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Onboarding a Model Employee

Leveraging the benefits of a digital teammate

Think about your current employee onboarding practices; how long does it take for an employee not to be “new” anymore? When do you get to a point where a person is fully trained and capable of being successful at their job without any further assistance? Many companies focus on a typical 90-day evaluation period, however, by one account it takes about six months before an employee feels like they are being productive in their role.

Extending that timeline even further, there are also two-year rotation programs where an employee works in a variety of teams and capacities, experiencing multiple facets of the organization. At the end of the rotation program, the employee has a broad perspective across the company and then moves into a permanent position. How long and willing are you to wait to see returns on your employee investment?

It’s a tricky question because of the persistent variable in the equation: the human. Depending on the experience, background, character traits, learning style, and a host of other factors, each person has their own length of runway before they’re ready to fly solo. Most are fully capable within that 90-day period, some take longer, and others seem to be high performers from day one. These are the people who don’t waiver when you use phrases like “trial by fire” or “sink or swim” to describe the working environment.

But then there are times when employees forget how to do certain things because they haven’t done them in a while. They get rusty or require some retraining to get back up to speed. Maybe you’ve forgotten to do a small thing here and there, like responding to an email? You can chalk that up to human capacity too. Ever had to plan around an employee’s time off? It gets even worse when you realize there’s only one person who knows how to do something and this is the week they’re on vacation.

One interesting thing about artificial intelligence (AI) is that you take away all this variability. Your AI solution is taught how to perform a function by the rules you’ve already established. It knows what success is because you decide what success means. It knows only what you want and stays within the boundaries you define. There’s no question what your AI will do because you’ve dictated everything it can do.

A process automation AI is never bored, unmotivated, or disengaged. They always follow orders, work 24/7, and are 100% accurate.

As a simple case scenario, let’s say you have a printed form that requires a person to write their name, phone number, email, and home address. And then all of this data needs to be transcribed and entered into a database (which would typically require another person doing data entry). In this example, you can implement an AI solution to look only at the “Name” field and transcribe it into a database. In other words, it will ignore all the other fields because you didn’t tell it to look at them.

Now let’s say you want to add in the rest of the fields and have your AI transcribe all the entries—it will continue to only look at those designated fields, all day every day. It doesn’t forget how to complete these actions. It doesn’t sometimes miss a field by mistake. It doesn’t randomly decide to look at a completely separate form. All this said, your AI solution is a robot—a high-performing, sophisticated robot but still only doing the functions you’ve decided on.

To measure the performance difference between an AI and a traditional robotic machine (such as on a car assembly line), you don’t need to look very far. On one hand, the defrost button on a toaster has a more advanced system than the computer used to land astronauts on the Apollo 11 mission. Now think about how much more sophisticated your smartphone is than your toaster. Your smartphone doesn’t send text messages or browse social media sites by itself—it’s a tool you use the same as you would an AI solution. And if you think your smartphone is helpful to you, think about how an AI can be even better.



Harvard Business Review

Blog Author

By Brad Mascho
Chief Artificial Intelligence Officer, NCI