Cultivating better managers: AI for improved performance management | Atomicwork Blog

Managers play an inordinate role in employee success. Yet, they are the least trained for their jobs. AI can fix that.

Writte by Hallie Bregman, edited by Sadhana Balaji.

As the adage goes, people join a company but leave a manager. In every company today, real employee success is almost entirely in the hands of their immediate manager. Most often, managers aren’t trained to shoulder this responsibility. In fact, Gallup found that the top two reasons managers become managers are: “success in a prior non-management role and tenure.”

Being a good manager takes practice, which means that regular coaching and on-the-job nudges are likely more effective than classroom training. Artificial Intelligence (AI) has great potential to consistently deliver this coaching, cultivate better managers, and maximize employee success.

Nudging positive behavior

With so much happening day-to-day, it is practically impossible for organizational leaders to monitor and give feedback on manager behaviors. For instance, a manager might cancel or reschedule too many calls at short notice. Unless someone complains, there is no way for such behavior to be known to the senior management.

AI can help flag such things. Every time a manager reschedules a meeting, an AI chatbot can request them to reconsider. If they speak more than they listen in meetings, AI can be the checker. If they haven’t communicated with their direct report in several days, AI can remind them to check in.

AI can also help identify struggling employees and encourage the manager to help them. It can say, “This employee has had only three touch points outside of their team this month.” The manager can then look at the projects the employee has been working on and evaluate if this is an appropriate concern. These kinds of nudges still keep the authority and responsibility with the managers while giving them timely reminders to support their teams.

Plus, AI can be trained to coach managers to behave in line with identified competencies and behaviors.  What makes a good manager in one organization (and even one department) might be completely different than another.  It’s the ability to customize and personalize feedback that is so critical.  

Giving better feedback

In most organizations, managers aspire to give relevant, actionable feedback to their employees.  Yet, the quality of feedback varies significantly.  For new managers who aren’t experienced at giving feedback, they might provide less tangible recommendations or more subjective feedback.  Feedback acts as the barometer for employee performance, especially in startups and smaller organizations, where things change quickly. 

Yet, a lot of this feedback is heavily biased and subjective. AI can help interrupt bias in action.  For instance, AI can say, “The language you are using is gendered. Please reconsider your feedback.” or “There are things you say about Hallie that you’ve never said about John. Please check for any underlying bias.”

We’re not at a place where AI can emphatically declare whether specific feedback is biased. But it can most certainly give directional insights by flagging issues that managers can correct for themselves. If we design the AI product to err on the side of caution, we could make empathy, inclusivity, and belonging an everyday act rather than an ambition that it is for most organizations today.

Driving effective performance reviews

Irrespective of an organization’s best efforts in creating 360-degree performance reviews, a disproportionate amount of importance is placed on the manager’s input. Merely writing detailed performance reviews for a dozen team members might be much more complex than we imagine. 

AI can help structure this thought process and build great performance reviews in the following ways:

• Use a template to ensure all aspects of the employee’s performance are covered
• Eliminate recency bias by inviting managers to consider the entire year as a whole
• Nudge managers to use unbiased language
• Guide them to map feedback to competencies and job responsibilities
• Summarize salient points in a language that’s most useful to the employee whose work is being reviewed

AI’s potential to help build better organizations is limitless. However, we must remember that no AI tool is a band-aid solution to any problem. No AI has evolved so much that we can say it’s 100% there and wash our hands of it. It very much requires human interaction. The power is still in the hands of the people — i.e., managers — to guide their teams toward success.  

About Hallie Bregman

Hallie Bregman, PhD, is a renowned expert in people analytics and strategy with a strong passion for data, technology, and innovation. As the Founder and CEO of The Bregman Group, Hallie leads the way in helping Chief People Officers transform employee insights into measurable improvements in organizational effectiveness. Her extensive experience includes supporting esteemed clients such as Bain & Company, Brooks Automation, and 10x Genomics.

Having served as a thought leader in the talent industry, Hallie has spearheaded people analytics initiatives at prestigious companies like Wayfair, Toast, and PTC. Her expertise and vision have earned her recognition as an accomplished professional in the field. Hallie's mission revolves around helping organizations measure what truly matters, enabling them to make informed decisions that drive business success and create a positive workplace environment.