New Study Finds Resource Management at a Strategic Crossroads as AI and Outcome-Based Delivery Reshape Professional Services

LONDON & IRVINE, Calif.--(BUSINESS WIRE)--Resource management is being pushed into a more strategic role as AI changes what the “ideal team” looks like and professional services firms face growing pressure to deliver outcomes, not just effort. But a new study from the Resource Management Institute (the RMI), commissioned by Kantata, finds most organizations are still early in that transition, with significant gaps in readiness, visibility, and execution.

While interest in AI-augmented resource management is high, most organizations remain early in their maturity, operating with traditional, utilization centric models and limited readiness to orchestrate hybrid human and AI teams.

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The study, “Resource Management in the Age of AI,” found that the biggest barrier to AI-augmented resource management is limited understanding of where and how AI should be applied in resource management, cited by 49% of respondents. That was followed closely by poor data quality or fragmented data across skills, outcomes, demand, and capacity (47%), technology limitations that leave systems unprepared to support both AI-driven staffing and the orchestration of hybrid teams of human experts and AI agents (41%).

According to the RMI, “While interest in AI-augmented resource management is high, most organizations remain early in their maturity, operating with traditional, utilization centric models and limited readiness to orchestrate hybrid human and AI teams.”

According to the study, 39% of respondents say their organizations are still in a “traditional staffing” mode, where resource management still focuses primarily on skills, availability, and utilization with only ad hoc use of AI, while another 30% say they are only exploring and experimenting, with AI and/or outcome pilots in place but workflows and governance unchanged. That leaves just 31%, less than one third, reporting they are beyond experimentation, spanning organizations operationalizing hybrid delivery through to more advanced forms of data-driven and outcome-optimized orchestration.

As AI begins to change the composition of the delivery team, most resource managers do not yet feel ready to orchestrate blended teams of humans and agents. More than half of respondents (52.7%) said they are not equipped to manage hybrid teams, and another 28.4% said they are only slightly equipped. Only 4% feel well equipped, signaling a near-term need for playbooks, skills enablement, and workflow changes before hybrid staffing becomes routine.

The study also shows that resource managers are being asked to support a more outcome-oriented model without reliable access to outcome intelligence. Only 7.3% of respondents said outcome data is easily accessible and routinely used in staffing decisions, while 24.6% said only major wins or failures are known informally and another 24.6% said outcomes are not available to resource management at all.

That visibility gap is increasingly consequential. Nearly three quarters of respondents — 73.4% — said it would be very or extremely valuable to know which combinations of people or agents consistently produce strong outcomes for specific clients or projects. And 50.9% said the ability to demonstrate outcome experience already has a high or very high influence on staffing recommendations for prospective deals.

Respondents acknowledged that if outcome-based pricing becomes more common, resource management will need to shift from filling hours to maximizing delivery success, profitability, and achieved outcomes, while taking on greater responsibility for team composition, delivery risk, and delivery economics. But 1 in 2 respondents said they are unsure whether their organization will meaningfully adopt outcome-based pricing. That uncertainty underscores how difficult it can still be for resource management leaders to see — and help shape — the bigger picture around how work will be priced, sold, delivered, and billed as business models evolve in the Age of AI.

That strategic distance shows up elsewhere in the data as well. The study found that 72% of respondents say the resource management function is primarily (or solely) operational in their organization, with limited strategic influence. The main factors limiting resource management from playing a more strategic leadership role included competing operational demands (49%), lack of executive mandate or influence (48%), organizational resistance to change (45%), insufficient data or insight (44%), and limited tooling or systems (41%).

“Resource management continues to be viewed largely as an operational function, constrained by fragmented data, unclear AI application models, and insufficient outcome visibility,” writes the RMI. “At the same time, the results signal a clear aspiration shift: resource management professionals are seeking more data-driven, outcome-aware, and strategically influential roles, where skills intelligence, forecasting accuracy, and proof-of-delivery impact become as critical as capacity and utilization.”

“Professional services firms are entering an era where the ideal team is no longer defined only by human availability or role fit,” said Sarah Edwards, Chief Product Strategy Officer at Kantata. “Resource managers are increasingly being asked to weigh skills, outcomes, economics, and the role of AI in delivery — often without the data foundations or workflow support to do that confidently. This research underscores both the scale of the opportunity and the operational gaps organizations still need to close.”

Kantata will present the findings of this research at the seventh annual Resource Management Global Symposium, taking place in Indianapolis from April 20–22, during a session titled The End of ‘Who’s Available?’: What Resource Management Will Look Like in 2028 — and How to Get There. The session will examine how AI, changing client expectations, and outcome-based delivery are reshaping the composition of the ideal team and what resource management leaders need to do now to prepare.

For this research, Resource Management Institute surveyed professionals from 44 organizations across a broad spectrum of industries including professional and consulting services, Enterprise IT, product development, engineering, marketing agencies, accounting, audit, tax and advisory firms. Respondents included services executives, resource managers, resource management office leaders, project managers, and delivery leaders.

For additional insights and to download a full copy of the report, click here: http://kantata.com/resource/resource-management-in-the-age-of-ai

About Kantata

Kantata is a leading provider of Professional Services Automation (PSA) solutions that help professional services organizations and agencies ensure consistent excellence and profitability across projects. More than 1,500 organizations worldwide rely on Kantata to instantly assemble the ideal team, easily amplify institutional knowledge, and confidently forecast outcomes. Recognized as a Leader on G2’s PSA Software Grid® and Resource Management Software Grid® and consistently ranked among the top project management software products in G2’s annual Best Software Awards, Kantata supports the full services lifecycle — from scoping and staffing to delivery and forecasting. For more information, visit www.kantata.com.