Ask an Expert: As an SME insurer, what should we prioritise for an investment in AI?

Great question. And it’s one I hear a lot, because let’s face it, for medium-sized insurers and brokers, the AI hype can feel like a wave coming at you, but you’re not sure if you’ve got the board to ride it or just get knocked over. So let me break it down.

Start with what you already have: your data.

The number one priority is to understand your data environment. Where is your data stored? Is it structured? Is it accessible? If the answer is “it’s in 12 different legacy systems” (which is common), don’t panic. You don’t need to boil the ocean.

Look at ways to centralise policy, payment and customer interaction data into a manageable, connected layer. You can’t do anything meaningful with AI without first getting this foundation right.

Pick a practical, high-volume problem.

Don’t aim for a sci-fi future out of the gate. AI can do some brilliant things right now, especially with robotic process automation (RPA) and basic decision trees.

Think about customer self-service tools, arrears management, or automating responses to the 80% of repeat customer queries your team gets every day. These are low-hanging fruit that drive measurable ROI fast, like reducing inbound calls by 47%.

Control is key.

Once you start deploying AI, even if it’s simple automation, you need the right governance. Who signs off the process logic? Who owns the data flow? Can you trace decisions back to an audit trail?

In insurance, we live and breathe risk, so apply the same lens to your AI journey. Especially if it’s touching payments or claims. Think “if this went on the front page of the newspaper or to social media, would we be comfortable explaining it?”

Don’t get trapped in core system thinking.

One of the biggest blockers I see is businesses thinking innovation must happen inside the core policy or billing systems. It doesn’t.

Middleware and API integration can help you innovate alongside those systems. No core surgery required. This lets you run small, controlled experiments while still building towards a broader transformation.

And finally, measure it.

From day one, know what success looks like. Fewer customer service calls? Faster claim turnaround? Lower cost per transaction? Define your KPIs early so you can track real impact and build the case for further investment.

To wrap it up: start small, solve real problems, control tightly, integrate smartly, and measure relentlessly. That’s the roadmap for AI success in medium-sized insurance or broking businesses.

Attributable to Shaun Quincey CEO and Co-founder Simfuni

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