KEY FINDINGS FROM THE RMI SURVEY SERIES
Efficiency got you here. Expertise gets you to what's next.
New research from the Resource Management Institute and Kantata found that most RM teams use AI to save time, not as a transformational driver of better business outcomes.
RMI surveyed professionals across 106 organizations to understand where resource management stands today and explore the gap between reality and expectations.
AI mastery starts with maturity
Resource management teams have already adopted AI, but low maturity has left most stuck in experimentation mode. They're testing isolated use cases instead of scaling AI into the repeatable processes that power intelligent resource management.
60%Use AI to support resource management
50%In the "Experimentation" stage of AI
<15%Report systematic AI use
2%Describe themselves as AI-native
Bad data is the real barrier to intelligent resource management
Intelligent resource management isn't a tech problem. It's a data problem.
Internally, 61% of RM teams cite data quality as the single biggest obstacle to AI adoption, ahead of a lack of bandwidth, limited expertise, or missing tools. And 75% rate their org's data readiness as "Average" — or worse.
External-facing teams experience similar challenges, with poor data quality (56%), lack of tools (47%), and limited expertise (40%) topping their list.
What are the biggest barriers to adopting AI-driven Resource Management in your organization? (Select up to 3)
Source: © 2007- 2026 Resource Management Institute, a Belcan Company. All Rights Reserved
(Internal team data)
The maturity disconnect between internal and external teams
Get the ReportInternal RM teams report more than 2x the rate of moderate or better improvements in outcomes from AI than external-facing teams. With fewer commercial pressures and the ability to standardize AI processes before scaling, internal teams have shown what AI maturity looks like in intelligent resource management.
Efficiency without transformation
RM leaders use AI mostly to do the same work faster: resource matching, skills inference, forecasting. But real transformation starts when they use AI to amplify their expertise and rethink resource management altogether.
>80%
Cite reducing manual effort as their top reason for AI adoption
Go beyond efficiency with expertise
While most companies have only seen small efficiency gains from AI, nearly two-thirds expect AI to have a strong or transformational impact on resource management in the next two years.
The gap between current wins and future expectations won't close on its own. The firms that'll get there first are the ones that stop treating AI as an efficiency tool and start using it to scale the thing AI can't replicate: the expertise that lets RM teams always deliver amazing.
What's next: intelligent resource management
These findings are just a glimpse of what 100+ resource management leaders told us about AI adoption, maturity, and where the industry's headed. Download the full report to see what's holding firms back and what mature organizations are doing differently.
Once RM teams move past efficiency and get strategic with AI, they can achieve the strong or transformational impact they're hoping for in the next two years.
Download the Full Report