How AI Agents are Reshaping the BPM Team of the Future

AI is rapidly entering the field of BPM and transforming how BPM activities are performed. With more organisations ready to adopt AI, what will the BPM team of the future look like? What will the team size be? Will AI replace humans or take on specific tasks?

As with any major technology shift, questions and concerns around AI in Business Process Management loom large. In this blog, we look closely at what the BPM team of the future could look like, how the role of humans will evolve and what this could mean for BPM capacity.

The Current BPM Team

Traditionally, BPM teams have relied heavily on people to drive activities across the BPM lifecycle — from discovering processes and interviewing subject matter experts to creating process maps, analysing processes, identifying improvement opportunities and supporting implementation.

While BPM software has been used to support this end-to-end cycle, people have remained at the centre — using the technology, interpreting process information and driving outcomes.

AI agents have the potential to change this working dynamic. They can take on more of the repetitive and manual work, enabling people to concentrate on higher-value activities such as validation, decision-making, implementation and change management.

The Future Team: Don’t Think Either-Or

As purpose-built AI agents become capable of taking on more BPM activities, the team itself could start to look very different.

So, will BPM teams be replaced by AI agents? The future is more likely to be a hybrid model, where AI takes on more of the structured, repetitive and manual work while people focus their expertise where human judgement, context and engagement matter most.

The idea is to create the right balance between AI and human expertise. One emerging approach is the 70/30 model, where AI handles around 70% of repetitive, predictable or data-heavy tasks, while people retain responsibility for the remaining 30% requiring strategic oversight, contextual understanding and business judgement.

The exact balance will naturally differ depending on the organisation and activity. The underlying principle, however, remains the same: AI doesn’t replace humans but works alongside them to help teams achieve results faster.

The Rise of AI Co-Workers

Rather than thinking about AI as just another tool used by the BPM team, a more useful way to think about the future may be as two teams working together: a physical team and a virtual team made up of specialised AI agents.

For example, a future BPM team could work with:

• Process mapping agents that turn existing process information into process maps.
• Process analysis agents that examine processes for bottlenecks, delays, waste and improvement opportunities.
• Process redesign agents that help teams explore potential changes to the way work is performed.
• Process insights agents that provide process information through simple chat or prompts, without requiring users to manually search through hundreds of process maps.

Together, these AI co-workers can take on specific activities that traditionally require significant manual effort, while people remain responsible for the context, judgement and decisions needed to drive improvement.

Which BPM Activities Should Move to AI Agents?

AI brings speed and scalability to BPM projects. But that doesn’t mean every activity should move to AI.

Process mapping is a good example. Traditionally, process professionals may spend considerable time gathering existing information, interviewing SMEs, translating that knowledge into process maps, reviewing the maps and making revisions.

An AI agent trained in process mapping standards and provided with the right guardrails can take existing process information and perform much of the initial mapping work.

Process analysis offers a similar opportunity. Rather than an analyst manually reviewing every activity to look for bottlenecks, delays, automation opportunities or process variations, an AI agent can perform an initial analysis against clearly defined objectives.

However, activities involving significant judgement, organisational context, stakeholder engagement and change are still much more dependent on people.

The question, therefore, isn’t simply “What can AI do?” It is “Which activities are best suited to AI, which need human expertise and where can the two work together?”

How the Human Role Evolves

If AI performs more of the manual work, where can BPM professionals add greater value?

The answer points to a shift in responsibilities rather than the disappearance of the human role.

Instead of spending large amounts of time manually documenting and analysing processes, BPM professionals can increasingly focus on discovering the right processes to improve, understanding business context, validating outputs, making decisions, engaging stakeholders and implementing change.

Validation becomes particularly important.

The BPM professional increasingly becomes a validator of AI-generated work — checking whether the output is accurate, relevant and aligned with the organisation’s objectives before it is committed or acted upon.

The role begins to shift from manually creating every output to validating the output, applying business context and deciding what happens next.

What Does This Mean for BPM Team Size and Capacity?

Traditionally, doing more often meant adding more analysts, bringing in external resources or extending project timelines.

With AI agents handling much of the manual heavy lifting, the relationship between team size and BPM capacity could change.

By identifying which tasks are suited to people and which are suited to AI agents, organisations could support more processes and more improvement initiatives without requiring their physical teams to grow at the same rate.

This doesn’t necessarily mean BPM teams will become smaller. Instead, the same team could potentially take on more work, support more initiatives and spend a greater proportion of its time driving improvement rather than manually creating and analysing process information.

As physical and virtual BPM teams increasingly work together, the measure of BPM capacity may no longer be simply how many people are on the team, but what that combined human + AI team is capable of achieving.

What Does This Mean for BPM Leaders?

Building the BPM team of the future requires more than simply deploying AI agents. The way work is distributed across the team needs to be redesigned.

Leaders need to decide which activities should move to AI, what should remain human-led and how the two will work together.

The starting point should be selecting the right use cases. Activities with clear expectations, defined rules and repeatable steps are generally better candidates for AI than work requiring extensive judgement or dealing with numerous unpredictable variations.

Another key consideration is standardisation. The activities being assigned to AI need to be sufficiently standardised, while the AI agents themselves need appropriate training and guardrails.

Defining role clarity is also crucial: if an AI agent starts performing activities previously undertaken by a process analyst, what should that professional focus on instead? How can their expertise be redirected towards higher-value work?

Lastly, organisations need a clear governance framework to prevent AI adoption from becoming counterproductive. BPM leaders need to consider questions such as:

• Who operates and modifies the AI agents?
• How are AI-generated outputs reviewed and validated?
• When should AI agents be reviewed and recalibrated?
• How will AI usage and outputs be monitored?

Ultimately, creating a hybrid BPM team isn’t just about introducing AI. It is about rethinking how people and AI can work together across the BPM lifecycle.

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