I once spoke with the Global VP of Professional Services at a major tech firm, and he said something that’s stuck with me ever since:
The past year pushed professional services into a new operating reality, with AI agents on the verge of becoming operational team members that have a role in every step of the services lifecycle.
Kantata’s upcoming State of the Professional Services Industry report captures this shift clearly, with 87% of leaders saying they are preparing to manage AI agents alongside human employees as part of their workforce — and resource managers are at the center of this change.
In my conversations with Kantata experts and the PS leaders they advise, one theme comes up repeatedly: the next year will demand a new kind of resource management. AI is starting to take its place as a working member of your team rather than an experiment or side project. Delivery models are tilting toward outcome accountability. Data trust will determine which firms accelerate and which stall. These changes are already influencing how leaders evaluate talent, structure projects, and make day-to-day decisions.
As we move into 2026, resource management will become the function that either unlocks AI-powered performance gains — or exposes the cracks in a firm’s operating model.
Here are the top three predictions every RM leader should prepare for:
Prediction #1: AI agents will become part of the team
In 2026, AI will not sit on the sidelines. It will function as a real contributor inside delivery teams.
Many organizations already use AI for task-based work, but the year ahead will bring deeper integration into core delivery workflows. This will create a new category of responsibility for resource managers: designing teams that blend human expertise with AI capability.
This shift has already begun, as Kantata’s Chief Product Strategy Officer, Sarah Edwards, has seen in her talks with PS leaders: “We’re moving toward a world where AI agents are treated like billable contributors on a project team. Many firms have already built agents—but they haven’t yet solved how to measure their value or manage them like any other resource. The leading organizations are now focused on tracking agent impact, outcomes, and cost so hybrid teams can be planned and governed with confidence.”
This will be a defining factor for firms in 2026. They’ll expect more from their AI agents, but their systems and staffing models are not yet built to handle the complexity. Attribution is no longer an enhancement, it’s a requirement — which is why figuring out how to do so is an urgent need, with 90% of leaders saying that their systems must attribute work outcomes and costs to both people and agents.
And as AI absorbs more routine, repeatable work, the value of human expertise will only increase. As Kantata’s Vice President of Industry Solutions, Melissa Korzun, shares: “Agents will take on more of the routine work, but human expertise becomes even more valuable—especially change leadership. The teams that win won’t just automate tasks; they’ll elevate the people who can drive adoption, guide clients, and lead through change.”
In 2026, the resource manager becomes a hybrid workforce architect. They will need to understand AI capacity, align AI capability with the right human roles and skills, and measure performance across both. The firms that treat this as a strategic design challenge, not a technical one, will move faster and deliver more effectively than their peers.
Prediction #2: Delivery will become a discipline centered on outcomes, not execution
Outcome-based pricing continues to gain traction, but most organizations are still not structured for outcome-centered delivery. The State of the Professional Services Industry report shows that nearly half of firms use outcome based pricing in some form, yet more than half report consistent budget misses — showing that the industry is making outcome promises without the infrastructure needed to deliver them predictably.
The transformation underway is not about changing pricing models, but about changing delivery identity. This new landscape will focus on creating the conditions that produce outcomes, not simply executing tasks.
Edwards describes this shift and the coming evolution for delivery simply: “Many services leaders will remain skeptical of outcome-based pricing, and pricing models will still be largely fixed fee or annuity based in a lot of companies for the foreseeable future, but delivery leaders need to become outcome-aware by default, even if they’re not pricing based explicitly on outcomes. You’re not just managing projects—you’re managing relationships, client health, and the results clients actually care about. Firms need fewer on-the-ground coordinators and more people who can steer outcomes and navigate stakeholders.”
AI will accelerate this evolution by strengthening onboarding, reducing bottlenecks, surfacing risks earlier, and supporting smoother handoffs. Resource managers will need to be embedded earlier in each engagement lifecycle so that staffing, skills alignment, and risk identification begin long before delivery starts. RM leaders will shape the clarity of the outcome, the predictability of the timeline, and the likelihood of client success, while AI will support the strategies and workflows they create.
In 2026, outcome readiness becomes a delivery advantage, and resource management becomes the lever that makes it possible. Firms that deploy talent and AI intentionally will deliver more value and earn deeper trust.
Prediction #3: Data trust will separate high performing firms from everyone else
While AI adoption is accelerating, trust in AI-generated insights remains uneven.
The State of the Professional Services Industry report underscores a reality RM leaders feel every day: AI doesn’t create leverage if every output requires intensive review. A light human-in-the-loop check is healthy. But when teams must repeatedly validate, correct, or discard AI-generated work, verification becomes a hidden capacity drain—pulling time away from forecasting, staffing decisions, and proactive risk management.
The coming year will widen the gap between firms that have strong data foundations and those that do not. The people with the right infrastructures, domain-specific language models, and connected knowledge graphs, are going to arrive at a level of trust that wasn’t possible last year.
Edwards highlights this shift: “I think there’s been a lot of healthy skepticism around trusting AI in delivery workflows. But next year we’ll see trust accelerate because people are seeing real success in real workflows. As those examples grow and get codified into playbooks, confidence builds — and teams start moving faster.”
Korzun sees the same trends, noting that “AI is entering a trust zone. We now have tested, validated applications that reduce fear of hallucinations. As trust increases, teams become more willing to operationalize AI, not just experiment with it.”
That trust won’t extend to all tools. Tools built on old models are showing their limitations. Spreadsheets won’t disappear overnight, but their ability to support modern RM needs is fading. Even PSA platforms must evolve to better leverage data and expertise to deliver value.
In 2026, data trust becomes a competitive divider. Firms that can explain and trace every AI recommendation will operate with speed and confidence. Those that can’t will remain stuck in verification mode while competitors move ahead.
The implications for resource managers are enormous. When data is fractured, stale, or opaque, resource management becomes slow and reactive. But when data is unified, explainable, and trustworthy, RM becomes an accelerator—improving forecasting, capacity planning, and day-to-day decision making.
Looking ahead
Resource management is stepping into a new era. Hybrid teams, outcome-centered delivery models, and trustworthy AI-powered intelligence will redefine how work is planned, staffed, and delivered. The organizations that lean into these shifts early will move faster, deliver better outcomes, and build stronger client confidence. Those that don’t won’t stand still — they’ll fall behind.