Discover The 5 Big Reasons AI Projects Fail
Avoid AI Failure
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Over 18 years, we have helped many business leaders avoid costly mistakes and gain real value from AI.
All aspects of AI projects
The reasons cover all aspects of AI projects and are compressed into 5 categories to be easier to comprehend.
You will find examples both from our 18+ years practice and those that can be found in the literature.
We will provide you with practical tools that you can use for your projects.
We’ll provide examples, help you identify if you’re in this situation, and tell you how to prevent failure.
Real cases and examples
Learn from the mistakes of leaders like Microsoft, Amazon, and IBM who failed to deliver on AI promises.
The authors share real (and sometimes anonymized) tales of AI disaster!
You can apply these lessons to improve your AI project today to avoid failure.
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F33.ai revolutionized our AI journey by breaking down communication barriers, streamlining processes, and empowering us to prioritize and implement over 30 initiatives with transparency and success.
F33.ai helped us to structure the AI innovation management process around our product. We were provided with complete guidance with templates of processes and documents. This allowed us to open up communications between the product team and the engineering team, and the stakeholders. The result was 30+ initiatives we can transparently prioritize and implement.
Principal Product Manager
F33.ai helped us to unlock communication bottlenecks between our team and business. We were provided with a fully functional AI end-to-end development process with documentation templates so we could speed up our AI journey. F33.ai also helped the product team to understand better how to talk to the AI team to secure business success.
Senior Engineering Manager, Data Science
F33.ai transformed a retailer wholesaler's CRM system by resolving underperforming AI models, delivering detailed analysis, prescriptive recommendations, and enhanced guidance for effective CRM optimization.
F33.ai helped us identify the causes of our AI models' inefficiencies, described in a detailed report. We were also provided with prescriptive recommendations on how to proceed in the future. Working with F33.ai made our AI work transparent to business stakeholders, which allows in future better support from them to overcome bottlenecks.
CRM AI team manager
F33.ai helped us to understand how KPIs and business processes are critical to building working AI models. They helped us to identify and understand causes and what was most helpful by providing guidance on how to proceed in the future to use AI as a CRM optimization tool.
The author Wit Jakuczun, is a mathematician and industry-recognized AI expert with 18+ years of experience in delivering over 100 AI solutions for various industries, including gas & energy, supply chain, retail, telecoms, and banking. I have also worked closely with C-level managers and supervised consulting teams. His expertise lies in building AI-driven decision support systems by combining operations research and predictive modeling, resulting in impactful solutions that deliver value to businesses.
Why should you
IT Director / CIO, Dino Company
Wit Jakuczun has been delivering AI results for business before anyone knew it was a thing. His depth of knowledge is unparalleled to anyone I've met in the field, and I've talked to many AI "artists". What I like most about Wit is that he doesn't just look at a problem and add AI; he is always searching to find the real problems – the kind you must dig to understand. What sets Wit apart is his approach to problem-solving. He doesn't simply apply AI to any given problem, but rather, he meticulously seeks out the core issues that need to be addressed. These are often complex problems that require deep understanding and analysis to unravel.
What makes this whitepaper different from other resources on AI project failures?
This whitepaper stands out due to its comprehensive coverage of the top 5 reasons why AI projects fail, supported by both documented examples and real-world experience. The author, an industry-recognized expert with a PhD in machine learning and 18 years of practical experience, shares prescriptive recommendations based on successful AI implementations. The unique combination of expertise, practical insights, and practical recommendations sets this whitepaper apart.
How can this whitepaper benefit me if I'm new to AI implementation?
If you're new to AI implementation, this whitepaper is an essential guide that offers valuable insights and best practices to help you navigate the challenges. The author's extensive experience in delivering AI projects to various industries ensures that the recommendations are practical and relevant. By following the prescriptive recommendations and understanding the common pitfalls, you'll be better equipped to avoid mistakes and set your AI projects on a path to success.
I've already had some experience with AI projects but encountered challenges. Will this whitepaper still be relevant for me?
Absolutely. This whitepaper is designed for those who have encountered challenges in their AI projects or are looking to improve existing processes. The author's expertise and real-world experience in overcoming common pitfalls provide valuable insights and recommendations that can help you address specific pain points and enhance your AI implementation. Whether you're starting from scratch or seeking to optimize your current processes, this whitepaper offers practical guidance to improve your chances of success.
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Avoid AI Failure