17-06-2025
How Enterprises Can Keep Up With Rising Complexity
Jakob Freund is the CEO of Camunda, a software company innovating end-to-end process orchestration.
Digital transformation efforts are pushing many businesses to automate more. For the typical enterprise, however, increasing the level of automation is becoming more complicated than expected.
My company commissioned an independent research firm to survey 800 senior IT decision-makers, business leaders and software architects for the 2025 "State of Process Orchestration & Automation" (SOPO&A) report. The results indicated that "organizations average about 50 components/endpoints" in their automated processes, a number that has increased 19% year-over-year. These endpoints include people, systems (including legacy systems, microservices and AI) and devices.
Paired with the rapid pace of innovation around tools like generative AI and agentic AI, many are concerned about their ability to integrate even more technologies into their existing workflows—without disrupting their overall automation efforts.
In fact, 77% of organizations surveyed for the SOPO&A report say "a lack of control has resulted in increased risk that core business processes are not working anymore." An overwhelming majority say that if left unchecked, these risks could lead to an 'automation armageddon,' where automation errors snowball into catastrophic consequences.
Organizations can't afford these compounding risks, so the time to act is now.
The topic on everyone's minds is incorporating more AI into automated business processes to increase efficiency and improve customer experience. However, the adoption of AI hasn't gone as smoothly as many companies surveyed for the SOPO&A report would have liked: Eighty-five percent of organizations said "they face challenges being able to scale and operationalize AI across their organization."
Research from McKinsey also shows that only 1% of C-suite executives describe their generative AI rollouts as mature. These same leaders surveyed by McKinsey are increasing their investments in AI, with 92% expecting to boost spending in this area. To get the maximum benefit and ROI from AI, 93% of organizations surveyed for the SOPO&A report agree that AI "will need to be orchestrated across their business processes."
The same orchestration principles hold true for other technologies involved in an automated process, along with the people who use them. Combined with inflexible legacy systems, many organizations face issues with outdated processes and a general inability to keep up with the rate of change.
Other McKinsey research found that "as much as 70 percent of the software used by Fortune 500 companies was developed 20 or more years ago." To help increase the efficacy of their automation efforts, 89% of companies surveyed for the SOPO&A report are orchestrating older technologies and human workflows alongside what's new.
Well-coordinated processes are the secret to automation success for many of the organizations surveyed. In fact, 72% of organizations surveyed for the SOPO&A report "believe process orchestration plays an important role in digital transformation."
By improving their processes, these companies have experienced real business benefits from their digital transformation efforts. For example, more than half of the companies that have leveraged process orchestration in the SOPO&A report have improved their customer service and customer experience. By standardizing processes with orchestration, 44% of these same organizations have become more efficient.
Yet, not all organizations are at the level of process orchestration maturity they desire: Eighty-two percent of companies surveyed for the SOPO&A report still say "they need to have better tools to manage how their processes all intersect."
As many organizations look toward future trends like the fully autonomous organization, orchestration will become even more important. While the idea of automated and AI-based systems making decisions independently sounds appealing, organizations must make sure they can trace these AI-powered decisions and maintain compliance with industry regulations.
By centralizing and orchestrating processes, organizations can gain better visibility into their process outcomes, regardless of the endpoints involved, and reduce the risk of error. It's all about taking back control while still keeping up with a rapid rate of change that otherwise would seem too difficult to manage. Automation teams who orchestrate their processes prove that it is possible to move fast without breaking the core business processes that give their organizations a clear competitive advantage.
As we've seen from the data, automation on its own isn't enough. Without orchestration, things can get messy fast—more tools, more complexity and more risk. The good news is that with the right approach, it's possible to stay in control even as everything speeds up:
A major obstacle to orchestration maturity is misalignment between business and technical stakeholders.
Without a shared language, even the best automation tools can't deliver business value. Organizations should adopt visual process modeling standards like Business Process Model and Notation (BPMN) to bridge the gap. These standards make process automation understandable for everyone, from IT architects to line-of-business leaders.
Cross-functional alignment also means involving stakeholders earlier. Instead of treating orchestration as an IT-only initiative, bring different business functions into the planning phase. This fosters shared ownership and helps ensure that automation outcomes map directly to business needs.
Many enterprises are sitting on a mix of legacy systems, SaaS platforms and manual business processes. Rather than waiting for a massive digital transformation, organizations should begin by orchestrating what they already have.
Start by identifying high-impact processes that touch multiple systems or teams. Use orchestration to link systems together—even if some of them are outdated or siloed. This creates a foundation for end-to-end automation, which is more powerful than isolated fixes.
At the same time, avoid point solutions that create more silos, like AI technologies or RPA bots deployed without governance or oversight. Instead, orchestrate around a vision that spans business functions, channels and data sources.
Orchestration maturity doesn't stop at deployment. Leading organizations treat automation like a product: launched, monitored and iterated over time. This requires real-time visibility into process performance. Ensure that your team is tracking key metrics, identifying bottlenecks and responding quickly to changes.
The goal is to shift from reactive triage to proactive optimization. That way, teams can forecast outcomes, simulate improvements and make better decisions.
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