The CIO’s Guide to AI, Strategy & Business Alignment.
We are living in an exciting time for IT leaders. For years, IT teams were seen primarily as service providers, there to implement products and keep the lights on. But today, that perception has changed. IT leaders finally have a seat at the table – recognized not just as technology enablers, but also, and more importantly, as transformation leaders, value creators, and data wizards who can drive both top and bottom-line growth.
Think about it: Digital Transformation has been a priority since the early 2010s, but it wasn’t until the pandemic - and now the AI revolution - that it finally became an absolute necessity. Today, AI is poised to reshape industries, and IT teams are leading the charge.
Here’s the hard reality - most AI projects fail.
According to IDC, 70% of CIOs reported a 90% failure rate for their custom-built AI application projects. Two-thirds reported the same failure rate for vendor-led AI proof-of-concepts. That is a staggering statistic for a technology that, on paper, is supposed to be a game-changer.
The root causes of this high failure rate are numerous, but here are the key ones.
- Underestimated costs
- Unclear return on investment (ROI)
- Inadequate understanding of the technology
- Lack of leadership commitment
Now, to put things in perspective, studies show that AI transformation initiatives happen to have similar success rates as other transformation initiatives. So yes, your AI initiative will fail—but so do most transformation initiatives.
It’s easy to look at these numbers and feel discouraged. AI transformation failures are not unique – they’re part of the transformation itself. But here is the good news - just as with any transformation, leaders who approach AI initiatives with the right strategy—one that embraces Strategic Portfolio Management (SPM)—can dramatically improve their chances of success.
How to Fail Forward with AI
The best IT leaders aren’t trying to avoid failure altogether. They’re embracing the risk, learning fast from it and getting better outcomes! Here is how they do it:
- Start small, think big, scale fast: When faced with high costs, uncertainty, and unclear outcomes, break down your initiative into smaller, focused pilots. Show quick wins early at a limited cost, then use those successes to build momentum and scale quickly. For example, a manufacturer tested AI-driven maintenance on one production line. When it cut downtime and costs, they expanded it across factories.
- Don’t do it alone—build alliances: AI transformation shouldn’t be an IT-only effort. Engage executives from impacted departments, secure their commitment, and ideally, have them both co-fund the initiative and be accountable for its success. When business leaders have skin in the game, AI projects are more likely to move from experimental to operational.
- Fail fast but fail less over time: The best teams track their AI initiatives, learn from early missteps, and refine their approach before small problems become big failures. Over time, your failure rate will decrease and your ability to deliver results will improve.
SPM helps teams keep track of AI projects, spot problems early, and adjust before small issues turn into big failures.
The Common Denominator of Why the Best IT Leaders Succeed
Companies that turn AI failure into AI progress all share one thing in common: they stay focused on business value, not just technology. That’s why Strategic Portfolio Management (SPM) matters—it gives IT leaders a structured way to prioritize, track, and scale AI investments effectively.
- SPM helps teams focus on the right AI bets, identify early warning signs, and make data-driven course corrections.
- Platforms like Planisware provide the visibility and governance to ensure AI projects stay aligned with business goals—so every failure moves you closer to success.
So yes, your AI initiative will fail—but with the right approach, that failure becomes a steppingstone to success.
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