How to streamline performance reviews with Asana AI: Tips from Asana's head of digital

As a team leader, I’ve always believed that performance reviews are more than just a checkpoint—they’re a chance to connect with your team on a deeper level. It’s about more than just reviewing work; it’s about diving into the skills and growth opportunities that drive careers forward. For my team, performance reviews are key moments to reflect on progress, celebrate achievements, and identify areas for improvement.

But let’s be honest: the traditional performance review process has its challenges. It can be time-consuming and subjective, and often means digging through emails, Slack threads, and project updates to piece together the full picture of an employee’s impact. That’s why I decided to bring Asana AI into my review process.

Using Asana AI, I transformed how I prepare for and run performance reviews. Asana AI helps by surfacing key insights from across my team’s work, giving me a clearer, more holistic picture of each person’s contributions that I can use to make decisions and recommendations. Here’s how I do it. 

How Asana AI transforms performance reviews

Integrating Asana AI into my performance review process has helped me tackle many of the challenges that come with traditional reviews. Here are some of the biggest benefits I’ve seen:

• Saved time: Prepping for reviews used to take me hours. Now, I can quickly surface key insights, cutting down prep time without losing the depth or accuracy I need to create a well-rounded review.

• Improved objectivity: By analyzing metrics like task completions and goal progress, AI offers data-backed insights—like whether a goal was met or how a project progressed. These insights ground my review in measurable outcomes, taking some of the subjectivity out of the process when I make my final evaluations. 

• Centralized insights: Instead of jumping between tools, Asana AI pulls the information I need from tasks, projects, and goals, giving me a clear view of a team member’s contributions.

• Better recall: With how quickly my team moves, it’s easy to lose track of smaller wins or tasks. Asana AI surfaces projects or tasks I might have overlooked, making sure no effort goes unnoticed.

• More visibility: Even for projects I wasn’t directly involved in, Asana AI identifies tasks or comments that give me additional context and a better understanding of my team member’s work for when I draft my review. 

Streamline your performance reviews in 4 easy steps

Here’s the step-by-step process I prepare performance reviews with Asana AI.

Step 1: Assess impact

I start by asking Asana AI to analyze a team member’s recent work. I always start by prompting around goals—for example, “What’s Chloe’s goal status for this year?” This connects directly to Asana Goals, where progress toward larger objectives is tracked.

From there, I dig deeper with more more specific questions, like “What projects did Chloe work on or complete in the last quarter?” Asana AI pulls together a summary of Chloe’s contributions, highlighting key projects, goals achieved, and deadlines met.

For example, the AI might highlight major initiatives where Chloe played a crucial role or share specific outcomes that came from her work. These insights create a clear, data-backed foundation for her performance review, helping me understand her impact more comprehensively when I write my final review.

Step 2: Identify opportunities for growth

Next, I use Asana AI to explore areas where Chloe could improve. I’ll start with a straightforward question, like, “Show me examples where Chloe faced challenges in the last three months.”

Based on that prompt, the AI pulls relevant context from task comments and project updates, helping me spot patterns—like the types of tasks Chloe excels at, areas where she struggled, missed deadlines, or unmet goals. 

From there, I use these insights to identify key themes and areas of focus. For example, maybe Chloe excels at problem-solving but could improve her time management skills. This is helpful information I can refer to when providing constructive feedback, suggesting specific areas where Chloe could benefit from training or support, and setting targeted growth goals.

Step 3: Gather peer feedback

Collaboration is at the core of what we do, so including peer feedback is a key part of the review process. Asana AI makes this easy by analyzing collaboration patterns. I’ll start with a prompt like, “Who has Chloe worked most closely with this quarter?”

The AI reviews Chloe’s shared projects and tasks to identify her key collaborators. It might generate a list of team members she’s worked with, along with the specific projects or initiatives they worked on together. 

With this information, I can reach out to those colleagues for feedback. That way,  my review will reflect Chloe’s individual contributions as well as her teamwork and communication skills.

Step 4: Compile insights and refine tone

Finally, I put all the information in an Asana task and use Asana AI’s editing features to fine-tune my feedback. Depending on the context, I’ll prompt the AI to adjust the tone of my review—whether it needs to be more celebratory, professional, or constructive.

The AI can suggest more impactful ways to phrase feedback or adjust the tone to match the intent of the message. For example, it might suggest more encouraging language for addressing areas of improvement or help me celebrate achievements in a motivating way.

This step is all about finding the balance between recognizing accomplishments while offering growth-focused guidance. While AI gives me a strong starting point, I always personalize the feedback to reflect my unique relationship with the team member.

How to help your team reflect on their performance with Asana AI

In addition to using Asana AI to support my performance review process, I encourage my team to leverage the tool for their own self-reflection. Here’s how I guide them through the process.

1. Help them explore their own performance data. Just like I do in my performance review process, I encourage my team to use Asana AI to gather insights about their own work by asking questions like “What projects I have contributed to this quarter?” or “Give me a summary of all the work I’ve accomplished over the past six months.” Based on those prompts, Asana AI surfaces key insights that help each person get a clearer picture of their own performance and achievements. 

2. Hold reflective conversations. Once they have the data, I ask them open-ended questions to guide their reflection, like “What accomplishments stand out to you?” or “Where do you see room for improvement?” These conversations are a chance for them to really think about the trends Asana AI surfaces. For example, if the AI highlights that they’re consistently missing deadlines, we can discuss why that might be happening and what steps they can take to improve. Because Asana AI can identify patterns across different projects and tasks, it’s easier for team members to pinpoint specific areas for growth and adjust accordingly.

3. Support data-backed goal setting. Once they’ve identified areas of improvement, Asana AI gives us a strong starting point for setting new goals. Let’s say the AI surfaces a pattern where a team member is struggling to meet deadlines. We can work together to set a concrete goal like, “Reduce missed deadlines by 25% in the next quarter.” Encouraging your team to base their goals on insights from Asana AI ensures they’re grounded in real work context. 

Six tips for getting the most out of Asana AI

Ready to integrate Asana AI into your review process? Here are a few quick tips to get started.

• Prompt thoughtfully: Be specific with your queries and include timeframes (e.g., “in the last three months”) for more accurate and relevant insights.

• Iterate on prompts: If AI’s initial response isn’t quite what you’re looking for, try rephrasing your question. Often, small tweaks in how you frame your request can lead to clearer and more useful responses.

• Balance AI with human input: While AI is great for surfacing insights, it can't substitute human decision making. Use the information it surfaces as context to inform your thinking and complement—not replace—your judgment as a leader.

• Be consistent: Make AI a part of every review cycle to build a repeatable, efficient process.

• Keep all your team’s work in Asana: To get the most out of Asana AI, make sure your team is using Asana to track their work, goals, and projects. The more information you have in the platform, the richer the insights Asana AI can provide—making your reviews even more impactful.

• Use it for your own self-review: In addition to using Asana AI to assist with my team reviews, I use it to reflect on my own performance during self-reviews. I’ll ask questions like, “What were some of the key things I worked on over the past couple of months? Where did I face challenges? Where did I find success?” to help me surface accomplishments and growth areas I might otherwise overlook.

Empowering your team with meaningful reviews

Performance reviews shouldn’t feel like a chore—they’re an opportunity to celebrate wins, address challenges, and inspire your team to grow. With Asana AI, you can simplify the process by quickly surfacing data-backed insights that can assist and enhance human decision-making. The result is more meaningful conversations and development plans that actually move the needle.