Here’s a hint as to what is separating the AI failures from successes: skip the proof of concept. When it comes to AI projects go right for pilot projects. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss AI Pilots vs. Proof of Concepts.
AI Pilots vs. Proof of Concepts
A proof-of-concept is a project that is a trial or test run to illustrate if something is even possible and to prove your technology works. Proof of concepts (POCs) are run in very specific, controlled, limited environments instead of in real world environments and data. This is much the way that AI has been developed in research environments. Howver, the problem with these POCs is they don’t actually prove if the specific AI solution will work in production. Rather, they only if it will work in these limited circumstances. In this episode we discuss why you should always skip POCs and go right for pilots.
Pilot projects, on the other hand, focus on building a small test project in the real world. They use real-world data in a controlled, limited environment. The idea is you’re going to test a real world problem, with real world data, on a real world system with users who may not have created the model. This way, if the pilot project works you can focus on scaling up the project versus applying a POC to an entirely different environment. As a result, a successful pilot project will save an organization time, money and other resources.
Following best practices approaches
It is much better to run a very small pilot, solving a very small problem that can be scaled up with a high chance of success rather than trying to solve a big issue with a proof of concept that could fail. This approach to small, iterative successes focusing on pilots is a cornerstone of <a href="https://www.cognilytica.com/cpmai/?utm_source=forbes">best-practice AI methodologies</a> such as CPMAI. CPMAI aims to give guidance on how to develop small pilots using short iterative steps to obtain quick results. Focusing on the highly iterative, real-world AI pilot will ground your project in that one simple method that many AI implementers are seeing with great success. In this episode we discuss why adopting this approach is key to AI project success.
Show Notes:
<ul>
<li><a href="http://aitoday.live/cpmai">FREE Intro to CPMAI mini course</a></li>
<li><a href="http://www.cognilytica.com/cpmai">CPMAI Training and Certification</a></li>
<li><a href="https://www.cognilytica.com/ai-today-podcast-ai-failure-series-iteration-time-proof-of-concept-vs-pilots/">AI Today Podcast: AI Failure Series – Iteration Time & Proof of Concept vs. Pilots</a></li>
<li><a href="https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=6919643576205234176">Subscribe to Cognilytica newsletter on LinkedIn</a></li>

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Kathleen Walch

Ron Schmelzer

Skip the AI Proof of Concept [AI Today Podcast]

Here’s a hint as to what is separating the AI failures from successes: skip the proof of concept. When it comes to AI projects go right for pilot projects. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss AI Pilots vs. Proof of Concepts. AI Pilots vs. Proof of Concepts A [&hellip;]

AI Today Podcast Episode #456

Skip the AI Proof of Concept [AI Today Podcast]