As we navigate the performance review season, it’s crucial to acknowledge the significance of these evaluations for employee development and organisational alignment. Lucy Debono, Modern Work Business Group Leader at Microsoft Australia and New Zealand sheds light on how AI is proving to be a game-changer in this space.
With multiple responsibilities, projects, deadlines, meetings and daily tasks, preparing for a review can often feel daunting. Many employees struggle with starting from a blank page, reflecting on many months of activity and unsure how to articulate their impact without seeming boastful.
Fortunately, there’s an emerging ally in this process: generative AI. This technology can be a game changer in helping employees and managers kick start their approach and improve their written submissions for the review process.
I discovered this firsthand when preparing for my most recent performance reviews – which we call ‘Connects’ at Microsoft – as both an employee and a manager.
Initially, I felt a bit uncomfortable using generative AI for my Connects, almost like it was an unfair advantage or an inauthentic approach. This sentiment is echoed in Microsoft’s latest global Work Trend Index, which highlights employees’ nervousness about sharing AI use cases due to fear of judgement. The index found that 52 per cent of people who use AI at work are reluctant to admit to using it for their most important tasks. Whilst this is potentially a reflection on Australian culture, it is also a signal that we need to fully support and empower our teams to experiment with these new ways of integrating AI into their workflows and reap the benefits.
Embracing generative AI is a necessary cultural and mindset shift. It’s not about AI fully completing tasks for us or replacing us – it’s about AI helping us achieve greater results. Think of AI as a tool that boosts our capabilities, allowing us to focus more on the strategic, creative and uniquely human parts of our work. This AI partnership can make us more productive and ultimately enhance our overall performance.
In my case, generative AI significantly reduced the time required to complete my Connects by synthesising lots of data and inputs and accelerating me beyond the blank page, and improving the quality of my Connect compared to previous years. As a result, I noticed my review meetings were more thorough and my responses aligned more closely to organisational goals. By getting this head start on the written parts, it allowed me to spend more time thinking deeply about individual impact and the opportunities ahead.
So, in the spirit of experimenting with Copilot and sharing the learning, I thought it would be beneficial to share my experience as people approach their mid-year or end of year performance reviews.
Developing quantitative or qualitative success measurements
At Microsoft, our reviews are guided by three ‘circles’ of impact: individual achievements, contributions to others’ success, and building on the ideas and work of others. Our core company priorities are consistent across teams, and we identify goals specific to our individual roles.
One of the most effective AI prompts I used was to develop quantitative or qualitative success measurements. I provided Copilot with my job description and asked it to generate ideas for success measurements based on my role, focusing on specific actions taken and their positive impact.
Actual prompt: <link to job description> I want to write a self-assessment for my annual performance review. Using this document as a reference for my role, provide 10 ideas, either quantitative or qualitative success measurements, that I can include in my review. The ideas must each reflect a specific action taken and the positive impact it had, aligning with the responsibilities and expectations of the role outlined in the document, as well as the type of work I focused on by looking at all emails, chats, transcripts and documents that I’ve worked on over the past six months.
Make sure to showcase the business value and impact. For example, “I successfully planned and delivered four workshops in the last quarter, which helped my customers achieve their goals with digital transformation and adoption of cloud solutions.” Quantify the impact where possible, such as the number of workshops delivered or the percentage increase in customer satisfaction.
This prompt helped me quantify my contributions and reflect on my achievements in a structured manner.
Another useful prompt involved identifying my key activities and accomplishments over the past six months and categorising them into the three circles of impact.
I asked Copilot to read my emails, chats, meeting notes and specific documents, then detail my key activities and accomplishments, highlighting the impact of each one. This helped me recall and organise my activities, providing a good base structure for my responses that I could build on through further experimentation with Copilot.
Assessing achievements against core priorities
Generative AI can also act as a virtual coach, quizzing employees on their key performance indicators and prompting reflections on specific metrics, goals and milestones.
One of the prompts I used was to assess my achievements against core priorities. I provided Copilot with my core priorities and a list of my achievements (which I had already collated from a previous prompt). It then helped me structure my responses in line with our three circles of impact, ensuring each core priority included key individual accomplishments, contributions to others’ success, and results building on the work of others.
Actual prompt: I need to write a self-assessment for my annual performance review under each category of core priorities mentioned in this document. I will provide you with my achievements. Each core priority must include components of key individual accomplishments, contributions to the success of others and results that build on the work, ideas or efforts of others in bold, as well as success measures for each component. Here are my achievements <list the achievements that you developed off the back of the last prompt>.
This approach enabled me to refine my language and align my achievements more directly with the questions being asked in my Connects, enhancing the impact of my responses.
Setbacks and growth opportunities
Reflecting on setbacks and challenges is a crucial part of any self-assessment. Generative AI also provided valuable guidance for this part.
I asked Copilot to help me respond to a question in my Connects about setbacks, acting as a career coach to suggest elements our leaders at Microsoft want to see when discussing failures. This included identifying specific instances where I could have done something differently, articulating the lessons learned and describing how I plan to apply these learnings to make an even greater impact in the future.
This exercise was incredibly valuable as it provided a structured approach to reflecting on setbacks, applying a growth mindset and ensuring that my response was comprehensive and aligned with our leadership’s expectations.
Generative AI can also help to identify growth opportunities. For instance, I asked Copilot to highlight my key focus areas based on Microsoft Teams chat communications where I am an active participant and identify actions for learning, growth and development over the next year. The results jump-started my thinking and gave me some useful ideas to build upon, providing a forward-looking development perspective in my review.
Using generative AI as a manager
As a manager, generative AI can also act as an invaluable tool for drafting performance evaluations. I used the following prompt to get started on comments for my team members:
In the voice of a manager writing a six-month performance evaluation and expressing gratitude for a team’s contributions to recent deliverables, please summarise in eight to 10 sentences my perspective on [team member’s] impact, achievements and opportunities that existed for more significant outcomes.
This prompt helped me create thoughtful and meaningful evaluations, ensuring my feedback was both constructive and appreciative. As always, it never produced the final commentary, but provided a solid start and I was able to spend more time refining and thinking deeply and deliberately about the feedback I gave.
The future of reviews: AI-enhanced and high-quality
As you can see from these performance review examples, generative AI is transforming how we work and approach common tasks. By reducing the time required to search for information and draft responses, tools like Copilot enable us to enhance the quality of our reflections and produce more thoughtful, strategic and aligned self-assessments.
As we embrace this new world of AI powered productivity, it is so valuable to share these tools and techniques with our teams, helping everyone benefit from generative AI’s potential. The future of work is here, and it’s brighter, more efficient and more enriching for everyone involved.
Lucy Debono, Modern Work Business Group Leader, Microsoft Australia and New Zealand.
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