BPM trends that matter right now
Old BPM is dying because modern BPM replaced it. Here are the trends driving that shift and why AI agents make structured processes more important than ever.
Summary
- Old BPM is dying, modern BPM is replacing it - The shift from IT-controlled, flowchart-heavy systems to self-service, mobile-first tools is well underway and old-school BPM vendors can not keep up
- AI agents need structured workflows to function - More model parameters won’t fix the absence of a defined process. But Nature reports over 40% of agentic AI projects will be canceled by end of 2027 because they lack the process infrastructure to succeed
- “Agent washing” is the new greenwashing - Gartner estimates only about 130 of the thousands of “agentic AI” vendors are real - the rest are rebranded chatbots and RPA tools
- Process definition is the foundation for AI adoption - AI doesn’t fix broken processes. It scales them. See how Tallyfy provides real-time collaboration
“Old BPM” is dying because it’s being replaced by “modern BPM.” The trends below explain exactly why that replacement is happening - and what matters if you’re choosing a business process management tool today.
Deploy an agent without a workflow and it just sits there looking expensive. That gap is where most AI projects go to die.
Business Process Management Made Easy
Old BPM vs modern BPM - the core shift
In “old BPM,” IT made the decisions and called the shots. Not anymore. It takes a quick search to find and try out pretty much any software out there. People now expect to try something for free before committing to a purchase. Modern BPM supports that expectation.
“Old BPM” couldn’t be tried without wading through lots of chats with a sales person and weeks of combing through manuals. That entire buying model is gone.
Old BPM was also too focused on internal use cases. “Modern BPM” is simple enough to run external-facing workflows - something the old tools never handled well.
A whole sector has emerged called “integration as a service.” Unlike old BPM, where armies of IT staff used to write code, there’s no need to know any code to quickly snap two apps together. But that requires an API - which is generally only available with a modern BPM.
Next-gen AI vendors are API-first. None of the old BPM vendors are. By being API-first, modern BPM tools like Tallyfy enable easy integration and snap-in capabilities as they emerge from AI research.
BPMN is a horrific solution to a problem that does not exist
For most businesses it is just dead weight, and it will either be resented or ignored (or both)
“Modern BPM” caters to the way people work today - collaboratively, on phones, without flowcharts. Old BPM was really just for big companies. Modern BPM appeals to companies of all sizes by putting usability first. We’ve seen teams adopt modern BPM in days rather than the months that old BPM required. I learned this the hard way at Tallyfy - the biggest barrier to adoption isn’t functionality. It’s complexity. Every time.
This opens up the other 90% of the market that never had BPM.
Stop treating AI agents like magic wands
Here’s where it gets interesting. The biggest BPM trend right now is not a new feature or a fancier dashboard. It’s the realization that AI agents are useless without structured processes to follow.
Nature reports that over 40% of agentic AI projects will be canceled by end of 2027. The main reasons? Escalating costs, unclear business value, and inadequate controls. In other words - no process infrastructure underneath the AI.
And it gets worse. Gartner also flagged something they call “agent washing” - vendors rebranding their existing chatbots, RPA bots, and AI assistants as “agentic” without any real autonomous capability. They estimate only about 130 of the thousands of agentic AI vendors are genuine. That’s a staggering amount of noise drowning out actual progress.
Research makes a point I think about constantly: leading enterprises do not simply layer agents onto existing workflows. They redesign processes to use the unique strengths of agents. That requires examining end-to-end processes, not just finding automation opportunities within current operations.
The numbers from Deloitte’s State of AI report tell the story pretty clearly - only 21% of companies have a mature governance model for autonomous agents, even though nearly 75% expect to be using agentic AI within two years. That’s a massive gap between ambition and readiness.
This is exactly why we built Tallyfy the way we did. AI treats your broken process like gospel and runs it at full throttle. Automating a flawed process doesn’t fix it - it just makes it fail faster and at greater scale. Process definition and standardization is the foundation for AI adoption - not the other way around.
Think about it. An AI agent needs to know:
- What step comes next
- Who’s responsible
- What happens when something goes wrong
- When to escalate to a human
Without a structured workflow underneath, you’ve just got a chatbot with a fancy title. Every time we onboard a new team, the same issue surfaces - the organizations that define their processes first get 10x more value from AI than those who bolt AI onto chaos.
There’s more process management software on the market than ever before. Check out our guide to BPM Solutions to learn how to pick the right one.
Real-time analytics and why most people get them backwards
One of the key aspects of BPM is the ability to monitor processes through analytics. A major trend is the rise of real-time analytics. Being able to analyze and adjust your processes on-the-go is hard to pass on.
As technology improves and becomes more accessible, real-time tracking means problems can be spotted earlier and addressed before they spiral.
Business analytics as a whole have potential to be used much more scientifically. This is taking the form of predicting trends within processes and outputs - identifying issues or opportunities that can be minimized or maximized.
The most important thing? These patterns can be identified using the data generated by BPM, and the processes need to be agile enough to respond quickly. After watching hundreds of teams try this with operations leaders, the ones who win aren’t using the fanciest analytics tools - they’re the ones whose processes are structured enough to generate useful data in the first place.
I think most people get this backwards. They buy analytics tools and then realize their processes are too messy to analyze. Fix the process first. The data follows. The question we get asked most often about analytics is “what should we measure?” and the honest answer is that if you can’t describe your process in clear steps, there’s nothing meaningful to measure yet. You end up tracking activity — how many emails were sent, how many meetings were held — instead of tracking outcomes like cycle time, error rate, or throughput. Activity metrics feel productive but tell you almost nothing about process health. Outcome metrics require a structured process to generate them. That’s the whole point.
Remote teams changed everything about process management
More businesses employ staff that’s rarely, if ever, visiting an office. They might even be located on the other side of the world.
Even in a very traditional office with on-site staff, it can be extremely hard to collaborate, ensuring that every employee knows their to-dos and responsibilities.
One of the major BPM trends is the way technology helps improve workflows with easier collaboration through shared software tools. At Tallyfy, we’ve seen this play out in real scenarios - a government contractor told us their HR team now manages 10-20 simultaneous employee onboardings with just one person, down from requiring multiple coordinators, because everyone can see exactly where each process stands regardless of location.
Process templates for distributed teams
Giving distributed teams the same access to real-time interfaces and tools means that no matter where an employee may be, the business processes continue to run smoothly and collaboration isn’t affected.
Middleware trap and what comes next
Here’s something that drives me a bit crazy. People are still paying per-zap, per-task, per-connection for middleware tools that create brittle point-to-point integrations. Every time one app updates their API, half the automations break.
The future isn’t drag-and-drop connector marketplaces. It’s describing what you want in plain language and having AI build the integration. No flowcharts. No connector hunting. No per-zap billing.
This matters for BPM because process management used to mean managing the connections between systems as much as managing the work itself. Modern BPM tools need to be the hub, not just another spoke. When your BPM tool has a proper API - like Tallyfy does - the integration problem shrinks dramatically because AI can write the connections for you.
IBM’s analysis of tech trends points to this same direction - the opportunity in agentic AI isn’t just building more agents, it’s building the infrastructure around them. Orchestration layers, control planes, approval workflows, and observability tools. Autonomy without structure is just chaos with a faster clock speed.
Process definition as AI infrastructure
I’ll be blunt. Most “digital transformation” efforts fail because they skip the boring part. They jump straight to AI, automation, and fancy dashboards without first answering: what’s the actual process?
Deloitte’s agentic AI research confirms what we’ve been saying for years - agents can handle a range of transactions, communicate with each other, and collaborate to achieve a business outcome. But only when the underlying processes are structured to support these capabilities. Their report also highlights a governance gap - 42% of organizations are still developing their agentic strategy roadmap, with 35% having no formal strategy at all.
This is probably the single most important BPM trend: process definition as AI infrastructure. Not as documentation. Not as compliance theater. As the actual operating system that AI agents run on.
Based on hundreds of implementations, the pattern is clear. The organizations that struggle with AI aren’t the ones with bad technology. They’re the ones with undefined processes. You can’t automate what you haven’t defined. You can’t improve what you can’t see. And you definitely can’t hand it to an AI agent that needs clear instructions to function.
One mid-sized media production team told us they tripled revenue in just 4 months while maintaining quality - they attributed this directly to having standardized, repeatable workflows for their 60-step production process that scaled without adding headcount. The AI conversation was irrelevant until the process was solid.
Since the world of process management is always changing, we’ll keep updating this article with new trends as they emerge.
Related questions
How is AI changing BPM practice?
BPM is being reshaped through AI applications that add predictive capabilities and smart automation. Rather than following a predetermined set of rules, processes that use AI can now learn from data, detect patterns, and make intelligent decisions.
For instance, AI can direct service requests to the proper department based on the content of the message, or anticipate when equipment will need maintenance before it breaks. Around 64% of organizations plan to deploy AI and ML tools in their BPM systems - though the real challenge isn’t adoption, it’s having the process foundation to make AI useful.
What are the key BPM trends shaping the future?
The major trends include low-code platforms that allow anyone to design a process, mobile-first BPM tools for remote teams, and agentic AI that brings autonomous decision-making to traditional workflows.
Cloud-based BPM is also proving more popular as it’s more flexible and supports collaboration between sites. But my honest take? The trend that matters most is this: process intelligence has emerged as the essential starting point for BPM success. Without it, everything else is noise.
How is remote work affecting business process management?
Remote work has forced companies to re-evaluate how they operate for a distributed workforce.
Businesses have shifted focus to digital-first processes that operate consistently between locations and support virtual collaboration, cloud access, and mobile.
That change has made process transparency and documentation more important than ever.
What role does data analytics play in modern BPM?
BPM is increasingly about data analytics to understand and analyze how well your process is running.
Enterprises use process mining and analytics today to uncover bottlenecks, forecast possible outcomes and continuously improve workflows based on data, not assumptions.
How are expectations changing BPM?
People today expect faster, more personalized services.
This reality is prompting organizations to create more agile processes. It’s driven experience-first BPM where business process structures are formed around the user journey rather than just internal efficiency.
What impact is no-code and low-code having on BPM?
No-code and low-code platforms let organizations take control of their processes without requiring technical knowhow.
This is accelerating process change and reducing the requirement for IT - you get faster time to addressing something in the business.
How is process automation evolving?
Automation is getting smarter and more advanced. It’s no longer just task autopilot - it covers process management from A to Z.
Modern automation can make complex decisions, understand natural language, and learn from human behaviors to improve over time. But here’s the catch - Nature reports at least 15% of day-to-day work decisions will be made autonomously by AI agents by 2028, up from 0% in 2024. That’s a massive shift, and it only works if the process underneath is solid.
Start with these ready-to-use modern BPM templates
About the Author
Amit is the CEO of Tallyfy. He is a workflow expert and specializes in process automation and the next generation of business process management in the post-flowchart age. He has decades of consulting experience in task and workflow automation, continuous improvement (all the flavors) and AI-driven workflows for small and large companies. Amit did a Computer Science degree at the University of Bath and moved from the UK to St. Louis, MO in 2014. He loves watching American robins and their nesting behaviors!
Follow Amit on his website, LinkedIn, Facebook, Reddit, X (Twitter) or YouTube.
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