In conversations across major insurance industry conferences this spring, ISI team members heard a consistent theme from property and casualty (P&C) carriers and MGAs: organizations are reducing operational complexity to improve efficiency, strengthen data quality, and apply AI with greater confidence.
For many insurers, that means:
- Fewer systems to manage
- Cleaner, more consistent data
- More connected workflows across underwriting, claims, and operations
- A stronger foundation for decision-making and AI adoption
Fragmented systems make it harder to move quickly, govern effectively, and create a reliable view of the business.
One System, One Source of Truth
At PLUS (Professional Liability Underwriting Society) and the MPL (Medical Professional Liability) Association Conference, platform consolidation was a frequent topic. The pain points are familiar: disconnected systems create data gaps, manual reconciliation consumes underwriter and adjuster time, and critical information lives in too many places to be fully useful.
This is especially important in professional liability, where decisions depend on complex submissions, detailed documentation, and careful risk evaluation. A trusted platform foundation connects policy, claims, billing, accounting, reinsurance, and reporting workflows into a more consistent operating environment.
For ISI, this has long been a core focus. ISI Core supports the full insurance lifecycle on a unified platform, including professional liability and specialty insurers that require accuracy, configurability, and governance.
AI Embedded Where the Work Happens
Carriers are not just asking what AI can do. They are asking whether it can improve work inside existing operations and deliver measurable value.
Several carriers described practical AI needs, including:
- Supporting triage and prioritization of submissions
- Ensuring applications and submissions are complete and accurate before underwriting review
- Reducing manual effort caused by missing or inconsistent information
- Identifying high-risk claims that could results in nuclear verdicts as well as other red flags earlier in the process
This is where ISI AI fits naturally into the broader platform discussion. Rather than treating AI for insurance as a separate layer, ISI AI agents support submission handling, underwriting review, and decision support within connected workflows. The value is not simply faster extraction. It is accurate, source-validated data teams can trust and act on.
A Legitimate Caution
Not every voice was fully confident in AI adoption. Some attendees raised concerns about using AI to review complex professional liability applications and claims, with worries that AI could introduce gaps that increase litigation or claims exposure.
That concern reinforces an important point. In complex lines, AI should inform human judgment, not replace it. For ISI, that is a guiding principle. ISI AI keeps experts in the loop by supporting underwriting judgment with accurate, traceable, and source-validated information rather than replacing underwriter experience and accountability.
What Leaders Should Consider
The message from these conferences was clear: insurers need simpler ecosystems, trusted data, and AI that can support better decisions without adding risk.
That also puts ROI under greater scrutiny. Capgemini’s 2026 World Property and Casualty Insurance Report found that 55% of P&C insurers reported no clear ROI on AI initiatives, reinforcing the need to connect AI investments to measurable outcomes.
For leaders, the key questions are:
- Are systems connected enough to support reliable data and workflow visibility?
- Can AI outputs be traced back to source information?
- Can teams measure where time is saved, quality improves, and risk is reduced?
- Are investments showing measurable impact through reduced manual effort, faster review cycles, improved data quality, and earlier risk identification?
This is where accuracy becomes central to ROI. With ISI AI’s Submission Agent and Underwriting Agent achieving 98%+ accuracy, carriers can more clearly connect AI to operational value through less manual validation, faster review cycles, and greater confidence in the data behind underwriting decisions.
The opportunity now is to simplify the foundation, then apply AI where it can deliver practical value. For professional liability insurers, that means pairing trusted core workflows with AI that supports expertise and keeps accountability where it belongs.
