Insurance organizations are under pressure to grow, modernize, adopt AI, and improve profitability, all while managing one of their largest and most complex expenses: people.
At Summit 2026, Stephen Murphy, Senior Practice Director for the Carrier Practice, and Amber Brethouwer, SVP of Strategic Accounts at ReSource Pro, made the case that capacity management is no longer just an operational exercise. It’s a strategic discipline connecting growth, transformation, workforce planning, and profitability. Capacity management measures workload, staffing levels, and productivity to ensure insurance organizations can meet demand efficiently.
As Murphy put it: “The single biggest lever you have for sustainable growth is how you manage your people.”
Organizations that want to grow without creating backlogs, burning out teams, overspending on labor, or missing the return on technology investments need a clearer view of workforce capacity.
You can’t scale what you can’t see
Insurance operations are people-intensive, and even as technology, AI, and process partnerships reshape the industry, people remain at the center of how work gets done. Revenue growth demands more support capacity. Systems integration changes how teams work. Shifting work to a strategic business process outsourcing partner moves it from one group of people to another. AI can streamline tasks and change role definitions. Each of these forces shifts the demand curve for talent.
Without visibility into capacity, organizations react instead of plan: hiring after backlogs build, approving headcount after teams are already overwhelmed, relying on spreadsheets or gut feel. Over-hire and labor costs linger and compound. Under-hire, and service levels decline, backlogs grow, and employees burn out. Capacity clarity moves leaders from reactive staffing to proactive planning.
From “I think” to “I know”
One of the strongest messages from the session: staffing conversations need to shift from opinion to evidence.
Without a reliable staffing model, headcount discussions become negotiations. A manager says, “I think I need 10 people.” Finance responds, “You can have five.” The result is a compromise, not a decision based on the actual amount of work required.
Murphy described capacity management as a communication tool as much as a calculator. A strong model translates work into hours, hours into full-time equivalents, and staffing needs into objective business cases.
The hidden cost of staff inflation
Murphy pointed to a concept he calls “staff inflation”: when organizations gradually lose productivity without realizing it.
Take a team that historically processes 200 policies per week with 20 employees. Later, part of that work shifts to a strategic partner, and the remaining internal team adjusts to a lower volume. When new volume arrives, the team feels overloaded, even though total productivity has actually declined compared to the original baseline. Headcount may rise, productivity may fall, and costs may climb, all while the change looks normal because it happened gradually.
Capacity management exposes these hidden dynamics: how work is actually changing, where capacity is freed up, where productivity is dropping, and where staffing decisions are being made without the right baseline.
Why AI raises the stakes for capacity management
Many organizations are investing in AI and automation expecting measurable savings. But as Brethouwer noted, leaders are increasingly asking: “Where is the savings?”
If an organization can’t measure how work changed or how many hours were saved, the return on an AI investment stays theoretical. Capacity management gives organizations the structure to measure that impact: when AI reduces the time required for a task, a good staffing model shows exactly how much capacity was freed, so leaders can decide whether to redeploy employees, shift work to higher-value activities, support growth, or reduce costs.
Capacity management is foundational to transformation
Brethouwer connected the conversation to ReSource Pro’s Integrate → Optimize → Digitize (IOD) framework. Integration requires understanding how work, systems, data, and roles connect. Optimization requires knowing whether workflows are efficient and teams are structured for the right outcomes. Digitization requires a baseline showing how technology and AI change the way work gets done.
Before organizations can modernize effectively, they need to know where they stand today: their staffing baseline, role definitions, workflow demands, and the capacity required to serve customers. Only then can they invest, automate, and plan for growth with confidence.
A competitive edge for insurance leaders
Murphy closed the session with three takeaways:
Growth breaks without capacity clarity. Staffing reactively adds risk with every hire.
Moving from “I think” to “I know” creates a common language for managers, executives, and finance teams.
Capacity management is a competitive edge, supporting growth, profitability, workforce planning, and technology transformation.
Insurance leaders are being asked to make faster, smarter decisions amid complexity, talent constraints, retirements, AI, and rising customer expectations. Capacity management gives them the visibility to align people, work, cost, and strategy, plan for growth instead of reacting to it, and measure the real impact of transformation. Sustainable growth starts with knowing what work needs to be done, who is doing it, how long it takes, and how that changes over time.
Interested in more insights from Summit 2026? Explore additional session takeaways and join the conversation as we look ahead to Summit 2027.
