Why do so many AI projects fail?
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Research shows that 80% of AI projects fail due to poorly defined goals, lack of the right talent, inadequate infrastructure, and misaligned tools. Gartner adds that 30% of AI projects are abandoned at the proof-of-concept stage because of high costs, low adoption rates, and unclear ROI.
Many companies get caught up in the excitement of adopting the latest AI tools but fail to align them with clear, measurable objectives. This leads to projects that lack focus, overrun budgets, and ultimately fail to deliver meaningful results.
Our checklist addresses these challenges head-on.
What’s included in the AI Checklist?
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The checklist outlines essential steps for building a successful AI project, including defining your use case, selecting tools, assembling teams, addressing security and compliance, and budgeting effectively. It also highlights common pitfalls and how to avoid them.
Who is this checklist for?
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It’s designed for tech leaders like CTOs, CIOs, and Heads of Engineering who want to implement AI projects efficiently without common pitfalls.
However, it’s equally valuable for project managers, data scientists, and business leaders looking to align technical execution with strategic goals, streamline collaboration, and ensure AI initiatives deliver measurable results.
How will this checklist help my AI project?
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By providing a clear roadmap for tool selection, team building, and strategy alignment, the checklist ensures your project stays focused, efficient, and results-driven.
Why is having the right people critical for AI project?
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AI projects are only as strong as the teams behind them. Without skilled data scientists, engineers, and AI specialists, even the most advanced tools will fall short. The checklist emphasises assembling a high-performing team tailored to your project’s unique requirements.
Can this checklist help us identify skill gaps in our team?
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Yes, the checklist provides a framework for evaluating your team’s capabilities and identifying gaps.
Can this checklist help us optimise costs?
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Yes! The guide includes proven strategies for budgeting, cost-efficient hiring (e.g., leveraging regional talent), and scaling AI solutions without compromising quality.
