Will Agile AI Help Non-Agile Teams Foster Agility?

In software development, the idea of agility sparks some very strong opinions. Some consider agile project management an industry gold standard. Others just can’t seem to make it work. This post is for teams in both camps, so stick with me.

Earlier this year, our founder, Aaron Upright, shared how AI will radically transform our understanding and implementation of agility. Today, we’re going to dig a little deeper and explore how AI could make the best parts of agile more accessible to teams struggling or hesitant to implement Agile. 

What Qualifies An Agile Team? 

Before we dig into the future of agility, we should take a look at what qualifies an agile team.

Sticking to the broad strokes, an agile team is…

• Collaborative
• Cross-functional
• And highly responsive to customer needs

While there are several sub-methodologies that fall under the agile umbrella — scrum and kanban are among the most popular — they all rely on a highly structured system of project management that’s intended to foster these qualities.

Agile frameworks generally include…

• Plenty of touchpoints (such as daily stand-ups and sprint planning)
• A very specific order of operations
• And regular feedback opportunities

When teams adopt (or try to adopt) agile practices, the intention is that they’ll be able to integrate feedback and deliver viable iterations of their product faster and more easily. 

This is all great. In theory. But when it comes time to apply agile practices, a lot of teams get lost in the weeds.

Non-Agile Teams: What Obstacles Stand In Their Way?

So, if agility is the key to responsive iterations and effective collaboration, why does it become a hurdle for so many teams, and why are some software devs actively put off by agile methodologies?

The short answer is that for inexperienced teams, agile can feel overly complex, tedious, and time-consuming — and that agile project management can become a burden when it’s meant to be a tool for efficiency.

And to be entirely honest, this is a totally fair critique.

How AI Could Simplify Agile Practices

I’m not here to force one specific agile approach on anyone. Even the Zenhub team takes what works and leaves what doesn’t when it comes to scrum methodologies. That said, I do believe that the best parts of agile breed amazing results — and that AI project management could be the answer for teams that struggle with agile.

We’re looking at an opportunity for…

• Automation
• Simplification
• And increased accessibility

There are a few ways artificial intelligence could help us achieve these things.

AI could reduce the pressure on agile experts — and even act as a stand-in on cash-strapped teams.

Agile teams generally rely on coaches and scrummasters as their go-to knowledge base for maintaining best practices. But with enough information, AI could simplify these roles and empower the other members of your team with knowledge.

Artificial intelligence could power tools that…

• Summarize and disseminate useful data
• Serve as a go-to source for your team’s best practices
• And identify areas for improvement based on team-specific insights
  

Clearly, this would be especially beneficial for small and medium-sized organizations that can’t afford to hire an agile coach or scrummaster but want to reap the benefits of agile methodologies.

AI could minimize the time and energy we spend in the “data weeds.”

When it comes to project planning, pattern recognition, and data analysis are key. And sure, software dev teams could meticulously track their work and make evidence-based predictions for project management, in theory — but who has time for this kind of thing?

As artificial intelligence becomes more heavily integrated into the developer workflow, it may have the power to…

• Provide instant insights we can’t currently access
• Make evidence-based suggestions based on the behavior of our teams
• And minimize the time and energy we spend on data analysis and tracking

AI could also reduce the time we spend in meetings.

Agile often comes with a lot of meetings — including standups, sprint planning, sprint review, retrospectives, and backlog refinement. These add up fast (especially when we all have other meetings to attend) and can result in packed calendars that feel overwhelming.

AI could free up calendar space by…

• Creating summaries that minimize the need for everyone to attend meetings
• Suggesting discussion topics and meeting structure for already busy teams
• And reducing or eliminating the need for some meetings (such as backlog refinement or sprint planning)

AI could simplify (and encourage us to stick with) the tedious parts of agile project management.

Let’s tell it like it is. Project management isn’t usually our favorite part of the job. Sometimes, letting things slip through the cracks feels pretty easy. This is where AI could help us achieve and stick with agility.

AI could eliminate grunt work and encourage adherence by…

• Automating some of the work associated with project documentation, refining product backlogs, and creating new sprints
• And automating and reminding us to stick to AI best practices (such as issue labeling)

Tip: Zenhub already offers AI-suggested labels to help your team stick with uniform labeling and make it second nature for everyone on your team. 

AI, Agile & Project Management: An Important Limitation

Obviously, all of this sounds pretty promising. Integrating AI into project management could save us time and money and allow our teams to become more agile with relative ease. But there’s one important thing we need to keep in mind here. 

AI is a tool — not a magic solution — and we will be faced with certain limitations. 

AI can’t force habit change. Just like a consultant and any other tool we use for insights, analysis, and automation, it will provide suggestions and help make things run smoother. But it will be up to our teams to run with them, ultimately.

The Future of AI in Fostering Agile Teams

The bottom line here is that AI is potential-packed and that we should leverage it in our pursuit of agility, but it’s up to us to make it work for our teams. It can help us adopt agile practices, but not without serious and proactive human involvement, so developers will need to show up with open minds and early adopter energy.

And make no mistake, this will be especially important for the people who build tools for software developers — like the Zenhub team.