AI Transformation Isn’t a Technology Problem. It’s a Talent Problem.
Every telco is investing in AI transformation. Most are getting it wrong. And the reason has nothing to do with the technology itself. I’ve spent seven years building talent strategies in HR and recruitment, including my first three years at iQmetrix on our People & Culture team. What I keep seeing is that companies treat technology adoption as a technology problem when it’s actually a people problem.
You’ve evaluated vendors, justified the investment, and deployed the system. But then something happens: months in, adoption stalls, teams revert to old workflows, and the transformation you counted on simply isn’t materializing. Your instinct is to blame the technology, to assume you chose the wrong vendor or that the system isn’t sophisticated enough. But that’s looking at the wrong problem entirely.
Research from Gloat shows that 70% of AI transformation initiatives fail due to employee resistance, not technology failure. The issue isn’t the software or the platform. It’s the people. More specifically, it’s whether the people you hired have the mindset, support, and culture needed to actually embrace the shift.
Here’s what telco executives rarely acknowledge: they’re treating AI adoption as a technology problem when it’s fundamentally a talent strategy problem.
The Gap: What Telcos Say They Need vs. What They Actually Need
In my years building talent strategies, I’ve observed a pattern that repeats across companies facing any major transformation. When major change looms, the conversation around hiring goes like this:
“We need experts in AI. People who’ve already done this. People who know the technology inside and out.”
What they actually need is different.
The fastest-moving companies navigating AI transformation aren’t hiring for deep AI expertise. They’re hiring for intellectual flexibility, curiosity about new ways of working, and comfort with ambiguity. They’re hiring innovative thinkers who get excited about AI removing repetitive work so they can focus on higher-impact problems. They’re hiring for culture-add, not culture-fit.
According to Deloitte, 68% of executives face moderate to extreme AI skill gaps. But the gap isn’t always about technical AI skills. It’s about hiring people who view AI transformation as an opportunity to work differently, not as a disruption they need to survive.
There’s also a harder truth from Integrate.io: 63% of executives believe their workforce is unprepared for AI adoption, yet 75% of employees need reskilling for AI and only 35% receive adequate training. The investment math doesn’t work. Companies are asking people to transform without giving them the support to do it.
The shift isn’t subtle. It’s: Stop hiring people who already know the AI destination. Start hiring people who are energized by figuring it out together.
What Your Organization Is Probably Missing
Hiring for the wrong things. You’re looking for someone with existing AI experience. Meanwhile, you’re missing the innovative person who learns quickly, asks the questions, and has shipped products across industries. They want to work on problems that matter, and they thrive during transformation.
Underestimating the cultural burden. Organizations keep treating AI transformation as a technology project instead of a human adoption challenge, investing in systems while underinvesting in the people who must use them. Your onboarding is probably still oriented around the old way of working. Your meeting structures assume AI isn’t changing anything. Your performance reviews reward individual speed. Then you introduce AI tools and wonder why people don’t embrace them. Culture doesn’t change through announcements. It changes through intentional design.
Not building for learning. According to BCG, organizations with formal AI training programs achieve 2.3x faster AI adoption and 67% higher AI ROI, with 70% of AI success attributed to people, process, and change. Most companies treat AI training as a checkbox. The companies winning provide ongoing, embedded learning where people experiment with AI, see peers succeeding, and share what’s working.
Forgetting that AI adoption happens in teams, not in individuals. When people try to figure out AI in isolation, anxiety naturally increases and job security concerns emerge. But when teams adopt together with psychological safety to ask questions, share struggles, and learn out loud, the resistance softens. Teams adopt faster. Trust accelerates adoption. The strongest teams aren’t ones where everyone already knows everything. They’re ones where people feel safe learning out loud together.
For Your Organization: The AI Adoption Audit
If you’re a telco executive or HR leader evaluating how prepared you actually are for AI transformation, ask yourself these questions:
1. Are we hiring for growth potential or current AI expertise? When you interview candidates for roles that will work with AI, what percentage of conversation is about what they already know versus how they learn, what excites them about AI adoption, and how they’ve adapted to change before? If it’s weighted heavily toward past AI experience, you’re already limiting yourself.
2. Is our culture built for collaboration and shared AI learning? Innovation during AI transformation happens when people learn together, not in isolation. This means creating structured moments for teams to share what they’re trying with AI, what’s working, and what isn’t. At iQmetrix, we run a weekly AI community hour where staff who are early AI adopters share what they’ve learned and help others level up. The point isn’t the format: it’s the intentional design around collective learning. Without it, knowledge stays siloed and AI adoption stalls.
3. Does your talent strategy account for the emotional reality of AI transformation? People are anxious during AI adoption. The anxiety isn’t always about competence. It’s about identity. “What does my role look like when AI handles this?” “Will I still be valuable?” According to meQuilibrium, employees who don’t feel supported by their lead don’t fare well in times of transformation. They are over four times more likely to leave their jobs and upwards of two times more likely to have poor well-being. This is a talent problem disguised as a productivity problem.
4. What does your onboarding actually teach about AI? If new hires spend their first weeks learning the old way of working without AI tools, they’re being set up to fight them. AI transformation requires rethinking onboarding from the ground up.
This Is What It Looks Like
At iQmetrix, we’re learning these lessons firsthand through HAIQU, our Human + AI transformation. Here’s what Krystal Commons, our Vice President of People & Culture, shared about how we’re approaching AI adoption:
“Through HAIQU, our Human + AI transformation, we’ve intentionally put people and culture ahead of technology. AI doesn’t fail because the tools aren’t good enough. It fails when organizations don’t invest in helping people build the confidence, mindset, and new ways of working needed to fully embrace it. We don’t measure success by how many AI prompts someone has used, but by how much humanity AI gives back. More time for meaningful conversations, stronger client relationships, and the moments that only humans can create. One of the biggest shifts we’ve made is recognizing that learning agility is now a core hiring competency. Technical skills will always evolve, but curiosity, adaptability, and a willingness to challenge how work has always been done are what will ultimately determine who thrives in the AI era.”
The Real Opportunity
Here’s what happens when a telco invests in AI without investing in talent strategy: adoption takes twice as long as projected, the tools become just another system in the drawer, early adopters get frustrated that their peers aren’t keeping up, and the ROI never materializes. Then the executive team blames the technology. But the technology was never the problem.
The telcos that move fastest through AI transformation don’t have the smartest people or the most cutting-edge systems. They have the right culture. They hire curious people who ask questions about AI. They celebrate the person who figures out a better workflow and shares it with the team. They protect time for teams to learn together. They acknowledge that AI adoption is disorienting and provide real support instead of just mandates.
If you’re leading an AI transformation, the hardest work isn’t the technology deployment. It’s answering this one question: Are you building a culture that makes people want to embrace AI, or one where people are just trying to survive it? Everything else flows from that answer.
Stay connected with iQmetrix’s latest thinking on AI transformation, commerce strategy, and what’s working in telecom.
