Category: Strategy and AI
ROI of AI automation: the metrics that actually work
72% of CIOs report that their organization is breaking even or losing money on AI investments. Only 1 in 5 AI initiatives achieves a measurable ROI. The wrong metrics don't just fail to measure value: they lead to wrong decisions on subsequent projects.
Communicating AI to employees: the problem isn’t resistance, it’s how it’s introduced
65% of employees are enthusiastic about using AI at work. Only 3% actively avoid it. Yet 37% don't use it because their colleagues don't. The problem isn't worker resistance: it's the urgency of executives that leads to rushed implementations without considering workforce implications.
Automating isn’t installing: the hidden cost of an AI system in production
72% of CIOs report breaking even or losing money on AI investments. Gartner predicts that over 40% of agentic AI projects will be canceled by 2027 due to costs that weren't anticipated. The real cost of AI automation isn't the deployment: it's what comes after.
The AI competence center: is it really needed or just a bureaucratic layer?
Only 1 in 5 organizations is getting value from AI tools, and only 1 in 50 is seeing transformative value. Gartner recommends building an AI center of excellence that works like an air traffic controller. But building it wrong is worse than not building it at all.
Which process to automate first: a strategic choice, not a technical one
72% of CIOs report that their organization is breaking even or losing money on AI investments. Over 40% of agentic AI projects will be canceled by 2027. The problem isn't the technology: it's the choice of starting point. Gartner has defined the criteria to get it right.
AI is changing how IT works: five moves that make the difference
Scaling AI in the enterprise does not just require new tools: it requires structural changes to the IT operating model. Five concrete practices adopted by CIOs who are already delivering results.
