4 Ways Scrum Masters Can Leverage AI Today & the Tools They Can Use to Do So

Scrum Masters, and those of us working in agile project management, are experiencing a paradigm shift with the arrival of AI.

The future is still in the process of arriving. But whether it’s arrived at your organisation yet or not, it’s almost certainly arrived for at least some of your competitors.

It’s as simple as this – over the coming months, those who learn to adopt AI safely can grow a significant competitive advantage.

The inverse is also true.

I recently wrote about how AI is transforming agile project management.

Plenty of you read it, so I wanted to expand on some practical details. Here are some practical ways to leverage AI for scrum masters and AI for agile project management today, along with AI project management tool suggestions.

So, how can Scrum Masters embrace AI to be more accurate, efficient and effective?

The pain AI takes away

Be honest: how long do you really spend each day coordinating things in Slack, chasing after progress updates or summarising meetings?

If you’re anything like the average Scrum Master, it’s probably longer than you’d like—hours per day.

Let’s be conservative and say it’s 2 hours every day. That’s 10 a week. If you have 5 weeks of annual leave each year, that’s 470 hours every year, or put another way, around 3 weeks out of each year.

But some people – perhaps many – spend far more time on this kind of work.

Agile teams thrive on collaboration and effective communication.

But keeping everyone in sync can be a herculean task.

The most common frustrations of Scrum Masters and agile project managers are things like miscommunication, poor collaboration, and unproductive meetings – I’m sure you’ve been there.

Now, AI tools are popping out of the ground practically overnight. A lot of the tech isn’t that impactful yet. Next, I’ll pick out four ways that Scrum Masters and people working in agile environments can benefit from AI straight away.

4 ways you can gain from AI today

This isn’t exhaustive. You only have to ask ChatGPT for a list of ways AI can change Scrum and Agile today, and you can generate an enormous list.

Instead, this is a list of practical ways you can use AI today, and the best-in-class, cutting-edge tools you can use.

AI gain 1: Better meetings, summarised automatically

AI can liberate Agile teams from the clutches of unproductive meetings. AI allows teams to focus on strategic and creative discussions during meetings by taking care of progress updates and data summarisation. This shift improves overall team morale and fosters a more collaborative and innovative project environment.

In a nutshell, AI is revolutionising team collaboration and communication within Agile project management. By integrating AI into their workflows, Scrum Masters can help their teams become more efficient, informed, and focused on delivering exceptional results.

My tool pick: Otter.ai – Want AI that records your meetings, automatically writes notes, captures slides and screen sharing and generates summaries? Of course you do! My team and I use and love Otter as our go-to tool.

Honourable mention: MeetingCulture.ai – This tool is AI for meeting management. It is designed to eliminate the pre-meeting planning process and create an impactful, efficient agenda.

AI gain 2: No more trawling

The constant influx of information from tools like Jira, Slack, and GitHub can be overwhelming.

AI can now sift through this sea of data, surfacing only the most critical information for the projects you care about.

By keeping an AI-powered finger on the pulse of your projects, Scrum Masters can ensure everyone stays informed without drowning in notifications. Adopt collaboration tools to improve the way projects run radically.

My tool pick: CollabGPT – This game-changing tool is custom-built for people who manage software projects and build software. People like us! It keeps track of everything happening in Slack, Jira and GitHub, providing rich summaries and suggestions on what to do next.

In my opinion, the coolest feature that sets it apart is the fact it’s not just a dumb layer over an LLM. It works with AI agents, that enable CollabGPT to have long-term memory.

Honourable mention: Slack AI – If you don’t work in software and have a more generalist use case, maybe you’ll like a shallower tool. It’s a simple layer over an LLM of your choice (like ChatGPT or Claude), and allows you to do things like summarise threads.

AI gain 3: Instant answers to pressing questions

Why spend hours digging through old messages or documents when you can simply ask your AI companion for answers? With advanced natural language processing capabilities, AI can now provide concise, actionable responses to any query about project progress, risks, or other pressing issues. This on-demand access to information empowers teams to make better decisions and adapt quickly to changing project dynamics.

My tool pick: CollabGPT – We talked about this one above, but it also allows you to ask deep-searching questions about anything that’s happened across the tools your software team uses (like GitHub, Slack, or Jira). Because it uses AI agents, it has a long memory of your projects.

Honourable mention: Slack AI – Again, a shallower tool, but if you have a non-software or straightforward use case, perhaps this is good for your team. It allows you to ask questions on recent activity, and it’ll use an LLM of your choice to deliver an answer.

AI gain 4:  Project planning

Project definition and planning can be time-consuming, repetitive, and mostly manual. ML, natural language processing, and LLMs are changing this.

LLMs make it easy to flesh out user stories and spot ambiguities or omissions. LLM outputs aren’t perfect, but they can take up to 80% of the heavy lifting out of the work.

My tool pick: ChatGPT – The market will develop, and I’m sure other options will beat ChatGPT soon. Right now, I think ChatGPT fits the bill just fine, and can shave off a tonne of time while scoping requirements or writing user stories.

Wrapping up

Scrum Masters and agile project management practitioners can leverage artificial intelligence to redefine their roles and enhance their effectiveness. It has the potential to transform the way we manage resources, including how we handle task dependencies across multiple projects, whether they're simple projects or more complex ones.

Adopting AI-based project management tools can drastically streamline the workflow on your Kanban board, making it easier for team members to track project progress and manage task lists. These collaboration tools, such as CollabGPT and ChatGPT, come equipped with collaboration features that improve communication, reduce miscommunication, and enhance the overall efficiency of software development teams.

With AI, the scope for competitive and strategic gains and losses are enormous.

Shifting the burden of drudge work onto AI frees you (and your teams) up to focus on strategic leadership and creative problem-solving.

The potential for increased efficiency, collaboration, and project success is immense.

I’m building CollabGPT, the AI companion for software projects. I’d love for you to try out what we’ve created. We think it’s a game-changer for agile teams.

Learn more about CollabGPT here.