Why Agile Teams Are Winning the Race to Create AI-Ready Cultures

Andrea Fryrear is an Entrepreneurs’ Organization (EO) member in Colorado, author, and co-founder of Agile Sherpas, which helps leaders modernize marketing teams to work smarter, move faster, and deliver better results with Agile frameworks. We asked Fryrear how business leaders can create AI-ready cultures.

It’s no secret to business leaders that AI can have a massive impact on how your organization functions. In most cases, the challenge you struggle with is creating AI-ready cultures. Getting your people to embrace technology as fast-moving and earth-shaking as AI isn’t easy. Conservative cultures resist change, individuals may feel AI threatens their roles, and even when people are convinced to try the technology, they may still backslide.

However, a recent report analyzing 430 marketers found that one particular group of professionals was embracing AI far faster than its peers. It also shows clear steps business leaders can take to get more departments to embrace AI and unlock its benefits.

Who is actually embracing AI?

In our survey of 430 marketers to learn who had fully implemented AI, a clear pattern emerged. Fully agile marketers—those who embrace the agile mindset and use frameworks like Scrum or Kanban—were more than three times more likely to have fully integrated AI into their work, compared with somewhat agile marketers (36 percent versus 11 percent). 

What about non-agile marketers? There was not a single one who had fully integrated AI. The data makes it clear that agile ways of working dramatically increase the likelihood that marketers will fully integrate AI and be successful in general. So, what about agile drives these stark differences?

Understanding agility

Agile can best be understood as a reaction to old ways of working. Instead of spending weeks formulating detailed plans that your team will follow for months (only to produce a result that’s no longer relevant for your customer), agile is built on breaking work into smaller pieces. It enables teams to test, iterate, and gather feedback. They can also constantly evolve their work as it’s being done to ensure you accomplish your goals.

In practice, this means working flexibly, breaking down silos for more open collaboration, ruthlessly prioritizing work, and limiting work-in-progress. It also means generally delivering work faster so you can get feedback and integrate that knowledge into the next iteration. There are many ways to be agile. However, what connects them is an agile mindset built around the principles of the original agile manifesto. Taking a step back, consider what this data means. It points to a few key, data-driven ways business leaders can build AI-ready cultures:

1. Support instead of mandates

A common mistake leaders make when encouraging AI adoption is simply telling teams to begin using AI. While permission is the first step, a mandate isn’t sufficient. In fact, 73 percent of fully agile teams reported that their leaders view agile as essential to success. As an experienced agile marketing firm, we consistently see that teams need strong support from leaders to fully transition to agile methods.

Servant leadership is crucial here. You must actively support your team in its AI transition. This means providing training and coaching and helping with key obstacles like compliance. Communicate clearly about what integrating AI will mean in the long run. It’s not enough to dismiss your team members’ fears. They need reassurance about what their work will look like in an AI-driven future.

2. Autonomy and experimentation

What’s true of virtually every business tool is true of AI. You won’t gain a competitive advantage using the same tools and techniques as everyone else. For AI to live up to its full potential, your team needs time, space, and resources to experiment.

Your team’s autonomy and ability to focus on a smaller number of high-value activities are directly linked to their AI success. With the increasing number of AI tools, your team needs freedom to experiment and figure out what’s going to work. Mandating a specific AI tool or method robs them of this essential process.

Experimentation will be ongoing. With the breakneck pace at which technology is improving, in order to create AI-ready cultures, your team will need to experiment to remain competitive. This requires building a culture of experimentation and continuous improvement. It goes beyond simply asking your team to test a new tool.

3. Focus

On average, more than six new AI tools are released per day in the marketing space alone. Your team could easily get overwhelmed by decision fatigue. Developing a habit of ruthlessly prioritizing work so your team can focus on tasks that truly matter can help a lot. Instead of postponing AI tests because there are too many options to choose from, decisions get made, tests happen, and results are used to improve how the team operates.

4. Mindset over practices

While it’s tempting to simply adopt agile practices such as breaking work into sprints, Agility’s true value comes from the agile mindset. When teams without an agile mindset try to be agile, they tend to backslide into old habits, undermining the entire attempt and creating a lot of frustration. Implementing AI, like nearly everything in business, relies on hundreds of tiny decisions made by people every day. If your team members don’t have an agile mindset, those decisions will pull the team away from agile ways of working and inhibit AI-ready cultures.

So, what is an agile mindset? It’s an approach to work that embraces flexibility, continuous improvement, experimentation, customer-centricity, and prioritization. The takeaway is not to think, “To implement AI successfully, we need to work in sprints and use a Kanban board.” Instead, it’s that you need to invest in education and training to shift how your team members think about their work. The practices can come later, but the foundation must be there first.

The agility factor

What ties all of these factors together is agile mindsets and ways of working. Agile teams are built on prioritization, experimentation, and autonomy. It’s hardly surprising that such cultures stand out when it comes to AI implementation. They’re ready to dive right in and start using tools, learning valuable lessons, and iterating until they get it right.

Whether you want to focus on building an agile culture or just implement some of its core components, the data shows that agility is vital for leaders who aim to create the right conditions for AI implementation.

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