Adaptavist predicts the agile trends for 2025 (Part 1)

In the past, project leaders built a business case for agile transformation purely around the fact that software would be delivered faster and at a higher quality. But in the current environment, there's a higher financial imperative to justify these initiatives (and others). Looking ahead, Phil says, the arguments people are making in favour of agile will need to be much more specific.

As we look ahead to 2025, the integration of AI tools into agile teams is poised to bring significant changes, with both promising advancements and potential challenges. Phil highlights his AI prediction below in three parts. Firstly, AI tools, like enhanced versions of Google, excel at summarising vast amounts of data and streamlining the information retrieval process. This capability is being increasingly adopted internally by organisations using Jira and Confluence, accelerating the speed at which information is delivered and enabling faster decision-making. However, this shift also risks disrupting the traditional dynamics of agile teams.

'There are a number of ways AI tools look set to impact agile teams,' says Phil. 'Firstly, these tools are really good at summarising large amounts of data. Think of it as Google on steroids. You can ask a question, and instead of needing to phrase it perfectly or sift through forum posts for answers, the summarising happens in the background. It's like having a blog post written for you every time you ask something.'

Traditional 'How do I…' questions historically typed into Google are now transformed into direct answers, with context, all within the same screen with AI tools like ChatGPT. This speeds up the process of knowledge gathering and saves valuable time and effort to get to the same answer. By using AI features within tools like Confluence and Jira from Atlassian, organisations can aim to improve efficiency, reduce manual workload, and enhance decision-making, thereby enabling teams to work smarter and more collaboratively.

'That's moving from the general world of all data—like ChatGPT—to a lot of customers bringing that capability internally for their data, whether they're using Confluence or Jira. What's interesting here is that it increases the speed of information delivery, allowing faster decision-making.

'However, it also changes the dynamics. Normally, you'd ask for information, go find it, and have a conversation about why it's important. Now, those conversations might not happen, so we need to find new ways to maintain feedback loops that are crucial to agile. Otherwise, everything might just end up as "I can ask ChatGPT, and it'll give me the answer," which risks losing interpersonal collaboration.'

As we embrace these technological advances, we should be mindful of not losing the human aspect. Without doing this, we risk reducing complex discussions to mere AI transitions. This could seriously undermine the interpersonal collaboration and learning that drives innovation and value in agile environments.

'The second point is an extrapolation of this—using chatbots to assist with processes. These could range from HR processes like submitting expenses to more advanced roles, like answering questions about agile workflows. In theory, you could have an agile coach available to everyone, everywhere.'

Over-reliance on AI agents could lead to potential issues and challenges, such as reduced human interaction, as already mentioned, but also the loss or reduction of critical thinking and problem-solving skills that have been developed in human agile coaches through experience and mistakes, a key proponent of agile. People might become less able to analyse a situation and make an informed decision independently.

'The flip side is that governance for AI agents isn't fully developed yet. This makes some organisations hesitant to adopt them or forces them to experiment on the fly. There's a lot of opportunity to maximise impact and efficiency, but it's still risky if these tools bypass important steps.'

AI systems are still maturing and can be vulnerable to cyber attacks, data breaches, and other security threats. An overreliance on AI without adequate security or governance can pose a risk to an organisation's privacy.

In the fast-paced world of agile software development, the allure of AI to improve speed and efficiency is appealing. However, prioritising speed over team alignment carries a critical risk, which Phil explores in his next prediction.

'Finally, there's the broader implication of speed,' says Phil. 'Efficiency allows you to skip steps, but skipping steps often means losing implicit feedback loops or essential conversations. Organisations must ensure they're still checking with finance, staying compliant, and aligning with other teams. If we move too fast, we risk breaking the very things agile frameworks seek to align. Speed is attractive, but the core of agile is about alignment, not just speed.'

Organisations must strike the all-important balance between speed and alignment. If they get it wrong, they risk derailing agile processes entirely, compromising the principles on which agile methodologies are founded.

Traditionally, agile has been the domain of software development teams, but we're already seeing a much broader inclusion of people into agile. More people across the organisation are involved in the core product, meaning non-technical teams, like HR, for example, are increasingly adopting agile practices.

'While agile principles remain the same, they translate differently when applied to managing people instead of building products,' says Phil. 'This extends to agile marketing, sales, and other areas. As agile frameworks intersect with traditional practices, they create opportunities for innovation and iteration within these disciplines.'

Another big trend to watch out for in 2025 is the closer integration of the three core pillars of product development: business, finance, and technical teams. 'These groups need to work more closely together, using shared data and a common language,' Phil explains. 'Frameworks like TBM [Technology Business Management] help bridge these gaps, aligning infrastructure, people, and product development costs to support decision-making.'

However, because these groups come from different organisational backgrounds, they don't necessarily speak the same language, which brings its own unique challenges. That's why it's so important for enterprises to align priorities across all parts of the business for successful agile transformation and effective collaboration.

Agile finance frameworks, such as Beyond Budgeting and Lean Budgeting, that offer guidance on adapting financial practices are gaining attention. Here's a simple explanation of how they work.

Imagine you have a $1 million budget over ten days. Traditionally, you allocate specific amounts to projects upfront, often for the entire year. Finance's job is then done until the following annual review. But with faster feedback, you can adjust mid-course. For example, suppose Project X isn't performing, but Project Y is thriving. In that case, you can reallocate resources from X to Y within days. This agility avoids wasted spend while still adhering to the overall budget.

'Historically, such mid-course adjustments were non-starters due to rigid structures,' says Phil. 'But tools and frameworks now allow shuffling resources without breaking budget systems. This flexibility empowers finance to align spending with actual outcomes dynamically. As a result, we're seeing the rise of a new type of CFO—someone who deeply understands how technology works in a business context. These CFOs use agile frameworks to make more informed, adaptive decisions.'