Getting business employees to understand how Artificial Intelligence (AI) works is often the critical point of success or failure for AI projects that work inside the business process.
This does not include AI projects such as working with images, speech, and so on. I am talking about AI that helps people do their jobs better by making recommendations that need to be acted upon. For example, among many human-driven business processes, people need to act on AI model output, including product recommendations or customer retention needs. In these human involved business processes, AI can impact, but the primary action is by the human stakeholders.
Importance of Trust
People want to understand what they are doing. Very few people want to be treated like a small part of a big machine. They want to feel like what they are doing is consequential.
That brings me to an important point - AI scares people.
Between science fiction stories or news stories, AI scares people to the point where they often don’t want to work with the AI system. That is just intensified if the AI model and its action recommendation are thrust onto them with no explanation of why and how about the AI model.
People can easily feel their job is threatened by automation.
In that environment, business users will likely revert to how they were doing the business process as before. Think of salespeople who would disregard a recommendation on when to call a customer or marketing analysts that continue to use the same segmentation models as before.
People need to be reassured that the AI model and its recommendations are going to help them.
It is going to help them adopt the output of the AI project.
Acknowledge People Are Important in AI
The first step is to create educational materials directed at business users. Do not expect to make every business user into a data analyst.
That will not happen.
The goal of an AI operationalization program should be to make people comfortable with the technical process used the develop the AI model. It also needs to highlight how the AI model will aid employees in doing their job better. Combined, these two areas should help most business users trust the AI model recommendations so they will use them.
Pitfalls
As mentioned above, do not try to make employees into junior data analysts. Technical teams usually do this because they are proud of their analytic skills and show off how much they know. (To be fair, data scientists are no different than other job types in going for an information overload approach about their special skills.)
Business executives often make poor messengers as well. It often comes across as a top-down, my-way-or-the-highway message.
You need something in the middle. Also, remember that most people forget most of what they are trained on within a few weeks.
You need to create materials which support a rollout and, also, long term learning reinforcement. This applies to veteran employees and to new employees too.
