How to Ensure a Successful Proof of Concept for AI

Feeling pressured to spin up an AI pilot quickly? If you are, you’re not alone. After all, it’s easy, right? Just turn it on and see what happens.

Many analyst firms and vendors claim this is the year when AI proves its value, which is adding even more pressure on companies to get started. But rushing into a pilot project—or a proof of concept (POC)—without first doing the necessary groundwork is risky. Here’s how you can set yourself up for success:

1. Don’t begin until you have a well-defined use case
   

   I covered this topic in an earlier blog on defining AI use cases, but it’s worth repeating. AI is about delivering outcomes that are tangible and measurable and directly linked to your company’s success. This is what your POC needs to prove or disprove.
   

   Conducting a POC without a clear use case is like sailing a boat without a destination. Unfortunately, executive pressure and market excitement can lead companies down this path. One company I met with recently was on the verge of deploying AI, with the idea that they would start with 50 users, show the technology works, and then deploy it for the remaining 2,000 people in the company. When asked which users would be involved in the POC, they could not name them. When asked about the use case they were trying to achieve—what they expected AI to do for their business—they didn’t have an answer. At that point, it was clear that there were no defined success metrics for the POC and that it was set up for failure. They wisely decided to pause the POC and start over by working backwards from a defined business outcome and use case.

2. Define a finite scope
   

   This ties back to your use case definition. Your AI use case should be bound by a clear description of what is in-scope and what is out-of-scope. This includes data, users, security, location, governance, and more.
   

   This same concept is true for your POC. You need to define a finite number of users, a finite amount of data, and a finite timeframe for the POC phase. Your POC can’t be too small or too large, and you don’t want it to last a year. Defining a finite scope will help you avoid overinvestment upfront—and quickly fail fast and pivot, or succeed fast and scale.

3. Establish quantifiable success criteria

   Your POC is about proving or disproving specific outcomes, not about showing the technology works. What outcomes are you trying to prove? How will you know if you have achieved them? For example, if your goal is to increase efficiency by 20% by using AI, you need a baseline metric and POC results that prove that outcome is possible (or not) by delivering quantifiable efficiency metrics.

4. Get resource commitment

   Make sure you know who the critical stakeholders are that will participate in the POC and get management approval to get their time allocated. Don’t rely on people to work on the POC “when they have downtime”. If the POC is only a pet project and people are just doing it in their free time, it's never going to get done. Whereas if you say, for example, I've got 60 days and these people are allocated for eight hours per week, then you know that you're setting yourself up for success.

5. Don’t get hung up on failure

   With all the pressure to deploy AI, it’s easy to fall into this trap. If your POC fails to meet the success criteria, it doesn’t mean your POC failed. Remember, the goal is to prove or disprove that AI will deliver specific outcomes, before your company invests significantly in the technology. The purpose of the POC is to get up and running, prove out a concept, and then either 1) succeed fast and decide how you want to scale and press on the accelerator, or 2) fail fast and either abandon course because the technology was not what you thought it was going to be, or iterate and try again.

Artificial intelligence promises to be transformational for society, altering the way we live, work, and conduct business. The possibilities seem endless. Resisting the hype and executing proper planning will help you find the value AI can deliver for your organization. We have more AI content coming your way soon to help you on your journey. Watch for it.

For in-depth guidance, ePlus offers a comprehensive set of services, from envisioning workshops to defining use cases, measuring preparedness, determining deployment options, and conducting a proof of concept. Check out ePlus AI Ignite for more information.