Startups are rushing to build AI tools to automate workflows across finance, software engineering, and nearly every other field. One industry that often gets overlooked but is seeing its own AI revolution is the insurance industry. Notorious for manual workflows, 100+ page documents, and poor customer service, many VCs believe the industry is ripe for AI disruption.

AI systems can now analyze massive amounts of data and make decisions in real time for tasks like underwriting, claims processing, fraud detection, and customer support. This shift is enabling insurers to reduce costs, speed up service, and offer more personalized products, while redefining how risk is assessed and managed. As adoption grows, the industry is moving toward a future where human oversight guides AI, rather than executing every step manually.

Global VC investment in AI companies saw remarkable growth in 2024, as funding to AI-related companies exceeded $100 billion, an increase of over 80% from $55.6 billion in 2023, according to PitchBook data. Nearly 33% of all global venture funding was directed to AI companies, making artificial intelligence the leading investment theme in 2024, according to CB Insights data.

Within this broader AI funding boom, a specific battleground has emerged: the fight to automate the insurance industry’s most persistent productivity drain. The numbers tell a compelling story. The global artificial intelligence (AI) in insurance market size is projected to hit around USD 141.44 billion by 2034 from USD 8.13 billion in 2024 with a CAGR of 33.06%, per Precedence Research analysis.

AI remains a top priority for business leaders worldwide in 2025, with a strong focus on generating tangible results, according to BCG’s survey of C-suite executives. Perhaps more telling is what's happening right now: 78% of respondents said their organizations planned to increase budgets for tech spending in 2025.

While the insurance industry generates $400 billion dollars in annual brokerage revenue, according to IBISWorld industry data, a staggering reality lurks beneath these impressive figures: more than one-third of that revenue - over $130 billion dollars, vanishes into manual, low-value tasks that modern technology could eliminate tomorrow, per industry analysis.

The scale of this waste becomes clearer when examined at the individual level. The average insurance broker spends over six hours daily on administrative tasks: manually entering policy data, building complex spreadsheets, analyzing dense documents, and navigating legacy systems that often predate the internet.

This resistance to change is creating enormous opportunities for companies willing to tackle the productivity crisis head-on. Recent funding activity suggests investors have taken notice. While established insurtech companies have historically focused on consumer-facing applications or specific vertical solutions, a new wave of startups is attacking the broader operational inefficiencies that plague the industry.

One company building for the industry is Coverflow, an early-stage startup that leverages proprietary AI models to ingest, analyze, and extract critical data from any policy document. The company claims its technology can save brokers 6 hours a day, a number that it says scales to 1,500 hours annually.

Coverflow was founded by Matthew Fastow, a Princeton graduate and AI engineer who realized the massive opportunity to build AI applications for overlooked industries. He started by going door to door to dozens of insurance brokers in San Francisco and asking them about their pain points and most time consuming tasks.

"By harnessing AI to automate every step, from policy ingestion and analysis to system updates and proposal generation, we're empowering teams to reclaim hours out of their day and double down on client relationships and business growth," Fastow said in a statement.

The company announced $4.8M in seed funding led by AIX Ventures, along with Founder Collective and Afore Capital. The company says it has 400 users across 21 brokerages already using their platform.

InsurTech startup 1Fort has raised $7.5 million in a funding round to enhance the AI capabilities of its platform for business insurance, with the New York AI startup securing funding to streamline commercial insurance for small businesses with its broker-focused platform that cuts paperwork from hours to minutes.

1Fort, the AI platform for business insurance, announced it raised $7.5 million in an oversubscribed funding round led by Bonfire Ventures, bringing its total funding to $10 million. The round also included contributions from Draper Associates and other investors.

The company focuses specifically on the commercial insurance market for small businesses, addressing what it calls America's 24 million underprotected small businesses. 1Fort's platform aims to become the "operating system" for commercial insurance, helping brokers automate applications and reduce manual work.

Gradient AI secured $56 million to enhance insurance industry efficiency, representing one of the larger funding rounds in the AI insurance space. The company focuses on specific insurance functions such as claims processing and underwriting, taking a more targeted approach than comprehensive workflow platforms.

Founded in 2010, WorkFusion has raised $121 million in venture funding. The startup offers an AI platform called the Intelligent Automation Cloud, which the company claims can help insurance carriers improve their claims and appeals processes along with their KYC infrastructure.

WorkFusion represents the more established players in the AI insurance space, demonstrating that both early-stage startups and mature companies are competing for market share in this rapidly evolving sector.

The AI insurance automation market has attracted a diverse field of competitors, each taking different approaches to the productivity challenge:

: Established insurance software companies have layered AI features onto existing platforms. These solutions often excel at specific tasks but typically require extensive integration and customization, limiting their appeal to resource-constrained brokerages.

: Companies like Lemonade have pioneered AI-first insurance models, demonstrating the technology's potential when properly implemented. However, their focus remains primarily on direct-to-consumer insurance rather than broker operations.

: Companies like Gradient AI focus on specific insurance functions such as claims processing and underwriting, while others target particular market segments or use cases.

: The newest entrants, including companies like Coverflow and 1Fort, are taking a comprehensive approach—focusing specifically on end-to-end broker productivity rather than trying to solve every insurance problem at once.

Out of the AI insurance startups in the United States, 144 startups are funded, with 78 having secured Series A+ funding, and 4 achieving unicorn status. Over the past 10 years, an average of 17 new companies have been launched annually, reported by Tracxn.

Despite billions in investment, most insurance AI initiatives have failed to deliver transformational productivity gains. Three key factors explain this pattern:

: Most existing AI tools require months of IT integration, custom configuration, and extensive staff training. For an industry built on relationship-driven service, these lengthy implementations often fail before they deliver value.

: Many solutions require extensive manual setup, document templates, and ongoing maintenance. When every policy and carrier uses different formats, template-based approaches quickly become unmanageable.

: Point solutions that automate one task while leaving ten others manual often create more work than they eliminate. Brokers need comprehensive workflow automation, not piecemeal tools that require constant switching between systems.

What's different about the current wave of insurance AI? Three technological advances are converging to make comprehensive automation finally viable:

: Modern AI can now understand unstructured insurance documents without templates or manual tagging. This breakthrough eliminates the biggest historical barrier to automation—the endless variety of policy formats and carrier-specific documentation.

: Cloud-based platforms that require no IT integration allow brokers to deploy automation tools immediately rather than waiting months for technical implementation. Companies like Coverflow claim their web-based platform requires "zero IT integration" and can be deployed without touching a line of code.

: Rather than automating individual tasks, new platforms can handle complete workflows from document ingestion through system updates and client communications.

One VC leading that charge is AIX Ventures, which recently raised $202 million for its second fund and invests exclusively in AI startups, including Coverflow. The firm was created in 2021 by some of the world's leading AI researchers and operators including Richard Socher, Shaun Johnson, and Chris Manning. The fund has backed several AI unicorns including Perplexity, Hugging Face, Weights & Biases, and others.

The fund recently hired Jason McBride, a former investor at Microsoft's M12 Ventures to lead investments in the application layer with a focus on legaltech. McBride believes legal, insurance, and other industries that rely on paperwork, hourly billing, and manual workflows will see the most automation in coming years.

"Coverflow addresses some of the insurance industry's largest bottlenecks caused by manual and paper workflows," said Jason McBride, a Partner at AIX Ventures. "By saving brokers 6+ hours each day, Coverflow is poised to become the operational backbone for every broker."

The financial pressure on insurance brokerages is intensifying. Rising labor costs, increasing client expectations, and competitive pressure from direct-to-consumer insurers are squeezing traditional brokerage margins. Brokers who can't dramatically improve productivity will struggle to remain competitive.

According to BCG analysis, considerable efficiency gains of 20% to 30% can be achieved through streamlined documentation, with even greater savings generated from reducing assessor-related spending using end-to-end automated claims appraisals.

Several market dynamics are accelerating AI adoption beyond mere productivity considerations:

: By automating routine tasks, AI allows brokers to shift their focus towards building client relationships, fostering a more personalized and engaging customer experience. This shift is particularly valuable as brokerages struggle to attract and retain top talent willing to perform manual administrative work.

: Modern business clients expect faster response times, more accurate documentation, and seamless digital experiences. Manual processes increasingly fail to meet these expectations.

: As some brokerages achieve dramatic productivity gains through automation, others face deteriorating competitive positions. The productivity gap between automated and manual operations will only widen as AI capabilities improve.

According to McKinsey's latest analysis, instead of focusing on the 92 million jobs expected to be displaced by 2030, leaders could plan for the projected 170 million new ones and the new skills those will require. This perspective is particularly relevant for the insurance industry, where AI is expected to augment rather than replace human expertise.

The insurance industry stands at an inflection point. The question isn’t whether AI will transform broker operations; it's whether existing brokerages will lead that transformation or be disrupted by AI-native competitors.

Early adopters are betting on transformation from within, using AI to amplify human capabilities while focusing staff on higher-value client relationship building. Companies like Coverflow and 1Fort are positioning themselves as the infrastructure layer for this transformation, enabling brokers to eliminate manual workflows without disrupting client relationships.

There are estimates that AI could add 14%-or roughly US$15.7 trillion - to global GDP by 2030, according to PwC research, suggesting the productivity gains from AI adoption will be massive and permanent. In insurance, this creates a winner-take-all dynamic where early automation leaders may capture disproportionate market share.

The $130 billion in annual waste represents more than inefficiency; it's the prize in a race to define the future of insurance distribution. Companies that successfully automate their operations while competitors struggle with manual processes will gain compound advantages that may prove insurmountable.

As BCG notes, workers' confidence in GenAI has grown in the past year, though so has their fear of job loss. This dynamic creates both opportunity and challenge for insurance companies implementing AI solutions.

The window for gradual transformation may be closing faster than many industry participants realize. As platforms like Coverflow and 1Fort demonstrate the feasibility of comprehensive workflow automation, the competitive pressure on manual operations will intensify dramatically.

Companies plan to invest more in GenAI in 2025 than last year—even as they realize that the intuitive, friendly feel of GenAI masks the discipline, commitment, and hard work required to introduce these technologies into the workplace.

The age of AI-powered insurance isn't coming—it's here. The only question is which companies will control the future they're creating. With established players like WorkFusion competing against nimble startups like Coverflow and 1Fort, and with major consulting firms like McKinsey and BCG advising on AI transformation strategies, the insurance industry is experiencing a fundamental shift that will determine market leaders for the next decade.

The convergence of technological capability, market pressure, and available capital has created the perfect storm for AI adoption in insurance. Companies that move quickly to implement comprehensive automation solutions will likely capture disproportionate market share, while those that delay risk being left behind in an increasingly automated marketplace.