The AI hype train is running at full steam, but interestingly, two key executives who should be its biggest champions—CIOs and CMOs—are often the ones applying the brakes. I’ve been watching this resistance pattern emerge, and it’s fascinating how similar yet distinct their concerns are.

Let’s break down what’s happening here. The business world has fractured into several camps on AI adoption:

1. The enthusiasts who believe AI will transform everything immediately
2. The skeptics who see more problems than solutions
3. The cautious adopters waiting for proven ROI
4. The overwhelmed executives facing practical implementation challenges

Taking a step back, I think there are two things that can simultaneously be true: AI absolutely has transformative potential, AND the path to realizing that potential is genuinely difficult right now.

For CIOs, the resistance isn’t philosophical—it’s practical. They’re staring down volatile costs with unclear ROI, trying to justify significant investments to boards that want immediate results. The talent gap is enormous; finding and keeping AI specialists is like trying to catch rare Pokémon with a broken Poké Ball. Then there’s the data problem—AI systems need clean, integrated data, but most organizations are sitting on fragmented information silos that would make Marie Kondo weep.

Meanwhile, CMOs are fighting their own battles. I’ve noticed they often fall into the trap of unrealistic expectations—they want AI to revolutionize marketing overnight, then abandon projects when the magic doesn’t happen immediately. There’s also significant cultural resistance, particularly from creative teams who view AI as either a threat to their jobs or an affront to their craft. And let’s not forget the infrastructure gap—many marketing departments simply don’t have the technical foundation to support sophisticated AI implementations.

What’s particularly striking is how both executives face similar core challenges but experience them through different lenses. Both struggle with ROI justification, but CIOs worry about technical implementation costs while CMOs fret about creative output quality. Both face talent gaps, but CIOs need data scientists while CMOs need AI-fluent marketers who won’t revolt at the mention of automation.

I don’t believe this resistance indicates a lack of vision. Rather, it reflects the genuine complexity of integrating AI into established business operations. The gap between AI’s theoretical potential and practical implementation remains substantial.

The timing of this resistance is also telling. We’re at that awkward adolescent stage of AI adoption—past the initial excitement but before the development of mature, proven implementation frameworks. Organizations that push through this uncomfortable middle phase will likely emerge with significant competitive advantages, but the journey isn’t easy or straightforward.

What’s the path forward? I suspect we’ll see a gradual shift toward more focused, targeted AI implementations with clearer ROI cases, rather than sweeping transformations. The winners won’t be those who adopt AI fastest, but those who adopt it most thoughtfully, with clear alignment between technology capabilities and business objectives.

In the meantime, CIOs and CMOs will continue their cautious dance with AI—neither fully embracing nor rejecting it, but carefully testing where it can deliver genuine value without upending their organizations or budgets.