Start the New Year Right: Five Keys to Choosing the Right AI Tool and the Right Partner for Profitable Risk Management

Each year, your company starts with a clean slate. New goals, new objectives and a new strategy for getting there. Whether you’re looking to increase key investments in staff or technology or just redirecting those dollars into more efficient processes or identifying a vendor better aligned to your goals, the bottom line is still the same. Profitable growth. In this Blog post, we outline five practical criteria   to help organizations evaluate AI tools and partners that actually drive profitable growth, not just better reporting.

 

Whether you’re a carrier, consultant, MGA, captive, pooled risk group, or PEO, your challenge each year remains how to better manage and project risk, while growing your book of business. Some of those goals or obstacles have not changed from last year but your strategy and tools utilized need to be addressed and refined to reach your objectives in 2026.

 

Here are five key considerations in choosing the right tool and the right partner:

 

1. Get the right data to make accurate decisions.

Whether you use an in-house tool or a third-party solution, without the correct – and timely – data, you are lost.  Ask yourself and your team:

 

• Are you getting the detail for risk assessment that shows not just claims that have already occurred but anticipated claim costs in the future?
• Does your AI solution provide at least a 90% match rate on medical, Rx, Rx specialty and/or lab of the headcount provided in a census?
• Can your current tool fill the inevitable gaps in data that come with every census?
• If you answered no to any of these questions, you need to look for a new AI solution.
• Remember, a pivotal component to risk management is risk projection. You can’t change what was. You can change and impact what will be.

“Prior to partnering with Gradient AI, we could only look through the rear-view mirror at past claims data. Now we can look through the windshield to better predict costs our clients can expect to incur.”  

- Aaron MacDonald, chief strategy officer at Michigan Planners 

 

2. Make sure your AI solution evolves and provides the insight you need.

Innovation can be an overused term. And every company claims to be “an innovator.” How do you know you’ve partnered with the right AI provider?

 

First, are you getting the complete picture of risk and all its drivers or are you a victim of “black box underwriting?” Black box underwriting means the reasons behind the risk score are not easily explainable or transparent. Your AI partner should not only provide a risk score, but they should also be able to share the detail around that score which you can apply to the business case at hand.

 

For example, among numerous other data points, does your AI partner deliver:

• Top conditions
• Top drugs
• High-cost claims reporting
• Stop loss risk scores
• Condition flags

 

At Gradient AI, we’re constantly iterating and striving to improve our outputs. We were the first to provide access to medical, lab and prescription data and the first to provide actionable insights.

 

“We sought a tool capable of greatly enhancing our risk assessment efforts, especially in areas with limited or no detailed group-specific data. Gradient AI’s solution not only helped us make better-informed decisions but provided us with the critical detail of what is driving that risk. With other competitors’ models, that critical information was missing.”

- Jennifer Taylor, Director of Alternative Risk, Evolution Risk Partners (MGU)

 

3. Choose AI That Connects the Entire Risk Lifecycle.

AI offers clear advantages in speed, consistency, and analytical depth. However, realizing the benefits of AI in risk management requires more than simply adopting AI point solutions in isolation.

Organizations that use separate tools for new business underwriting, renewals, and population health often struggle to generate consistent, actionable intelligence. Fragmentation creates blind spots that limit both performance and scalability, including:

• Disconnected data and learning loops, preventing insights from being reused across the risk lifecycle
• Inconsistent pricing and decisioning, making outcomes harder to track and compare
• Missed changes in group risk profiles, such as new members or emerging health trends

To truly improve performance, you must move away from siloed processes and toward coordinated full-cycle workflows that align risk management across new business acquisition, population health management, and existing group renewals.

When evaluating AI solutions and partners, prioritize those that support integrated workflows and enterprise-wide risk intelligence—not isolated use cases. The right AI partner helps unify these workflows—ensuring insights flow seamlessly across the entire book of business.

4. Find a great partner, not just a great tool.

The right AI tool is important, but the right AI partner is essential. True value comes from a partner who is easy to work with, understands your business at a deep level, and helps turn data into decisions—not just dashboards.

A strong AI partner delivers value through:

• Consultative subject matter experts, not just technical expertise
• Provides access to underwriting and risk management experts who understand the challenges of your business.  
• Works alongside your team to improve speed, accuracy, and profitability in underwriting
• Takes the time to learn your underwriting philosophy, unique cases, and workflows

• The right people supporting the right data
• Assigns experienced support teams who know how to source, validate, and structure the data that actually matters
• Helps translate complex data into actionable underwriting insights
• Recognizes that data alone doesn’t solve problems—getting the right data does

• Solutions that meet you where you are
• Adapts to your organization’s position on the technology adoption curve
• Delivers practical solutions that fit your current workflows while enabling future growth
• Addresses your goals rather than forcing a one-size-fits-all approach

At Gradient AI, we see successful partnerships as more than just fair pricing. They’re built on taking the time to understand your business, the nuances of your risk decisions, and the processes that support them. This insight enables us to design solutions aligned with your objectives and challenges, instead of asking you to conform to a standardized approach.

“This is not meant to be a standalone underwriting tool. It is advanced decision support. Do your due diligence. Conduct your market research.  If you want to see where our competitors will be in the future, look at Gradient AI today.”

- Matt Weaver, Senior Sales Director, Gradient AI.

 

5. Change Management: where adoption succeeds or fails.

Change management is an art, not a science. How you introduce AI matters just as much as the technology itself. Successful adoption starts with aligning your people, processes, and goals, plus clearly communicating why change is happening and how it benefits your underwriting teams.

A strong change strategy focuses on your ability to:

• Assess readiness before you deploy
• Evaluate your staff, resources, and workflows with a change-readiness assessment
• Understand upstream and downstream impacts across underwriting, operations, and leadership
• Reinforce that AI supports underwriters, it doesn’t replace them

• Align the tool to your team and objectives

o  Adopt AI that fits your current capabilities and scales with your goals

o  Avoid forcing change for the sake of technology

o  Equip teams with tools that increase confidence and consistency in risk decisions

• Set clear expectations and outcomes
• Communicate why you’re adopting AI, or why you’re switching tools
• Define success in terms that matter, such as faster turnaround times, better decision support, reduced backlogs
• Managing risk, pricing right, and enhanced decision-making lead to better outcomes for your customers, your team, and your company.

The true value of AI is realized when change is introduced with clarity, purpose, and alignment, turning technology investments into lasting adoption and measurable results.

As you plan for the year ahead, the most successful organizations will rethink not just the AI tools they use, but how those tools fit into their teams, workflows, and long-term goals. When AI is implemented with purpose and supported by the right partner, it empowers underwriters to see risk more clearly, act more decisively, and deliver better outcomes across new business, renewals, and population health.

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