Enterprise automation is entering a new phase where workflow engines, AI agents, business rules, and human oversight are converging into unified orchestration platforms. As organizations accelerate AI adoption, the challenge is no longer simply automating tasks — it is governing increasingly dynamic systems operating across departments, applications, and decision environments.

That transition is fueling interest in adaptive process orchestration (APO), an emerging software category identified by Forrester as enterprises seek more controlled approaches to AI-driven automation. This week, Decisions + ProcessMaker announced that Decisions was included in Forrester’s Adaptive Process Orchestration Software Landscape, Q2 2026 report covering 35 vendors operating in the space.

For years, enterprise automation strategies revolved around narrowly defined systems such as robotic process automation (RPA), digital process automation (DPA), and integration platform as a service (iPaaS). Those technologies helped organizations streamline repetitive workflows, reduce manual labor, and connect fragmented applications.

But generative AI and agentic systems are rapidly reshaping automation architecture.

Modern enterprise environments increasingly require systems capable of managing nondeterministic processes — workflows where AI agents can dynamically interpret context, make decisions, and adapt actions in real time. That evolution introduces new operational complexity around governance, auditability, compliance, and human oversight.

The emerging APO category attempts to address those challenges by combining traditional workflow orchestration with AI coordination and policy enforcement.

According to Forrester, adaptive process orchestration software integrates AI agents, deterministic workflows, and nondeterministic control flows to support autonomous decision-making while still aligning with enterprise business objectives.

The category is gaining attention because many enterprises are struggling with fragmented automation environments built from disconnected tools accumulated over years of digital transformation initiatives.

Decisions + ProcessMaker says its platform is designed to unify workflow automation, orchestration, rules management, and AI-driven process execution within a single governance framework.

The company positions its approach around what it describes as “universal orchestration,” a model intended to coordinate AI agents, business systems, employees, and decision engines while preserving enterprise-grade oversight.

“Companies are moving beyond isolated automation tools,” said Giles Whiting, CEO of Decisions + ProcessMaker, in the company’s announcement. “They need one place to coordinate AI agents, people, systems, and decisions with enterprise-level governance to make automation safe, transparent, and scalable.”

That focus reflects broader enterprise concerns surrounding AI adoption.

Organizations deploying AI into operational environments increasingly face pressure to demonstrate explainability, compliance, and accountability — particularly in regulated industries such as finance, healthcare, and insurance. AI systems capable of autonomous action create new risks around inconsistent outcomes, hallucinated decisions, and unclear audit trails.

As a result, governance is emerging as one of the defining battlegrounds in enterprise AI infrastructure.

Major enterprise software vendors including Microsoft, Salesforce, ServiceNow, and IBM are all expanding orchestration and AI governance capabilities within their broader automation ecosystems.

The market is also shifting away from standalone RPA deployments toward more integrated automation architectures capable of coordinating APIs, AI models, workflows, analytics, and business rules simultaneously.

Industry analysts increasingly view orchestration as the connective layer enabling enterprise AI adoption at scale.

Research from Gartner suggests organizations are prioritizing platforms that combine automation, decision intelligence, and AI governance rather than purchasing disconnected point solutions. Meanwhile, IDC projects continued growth in AI-enabled workflow automation spending as businesses modernize operational infrastructure.

The APO category reflects that convergence.

Rather than treating automation as a fixed workflow problem, adaptive orchestration systems are designed to manage dynamic processes involving AI-generated outputs, real-time decisions, and evolving execution paths. That includes human-in-the-loop workflows where employees validate or intervene in AI-driven actions before final execution.

For enterprise marketing, customer operations, and digital transformation teams, the implications are substantial.

Modern customer experience ecosystems increasingly rely on interconnected AI systems operating across CRM platforms, marketing automation tools, customer data platforms, and analytics environments. Coordinating those systems securely and transparently is becoming a strategic requirement rather than a technical enhancement.

The rise of APO platforms also aligns with broader enterprise interest in agentic AI architectures — systems where autonomous agents collaborate across workflows while remaining subject to organizational policies and governance controls.

That transition may ultimately redefine enterprise automation itself.

Instead of static process automation operating behind the scenes, organizations are moving toward continuously adaptive orchestration layers capable of balancing AI autonomy with human accountability.

The inclusion of Decisions in Forrester’s APO landscape signals growing recognition that governance, not just automation speed, may become the central differentiator in enterprise AI infrastructure over the next several years.

Market Landscape

The adaptive process orchestration market is emerging at the intersection of AI infrastructure, workflow automation, decision intelligence, and enterprise governance.

As organizations deploy generative AI into operational systems, demand is rising for platforms capable of managing both deterministic workflows and dynamic AI-driven processes within unified governance environments.

Large enterprise ecosystems led by Microsoft, Salesforce, IBM, and ServiceNow are increasingly integrating orchestration, automation, and AI governance into broader digital transformation strategies.

According to IDC, enterprise spending on intelligent automation and AI-enabled workflow technologies continues to accelerate as businesses modernize operations and reduce reliance on fragmented legacy systems.

At the same time, Forrester analysts have identified governance, explainability, and auditability as critical requirements for scaling AI automation responsibly across enterprise environments.

Top Insights

• Decisions + ProcessMaker was included in Forrester’s Adaptive Process Orchestration Software Landscape as enterprises seek governed AI orchestration platforms.
• Adaptive process orchestration combines traditional workflow automation with AI agents, nondeterministic processes, and human oversight to support enterprise-scale operational automation.
• Governance, auditability, and explainability are becoming central priorities as organizations deploy AI-driven automation into regulated business environments.
• The APO category reflects broader industry convergence between RPA, iPaaS, workflow automation, and AI coordination platforms into unified orchestration systems.
• Enterprise vendors including Microsoft, Salesforce, and ServiceNow are expanding orchestration capabilities as AI adoption accelerates.

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