AI for managers: your day with AI in the flow of work

Most 1:1s start with some version of “So, where did we leave off?” It's a reasonable question, and the answer exists — somewhere. But more than likely, it’s buried in last week’s notes, an old Slack thread, or a goal that hasn't been updated in a month. Putting it in the one place it should live, the performance system, is a manual task that’s easy to procrastinate or completely forget.

Managers already spend their day going back and forth from meetings to Slack, email, spreadsheets, and AI tools like ChatGPT and Claude. As AI assistants and AI agents become a normal part of how work gets done, asking managers to leave all of that to update a separate system makes less and less sense. 

That's the gap Betterworks has focused on solving. Instead of adding another destination, we’re bringing AI for managers into the flow of work, so useful performance context can be captured as part of the work itself. It's a big part of why performance management is moving from continuous to real-time.

The results of getting this right are significant. According to Betterworks' 2026 State of Performance Enablement report, 89% of employees in AI-enabled performance systems report high satisfaction, compared to just 40% of those without AI in their process.

Here's how one manager's day improves with Betterworks’ AI tools in the flow of work. We'll call her Maya.

8:45 a.m. | Get ready for a 1:1 with AI-powered meeting prep

Normally, Maya would spend the few minutes before her 1:1 with Jordan scrolling through old notes and trying to remember which project is due.

Instead, she opens a meeting prep brief that Betterworks AI generated. It reviewed their last few 1:1 conversations and pulled out what matters: areas that need attention, how Jordan is tracking against his goals, and guidance on where to coach. 

She walks in knowing where they left off, and so does Jordan, who gets his own brief.

9:00 a.m. | Run the 1:1 without worrying about notes

Whether Maya takes notes herself or relies on a meeting transcript, the follow-up work is the same: sorting through what was said, pulling out action items, and updating goals. Most weeks, some of it slips.

With AI in the flow of work, it’s a much smoother process. 

Now, after the call, Conversational Intelligence pulls in the completed transcript and connects it to their 1:1 in Betterworks.

From there, AI creates a recap and suggests action items, discussion topics for next time, and goal updates. When Jordan mentioned during the meeting that he'd hit a milestone on a project, Betterworks flagged it and suggested updating the related goal. 

All Maya has to do is review the suggestions and confirm what to keep. The notes are handled, and her attention could stay entirely on Jordan during the meeting.

For a closer look at how this works, see how Betterworks turns 1:1s into more than meeting notes.

10:30 a.m. | Check and update goals from ChatGPT

Mid-morning, Maya is planning her week in ChatGPT and wants to know where her team's goals stand. Before, that meant opening the performance system in another tab, finding each goal, and copying details back into her chat.

With the Betterworks MCP Server, she just asks her assistant directly. Betterworks connects to ChatGPT, Claude, Microsoft Copilot, Gemini, and other AI systems that support MCP (Model Context Protocol), and only shows Maya the data she already has permission to see. 

She can ask for a quick brief on Jordan's goal progress and recent recognition before their next check-in, or flag which team goals are at risk. She can also ask her assistant to update progress on Jordan's Q3 goal or move a deadline back two weeks, confirming the change before it’s saved back to Betterworks.

This is one of the more practical AI use cases for managers, and it also helps with AI adoption. Maya doesn't have to learn a new tool or change how she works. Betterworks shows up inside the one she’s already using.

11:30 a.m. | Turn a career conversation into a development plan

During their 1:1, Jordan mentioned he'd like to move into a team lead role. Maya is supportive, but conversations like this often lose momentum. Between everything else on her plate, it's hard to keep track of each person's career goals, and without a clear plan, progress can take months.

Now, Jordan can be proactive, creating a Development Goal in his Individual Development Plan around a skill he'll need for that role. Betterworks offers AI-driven recommendations for specific development actions based on his role, the skill he picked, his current skill level, and the capabilities he already has. He chooses the ones that make sense and adds them as milestones. 

Maya can see Jordan's Development Goals on his Talent Profile, alongside his skills and performance history, so she has everything she needs in one place to coach him and support his progress.

Read more on this in our post on building skills that matter to the business with IDPs and adaptive learning.

12:15 p.m. | Build a more connected learning experience

Jordan knows which skill he needs to build, but his learning platform doesn’t. His development plan lives in one system, and the course catalog lives in another, so nothing points him to the courses that fit his role or skill level. The work falls back on Maya, who has to dig through thousands of options, send him a few links, and keep checking in to see if he’s following through, all on top of supporting the rest of her team.

That changes with AI in the flow of work.

Adaptive Learning & Upskilling recommends relevant courses from the company's connected LMS based on Jordan's development context. Betterworks integrates natively with Udemy for Business, Docebo, and LinkedIn Learning, so Jordan can add a course straight to his Development Goal as a milestone. As he works through it, his progress flows back into Betterworks without anyone updating it by hand. 

The result is a learning experience tied to the skills he's actually trying to build, and a step toward connecting learning to performance rather than just tracking course completions.

2:00 p.m. | Give recognition and update goals from the tools you’re already using

Later in the day, a teammate gives Jordan a shout-out in a Zoom chat. In the past, that kind of moment would get a few emoji reactions and then disappear. Now Maya can turn it into recognition or feedback directly from the channel.

The same goes for the rest of her tools. While she’s catching up on email, Maya can update the milestone on Jordan’s Q3 goal from Gmail without opening Betterworks. And when work is tracked in connected systems, goal progress can flow back into Betterworks. When she's away from her desk, the Betterworks mobile app lets her check goals, give recognition, and capture 1:1 agenda items and action items on the go.

You can see the full list of Betterworks integrations here.

4:30 p.m. | Give HR a clearer view without adding process

Meanwhile, HR is gearing up for performance review season. They send reminders asking Maya and other managers to update goals and log feedback, and the data they get back will only be as good as what people remembered to enter.

That’s a problem for HR’s AI investment, too. If they’re counting on AI to summarize performance or surface insights at review time, those tools can only work with what’s in the system. AI systems, from generative AI to machine learning, are only as useful as the data behind them, and plenty of AI projects stall because that data is incomplete. AI solutions that require yet another login rarely fix the problem.

With AI in the performance workflow, HR starts from a much stronger place.

Because Maya's day already ran through Betterworks, from her 1:1 with Jordan and goal updates to recognition and learning progress, that context is captured as work happens. HR gets a more complete, up-to-date picture across teams, and Maya doesn't have to reconstruct months of work at review time. That's the difference between AI that writes reviews and AI that understands performance. 

For HR leaders building a business case for AI-ready performance management, that's a meaningful shift, especially in fast-moving industries like financial services, where AI is already changing how work gets done.

Why AI for managers works best in the flow of work

In the first version of Maya's day, she walks into her 1:1 unprepared, lacks the tools to support Jordan's goals, and ends the day trying to remember what they discussed. In the second, she has the same meetings and uses the same tools, but that work keeps Jordan's goals current, gives his career goals a real plan, and sets up their next 1:1.

Leveraging AI this way doesn't take judgment away from managers. They still decide what to coach on and how to support Jordan's growth. The best AI technologies for managers reduce the record-keeping burden so they can focus more of their time on coaching.

AI isn't replacing managers. It's changing what they get to spend their time on.

See AI for managers in action

What would your managers' days look like if performance management came to them? Explore the latest release or book a demo to see it in action with our team.