the hardest part was rarely the technology itself. It was getting people to adopt the change. We relied on proven change management models to reduce productivity dips and accelerate adoption - models that worked well across industries. With clear communication, patience, and steady leadership, those efforts succeeded again and again. But AI transformation is different. This shift is different in its speed, scope, and emotional impact. Say "AI" in a room and you are likely to get a visceral response: excitement, skepticism, fear. Let's be honest: no one was afraid that Salesforce would take their job. No one worried that SAP might destroy humanity. But generative AI has entered the cultural conversation in a way no enterprise software ever has - complete with hype, headlines, and mythology. Those emotional undercurrents are real. And if leaders treat AI like just another technology rollout, they will miss the mark. Change management for AI requires more than a familiar playbook. It demands a different kind of leadership - one that helps people navigate uncertainty when the stakes feel personal. The Human Element - Helping People See Their Value in the Age of AI AI transformation is faster, broader, and more emotionally charged than the digital transformations we've led in the past. While speed and scope are challenges for leadership teams, the emotional impact on employees may be the most critical - and most overlooked - factor to manage. Here's the truth: AI will replace some jobs. That's not a threat - it's a reality. And it's why fear and resistance aren't irrational; they're human. So how do we lead through that? We do it by offering purpose, clarity, and empathy - through real communication and real training. A recent Lifewire survey found that 74% of full-time employees now use tools like ChatGPT or Gemini at work, and 65% say it has made them more productive. But only 33% have received formal training. And as Boston Consulting Group reports, 46% of employees at AI-intensive organizations are more worried about job security. Training reduces uncertainty. But it's not just about how to use AI tools - it's about why you matter once the tools are in place. Employees don't just want to know how AI works. They want to know how they will continue to bring value. In the age of automation, clarity of purpose is everything. What do you expect of your team when AI takes care of the admin work? Where should they reinvest that freed-up time? How does their role evolve? This isn't a side conversation - it's the conversation. In high-touch industries like healthcare, for example, AI can offload documentation so caregivers can spend more time delivering meaningful, personal experiences. That's not just a workflow shift. That's an identity shift. If leaders don't articulate the path forward, fear will fill the gap. When leaders provide training, communicate purpose, and reaffirm the human value behind the work, people lean in. When they don't, people disengage - or resist. AI transformation succeeds only when people see where they still belong. Leadership Buy-In - Why AI Transformation Starts at the Top The emotional burden of AI transformation - especially uncertainty around job security - makes leadership alignment more important than ever. That reassurance employees need? It starts with leadership. In my experience, few things derail a transformation faster than a lack of alignment and clear messaging from the top. And with AI - where fear, unfamiliarity, and mythology all collide - alignment becomes mission-critical. Leaders set the tone. Trust is built when teams hear a unified message grounded in transparency and purpose. But alignment starts with education. Especially in non-tech organizations, leadership teams must first understand AI's capabilities, limitations, and implications. That foundational knowledge does three important things: - Dispels myths (no, the robots aren't coming for everything) - Clarifies the "what" and "why" behind the transformation - Creates urgency to lead proactively - not reactively Because once you understand the paradigm shift we're facing, it's hard to unsee it. And when leadership is educated, aligned, and speaking with one voice, employees notice. The message feels less like a script - and more like a shared vision. That's what builds trust. That's what sets the foundation for real transformation. Upskilling with Purpose - How AI Training Builds Confidence and Value Leadership alignment alone doesn't make transformation happen. It has to be operationalized. The next step is equipping teams to not just understand AI - but to use it with confidence and purpose. The goal of any AI transformation should be this: Raise the AI fluency of the organization beyond that of the leadership team. That's how companies flourish - not just adopt. Given the pace of innovation, this can't be a one-time training push. It requires a continuous learning strategy, integrated into daily routines. Too often, companies hand out access to AI tools with no messaging, no structure, and no support. That approach: - Confuses employees - Puts sensitive data at risk - Limits adoption to only 10-12% (typically innovators and early adopters) The result? Confusion, anxiety, and growing resistance. Instead, start with the basics: What is AI/ML? What's an LLM? How do prompts work? What's an agent - and how can it be used? Platforms like Coursera, DeepLearning.ai, and smarterX.ai are great starting points. So is a simple internal video or workshop series. But beyond that, organizations must create space for learning. Give people time every week to explore tools. Host team-level AI share-outs. Celebrate AI-driven workflow wins. Because your people already know their jobs. When you give them the tools - and the trust - to use AI, they'll find new ways to drive value. And when that happens? AI stops being something happening to them and starts becoming something they lead. Busting the Myths - Tackling the Sci-Fi Fears and Finding the Fun As AI adoption accelerates, mythology has grown alongside it. A mix of ambiguity, limited understanding, and a steady diet of Hollywood drama has fueled some of the strongest narratives I hear about AI. Here are three of the biggest myths - and why we need to see them for what they are. Myth #1: AI is like magic - it can do anything. I wish. I use LLMs constantly - building web pages, creating apps, drafting content, doing research. And while they're powerful, they're far from magical. They make mistakes. They hallucinate. They get lost in long threads. Like any tool, their value depends on the skill of the person using them. Poor prompts = poor outputs. The sooner people actually work with AI, the sooner they realize it's not magic. It's a power tool that requires practice. Myth #2: AI will take all the jobs. A Reuters poll in August 2025 found that 71% of Americans fear AI could cause permanent job losses. It's true - AI will eliminate certain roles and tasks. But history tells us something important: Innovation also creates new opportunities. Nearly 60% of the jobs that exist today didn't exist in 1940. The challenge for leaders is clear: Invest in education and upskilling now so employees are ready to grow into the roles AI will inevitably create. Myth #3: AI will become sentient and destroy humanity. This one makes for great movie scripts. But reality? We don't even have consensus on what sentience would mean in machines - let alone whether it's possible. What experts do agree on is that superintelligent AI - systems that vastly outperform humans - could emerge someday. Predictions range from soon to centuries away. Either way, it's not the most urgent concern for employees trying to keep, grow, or transform their jobs today. It's an interesting debate over drinks. But not a reason to stall transformation. The takeaway? Don't get caught up in the mythology. Learn how AI works. Train your people. Focus on how it can make your organization better at what it does today. Because transformation doesn't happen by waiting for answers about the future. It happens by leading with clarity in the present. Leading Through AI Transformation - The Big Picture Over the past few weeks, we've explored the unique challenges of AI transformation - and how it differs from the digital transformations of the past decade. Here's the big picture: 1. AI is different. It's faster, broader, and emotionally heavier than the digital transformations we've known. 2. It's not just technical - it's human. Employees want clarity on how they will continue to add value in an AI-powered workplace. 3. Leadership alignment matters. Nothing derails transformation faster than mixed messages from the top. 4. Training must be structured and continuous. Handing people AI tools without purpose or guidance creates confusion. 5. Don't get lost in the myths. AI isn't magic. It won't take all the jobs. And it isn't about to turn sentient and destroy humanity. The Through-Line AI transformation succeeds when leaders combine clarity, empathy, and education - turning fear into trust and potential into progress. AI isn't a spectator sport. The leaders who lean in today - guiding their people with purpose and equipping them with skills - are the ones who will shape what comes next.