Enterprise automation stands at a crossroads in 2026!

2026 will be pivotal for enterprise automation. The paradigm of scripting and deterministic control is still indispensable for compliance and reliability but no longer defines the frontier. 

Vendors and enterprises are embedding reasoning and adaptive behavior into automation, testing how far they can push agentic capabilities without eroding foundational elements like trust or governance. This is causing markets like robotic process automation (RPA), integration platform as a service (iPaaS), low-code, and process intelligence to collide as boundaries blur. 

The result is uneven progress: Innovation is accelerating at the edges, but core adoption is tempered by risk, testing bottlenecks, and immature runtime controls. Against this backdrop, our predictions for 2026 map where automation will break forward. Among the key developments in 2026:

Strategic robot innovation will unlock 20% of new enterprise use cases. 
Robots are becoming dramatically more practical thanks to three breakthroughs: Generative AI accelerates robot learning via synthetic motion generation, imitation learning frameworks, and multimodal foundation models, as large behavior models begin to displace the laboriously scripted workflows used to control robots; physical AI for embodied intelligence bridges gaps between simulation and reality and enhances real-world agility; and component and materials innovation like motion plastics helps lower hardware costs. 

Together, these innovations enable robots that understand plain English commands, fix their own mistakes, and apply learned skills to new situations, dramatically reducing deployment complexity and costs for 2026 rollouts, although mass enterprise adoption is still three to five years away. Current deployments are concentrated in controlled environments like warehouses and manufacturing. Broader service applications still require significant customization and human oversight.

Less than 15% of firms will turn on the agentic features in intelligent automation suites. 
RPA and digital process automation (DPA) platforms boast massive installed bases compared with emerging agentic planforms, but enterprises are hesitating to enable AI-driven process execution. 

Three critical barriers are stalling adoption: Organizations struggle to test model-driven decisions within complex workflows; governance frameworks remain incomplete; and pilot projects show limited payback. 

High failure rates reinforce enterprises’ preference for deterministic automation over unpredictable AI agents in critical workflows. RoI challenges and insufficient testing capabilities will keep most organizations running traditional rule-based automation through 2026 despite vendor pressure to adopt agentic features. 

Enterprises should review Forrester’s AI agent and agentic AI progression models when evaluating which use cases justify the operational complexity of agentic automation.

ServiceNow will acquire Boomi, portending additional vendor consolidation.
The shift from screen-scraping RPA to API-driven agents is forcing automation vendors to acquire integration platforms or risk obsolescence. Expect ServiceNow to acquire Boomi, at least one other automation vendor to acquire an iPaaSvendor, and at least one pure-play automation vendor to launch a competing iPaaS product to challenge incumbents. 

This consolidation is the result of enterprise demand for unified platforms that can orchestrate traditional automation and AI agents through REST APIs and modern integration protocols. Vendors with weak API orchestration capabilities face an existential choice: Build, buy, or become acquisition targets. The offerings resulting from this consolidation will strengthen the nascent adaptive process orchestration market. 

Automation leaders intending to combine AI with classic automation technologies (RPA, DPA, iPaaS, low-code) should review their platform vendors’ API-first roadmap. Those without credible integration strategies may not survive the coming shakeout.

Eighty percent of HPIT organizations will pivot from task-centric automation to workflow archaeology. 
Tech teams at firms that lead on Forrester’s high-performance IT (HPIT) metrics will move beyond automating discrete tasks, and instead, apply task intelligence to systematically dissect and unbundle complex workflows to uncover where AI agents can augment human work for transformational outcomes. 

Rather than abandoning process automation, they will adopt hybrid orchestration that blends deterministic workflows with agentic AI, supported by new artifacts: skill catalogs to inventory human competencies, workflow maps to identify agent insertion points, and human/agent collaboration frameworks to define partnership levels. 

Forward-thinking organizations will sequence adoption from IT operations and customer support into revenue-generating workflows like product development, creating competitive advantage by redeploying talent to higher-value work while agents handle routine cognitive tasks and delivering measurable productivity and innovation gains within 18 months.

Process intelligence will rescue 30% of failed AI projects. 
Most AI failures stem from training agents on idealized processes that don’t match operational reality, causing inconsistent behaviors and unreliable outcomes. Process intelligence tools map how the work actually gets done, not how it’s supposed to happen, providing the ground truth for effective AI deployment. 

Organizations using process intelligence ahead of launching agents see higher conformance rates and clearer RoI measurement. This real-world process data and insight becomes the foundation for autonomous or semiautonomous operations, the North Star for many automation leaders. AI project leaders should mandate process discovery before agentic deployment, treating process intelligence as a foundational capability, not optional tooling.

Summary
The next 12 months represent a pivotal moment for enterprise automation. As agentic AI continues to redefine the frontiers, traditional market categories will collide and converge. 2026 will be a year of strategic choices; automation buyers will attempt to align deterministic and cognitive automation technologies into a common framework for stable, value-oriented enterprise autonomy.

-- Source: Forrester Research, USA & Australia.