There’s no question that Artificial Intelligence (AI) is revolutionizing insurance by processing claims faster, generating more accurate price quotes, and catching fraud that would slip by human eyes. All that shiny technology comes with significant responsibilities.
When AI gets it wrong, however, real people pay the price. That’s why the conversation about ethical AI in insurance is more important than ever.
It boils down to three key principles: fighting bias, maintaining transparency, and being accountable.
Bias: When AI Inherits Our Human Flaws
AI systems don’t come into the world knowing how to be fair. They learn patterns from historical data, and if that data reflects biased decisions or unequal treatment, AI can perpetuate those biases.
Imagine an AI-powered underwriting tool that has learned from decades of data that specific ZIP codes were charged more simply because of who lived there rather than based on actual risk. If no one checks for bias, the AI might unfairly charge people in those areas just because that’s what it “thinks” is normal.
The insurance industry has a responsibility to implement algorithms that do not reinforce old injustices or create new ones. The results should be:
- Testing AI systems for bias before they go live
- Continuously monitoring decisions to spot patterns of unfairness
- Using diverse, representative data when training AI.
Insurance is supposed to protect people, not punish them based on things like race, gender, or ZIP code.
Transparency: Shedding Light on the Black Box
One of the biggest complaints about AI is that it can feel like a black box. How did it decide to deny your claim?
Why is your premium suddenly higher? When an algorithm is a mystery, customers lose trust, and regulators begin to ask tough questions.
Transparency doesn’t mean giving away every line of code, but it does mean explaining decisions in clear, human language. If your AI-powered system rejects a claim or increases a premium, there should be a reason you can understand.
This is where concepts like “explainable AI” come into play: building systems that clearly explain, in plain language, how AI arrives at a decision. Proactively sharing this information with customers addresses the issues that people can feel when they encounter a faceless machine.
Accountability: Owning the Outcomes
AI can make mistakes. A typo in a data feed, a glitch in a model, or an unforeseen scenario can lead to bad AI decisions.
The worst thing insurers can do is shrug and say, “It wasn’t us—it was the AI.” Accountability for insurers means standing by their technology and taking responsibility for their decisions, as it’s ultimately the insurer’s decision. This means:
- Having transparent processes for people to appeal to or challenge AI decisions
- Auditing AI tools regularly
- Creating teams that can jump in when something goes wrong.
If AI makes a mistake, it’s still the insurer’s responsibility to rectify the issue, as the system acts in the insurer’s name. Not accepting responsibility costs insurers credibility, with the people who matter most – their clients.
Why it Matters
This isn’t just about avoiding bad press or incurring fines from regulators. Ethical AI is a trust issue.
When customers believe they’re being treated fairly, they’re more likely to stay with an insurer and recommend it to friends and family. Ethical AI isn’t just the right thing to do morally; it’s also good for business.
Insurers who lead in AI fairness, transparency, and accountability will have a significant advantage as consumers become increasingly aware of how AI is utilized in the insurance industry.
Moving Forward: Ethics by Design
The good news is that many insurance companies are now incorporating ethics into the design of their AI systems from the outset. Insurers’ AI design teams now access diverse disciplines, including ethicists, which build frameworks that prioritize fairness.
Some insurers are even joining industry groups that set and share standards for the responsible use of AI. Fighting bias and building transparency isn’t something one company fixes alone; it’s something the whole industry needs to tackle together.
AI is here to stay and is already making insurance faster, more innovative, and personalized. However, without ethical guardrails, the same technology creates new problems or exacerbates existing ones.
Every insurer embracing AI must also commit to the hard work of combating bias, maintaining transparency, and taking accountability seriously. When AI is fair and accountable, it makes insurance better for everyone, and that’s the kind of future we should all want to “insure.”
Agility Holdings Group (AHG) invests in innovative InsurTech, HealthTech, and related companies that aim to revolutionize access to insurance products, establish patient care, and improve health outcomes. Please visit our LinkedIn page for more information about AHG.