The administrative load placed on managers has been steadily increasing for years. On the performance management front, that means an increasing cadence for feedback, more pressure to make feedback thorough and actionable, and ballooning reporting requirements. Managers are, understandably, looking for ways to lighten the load.
That’s where AI tools come in.
As managers are expected to shift from reacting to performance issues towards predicting them and acting on them proactively, AI tools give them what they need to make that shift. Platforms like 15Five build AI features into broader performance management tools, helping managers analyze performance trends, fine-tune their feedback, and match team members with growth opportunities.
Here’s how.
Key Takeaways:
- AI tools for performance management enable proactive identification of performance risks
- Managers can use predictive insights to improve engagement, retention, and productivity
- AI tools for workforce management centralize and analyze employee data at scale
- Real-time feedback and sentiment analysis improve decision-making
- AI-powered platforms like 15Five AI help managers take timely, data-driven action
- Integrating AI into performance strategies strengthens HR’s role as a strategic partner
What are AI tools for performance management?
AI tools use technology like machine learning, natural language processing, and predictive analytics to streamline some elements of performance management and enhance others. Here’s what they do and how they help managers:
- Machine learning: A broad category that describes algorithms that improve as they process more data. In performance management, this means AI tools can “learn” the particularities about your industry, what top performers look like at your company, and how to best help managers.
- Natural language processing (NLP): This allows AI tools to analyze written text and extract meaning from it. It turns check-in responses, survey comments, Slack messages, and more into data AI tools can then use for other tasks.
- Predictive analytics: AI tools can use historical data to create accurate forecasts in a fraction of the time it would take a manager to. This allows managers to get a sense of which team members are more likely to leave, which teams are trending towards disengagement, and how certain strategy decisions might affect metrics like employee engagement and turnover overall.
- Generative AI: This AI technology produces new text, images, and even videos that approximate what a human might make. In performance management, generative AI allows for everything from drafting meeting notes to turning engagement survey answers into reports.
- Pattern recognition: AI algorithms can crunch through massive amounts of data to isolate patterns for forecasting and reporting. This turns data points in performance management into insights managers can use.
These tools can be used by managers for just about anything, from analyzing performance trends throughout their teams to turning long meeting transcripts into quick summaries for future reference.
Why predicting performance challenges matters for managers
Most managers are still trapped in a cycle of reactive performance management. Performance issues arise and managers have to scramble to solve them without a pre-planned initiative in place. Once the problem is resolved, it’s never addressed again. Managers return to their usual duties, waiting for the next problem.
This approach leads to significant challenges that affect performance management more broadly:
- Missed warning signs: Signs of disengagement or turnover should serve as opportunities for managers to intervene. But reactive performance management can cause them to miss these signs.
- Delayed feedback: Employees need feedback to keep growing, and they typically want more from their managers. When managers are drowning in administrative work, it’s difficult for them to capitalize on opportunities to give feedback.
- Inconsistent evaluations: Predictive analytics and pattern recognition allow managers and HR to standardize performance reviews and other evaluations. Without these initiatives in place, managers often approach evaluations with little context, making them inconsistent across teams.
Compare a manager who only identifies a disengaged employee during an exit interview and one who spots declining sentiment in check-in responses weeks earlier. The first manager is now stuck with a role to fill, a team to support as they adjust to an increased workload, and preventable turnover that needs to be explained to leadership. The second has multiple opportunities to prevent that turnover by having the right conversations, adjusting workloads, or connecting the employee with a growth opportunity that helps motivate them.
That’s the gap between reactive and predictive performance management. A gap that compounds across teams. It’s the difference between constantly putting out fires and preventing them.
Predictive insights give managers a better sense of what matters to their team and what impact their actions have. This can help improve employee engagement, retention, and productivity by making them more aware and more effective.
How AI identifies performance risks before they escalate
Behavioral pattern analysis
AI can turn the results of performance reviews, the answers in engagement surveys, and even the outcomes of day-to-day work into data points to form a potential pattern. Eventually, AI tools can essentially understand the behavior of each team member and flag warning signs or highlight positive improvements in behavior.
Sentiment and engagement tracking
Sentiment analysis is a technique that allows AI tools to determine the sentiment behind any bit of text. That allows AI-powered performance management tools to get a sense of how employees feel whenever they’re submitting feedback, responding to requests from managers, and more.
Productivity and goal tracking insights
AI tools can measure the work happening in project management tools and chat apps against performance goals. This gives managers real-time insight into how their teams are performing, where they can give their support, and where they can reward high performers. Inconsistencies and slowdowns are flagged before they lead to broader problems, allowing managers to address them proactively.
Predictive alerts for managers
Predictive analytics and pattern recognition allow AI to spot potential performance issues before managers can, alerting them so they can act at the right time. This is especially powerful when these AI tools are built into larger performance management platforms, since managers get alerts in the same platform they’ll use to act.
Core features of AI tools for workforce management
Real-time data aggregation
AI tools can aggregate data from multiple platforms through software integration. The more data they have access to, the better they get. For HR and managers, that means AI tools can centralize essential information from dedicated performance management tools, employee engagement surveys, feedback surveys, and other platforms.
Predictive analytics dashboards
The right AI tool should give managers a simple dashboard for reviewing the data it analyzes. A single, clear place for trends, potential risks, and even suggested actions allows managers to leverage AI throughout their day-to-day work without adding more of that work.
Automated feedback and insights
Managers shouldn’t have to go hunting for insights. With traditional tools, that’s what often ends up happening. AI tools can automatically surface these insights and flag them according to a manager’s priorities. AI models automatically learn from these priorities, employee performance, and company strategy. This allows them to find the right insights and filter out those that don’t fit a manager’s needs. Not only that, but they can assist managers in giving the right feedback at the right time.
Continuous performance monitoring
Most organizations only check in on performance yearly or quarterly at best. While this is more manageable from an administrative perspective, it only gives you a very limited amount of data. AI can continuously monitor performance signals across multiple tools, giving managers a real-time view of how their teams are performing according to pre-established metrics.
Use cases: How managers apply AI in performance management
Identifying at-risk employees early
With employee turnover being so costly — both for replacing the employee themselves as well as lost institutional knowledge — identifying at-risk employees is a huge priority for managers. Here’s how AI-powered tools can help them do this:
- Scan deliverables from employees for signs of declining performance.
- Identify signs of disengagement in engagement surveys over time.
- Dynamically track workloads to spot burnout before it happens.
Improving manager-employee check-ins
Planning for check-ins and performance reviews can sometimes take as much time as the actual check-in, especially if you don’t have a rigorous template in place. AI tools can help managers create these templates, modify them for specific employees, and even suggest discussion topics and priorities as the check-in happens.
Enhancing goal alignment and accountability
Goal alignment ensures every team member’s work contributes to the team’s broader goals, and each team’s goals contribute to the company’s overall strategy. While robust documentation can help managers and employees keep these goals in mind, AI can ensure they’re always accounted for when planning performance reviews, check-ins, and projects.
Supporting fair and data-driven reviews
Too many performance management decisions are made with incomplete information and gut feelings. That’s not because managers don’t care about using data; it’s just usually too time-consuming. AI can surface the right data at the right time, as well as turn disparate data points into trends managers can use to make the right call.
How 15Five AI helps managers predict and solve performance challenges
Generic AI chatbots can already help managers significantly in their performance management efforts, but they’re not as effective as dedicated performance management tools with built-in AI. That’s where tools like 15Five AI come in.
15Five is a performance management platform that powers everything from better performance reviews to manager enablement. 15Five AI builds AI into all of these features. So whether you’re looking for data on your team’s performance or drafting an outline for an upcoming check-in, AI is always right where you need it.
Some key capabilities of 15Five AI include:
- AI Agents, automated workflows that make performance management faster and less manual,
so you can focus on what's human. - Predictive insights, built on performance data, engagement surveys, and any other data you collect.
- Continuous feedback analysis, so managers know exactly how to address performance issues or reward top performance.
- Manager enablement tools that turn HR strategies into practical initiatives and alleviate the administrative work managers deal with.
15Five already supports proactive performance management with better data, streamlined performance reviews, and support for continuous feedback, but 15Five AI streamlines the work involved while allowing you to do more with the data you get.
Want to see what 15Five AI can do for your performance management workflows? Learn more here.
Support people with AI
Reactive performance management means managers are never getting ahead of the core issues that affect employee performance. That leads to employees lost to preventable turnover, projects grinding to a halt, and burnout throughout teams.
Dedicated performance management tools can give managers the visibility and tactics they need to prevent some of this, while AI supercharges these capabilities. It turns data into actionable insights in a fraction of the time, suggests next steps autonomously, and learns from your efforts to improve itself as it works alongside you.
Platforms like 15Five AI allow your managers to go from being reactive to being proactive, ensuring your teams always perform at their best.
