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Succeeding with AI: how to manage successful AI projects


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Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It’s filled with practical techniques for running data science programs that ensure they’re cost effective and focused on the right business goals.

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Succeeding with AI: how to manage successful AI projects

  1. 1. How To Manage a Successful AI Project From Succeeding with AI by Veljko Krunic Take 42% off the book by entering slkrunic into the discount code box at checkout at
  2. 2. Thesis of the book • Technical knowledge regarding AI algorithms isn’t sufficient to get business results using AI. • The fastest way to fail with AI is for the executive and business leaders to think, “AI can solve our problems; we don’t need to do anything except hire the right tech geeks and unleash them on our data.” • Or, for the whole data science team to think “business people take care of the business; we focus on technology.” Business and technology must work together for success.
  3. 3. How is Money Made • What you may have heard is • Data + AI = $ • If $ stands for cost, this is completely true. AI systems (and people operating them) would come with a significant cost attached. • However, if you want $ to stand for profit, the equation looks different: • Data + AI + CLUE = Profit
  4. 4. What is CLUE? • CLUE is an acronym for • Consider (available business actions) • What business actions are possible for you to take? • Link (research questions and business problems) • Can you achieve your goals better/faster using AI? If so, How? • Understand (the answer) • How will you know what the technical solution means in a business context? • Economize (resources) • Maximize your efforts so you don’t just end up burning $
  5. 5. How to Apply CLUE for the best results CONCENTRATE ON AVOID OVERFOCUS ON Infrastructure Volume of Data Algorithms Define Possible Business Actions Formulate Research Questions to Answer Triage Projects by Difficulty Formulate Business Metrics Initiate Individual Projects Initiate Individual Projects Initiate Individual Projects Initiate and Run Individual Projects C LUE
  6. 6. Start with “What Can I do?” • There is always something in the data! • “That is interesting… but what can I do with that info?” • Most of the time, you can’t act on random insight! • The number of good, effective actions you can take to affect the physical world is relatively small! • There will be many analyses you can perform that yield results that are not actionable • Therefore, always start an AI project by asking “what business actions are possible?”
  7. 7. Concentrate on the System, not on AI Algorithms • Every system is different • So is the answer to the question, “What part of the system should I improve next?” • Therefore • Analyze your ML pipeline! • MinMax analysis • Sensitivity analysis • Think about the reasons behind each step you are taking!!!
  8. 8. If you want to learn more about the book, check it out on our browser- based liveBook reader here. And don’t forget that by entering slkrunic into the discount code box at checkout at you can get 42% off your purchase.