Talent, Technology, and Transformation: 2025’s Claims Management Trifecta
Claims management in 2025 is being redefined. The talent pipeline is under pressure, automation is pushing into every corner of the claim’s lifecycle, and only those firms that transform internal processes—culturally, operationally, technologically—will maintain scale, reputation, and margin.
Labor market dynamics suggest a critical imbalance: the experienced claims professionals are retiring or moving out faster than they can be replaced. According to Insurance Journal, the number of claims roles is projected to decline by about 5% over the coming decade even as demand for resolution increases. The industry is already experiencing pressure: Gallagher Bassett’s 2025 Carrier Perspective Whitepaper reports that 72% of carriers cite labor and retention issues as having a “moderate to significant impact” on their ability to manage claims efficiently. (Insurance Journa)
These pressures are compounded by shifting workforce expectations. Newer professionals—Gen Z in particular—prioritize digital fluency, work-life balance, purpose, and flexibility. They tend to favor employers with strong mission statements, modern technology tools, and opportunities to work in hybrid or remote settings. Traditional claims operations—heavy with legacy systems, manual workflows, and rigid structures—are increasingly misaligned with those expectations. (Insurance Journa)
Meanwhile, technology adoption is accelerating—but unevenly. AI, RPA (Robotic Process Automation), predictive analytics, and process mining are among the top focus areas. According to Roots.ai’s 2025 State of AI Adoption report, the most common areas seeing gains are claims processing, fraud detection, data extraction, and customer service. The AI in Insurance Claims Statistics (2025) report suggests that insurers using AI tools have seen cycle times drop sharply—in some cases, from 10 days to around 36 hours for routine claims, especially where first notice of loss is enabled via digital channels. (CoinLaw)
Yet for many claims operations, adoption introduces challenges: data quality, legacy system integration, cost of implementation, cultural resistance. The article “AI in Insurance Claims Processing: Balancing Innovation with …” notes that especially for smaller firms, the financial investment needed for tech (software, infrastructure, staff training) is substantial, and payoff often depends heavily on scale and rigor. (EA Journals)
Transformation is not just about tech or talent in isolation—it requires reimagining how work flows, how people collaborate, and how performance is measured. For example, many leading claims organizations are shifting to cloud-first infrastructures, modular platforms, and API architectures to support faster adjuster deployment, remote inspections, and scalable onboarding. Process mining tools are being used to identify bottlenecks—coverage verification, field response delays, documentation handoffs—and address them systematically. Survey data suggests that insurers who invest in human capital—training, mentorship, competitive compensation, and flexible work models—are achieving measurably better outcomes in claims cycle time and customer satisfaction. (Risk & Insurance)
From the vantage of Edge Claims, we are adapting on all fronts. We have launched an internal development track targeted at adjusters and claims staff that pairs technical training (data analytics, digital tools) with claims domain expertise to build hybrid skill sets. We are phasing in automation for routine tasks: document ingestion, pre-validation of basic policy documentation, image-based damage assessments, and using AI to route claims by complexity in order to allocate human resources more efficiently. We are investing in process mining to analyze workflows—find redundant handoffs, reduce idle time, align field inspections more tightly with logistics and repair partners—and redesign those workflows to reduce cycle time without sacrificing compliance or accuracy.
Edge Claims is also expanding performance metrics, so success is measured more holistically. In addition to traditional KPIs (claim frequency, payment accuracy, cycle time), we now monitor employee turnover, adjuster satisfaction, customer sentiment, incidence of coverage surprises, and automation-efficiency ratios (i.e. how many steps or hours are saved per claim with new tools). We believe that measurement drives behavior—and strong metrics in these newer dimensions are essential to ensure transformation is real, sustained, and scalable.