Years ago, I sat in a performance review that lasted all of seven minutes. My leader smiled, said “You’re doing a great job!” and zipped through the HR form faster than I could sip my coffee. There was no written feedback, no examples of what I’d done well or where I could improve. It was nice to hear I was doing fine, but it wasn’t helpful. I walked out of that meeting wishing that my leader or someone (anyone!) had taken the time to give me a thoughtful assessment of my work.
Fast forward to today, and it seems I might get my wish, though not from a person. According to a recent Morning Brew article, JPMorgan Chase will begin letting employees use AI chatbots to draft their year-end performance reviews. The system, built in-house, can generate review summaries and performance narratives, though humans still have the final say and are barred from using AI-generated text to make salary or promotion decisions.
At first glance, it sounds like progress. Many managers dread writing reviews; it’s time-consuming, emotionally fraught and often inconsistent. If a chatbot can organize feedback, highlight achievements and even smooth out awkward phrasing, that might lead to better reviews for everyone. Employees could finally get more than “Great job” or the opposite with no helpful explanation. They might get specific, structured insights, perhaps even consistency across teams.
This shift also reflects a much larger transformation happening inside organizations. A Harvard Business Review article titled “4 Actions HR Leaders Can Take to Harness the Potential of AI,” noted that human resources leaders have a critical role to play in how companies adapt to the changes driven by generative AI. By helping redesign work and operating models to guide their organizations into the future, HR professionals can define not only how businesses use AI but also how people and technology collaborate to deliver results.
But the idea still raises uneasy questions. Do I really want an algorithm judging my work, even indirectly? A performance review isn’t just words on a screen; it’s a reflection of how someone perceives your growth, potential and value. When a machine crafts that story, does it reduce you to a dataset? Can an AI understand the nuance of a tough project or the quiet leadership it takes to hold a team together during chaos?
There’s also the issue of bias. AI systems learn from data, often data filled with the same blind spots and inequities as the humans who trained them. If past reviews contained subtle biases around gender, race or communication style, the model could reproduce those patterns at scale. Instead of one manager’s bias, you might get the algorithmic version of thousands.
On the other hand, humans aren’t exactly paragons of objectivity either. We play favorites, forget details and sugarcoat tough truths. Perhaps the ideal scenario is a hybrid: humans writing with AI assistance. Let the chatbot help with structure, grammar and summarization, but let the human heart (and judgment) remain in charge.
Performance reviews are one of the few remaining moments of genuine human reflection in the workplace. They’re a ritual of recognition and accountability. Handing that over to AI feels like outsourcing empathy itself.
So yes, I still wish for feedback that goes beyond a simple “Great job.” But these days, I think about how the leaders of the future will deliver it and how their teams will receive it, not just intellectually but emotionally. AI will continue to refine how we organize information and shape ideas, so it will inevitably inform performance reviews. But leadership will always be an act of human connection. Feedback should tell the story of someone’s work. And a story, in the end, deserves a human author.
I asked industry leaders to share their perspectives on the role of AI in performance reviews.
Anne Cooper, Ph.D., human resources executive, Altus CXO
An effective performance review is a strategic dialogue that assesses how well an individual’s objectives and results align with organizational goals. To ensure that your team members are growing, the review process should be fair, transparent and focused on development, providing clear expectations and ongoing feedback. AI can support this process by delivering data-driven insights, standardizing evaluations and recommending personalized learning opportunities. While AI streamlines administrative tasks, it is essential to balance technology with human judgment to avoid algorithmic bias and maintain meaningful connections. A two-way dialogue between two humans remains the most effective approach to ensure growth and productivity. Therefore, the optimal review integrates AI’s analytical capabilities with human empathy, transforming performance reviews into impactful conversations that drive growth for both employees and the organization.
Tom Florian, account manager, HPE Juniper Networking
An effective performance review needs specificity. Yes, there will be core competencies and metrics that must be reviewed, but for an employee to truly grow and shine, we must look at their specific areas of expertise and growth potential. AI can and will enhance the measurement of core competencies and analyze performance metrics (sales, ROI, etc.) allowing for a more consistent and level playing field for reviews, but it will still be up to people leaders to support their employees in achieving those more subjective and individualized performance goals.
Georgia Van Gundy, deputy director, Iowa Workforce Development
An effective performance review is built on honesty, accountability and a clear focus on the employee’s skillset. It should feel like a natural extension of the conversations held throughout the year, not a one-time event. Great leaders use this opportunity to help employees understand the skills required for various roles within the organization and how their unique strengths can drive the broader strategy and vision forward. Reviews should highlight which skills employees can further develop to meet their goals, as well as those they should continue to leverage. When done well, this process is constructive, empowering employees to see their role in the bigger picture and how they can grow and succeed. While AI can support the process by offering training resources, performance plans, and strategic insights, the review itself must remain personal and thoughtful. For that reason, I would not recommend using AI to write performance reviews.
Daniel Zinnel, Ed.D., CEO, Proteus
A truly effective performance review is one in which the employee hears nothing new. Employee performance should be evaluated throughout the year, with timely feedback that celebrates successes and identifies opportunities for growth. The annual review should simply reinforce what has already been discussed. I believe AI can enhance this process by helping managers plan and track ongoing feedback, ensuring it happens consistently rather than only once a year. These tools can support consistency and fairness across teams, ensuring every employee receives the attention and guidance they need and deserve. Reviews must remain authentic, which is why AI should not be used to write the feedback itself. Feedback must come directly from the manager to feel genuine and delivered in person to express the appreciation, coaching, and support employees are entitled to.
