According to Silicon Republic, Kyndryl’s latest Readiness Report surveying 3,700 senior leaders shows AI spending is up 33% year-over-year, with 61% of executives feeling more pressure to prove ROI. While 54% report positive returns so far, a staggering 62% of AI projects haven’t moved beyond the pilot stage. The main barriers? Infrastructure complexity and regulatory concerns. Meanwhile, cybersecurity remains a massive worry with only 37% of leaders feeling prepared for threats, and 82% experienced a cybersecurity outage in the past year. Geopolitical factors are also forcing companies to rethink data strategies, with 80% saying issues like data sovereignty are becoming more important in tech decisions.
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<h2 id="the-pilot-problem“>The Pilot Problem
Here’s the thing that really stands out: companies are actually getting better at starting AI projects. The initial on-ramp, as Kyndryl’s Gavin Goveia puts it, is becoming smoother. But scaling from proof-of-concept to real products? That’s where everything falls apart. And we’re not talking about a small percentage of companies struggling – we’re talking about the majority.
Think about what this means practically. Businesses are spending all this money on AI initiatives, getting excited about pilots that show promise, and then… nothing. They hit a wall. The infrastructure can’t handle it, or regulatory concerns pop up, or the organization just isn’t ready. It’s like building a fancy race car that can only drive around a test track.
The Infrastructure Crisis
Now let’s talk about the elephant in the room: 25% of mission-critical infrastructure is at end-of-service. That’s wild when you consider companies are trying to implement cutting-edge AI on systems that are basically technological dinosaurs. And 57% of leaders say foundational tech stack issues are delaying innovation efforts.
Basically, we’re trying to run before we can walk. Companies want the shiny AI capabilities, but they’re building them on shaky foundations. It’s no wonder three-quarters of organizations are investing in AI for cybersecurity specifically – they’re desperately trying to patch holes while sailing through stormy waters.
The Geopolitical Wildcard
What’s really interesting is how geopolitics is creeping into tech decisions. Companies are suddenly having to think about where their data lives, who can access it, and what happens if international relations shift. And yet the least concerned groups? US and Chinese companies. Go figure.
So we’ve got this perfect storm: companies need to modernize infrastructure, scale AI, navigate regulations, AND account for geopolitical risks. No wonder only 36% feel completely ready for AI. The question is, who’s actually going to figure this out?
The Tipping Point
Goveia calls this moment a “tipping point,” and he’s right. The gap between pacesetters and laggards isn’t about who has the fanciest AI – it’s about who has their basic IT house in order. Pacesetters are 35 points more likely to have infrastructure ready for disruption and 30 points more likely to have cloud systems that actually provide flexibility.
Look, 87% of respondents think AI will completely transform roles this year. But with all these scaling challenges and complexity piling up, good outcomes are anything but guaranteed. The companies that succeed won’t be the ones with the most AI pilots – they’ll be the ones who sorted out their fundamentals first.
