It seems that every time we discuss the impact of AI on employees, the conversation immediately goes to computers replacing humans. While there are serious implications that need to be discussed on that topic (particularly for those in “blue collar” professions), it is time for us to expand the dialogue to understand the positive impact that AI is having and will continue to have on employee productivity and satisfaction.

Freeing Your Employees to be More Strategic

According to Forrester Research, there are more than 865 million information workers across the globe. These information workers, who use internet-connected computing devices for work, are increasingly looking toward AI to free them up from doing mundane tasks, saving them valuable time and enabling them to be more strategic, creative and innovative. For example, leading sales organizations are increasingly leveraging workflow automation for contract lifecycle management. Not only does this speed up the time between a customer saying “yes” and actually getting cash in the door, automating these processes allows the sales team to spend their time following leads, not chasing contracts and signatures across multiple departments and organizations. 

Recent advances in artificial intelligence now enable them to become even more productive by using machine learning to identify anomalies in contracts (e.g., maybe pricing changes or contract lengths that fall outside the norms) and flag them up as areas that warrant human attention/intervention. And, rather than having contracts bottleneck waiting for somebody to read and review every single word of the document, machines can leverage natural language processing and machine learning to do much of the heavy lifting flagging nuances in contract language and calling a reviewer’s attention to those specific areas that warrant a closer look. Leveraging AI in these examples doesn’t “replace” humans; it frees up their time enabling them to be more strategic and focuses their time/attention on the things that matter increasing their overall productivity.

Be Wary of Using AI as a Stick

Another major benefit of using AI is the improved business intelligence across the company, at the department/business unit level and at the individual performance level. Depending on whether your glass is half-full or half-empty, you can see this as a way to identify your most or your least productive employees. It can certainly do both, but there’s a clear advantage to focusing on the positive here.

If you mention that you’ll be using AI to evaluate worker performance, people often fear that only their weaknesses will be evaluated. Were they absent from work too often? Did they miss a deadline? Did someone give them a less than glowing performance review? They’ll bring up Big Brother and threaten to throw their shoes into the machinery. AI will be seen as a soulless automaton, finding those employees who clocked out a minute early last Thursday and meting out reprimands and warnings. Instead of focusing on using AI to measure/monitor individual performance, leading companies use it to assess broad areas of underperformance or to identify differences in productivity/results between one group and another highlighting areas that need more leadership attention or require a manager to get involved to remove bottlenecks or address specific performance blockers.

Using AI Carrots to Drive Employee Performance

The real power and value of using AI to evaluate productivity will likely come from identifying the things that your 2-3xers are doing, seeing how they’re using the tools at their disposal, and determining how to make those behaviors into companywide best practices by incorporating them into your workflow automation. When you create highly personalized, highly contextualized processes and training based on actual performance, you’ll have tools that can benefit all employees encouraging and teaching best practices rather than simply focusing on weeding out bad ones. And, by using process automation and artificial intelligence, you’re doing it in a highly scalable, highly effective manner. 

Focusing on positive results rather than negative results is more than just a linguistic shift. Removing a negative process takes care of that one ineffective instance. The unwanted behavior from that one employee is gone. But adding a positive process to your workflow puts a proven procedure in place that can bring about repeatable, successful results. AI is an incredible resource to help you discover which behaviors are working in your current environment.

This is not to say you should ignore any negative data that AI might collect. AI might find that someone’s sales numbers are down. That’s certainly something you should investigate. But instead of coming down on that employee and telling them to get their numbers up or else, you can point them to the practices that AI is showing as successful.

Matt Fleckenstein
Matt Fleckenstein

has spent 20 years utilizing rules- and algorithm-based techniques to automate B2B and B2C customer experiences.  Matt is currently the chief marketing officer at Nintex, the recognized leader in Content and Workflow automation.  Prior to Nintex, Matt was the Chief Marketing Officer at Amplero, an AI Marketing Automation company that uses machine learning and continuous testing and optimization to enable marketers to achieve what’s not humanly possible.  Matt previously served as the VP of Product for the Salesforce Marketing Cloud and the Salesforce IoT Clouds.   Earlier in his career, he ran retention marketing for Office 365, using Big Data and Predictive Analytics to help Microsoft transition from being a perpetual software company to an online service/SaaS company.  An entrepreneur at heart, Matt was a cofounder of two adaptive algorithm startups — mSpoke (content recommendations acquired by LinkedIn) and Peak Strategy (algorithmic trading strategies for hedge funds acquired by Morgan Stanley).