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What Challenges Do Businesses Face with AI?

AI is powerful, but in enterprise planning, “probably right” isn’t good enough. In this video, we explore how Board helps overcome AI’s biggest accuracy challenges by combining AI speed with deterministic calculations, business-specific semantic context, and multidimensional planning intelligence. Watch to see how Board makes AI more reliable, relevant, and ready for real business decision-making.

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2:38 min

  1. One of the most common challenges around AI is around accuracy.

  2. The normal AI is a very probabilistic model.

  3. You ask the question 100 times, you're not going to get the exact same answer 100

  4. times. That's just the underlying technology we're playing with.

  5. But a lot of planning exercise is deterministic calculations that our customers are

  6. doing. As Board, we want to also understand the challenges that AI

  7. has, and we want to make sure a solution out of the Board platform addresses those

  8. challenges. Right? And so Board brings in a deterministic way to address that, so

  9. that in planning context, it is not acceptable for the FP&A team to ask 100 times

  10. what my EBITDA is and say that, oh, yeah, a few times you could get a wrong answer.

  11. That's just not an acceptable answer in an enterprise.

  12. So, second part of accuracy issue is around semantic understanding in a business

  13. context. If I have 10 people use the word, what are the profits on this?

  14. What is the cost of this? There are multiple definitions of profits and

  15. costs based on various businesses, based on different persona looking at it, and

  16. this is where a planning platform such as Board is usually the repository of

  17. all of this knowledge of how planning is done.

  18. And by bringing and enriching AI's speed and ability with all of that

  19. semantic context, you're going to improve the accuracy level. Right?

  20. So that's again, another way in which we do it.

  21. And the third piece of accuracy is just the context window.

  22. You cannot throw in terabytes and terabytes of data in front of AI and say, "Oh,

  23. go do this." This is where Board, through its multidimensional model,

  24. really understands planning and decision making.

  25. Board understands, okay, if I am a GM of the Americas, what is my

  26. context? What are the things that I'm looking at?

  27. What are the products I'm working on? What is the channel I'm working on?

  28. What are the customer segments? And it's able to really present the data in a very

  29. organized way with the right context, then for the AI to really have, again,

  30. layered on the semantic definitions to really improve the context.

  31. So in a nutshell, for us as Board, we want to embrace all of the strengths of AI,

  32. but augment all of the limitations of AI with the Board platform.

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