Last week, I attended the Excellence in Insurance conference in Carlsbad, California, hosted by Insurity. The event brought together executives, MGAs, brokers, and technology leaders from across the P&C industry to discuss how insurers can adapt to disruption — from AI in insurance and automation to climate risk and compliance.
What struck me most was not the sophistication of the AI demos or the size of the R&D budgets. It was how many insurers — even large ones — are still struggling with the basics of data management.
The truth is simple: AI won’t transform the insurance industry until insurers fix their data foundation.
The Reality: Excel Still Runs the Insurance Industry
Even in 2025, Excel remains one of the most widely used “core systems” in insurance. Many underwriting, pricing, and risk analysis processes still depend on workbooks shared by email or stored on local drives.
This legacy dependence has created an entire micro-industry of solutions trying to modernize Excel rather than replace it. One company, Coherent, has even built software that can convert an Excel sheet into an API — essentially turning decades of institutional spreadsheets into reusable data services.
It’s a clever workaround, but it also highlights a deeper challenge: insurers are still bound by legacy workflows and fragmented technology ecosystems.
Even among modern vendors, complexity reigns. Insurity, for example, offers a family of platforms — SureMGA, Sure Commercial, Sure Underwriting, Bridge, and others — each addressing a specific business function. While powerful on their own, these systems create vendor sprawl when deployed together.
Vendor sprawl happens when a company uses multiple, disconnected software platforms that don’t share data easily.
For insurers, vendor sprawl means data fragmentation: policy data lives in one place, claims data in another, and underwriting data somewhere else. Reporting becomes cumbersome, cross-system analysis is difficult, and every new regulatory requirement or executive request requires yet another manual data extract.
The complexity multiplies when an MGA uses tools from multiple vendors. We’ve seen this firsthand at Data-Sleek. One of our insurance clients faced this exact challenge — and our team helped them integrate data from multiple policy and claims systems into a unified data warehouse.
The real frustration is that not all vendor platforms offer APIs or easy ways to push data out. In an age when most SaaS applications offer one-click connectors to modern data warehouses, insurance software often remains a walled garden.
That’s not just a technology problem — it’s a strategic one.
The Rush to AI: Fast Isn’t Always Smart
A major theme at the conference was AI adoption — and the race to implement it quickly. The problem is that many insurers are rushing into AI without a clear data or AI strategy.
It reminded me of what happened during the early days of business intelligence. Companies built flashy dashboards and hundreds of reports, but few were used or trusted. The same pattern is emerging with AI: speed over strategy, pilots over planning.
During one session, the moderator asked the audience:
“If you had a $1 million budget to automate something with AI, what would you do?”
Very few people had a clear answer. That moment said it all. The appetite for AI is strong, but the clarity on why and how to use it is missing.
AI automation is still in its infancy in insurance. Many companies are experimenting — but without clean, governed, well-structured data, even the best models will underperform.
The reality is that companies with a clear data and AI roadmap will take longer to implement, but they’ll outpace the competition in the long run. Those who rush will spend the next few years fixing or replacing their initial investments.
The Good News: Innovation Is Happening
Despite the data and strategy gaps, there’s genuine momentum toward modernization.
- Document AI is evolving rapidly. One company, BandAI, is achieving impressive accuracy in document ingestion — even with scanned or handwritten files. This could eventually streamline submission processing, claims, and audits.
- Excel modernization is getting attention. Companies like Coherent are helping insurers bridge the gap between legacy spreadsheets and cloud data architectures.
- Insurity is investing $50 million in R&D focused on AI, which signals serious intent to address customer pain points.
- I even saw a preview of a prototype using n8n — an automation tool — integrated within Insurity’s platform. It could automatically detect an event (such as a change in business ownership on the web) and trigger a new underwriting workflow. That’s the kind of practical, data-driven automation that can transform operations when paired with the right data strategy.
And while many companies are still defining their AI frameworks, some forward-thinking insurers are approaching the problem in layers:
- Internal layer – empowering employees with AI tools to improve efficiency.
- Vendor layer – embedding AI within software platforms.
- Client layer – enhancing the customer experience with predictive insights.
This layered approach is promising — and aligns perfectly with the role of a modern data partner.
Predictive Analytics: The Industry’s Next Battleground
One of the sessions that stood out to me focused on predictive analytics. Insurity described this evolution as “Predict: From Insight to Impact.”
Here were four key challenges they highlighted — all deeply tied to data:
1. Shrinking Premium Pools & Rate Pressure
Global premium growth is slowing, particularly in mature markets. Economic volatility and affordability concerns are shrinking the pool of insurable risk, forcing insurers to find new sources of profitable growth.
2. Commercial Auto Profitability Crisis
Rising claims severity, supply chain disruptions, and inflation are squeezing margins. Carriers need data-driven underwriting and operational efficiency to stay competitive.
3. The Race for Relevant, Differentiating Data
Insurers are aggressively pursuing data strategies that go beyond traditional sources. The winners will be those who can harness ecosystem partnerships, unstructured data, and AI-powered insights.
4. Underwriting and Claims Are Being Rewritten
AI and GenAI are shifting workflows from reactive to predictive. The industry is moving from “detect and repair” to “predict and prevent.”
As one speaker put it, “Underwriters are being asked to do more with less — and they’ll need better data to do it.” The message was clear: data will define competitive advantage.
The Real Lesson: Data First, AI Second
If there’s one takeaway from the conference, it’s this:
The companies that will win in the AI era are not the ones that move the fastest — they’re the ones that prepare the best.
AI implementation without a data foundation is like building a skyscraper on sand. The foundation must come first: unified data architecture, governance frameworks, and integration across core systems.
At Data-Sleek, we’ve seen this pattern across industries — including insurance. Companies that start with a solid data strategy gain:
- A single source of truth across policy, claims, and underwriting data.
- Faster, more accurate compliance reporting (NAIC, state-level).
- The ability to scale predictive models and automation.
- Confidence in data lineage and governance.
Once those foundations are in place, AI isn’t just possible — it’s powerful.
Looking Ahead
The insurance industry is standing at a crossroads. The next wave of innovation will not come from a new AI model or another point solution.
It will come from insurers that build strong, compliant, connected data ecosystems — the kind that make AI implementation truly effective.
Technology vendors will keep evolving, but insurers need partners who can see the whole picture — from architecture to analytics, from governance to growth.
At Data-Sleek, we believe that’s where the real opportunity lies: helping insurers turn fragmented data into strategic advantage.
Final Thought
The Excellence in Insurance conference was a reminder that progress doesn’t come from rushing forward — it comes from building wisely.
AI will reshape insurance, but only for the companies that get their data house in order first. The future isn’t about replacing people with AI; it’s about empowering people with better data.
If your organization is navigating legacy systems, vendor sprawl, or unclear data strategy, now is the time to act.
Data-Sleek helps insurance companies modernize their data environments — from data strategy and warehousing to AI readiness.
