It’s tempting to think that stacking a team with top talent guarantees results. Add AI, and you’ve got supercharged individuals. But star performers don’t automatically create high-performing teams—and AI can make things worse.
Duke dean and professor Scott Dyreng saw this firsthand. His M.B.A. students worked in teams, with the option to “break up” for the final project. Before AI, about 5% did. After AI, over half went solo, he writes in The Wall Street Journal. Dyreng found that AI disrupted core teamwork skills, like negotiating and reaching agreements. But instead of banning it, he used AI strategically—for meeting analysis, summarizing discussions, and reporting participation. The tools didn’t replace communication—they strengthened it, encouraging more human interaction.
The lesson for leaders: it’s not whether to use AI, but how. Misaligned dynamics can neutralize even top talent. The best teams focus as much on how they work together as on who’s on the team—and they use AI to enhance, not replace, that collaboration. Here’s how.
Form balanced teams for each project
I’ve long been a proponent of cross-functional teams. At Jotform, employees work in small groups—usually a senior developer, front-end developer, back-end developer, designer, CSS developer, and sometimes a project or product manager. This structure creates a natural equilibrium where each person brings their distinct expertise to the table.
With each new project, roles shift. Different team members take the lead depending on the work. Understanding individual strengths and weaknesses helps ensure teams stay balanced and that the right person leads each project.
AI tools can help leaders gather these insights. Meeting analysis, for example, can reveal who takes the lead on specific topics. Communication trends can show where people excel across a project timeline—who initiates, who organizes, and who shines during execution. And if an employee is struggling—say, someone scrambling to manage deadlines—AI can help develop tailored learning solutions that fit their individual schedule.
Used strategically, AI can help organizations lean into team members’ strengths and address weaknesses where needed.
Build feedback touchpoints directly into workflows
As I’ve written before, top-performing teams are fueled by real-time feedback. Annual reviews are often too little, too late, not to mention, engender a very unproductive amount of anxiety. Instead, leaders can build systems with feedback loops, so that team members are accustomed to talking about their performance, including the positive notes, and understand how to improve.
As we’ve seen at Jotform, this removes the “dread factor” from feedback. It also encourages team members to productively and openly communicate ideas. As the WSJ article noted, AI and automation tools can offer feedback that team members can use to hone their skills.
Leaders can set up automated reminders for employees to provide feedback, both manager-to-employee and peer-to-peer. One company created tailored agents, embedded in the team’s workplace software, to coach employees in the feedback process, prompting them to provide immediate and more specific insight, and drafting responses for employees to edit and send. (We do this at Jotform using this template.)
With feedback touchpoints built directly into workflows, both employees and managers get a more comprehensive view of how teams are functioning and where they need to make adjustments.
Make team goals crystal clear at all times
At Jotform, our teams function like micro-enterprises. They manage themselves, including the goals that they focus on. To keep things crystal clear and make sure everyone is aligned, each team has a single-sentence mission at any given time, and it informs their day-to-day work. For example, our growth team might focus on the number of active users. The performance team, meanwhile, keeps its sights on the average response time taken for common activities. This narrowed focus on a single metric enables our teams to achieve quick wins and build momentum.
Setting clear goals and standards holds teams accountable both internally and externally. AI-powered platforms can help organizations and teams continuously set and refine those goals, rather than setting them and forgetting them. Platforms like Betterworks, for example, leverage AI to help teams create and update goals, ensuring they align with company objectives. Managers can easily track progress in real-time, fostering ongoing improvement. The AI-driven platform can analyze progress updates, flag when a team’s metrics are off-track, and suggest adjustments like redefining KPIs or reallocating resources.
When teams are working toward a single goal, they can course-correct better and faster. Team members can support each other when needed. The team succeeds or fails together. They learn together. They improve performance together, and over time, that translates to real, sustainable, bottom-line results.
