Knowledge governance seen as key to AI adoption gap

iManage has published new research highlighting a gap between strong interest in artificial intelligence and its routine use in day-to-day work, with knowledge governance emerging as a key constraint.

The Knowledge Work 2026 Benchmark Report is based on a survey of 3,185 business and technology decision-makers across 26 countries, covering organisations in legal, accounting and tax, financial services, and asset management.

The study found that 85% of organisations are piloting, implementing, or using AI, but only 17% have integrated it into daily operations. The results suggest experimentation is widespread, while operational adoption remains limited.

Governance concerns

Security and policy issues appear to be a major brake on deployment. Nearly one-third of respondents reported a policy-impacting incident linked to unregulated AI tools, and almost 30% said they had delayed adoption because of security or governance concerns.

The report also identifies a divide between organisations with formal processes and controls for knowledge and those without. It describes this as "knowledge work maturity", measured using iManage's Knowledge Work Maturity Model.

Laura Wenzel, iManage's Global Insights Director, said the research shows foundational work matters more than early experimentation.

"What this data shows is that AI success isn't about who experiments fastest - it's about who has done the foundational work," said Laura Wenzel, Global Insights Director, iManage.

"Organisations with mature knowledge environments are better positioned to deploy AI consistently, govern it responsibly, and earn trust from both clients and employees. Without that foundation, AI simply amplifies existing friction and risk," Wenzel said.

Client pressure

The survey suggests client expectations are shaping AI plans, particularly among organisations that score higher on knowledge maturity. Overall, 57% of respondents said customers influence their AI adoption, rising to 74% among knowledge-mature organisations.

Knowledge-mature organisations were also reported to be twice as likely to deploy AI in operational and client-facing workflows. The results suggest governance structures and well-managed internal information may help AI move from pilots into production settings that affect customers.

Business performance

The report links higher knowledge work maturity with stronger self-reported business outcomes. Organisations with higher maturity were nearly twice as likely as less mature peers to report year-over-year revenue growth, and were also more likely to report profitability and stronger financial performance.

These measures were based on respondent feedback rather than audited results. Even so, the report presents the correlation as a sign that information management practices and controls can influence how effectively AI is put to work.

Another theme was how organisations view AI's impact on jobs. Across the sample, 57% of respondents said AI is primarily enhancing existing roles. Knowledge-mature organisations were also more likely to report productivity improvements from AI-enabled workflows.

Knowledge search

Despite confidence in internal systems, respondents reported persistent friction in finding information. The study found that 86% of decision-makers were confident in their ability to find and reuse knowledge, yet professionals still spend an average of 37 minutes per day searching for information.

The data highlights a practical challenge for professional services and financial firms, where work often depends on locating prior documents, analysis, communications, and specialist expertise. It also points to a key dependency for many AI use cases, since AI tools typically rely on access to well-organised, current, and permissioned content.

Platform investment

The research also examined planned spending on information systems. It found that 72% of organisations plan to invest in a new document or knowledge management platform within the next two years. The findings suggest technology investment alone may not address security concerns or operational barriers without consistent governance.

Reena SenGupta, Executive Director at RSGi, said firms should treat investment in knowledge systems and AI as a strategic priority.

"This research confirms that investment in knowledge systems, architecture and AI is non-negotiable. Law firm strategy cannot be a wait and see, or be a second follower," said Reena SenGupta, Executive Director, RSGi.

"Competitive advantage is being won by the advanced knowledge organisations and now we have the data to prove it," SenGupta said.

iManage said the benchmark is intended to help organisations compare their approach to knowledge governance and AI adoption with peers, as demand for AI use cases grows and scrutiny of security and policy compliance remains high.