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Janine White recognizes that shopping for insurance isn’t most people’s idea of a fun Friday night.

“Buying auto insurance can be a pain point,” says Ms. White, vice-president of marketing and strategy development at Kanetix Ltd. “It’s not among the most pleasant things to shop for.”

But buying insurance using artificial intelligence (AI) can make the experience better, she says.

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Based in Toronto, Kanetix is a website where people shopping for insurance of all kinds can get comparative quotes, so they can choose the best deal. Since Feb. 2018, the company has been using AI to service those looking for auto insurance.

Ms. White says that they teamed up with Toronto AI company Integrate.ai to offer their customers a better experience. For everyone who goes to their site inquiring about auto insurance, Kanetix sends their non-personal information – no names, addresses or contact information – to Integrate, “and they feed it into a machine that continually learns,” she explains.

“The machine tells us things about the visitor that we might not know.”

For example, the AI might detect that a visitor is at the in-between stage of buying insurance – they’re not quite ready to buy, but they’re interested in doing so soon.

“We can use this information and then serve them in real time with things that might help them,” Ms. White says. “We might offer more content to help them make their decision, or we may offer a $20 gift card with an invitation to give us a call.”

AI is optimizing businesses of all sizes, says Jodie Wallis, managing director of artificial intelligence at Accenture Canada. One of the ways they are benefiting larger companies is through intelligent automation, she says.

“Businesses have already automated many processes, but intelligent automation lets the robots make decisions along the way,” Ms. Wallis says. “They can tell if something doesn’t look right.

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For example, a frozen food manufacturer can put sensors on its lines to analyze the settings and adjust them.”

Machine learning, a type of AI, takes automation a step beyond what people have traditionally experienced in the workplace, says Tomi Poutanen, chief AI officer at TD Bank.

“With traditional automation, information is coded into fairly rigid rules, which the machines follow to make decisions. With machine learning, there are no rules – the algorithms learn from the data to look at new ways to approach a problem. It’s an incredible increase in the ability of machines to make decisions,” Mr. Poutanen says.

For example, machine learning can help identify prospective home buyers who may be too shy or nervous to approach lenders, but who later on will want to get mortgage approval so they can buy a home. Lenders can then gently contact prospective borrowers and offer early information without a hard sell, Mr. Poutanen explains.

AI also enhances decision-making in companies, Ms. Wallis says.

“For instance, it can tell a rail company when it should perform maintenance on the tracks based on what’s actually happening to the equipment, rather than having the company simply rely on a schedule,” she says.

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Perhaps ironically, AI can also help businesses make interactions with customers more personalized, Ms. Wallis says. Unlike early automated helplines, AI can now process language in much more natural ways.

This makes it easier for customers to get online advice and assistance without having to hear, “Your call is important to us,” for hours on end, she says.

AI can be helpful as a way to detect fraud, hacking or identity theft, Ms. Wallis adds. And it can even help companies come up with new ideas.

“The term for this is ‘innovation diffusion,’” she says. “Companies are using AI to create new products and services.”

An earlier version of the story misidentified the name of Janine White, vice-president of marketing and strategy development at Kanetix Ltd.

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