Over the years, companies have encouraged their employees to experiment with artificial intelligence tools in hopes that they could discover new ways to streamline their work and boost productivity. Now, amid mounting pressure to show a return on those AI investments, more organizations are going a step further, requiring AI usage and formally incorporating it as a metric on employee performance reviews.
How to Answer AI-Related Questions in a Performance Review
When writing their self-evaluation, employees should try to quantify how artificial intelligence improves their performance and how those gains support broader business goals. They should also describe how they infuse their own judgment, expertise and problem-solving skills in their AI usage, and show that they take accountability for how AI is incorporated into their work.
Using AI on the job is “no longer optional,” according to the head of the developer division at Microsoft, where employees are now asked to quantify how they apply these tools in their performance reviews. At Meta, “AI-driven impact” is a “core expectation,” with managers tracking how employees incorporate the technology in their evaluations. Amazon and Salesforce also measure AI adoption, according to The Wall Street Journal, and Google has begun factoring it into this year’s review cycle as well. Coders at tech giants like OpenAI and Shopify are even being encouraged to compete in “tokenmaxxing” competitions, where they log their AI usage on internal leaderboards.
These days, most executives view AI skills as a baseline competency worth measuring in their workforce, but many employees are still unsure whether these tools truly save time, improve performance or fit naturally into their jobs. As AI becomes part of formal evaluations, workers are being asked not just to use the technology, but to prove the utility of a technology they’re still trying to figure out.
The Push to Turn AI Into a Performance Metric — and the Disconnect It’s Creating
By mandating the use of artificial intelligence, AI-evangelizing employers — which have invested hundreds of billions of dollars into these systems — hope to convince skeptics, resisters and other non-adopters to get on board. While executives tout this technology as a performance catalyst, the data shows that many employees remain skeptical, viewing it as a superfluous leadership initiative that does not align with their day-to-day work.
More than 80 percent of executives either require or encourage the use of AI, according to a Betterworks study, but only 16 percent of employees actually utilize it regularly or feel they understand their company’s larger AI vision. Nearly half of HR leaders rank AI use as a top influencer of employee performance, and yet only 9 percent of workers believe AI skills have become more important to their success.
Another study by the AI consultancy Section reaffirmed the disconnect between employers and workers. More than 40 percent of the executives surveyed said AI saved them more than eight hours of work per week, while two-thirds of non-management employees said AI saved them less than two hours a week — or no time at all. Nearly 70 percent of workers said they felt anxious or overwhelmed by AI, but less than 30 percent of executives felt the same way.
These workers may use AI for an occasional email, but they do not feel compelled to integrate it into their daily workflow. However, by measuring it on a performance review, leaders are making it clear to employees that AI is not just a priority but a skill they should be actively developing.
“Many organizations train employees on AI, but if those skills aren’t reflected in goals, development plans or performance conversations, people quickly revert to old ways of working,” Jaime Aitken, VP of HR Transformation at Betterworks, told Built In. “When AI usage is tied to goals and reviews, employees understand that learning and applying it is part of how success is measured. That creates accountability, reinforces new behaviors and ultimately helps organizations see a real return on their AI investments.”
If companies are going to evaluate employees based on their AI usage, though, they should be clear about what exactly they are incentivizing. An employee who churns out error-riddled “workslop” in record time may look like a high performer based on AI usage metrics, but the manager who reviews that work may have a differing opinion. Leaders should ensure employees receive proper AI training, articulate the organizational goals of AI use and provide clear examples of what good and bad AI implementation looks like. If this hasn’t been done already, it should happen before institutionalizing it as a formal performance metric.
How to Answer AI Questions In Your Performance Review
Employees may use AI on a daily basis, but they often struggle to describe how they use it, what impact it’s had on their work and why that impact matters to the organization. Discussions about AI can get pretty nebulous, but these tips can help employees tie their chatbot conversations to real-world results in their self-evaluations.
Track Your AI Usage
It’s difficult to remember what you did six months ago, or even two weeks ago. That’s why it’s important to track your AI usage year-round. No, that doesn’t mean you need to count how many prompts you typed into a chatbot or how many lines of code you produced with it (if your company wants that data, they will gather it themselves). Instead, you should keep a weekly record of instances where you used AI to save time, increase your output or improve the quality of your work. So when review season arrives, you’ll be able to jog your memory and pick out the most innovative or impactful uses.
Quantify the Impact
AI is a tool, and a tool is only valuable if it’s effective. To show that you are using AI effectively, quantify how it helped you save time, increase output, improve the quality of your work or learn a new skill. Bonus points if you find a way to streamline a recurring workflow or a task performed by multiple people, as those efficiencies could be scaled on a systemic level. The best answers will quantify not just how much time was saved, for example, but how you used those extra hours to make an impact.
“Quantify your results where you can,” Brandon Sammut, chief people and AI transformation officer at Zapier, told Built In. “‘I automated our weekly reporting process using AI, saving roughly six hours a week across the team that we’ve reallocated to generating 15 percent more leads per week,’ lands differently than ‘I’ve been using AI tools regularly.’”
Connect AI Usage to Organizational Goals
While increasing productivity within your role is great, a better answer would go a step further and explain how that benefits the goals of the larger organization. Phil Santoro, co-founder of startup studio Wilbur Labs, said he recently added AI usage questions to his company’s performance reviews, and he is looking for use cases that show a clear link to improved business outcomes.
“In the end, I want to see proactive examples of the measurable impact of employee-driven AI-powered initiatives,” Santoro told Built In. “By showing the quantifiable results of these initiatives and linking them to larger business objectives, an employee can demonstrate and articulate his or her value and strategic contribution to the organization through a compelling narrative.”
Explain Your Process
AI usage questions are not just about productivity and efficiency. Employers also want to see the judgment, creativity and problem-solving skills you incorporate in your thought process: How you decided on a specific prompt, how you tweaked your approach to improve outputs and how you tested the validity or accuracy of the output before incorporating it into your work.
Show That You Take Accountability
Managers don’t value workers who see AI as a shortcut to doing less work. They want to see that you can harness the efficiencies of AI while also avoiding its many harmful pitfalls. Highlight how you followed the company’s data policies, caught an error in an AI output or recognized when AI was either incapable or inappropriate for a specific task.
“Anyone can describe what they delegated to AI,” Sammut said. “What’s equally important is that you evaluate and are accountable to what AI produced. Talk about the times you pushed back on an AI output because it wasn't quite right, or where you combined AI’s speed with your own expertise to reach something better than either could produce alone. That type of accountability is a critical aspect of AI fluency.”
Frequently Asked Questions
Are companies requiring AI usage now?
Yes. Meta, Microsoft and other tech companies are not just encouraging AI use, but requiring it and measuring it in performance reviews. At some organizations, AI usage is now considered a core expectation and part of how employee performance is evaluated.
Why are companies evaluating AI usage in performance reviews?
Companies are trying to drive AI adoption to improve productivity and justify major investments in AI. By tying AI usage to performance reviews, leaders signal that using and developing AI skills is part of how success is measured at the company.
How can I show that AI is making a real impact on my work?
Quantify results wherever possible. This could include time saved, increased output, improved quality or measurable business outcomes. Strong answers will also include how saved time was reinvested into higher-value work.
