Five Sigma aims to disrupt insurance with smarter AI claims tech

Automation and artificial intelligence (AI) are no longer just incremental enhancements but core drivers of operational transformation in insurance. Five Sigma, an AI-native claims management technology company, is positioning itself as a key player in this value chain shift. With its AI-native Claims Management Platform (CMP) and Clive, its innovative AI Claims Adjuster, the company aims to supercharge claims processing by embedding artificial intelligence, automation, and data-driven decision-making at its core.

AI-driven claims: What Five Sigma is doing differently

Claims management has traditionally been manual-intensive and inefficient for insurers, Managing General Agents (MGAs), Third Party Administrators (TPA), and self-insured enterprises. Five Sigma aims to eliminate these bottlenecks with an AI-native claims platform designed for efficiency, automation, accuracy, and agility. Enterprise claims leaders are under pressure to integrate AI, reduce cycle times, and boost CX, but legacy systems make that nearly impossible. Five Sigma sidesteps the retrofit trap—delivering AI-native automation across the claims lifecycle without the integration nightmares typical of older platforms.

A key differentiator is Clive, Five Sigma’s AI claims adjuster, designed to automate routine functions such as First Notice of Loss (FNOL), triage, fraud detection, and documentation processing. While the company cites reductions in cycle times of up to 60% and processing costs by 35%, these gains depend heavily on the complexity of the claims environment and how well Clive integrates with existing systems.

Unlike many solutions that layer AI onto outdated workflows, Five Sigma is AI-native, offering Clive as a modular tool that can sit atop existing CMS infrastructure. This minimizes disruption and is expected to reduce the need for change management and process realignment.

Reported improvements include immediate time savings and cost reductions, faster settlements, and a better adjuster experience. These are encouraging, but success will vary depending on how insurers balance automation with the human expertise still required for nuanced or high-stakes claims.

Claims modernization with minimal disruption

Five Sigma’s impact is measurable and operational for insurers and self-insured enterprises struggling with speed, scale, and cost. Some examples are mentioned below:

• A self-insured enterprise made significant savings using Clive to analyze claims internally, avoiding costly external reviews and identifying litigable cases faster.
• An MGA focused on small business insurance reduced adjuster review time from 30–60 minutes to around 10, with Clive generating instant summaries of key claim details.
• A US pet insurer leveraged Clive to enable Straight-through Processing (STP) for vet bills, cutting claim cycle times by over 90%.

Automation isn’t a silver bullet: The hidden friction behind frictionless claims

Several critical challenges remain for insurers considering AI adoption in claims. Regulatory compliance remains a key concern, as automated decisions must meet strict legal and consumer protection standards. The risk of bias in AI models is another important factor—machine learning systems reflect the data they’re trained on, and inherited biases can lead to inconsistent assessments or reputational risks.

Beyond compliance, the complexity of claims itself adds friction. While AI can efficiently handle straightforward cases, more nuanced scenarios, such as disputed liability, ambiguous coverage, or emotional customer situations, still require human judgment. Many insurers are taking a cautious, phased approach, starting with narrow use cases such as automating the first notice of loss or enriching data during validation.

Even with Five Sigma’s low-disruption model, enterprise-wide adoption is not plug-and-play. It requires thoughtful process redesign, adjuster upskilling, and robust change management to ensure that AI enhances claims operations without unintended consequences.

The quiet advantage: Five Sigma’s low-disruption, high-impact approach

Five Sigma presents a strong case for insurers seeking a scalable, AI-powered approach to claims management. The ability to deploy AI adjusters without disrupting existing CMS infrastructure makes it an attractive option for enterprises looking to accelerate efficiency, reduce costs, and enhance decision accuracy. With direct impacts on claims cycle times, settlement speed, and operational costs, AI-driven claims automation is no longer a question of if but when.

However, AI in claims is not a pre-configured solution. A strategic approach must be taken to ensure that AI is governed, monitored, and integrated with human expertise to maintain compliance, fairness, and customer trust.

The Bottom Line: Five Sigma presents insurers with a compelling opportunity to modernize claims management without disrupting existing operations.

Five Sigma is not just digitizing claims but fundamentally trying to reshape the claims process through AI-driven automation. The potential upside for large insurers and enterprises is substantial: higher efficiency, lower costs, and improved scalability. However, AI-led claims processing also comes with risks, particularly around compliance, bias, and the limits of automation in complex claims scenarios. Five Sigma leverages Google Cloud, adheres to its strict data protection and privacy standards, and implements its know-how to mitigate many of these risks.

Enterprises that succeed in modernizing claims will blend AI-powered systems with structured governance and human oversight. The gains are too significant to ignore- reduced costs, faster settlements, better customer experience, and scalable operations.

But success requires bold moves now. Enterprises must stop retrofitting legacy tech and start building and adopting modern and effective claims-handling processes.