Middle managers are feeling the squeeze from all sides. In the face of uncertain market conditions, they’ve been thrust into unfamiliar situations: overseeing hybrid and remote teams, managing a 24/7 connected workforce that obliterates the line between work and personal life, and raising the performance bar higher than ever.
This is where AI often enters the conversation. AI, the theory goes, can ease managers’ burden by handling their busy work and making them more productive.
There’s just one problem.
The area where middle managers feel the most pressure is not with productivity but with people leadership. They’re being asked to get the best out of a workforce that’s burned out, dispersed and setting new boundaries and modes of working.
Good managers make the effort to know what their teams need, even as the economic and cultural conditions around them change: what’s important to them, how to relate to their perspectives and how to show up differently for employees with different engagement or performance statuses. Good managers think strategically about their people.
The good news is that HR can look for AI to help here, too, driving impact beyond simple productivity gains. In sifting through all the additional signals and feedback produced by the new ways we work, AI can help middle managers identify what matters to them and what to act on.
AI’s ability to analyze tremendous volumes of data and employee feedback empowers middle managers to refocus on their core competency: caring for their people, even if they don’t see them face-to-face. Here are the top three ways HR can use AI to empower middle managers to be more strategic in caring for their people.
Decode specific employee sentiments and their causes
No one becomes a manager because they love admin. They do it because they love seeing people succeed and want to create experiences and environments where employees do their best work. Finding out what makes their people tick is where the admin work comes in.
Middle managers spend at least one day a week doing administrative tasks, such as processing employee feedback found in surveys, using communication tools like Slack or Microsoft Teams, and even handling IT tickets. As we introduce new technology into the workplace, managers will find themselves absorbing an increasing amount of employee feedback data emitted by these tools, loading them with more and more admin work as a result.
Employee feedback contains tons of insights as to what’s impeding productivity or engagement, but humans can’t parse through it as efficiently or intelligently as AI can.
Advancements in AI with large language models (LLMs) and natural language processing (NLP) models can analyze hundreds of thousands of employee comments for emotional nuance. This is extremely valuable for managers at global enterprises who have to sift through large corpora of employee feedback.
AI models can identify the “intent” of feedback comments and the emotions behind them so managers can respond effectively and sensitively. AI surfaces issues that would otherwise fall in a manager’s blind spots—or just get lost in a sea of comments—to their top-of-mind priorities.
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Engage with feedback more proactively
When employees share feedback, they expect their managers to do something about it: acknowledge their perspectives, take action and communicate their improvement strategy. After all, they’re telling their managers what they need to be more engaged and productive. Lots of middle managers recognize how valuable these insights are but struggle to take action on them. Constantly asking employees for input and offering no follow-through sets them up for frustration and disengagement.
AI can help bridge the gap between insights and action plans so employees can see that their input is heard and incorporated. AI’s ability to organize and analyze raw feedback helps middle managers quickly identify the issues that matter most to employees.
AI tools can also deliver personalized leadership insights and recommendations to managers in their workflow. For example, AI might guide them to initiate a conversation with a struggling team member, turning an item of feedback—that would historically come from a point-in-time survey—into a real-time, two-way dialogue. This fosters a more meaningful connection, where middle managers are actively aligned with their team’s needs and engaged in supporting them throughout the year.
Coach every team member at every stage
Traditionally, employee coaching involves a trade-off between personalization and scalability. You have to choose one: hands-on coaching for a few of your favorite direct reports or “keep the lights on” support for the entire department with generic technology and coaching content. With AI, managers can start to offer more personalized coaching at scale.
AI’s ability to hyper-personalize can influence positive employee behavioral growth over time. First, it can uncover and even predict trends in employee engagement by analyzing countless individual data points. Then, it can intelligently give each team member insights, nudges and suggestions for action—and explain where its recommendations came from in the data—all while learning and measuring the impact on business outcomes.
Instead of relying solely on a one-time training or coaching session, middle managers get to meet employees where they are. They get to provide specific guidance to allow for behavior change over time, ultimately building a more resilient workforce.
Better care for your team
The essence of exceptional management boils down to one trait: caring for your people. Being an exceptional manager is about showing up differently for each individual and discerning how to adjust and improve their experiences based on their perspectives. It means recognizing what matters to them and responding in a way that nurtures their growth and wellbeing. To do this, HR has to help middle managers think strategically about how they take care of their teams.
When middle managers use AI to decode employee sentiments, engage with feedback proactively and provide hyper-personalized coaching, they’re equipping themselves to think strategically and thus care for their teams with a new degree of care and precision. AI gives managers the knowledge to be better leaders—ones who can tailor their approach to meet the unique needs of each employee—not just more productive leaders.
And when managers build stronger and stronger relationships with their reports, they can begin to alleviate some of the pressure they’re under in leading, motivating and supporting their teams through the ever-changing ways we work.
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