Organizations with strong process context are five times more likely to report successful AI outcomes, according to The 2026 Process Context Study, produced by ARIS and The Hackett Group.
The findings revealed a significant gap between enterprise AI ambition and operational readiness.
While 86% of global business leaders believe AI agents can’t be deployed reliably without process context, just over one in five (22%) say their organization has comprehensive, real-time visibility into end-to-end process flows.
A further 59% describe their current process visibility as fragmented across systems and functions, leaving enterprises with a critical gap to close as 76% view process context as critical over the next three years.
“This research exposes a clear readiness gap. As AI moves from assisting people to executing work, closing that gap will become increasingly important,” says Rick Gardner, senior director, advisory market intelligence, The Hackett Group. “Organizations need to give agents the operational understanding to know not only what they can do, but how work should actually get done.”
“AI is becoming more capable at extraordinary speed, but capability alone doesn't create business value,” says Guillaume Bacuvier, CEO of ARIS. “The differentiator will be how effectively organizations put that intelligence to work inside their businesses. Data tells AI things about your business – process context tells AI how your business works. The next phase of enterprise AI isn't simply about deploying more agents. It's about deploying the right agents into the right processes and giving them the business understanding to perform effectively. The Agentic Enterprise won't arrive through one giant transformation - it will emerge process by process.”
Key takeaways:
· The findings point toward targeting high-value workflows to deliver measurable business value such as financial planning, analysis, and accounts payable/receivable; spend analysis, contract management, and procurement workflows; IT service desks and automated incident management; and recruitment, employee onboarding, and customer operations.
· 78% report faster execution speed and reduced process cycle times.
· 75% achieve a reduction in manual, repetitive tasks.
· 71% experience improved process quality and consistency.
· 69% deliver higher-quality decision-making across core operations.
· 67% strengthen governance, risk management and compliance enforcement.
· Cost, data quality, and organizational silos account for over 70% of the primary obstacles to establishing actionable process context.
· Only 34% of organizations are confident in their ability to govern AI-driven decisions effectively, while just 18% have mature, enterprise-wide AI governance frameworks in place today.
· Meanwhile, 46% of enterprises still place AI accountability solely with IT.
