Insurance has always been built around managing risk. However, as AI ever increasingly reshapes the industry, InsurTech ventures face a particular challenge: they are expected to move with the speed of SaaS while also operating inside one of the most regulated industries.
The opportunity is significant.
McKinsey estimates that GenAI could unlock $50 billion to $70 billion in insurance industry revenue, with potential impact across marketing and customer operations, among other areas.
At the same time, insurers are moving toward agentic AI, which McKinsey describes as an emerging technology capable of managing increasingly complex, end-to-end workflows.
For Rick Folgmann, COO of Get Covered, the challenge goes beyond just adopting the latest technology.
In InsurTech, growth without discipline isn’t momentum—it’s risk, said the executive.
Get Covered replaces fragmented risk workflows with a single system for property management portfolios.
From Folgmann’s perspective, scaling an InsurTech requires building the operational foundations alongside the technology itself.
Building for scale before it becomes urgent
Insurance operations involve interconnected processes including eligibility, enrollment compliance and more.
As companies add customers, markets and carrier relationships, managing those processes can become increasingly difficult.
Folgmann argues that companies should address that complexity before growth makes it harder to change.
According to the executive, at Get Covered the company is focused on building repeatable, scalable workflows early, while the organization is still flexible enough to change.
That approach mirrors a broader shift in how insurers are thinking about AI. McKinsey’s 2025 report found that insurance companies that have successfully integrated AI across business domains have achieved 10% to 20% improvements in new-agent success and sales conversion rates, 20% to 40% reductions in customer onboarding costs, and 3% to 5% improvements in claims accuracy.
But those gains require more than adding AI tools to existing processes. McKinsey argues that insurers need to redesign workflows and operating models around the technology rather than simply layering AI onto legacy processes.
That is particularly relevant to InsurTech ventures, where rapid expansion can expose weaknesses in compliance and security.
For Folgmann, licensing, filings, disclosures, audits and regulatory responses need to become part of everyday operations rather than separate activities addressed after a company has scaled.
When compliance is operationalized correctly, it becomes an enabler, allowing faster market expansion, stronger enterprise partnerships, and deeper trust with regulators and carriers.
Growth without losing control
The balance between speed and control becomes more important as AI takes on a greater role in insurance workflows.
McKinsey notes that insurers are already using AI across areas including underwriting, claims and distribution, while emerging agentic systems could eventually manage multiple stages of processes with human oversight.
That creates another operational question: how much risk can companies automate while still maintaining visibility into what their systems are doing?
Folgmann’s answer is not to treat risk management as a brake on expansion.
According to Rick, risk management isn’t about slowing the business down. It’s about ensuring the business survive.
The same principle applies to customer experience. At an insurance technology company, the final experience depends on much more than the software itself. Support operations, service-level agreements, escalation paths and internal coordination all contribute to what customers ultimately receive.
Customer experience is often framed as a product or support issue. In reality, it’s the output of dozens of operational decisions. That puts the COO role closer to the center of an InsurTech’s growth strategy than its traditional back-office perception might suggest.
As AI moves from isolated experiments into core insurance workflows, the companies that benefit most may not necessarily be those that adopt it first.
They may be the ones that can build the processes, controls and operating discipline needed to scale it without compromising compliance, security or customer trust.
