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Common Costly Mistakes in AI Implementation - and How to Avoid Them!

Not aligning AI strategy with business strategy

One of the biggest mistakes is implementing AI without understanding how it supports business goals and priorities, or without ensuring alignment with the business strategy. This leads to wasted time and resources, with little or no return on investment (ROI).

  • Start with a clear business strategy, then explore how AI can support and accelerate it — Align AI/technology with business strategy, not the opposite

  • Focus on business value and solving real problems — avoid being distracted by AI hype or allowing teams to develop disconnected, siloed AI solutions

  • Create a Business Case that demonstrates AI’s value, ROI, and alignment with strategy (e.g., use NAFTA framework: Need, Alignment, Finance, Test, Analyse)

  • Align AI with Business, Data, and IT roadmaps, with scalability and long-term planning — target business-aligned, high-impact, feasible, measurable use cases

  • Develop an AI strategy with a phased roadmap — start small with pilot projects and scale based on proven value, feedback, iteration and business impact

  • Ensure leadership endorsement to sponsor, champion and support the vision

  • Link every AI initiative to clear, specific, and measurable objectives with KPIs from the start, including success metrics and milestones to track progress

How to avoid it:

MISTAKE 1: