Research reveals AI agent adoption is accelerating rapidly while governance and cross-functional coordination lag
Leah, an enterprise agentic AI company, today announced findings from new research conducted by IDC, detailed in The Three Pillars of the Agentic Enterprise. The findings show that while 66% of organizations use AI agents in production and expect the number of agents they deploy to increase sixfold by early 2027, many still lack the governance, interoperability, and cross functional coordination needed to manage them effectively and at scale.
"Right now, enterprise AI looks a lot like a thousand instruments playing at once without a conductor. Organizations are deploying agents across every function, but too often those systems operate in isolation, without shared context, coordination or oversight," said Anurag Malik, President and CTO of Leah. "The next phase of enterprise AI will depend on creating harmony among those agents while maintaining the governance and oversight necessary to build trust and deliver meaningful business value."
Based on responses from 400+ enterprise decision makers across legal and compliance, procurement and sourcing, finance and accounting, and logistics and supply chain, the research points to a widening gap between AI adoption and enterprise readiness.
Key findings include:
- AI adoption is scaling rapidly: Organizations are doubling their budget allocation for agentic AI over the next 12 months.
- Governance remains a critical challenge: 79% of organizations say tools to discover unsanctioned AI agents are either absent or not working well.
- Interoperability gaps persist: Agent implementations are increasingly cross-functional and multivendor, but only 29% of agents currently interact with each other a gap organizations will need to close.
- Cross-functional processes present significant opportunities: Contract management emerged as a strong example of a cross-functional process that organizations want AI agents to fix, with 79% of organizations reporting contract handoff delays and 59% saying delays add four to seven days to contract cycle times.
- Generic AI tools are falling short: 68% of decision makers said today's generic LLM-powered chatbots are only partially sufficient or worse for legal and procurement work, signaling demand for purpose-built, domain-specific agentic solutions with measurable ROI.
The release of the study comes as enterprises move beyond AI experimentation toward large-scale deployment. Rather than viewing AI agents as isolated productivity tools, organizations are beginning to recognize the need for coordinated, purpose-built systems that can operate across departments, workflows and decision-making processes.
"We're moving from the era of AI experimentation to the era of AI execution," said Malik. "The findings show that enterprises understand the opportunity AI presents, but they're also recognizing that scale requires more than deployment. Businesses must learn to coordinate thousands of decisions, workflows and agents as a single, governed system."
"The enterprises that succeed will be those that identify where AI can fundamentally change the flow of work, rather than simply adding it to processes that were designed for a different era," said Neil Ward-Dutton, Research VP, Agentic Automation AI Technologies at IDC. "Complex business processes rarely belong to a single department or system, and those who are managing agentic AI as a portfolio rather than a set of departmental projects will be the ones who see results. By standardizing how agents are built and monitored, prioritizing core processes that cross functions, and measuring results at the outcome level instead of counting deployments, these enterprises will see actual ROI, rather than just a collection of pilots."
Dive deeper into these findings in IDC's full study, The Three Pillars of the Agentic Enterprise.
FAQ
- What is The Three Pillars of the Agentic Enterprise Study?
This study is based on an IDC survey of 410 enterprise decision makers actively deploying or evaluating AI agents across industries, and it identifies three key pillars for enterprise agentic AI success: governance, orchestration, and cross-functional collaboration. - What are the key findings?
66% of organizations are already using AI agents in production and organizations plan 6x growth in deployments by January 2027, far outpacing governance. 79% of organizations say that tools to discover unsanctioned AI agents are either absent or not working well. - Why do governance and orchestration matter for enterprise AI?
Governance helps organizations maintain trust, compliance and accountability, while orchestration enables agents, systems and teams to work together across business functions. Together, these capabilities are critical for turning AI adoption into measurable business value.
About Leah
Leah is an enterprise agentic AI company designed to autonomously run complex work across legal, procurement, finance and shared services. Founded in London in 2015 and backed by SoftBank and Insight Partners, Leah serves 400+ global enterprises and supports mission-critical processes in regulated industries. Leah works with partners including Microsoft, Google, OpenAI, Anthropic, PwC and KPMG to support enterprise transformation programs globally.
Leah has offices across New York, London, Dubai, Mumbai, Sydney, Glasgow and Singapore.
IDC InfoBrief, sponsored by Leah, The Three Pillars of the Agentic Enterprise, EUR154841XXX-IB, September 2026
View source version on businesswire.com: https://www.businesswire.com/news/home/20260922537352/en/
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