Process intelligence will rescue 30 percent of failed artificial intelligence (AI) projects in 2026, according to Forrester.
The research giant released its predictions for the next frontier of automation, highlighting process intelligence as a key factor in successful AI adoption.
Process intelligence is a rapidly emerging, data-driven, technology-enabled approach to managing and improving business processes. In recent years, the process intelligence market has grown quickly, fueled by new entrants introducing innovative methods for capturing insights and analyzing how work actually gets done.
The PEX Report 2025/26 found that almost a quarter (23 percent) of surveyed firms use process intelligence to support business transformation. Meanwhile, 22 percent are planning to increase investment in process intelligence in the coming year.
The race to cognitive automation
The race to cognitive automation is well underway, Forrester wrote on Forbes. “For years, deterministic automation has been the backbone of reliability and compliance. While this paradigm still matters, it no longer defines the frontier. The growth of agentic AI has shifted the goalposts from task execution to contextual reasoning and adaptive decision-making.”
Process intelligence sits at an inflection point in this evolution with immense potential to provide agents with contextual awareness and process grounding, Forrester added.
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The rise of process intelligence in agentic automation
However, process intelligence has largely sat out the first wave of agentic automation, Forrester said. “Most process intelligence vendors have approached AI timidly, offering merely incremental enhancements such as chat-based explainers or conversational analytics.”
The real opportunity is in transforming process insights into active inputs for agent reasoning, providing live context, enforcing compliance constraints, and enabling continuous operational feedback loops. To remain relevant, process intelligence must evolve to embed itself directly into the fabric of agency as a foundational enabler of AI. Vendors that make this shift will position process intelligence as a core driver of autonomous, adaptive operations.
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How does process intelligence enhance agentic AI?
There are multiple ways in which process intelligence can make agentic AI more powerful, according to Marlon Dumas, chief product officer at Apromore.
Some examples include:
- Automatically discovering manual processes and creating virtual models of the steps involved. For instance, process intelligence can streamline accounts payable processes, highlighting redundant or overlapping work. This information helps agentic AI understand the context of a step or activity in a process and make smarter, more informed decisions.
- Monitoring agentic AI activities that use traditional robotic process automation (RPA). Process intelligence can record and assess the performance of agentic AI systems and pinpoint workflow frictions for action and adjustments.
- Enabling agentic AI to assess outputs and predict future impacts (such as bottlenecks created by overproduction that can’t be handled downstream). This feedback loop allows agentic AI to make adjustments in real-time and maintain smooth operations.