Implementing an AI Strategy While Enhancing Expertise and Experience
By Sharon Emek
Artificial intelligence (AI) is reshaping the insurance industry at a pace few organizations expected. From submission intake and document processing to underwriting analytics and client service workflows, AI-powered tools are improving efficiency across nearly every corner of insurance operations.
For many agencies, managing general agents and regional carriers, however, the real challenge isn’t whether to adopt AI. It’s how to implement these technologies while maintaining operational stability, preserving expertise and protecting service quality.
The shift toward automation is creating both opportunity and disruption. While AI streamlines routine tasks and improves speed, it also changes the structure of the workforce. As administrative roles shrink, experienced professionals are becoming more critical, and organizations are facing a growing gap between technological capability and human expertise.
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Successfully navigating this transformation requires more than technology alone. It requires a thoughtful strategy that combines automation with the experience and judgment that have always defined the insurance profession.
How AI Is Changing Insurance Work
AI is already transforming how insurance organizations operate. Modern systems can analyze submissions, process documents, identify patterns in large data sets and assist with risk evaluation at speeds that would have been unimaginable just a decade ago.
According to the McKinsey Global Institute, up to 30% of tasks in financial services roles can already be automated using today’s technology, particularly administrative and data-processing functions.
Across the industry, AI is being used to:
- Streamline submission intake and quoting processes.
- Automate document management and compliance checks.
- Assist with customer service triage.
- Analyze renewal and retention data.
- Improve marketing and lead qualification.
These capabilities deliver measurable improvements in productivity and operational efficiency.
Underwriting is also evolving. AI systems can quickly evaluate large volumes of data, helping identify patterns and potential exposures that may otherwise go unnoticed.
However, rather than replacing underwriters, automation is shifting the role toward judgment-based portfolio management. In other words, AI gathers and analyzes the information, but experienced professionals still interpret it and make the decisions.
Use AI Without Losing the Human Touch
While automation creates efficiency, it also introduces structural changes to the workforce. One of the most visible shifts is the reduction of clerical and administrative roles. Tasks that once required manual processing—data entry, document handling and routine policy administration—are increasingly handled by automated systems.
This change creates what many organizations are experiencing as “role compression.” With fewer entry-level and support staff, senior employees often find themselves responsible for both oversight and exception management.
At the same time, experienced professionals are becoming even more essential. Underwriters, claims specialists and operations leaders must now oversee automated processes, manage exceptions and ensure that decisions remain consistent with the organization’s risk appetite. As automation increases speed, errors can occur more quickly if proper oversight is not in place.
This creates a new operational reality: Technology improves productivity, but experienced professionals are needed to guide it.
The Risk of Experience Bottlenecks and Implementation
For small and midsized insurance organizations, the increasing adoption of AI places greater reliance on experienced professionals to provide the much-needed human oversight. Insurance has long faced a demographic shift as large numbers of baby boomers approach retirement. At the same time, fewer young professionals are entering the industry.
The Jacobson Group’s “Insurance Labor Market Study” has consistently shown strong demand for experienced underwriting and claims professionals. But as automation reduces entry-level roles, the pipeline of future talent may shrink even further.
Historically, many insurance professionals began their careers in administrative or support roles before moving into underwriting, claims or leadership positions. If those early roles disappear, fewer employees will gain the experience needed to step into mid-career and senior positions later.
Over time, this could create an experience bottleneck, where knowledge becomes concentrated among a smaller number of senior professionals.
Another challenge organizations face during AI adoption is operational disruption during the transition period. Implementing new systems rarely happens without friction. During rollout phases, organizations often experience workflow backlogs, quality control issues and temporary inconsistencies in decision-making.
Large national carriers typically have dedicated transformation teams to manage these transitions. Smaller organizations often do not. For regional carriers, agencies and MGAs operating on tighter margins and leaner teams, even temporary disruptions can pose meaningful operational risk. Delays in processing, customer service interruptions or underwriting inconsistencies can quickly affect client relationships and reputation.
This is why successful AI adoption requires both technological investment and strong operational oversight.
The Benefits of AI Are Real
Despite these challenges, the benefits of AI for insurance organizations are significant. AI technologies can help organizations:
- Analyze risk more effectively by processing large volumes of data.
- Identify emerging exposures more quickly.
- Automate compliance monitoring.
- Improve operational visibility through real-time analytics.
- Streamline marketing and client service processes.
In a competitive environment where many small and midsized organizations operate under tighter combined ratio margins, automation can become a powerful lever for improving efficiency.
But the greatest advantage may be the ability to free employees from routine administrative tasks and allow them to focus on higher-value work.
Why Human Expertise Matters More Than Ever
Ironically, as automation increases, the value of human experience becomes even greater.
AI excels at handling structured tasks and processing data quickly. What it cannot replace is judgment, contextual understanding and the ability to navigate complex or unusual situations.
Insurance has always relied on professional judgment. Market conditions change, risks evolve and each client situation carries its own nuances. Technology can support decision-making, but it cannot replace the experience that underwriters, claims professionals and operations leaders develop over decades.
Experienced professionals are particularly important in areas such as:
- Managing risk appetites and underwriting discipline.
- Overseeing quality control during technology transitions.
- Mentoring and training newer staff.
- Maintaining strong client relationships.
As organizations adopt AI-driven processes, these skills become even more valuable. The most successful insurance organizations will not treat AI as a replacement for people. Instead, they will view it as a tool that complements human expertise.
The optimal workforce structure includes three elements:
- AI-powered technology that automates routine tasks and improves efficiency.
- New professionals who bring fresh perspectives and long-term growth potential.
- Experienced professionals who provide judgment, oversight and mentorship.
This balanced approach allows organizations to modernize operations while maintaining stability and institutional knowledge.
Many organizations are also exploring new ways to incorporate experienced professionals into their workforce. Remote and flexible work models now make it possible for retired or semi-retired professionals to continue contributing their expertise without traditional full-time roles.
These professionals can play an important role in helping organizations:
Preserve institutional knowledge. Veteran insurance professionals bring decades of industry experience that can guide decision-making and help train younger employees.
Support technology transitions. Experienced professionals can help teams adapt to new systems while maintaining underwriting discipline and operational quality.
Mentor and develop staff. Knowledge transfer remains one of the most important elements of workforce development. Experienced professionals can help cultivate the next generation of insurance leaders.
Provide flexible operational support. Organizations can bring in experienced professionals to support underwriting, claims, compliance, accounting and other critical functions during periods of growth or transition.
The Future of Insurance Work
The insurance industry is entering a period of sustained workforce transformation. Automation will continue to reduce clerical workloads and improve operational efficiency. At the same time, the industry’s demographic shift will increase the importance of experienced professionals who can guide these new systems and maintain strong underwriting discipline.
Organizations that rely solely on automation may find themselves vulnerable to operational fragility. Those that combine intelligent systems with experienced oversight will be better positioned to improve efficiency while protecting service quality.
In the end, the future of insurance will not be defined by technology alone. It will be shaped by how effectively organizations combine the power of AI with the judgment, expertise and professionalism that have always been the foundation of the industry.
When technology and human experience work together, the result is a stronger, more flexible and more resilient insurance organization.
Sharon Emek, Ph.D., CIC, is founder and CEO of WAHVE, a leading talent solution provider for the insurance industry.
