Prior initiatives led by others largely emphasized theory and incremental change but were inadequately engineered for real‑world application. The Surety Blueprint is outcome-driven roadmap that aligns processes, technology, and stakeholders. It outlines each crucial component, offers structured solutions, and fosters collaboration.

Technology initiatives in the Surety industry have primarily relied on financing from Insurance companies. That model has repeatedly faltered when politics and the protection of self-interests slow momentum. Alignment becomes impossible, and the effort collapses when funding or executive sponsorship wanes. SuretyScience takes a different approach - backed by private equity and led by team of industry veterans with deep experience balanced across Surety operations, underwriting, and technology.

Extensive legal research has been conducted to establish a compliant path forward. SuretyScience is structured as an Insurance Support Organization, designed to mitigate antitrust concerns that can arise in collaborative initiatives owned or primarily funded by insurance companies, rather than by an independent company.

“Surety has reached an inflection point. Long standing processes and methods are rapidly losing relevance as technology continues to advance”, said Jeff York, CEO & Founder of SuretyScience. “Artificial intelligence, robotic process automation, and advanced analytics cannot be achieved unless the barriers to common standards, uniform data, and programmatically consumable information are eliminated.”

SuretyScience invites everyone to join its movement by signing the petition for universal Surety standards. By supporting this initiative, stakeholders across industries can help drive the adoption of robust guidelines that protect the interests of all participants in the new digital Surety economy.

The potential for artificial intelligence to transform underwriting workflows has caught up to the surety bonding industry. But it has also led to concerns about job security as a new survey by Lance Surety Bonds found 41% of surety professionals are worried about roles being replaced.

“It’s really a combination of concerns. There’s the obvious one of AI replacing jobs, but there’s also uncertainty around what happens when technology becomes the main decision maker,” Eric Weisbrot, digital marketing manager, Lance Surety Bonds, said.

He noted that alongside concern about job loss, many insurance professionals are “concerned about “overreliance on the technology and the lack of clear accountability if something goes wrong.”

In his view, the underlying issue is more about humans being removed from the loop and AI overshadowing human judgement.

“Once underwriting decisions start relying heavily on algorithms, questions about transparency and bias quickly follow. The real fear is not just job loss, but losing human judgment in the decision-making process. When real financial consequences are involved, that concern is understandable,” Weisbrot said.

However, the survey emphasized that AI itself is not the enemy. In fact, three out of five bonding professionals said they have already implemented automation in their bonding process and most said it can positively impact their roles.

As such, Weisbrot said balance between workflow modernization and workforce upskilling is key to navigating this new normal.

The case for modernization

Lance Surety Bonds’ survey confirmed what many industry leaders have already warned —- companies no longer have the luxury of avoiding AI in an era with increasing demand for technology-driven solutions.

“What’s important to keep in mind is that client demands are evolving faster than ever,” Weisbrot said. “Fifty-six percent of surety bond pros are saying it’s becoming more common for their clients to expect a digital-first experience. While that’s certainly an emerging trend in surety bonds, it’s really a trend happening across all types of insurance products.”

Surety bonding and risk management professionals surveyed also expressed confidence in AI’s capabilities, with 43% trusting it to be more accurate than traditional models, 58% saying they believe it can enhance underwriting roles and 66% saying going digital is key to staying competitive.

However, at the same time, one in five surety bonding professionals said their work is still manual — and most believe it’s causing their company to lose business. Fifty-nine percent of respondents said their firms are “losing money and speed because these more ‘old-school’ methods, like paper or fax, can be costly and time-consuming.”

Meanwhile, 70% of small owners surveyed said they would defect from their current surety bond provider “immediately” if they could get bonded in less than 10 minutes using AI instead.

“In an era where speed is crucial and businesses are having to do less with more, every second seems to count,” Weisbrot said.

Outpacing human skill

Concern about job loss is one of the potential downsides of AI being perceived as so effective, as indicated by the results of the study.

“If AI is already earning that trust and getting buy-in to outperform human judgment on assessing risk, one of the core skills of underwriters and advisors, then these roles built around human evaluation and processing are certainly feeling the pressure,” Weisbrot explained.

However, he believes the risk isn’t a simple matter of mass redundancy but a more nuanced concern about role transformation. While the term “skills gap” never appears in the research, he believes the results imply this could be a potential factor at play.

“The concerns around overreliance on algorithms and a lack of transparency in AI decisions signal that while some are adopting these tools, they still don’t fully understand them, which is a skills gap in itself,” Weisbrot said.

“Half of those we surveyed admitted they feel pressured to modernize, whether it’s due to competition from insurtech firms or internal bottlenecks. The pressure without capability is the perfect environment for a skills gap to take hold.”

Technological balance

The solution lies in integrating new technology while advancing AI literacy, according to Weisbrot, who emphasized that outdated workflows are costing companies who choose to do nothing.

“While leaders should invest in AI tools, you must invest in actual training as well; you can’t just integrate these new tools and expect your team to ‘figure it out.’ Build your staff and their confidence up by allowing them to upskill or train on these new technologies, and you should see an increased confidence in interpreting, auditing, and overriding AI decisions,” he said.

But individual professionals also have a role to play, he added, in learning to work with technology rather than fear it or see it as competition.

“Our research suggests pros best positioned for success are ones who can work alongside AI rather than go head-to-head with it. Combine speed and efficiency from these tools with your relationship management, ethical judgement and contextual knowledge that algorithms can’t replicate,” Weisbrot said.

The NAIC Big Data and Artificial Intelligence (H) Working Group has issued important updates about its AI Systems Evaluation Tool and related pilot program. Following discussions on February 9 and 17, the working group announced that California has joined the pilot, increasing total participation to 12 states. The pilot began on March 2, 2026, and will run through September 2026. Below are key developments that insurance industry participants should be aware of.  

Background: The Rise of AI in the Insurance Industry

The rapid growth of big data and the adoption of artificial intelligence and machine learning (AI systems) are significantly transforming the insurance industry. These technologies may provide substantial benefits to both insurance companies and consumers by enabling the development of innovative products, improving customer services, simplifying and automating processes, and increasing efficiency and accuracy. However, without strong governance and effective controls, the use of AI systems may lead to negative consumer outcomes or threaten the financial stability of insurance companies. Insurers are responsible for managing the risks associated with developing and implementing AI systems and must show regulators that appropriate risk-based oversight mechanisms are in place and working effectively.

Recognizing these dynamics, the NAIC’s Innovation, Cybersecurity and Technology (H) Committee tasked the Big Data and AI Working Group with developing tools that enable regulators to continuously identify and evaluate risks related to AI systems. This initiative addresses both financial and consumer risks specifically arising from insurers’ use of AI systems. The AI Systems Evaluation Tool is designed to complement existing market conduct, financial analysis, and financial examination procedures for reviewing AI systems. These optional exhibits help regulators determine how extensively a company uses AI systems and whether additional analysis focused on financial and consumer risks is necessary.  

California Joins Pilot Program for AI Systems Evaluation Tool

The working group announced an expansion of the pilot program, which now includes 12 states: California, Colorado, Connecticut, Florida, Iowa, Louisiana, Maryland, Pennsylvania, Rhode Island, Vermont, Virginia, and Wisconsin. California joined most recently, following earlier announcements about Louisiana and Maryland.

The pilot will enable regulators to field-test the AI Systems Evaluation Tool. Participating states will use the tool for various tasks, including market conduct exams and reviews, financial analysis, and financial examinations. The initiative will involve insurance companies across different lines, such as property/casualty, life, and health insurance.  

Pilot Objectives and Implementation

The pilot is designed to accomplish several key objectives. Primarily, regulators want to determine whether the tool helps insurers clearly explain their AI governance systems, while also assisting regulators in better understanding how companies use AI systems and implement standard governance practices. The pilot will also support ongoing improvement and development of the tool itself, help create long-term recommendations for market conduct and financial risk assessment review processes, and identify what additional regulator training may be needed in the future.

During the pilot, participating states will concentrate on domestic insurers and implement a principle of proportionality. This means regulators will prioritize examining high-risk AI systems that could cause serious consumer or financial issues, while paying less attention to low-risk back-office systems.  

Updates in AI Systems Evaluation Tool Version 4.0

Version 4.0 includes several key updates:

Clarifying that the tool does not create new requirements for AI governance risk assessments

Simplifying prior direct/indirect impact references

Reinstating references to unfair trade practices for model testing inquiries

Adding a new data field in Exhibit D for “Reasonable Accommodations or Policy Modifications”

Remaining issues under review include materiality and risk assessment definitions, the inclusion of generalized linear models, and terminology for defining the scope of model inclusion.  

Pilot Framework and Timeline

Information requested through the tool will be protected under the confidentiality rules of the administering state. Participating states will receive training and coordinate through monthly calls to prevent duplicative requests. Regulators will provide public updates at each NAIC national meeting. From March to September 2026, pilot states will meet monthly to share progress. The tool will be updated based on pilot feedback in September–October 2026 and re-exposed for public review, with adoption expected at the NAIC fall meeting in November 2026.

As artificial intelligence reshapes the global economy, insurers face a fundamental shift in how risk is created, measured, and transferred. Speaking at an event hosted by MS Re during Miami Reinsurance Week, futurist Amy Webb outlined why the next decade will demand a new approach to risk.

The session, hosted by MS Re and attended by almost 200 insurance professionals, reflected growing industry focus on how emerging technologies could reshape risk over the coming decade.

The applications “may be a threat to some consulting businesses of insurance brokers though we view them as force multiplier rather than an existential threat,” he added.

Insurify’s app uses ChatGPT to compare auto insurance rates using details about the vehicle, the client’s credit history, driving record and other inputs. The company said the app launched on Feb. 3.