“Shaun is the most down to earth, relatable, and approachable CEO I have EVER worked for. When I was first hired by his company, INflow, I was very shocked to see how approachable and outright fun their staff is. They invited me to visit the HQ and it was there where I met Shaun in person. I must say, his personality reflects in the overall feel of his company. I am a huge advocate for INflow, and would recommend that if you are a Government Contractor, that you contact INflow for a job. See, I wrote this recommendation for Shaun, but ended up talking about his company. That is how synonymous my experience has been with both Shaun and INflow. Absolutely Awesome!”
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How do you evaluate the feasibility of AI projects?
Projects are fun. But if you're trying to deploy a solution to solve a problem, take the time to define how the solution correlates with the big picture. If you're looking through a small lens, you won't be able to determine if the solution will help you or hurt you.
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How do you evaluate the feasibility of AI projects?
Understand the problem, especially the impacts to the users/organization, and then determine whether the solution will (a) cause more problems or (b) solve the problem. If a - it's unnecessary and a simpler solution exists. if b - define the stakeholders and understand the issues, impacts to their mission, and what they envision as ideal. Then, data requirements, technology assessment (can your infrastructure support it), redundancies, ethical implications, KPIs, how it will be deployed (and by who). Now again... will it solve the problem for the users? Encourage a thorough review of the cost-benefit to make sure it's worth it. Too many times, additional tech is added ($$) to solve a problem that doesn't require more tech.
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