Which industries are adopting artificial intelligence and how are they using it? You might be surprised.
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As a wave of companies rush to embed artificial intelligence into their operations, Matt Wood has noticed the technology’s fastest adopters are businesses more typically described as slow to change.
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Matt Wood, Amazon Web Services global VP of AI products (The Canadian Press / HO-Amazon Web Services)
The speedy adopters span regulated industries like health care, life sciences, financial services, insurance and manufacturing—a shock even for someone as plugged into the world of AI as Wood, Amazon Web Services’ global vice-president of AI products.
“If you’d have told me a year and a half ago that 160-year-old life insurance companies were going to be in the vanguard of artificial intelligence usage, I probably would have been a bit surprised, but that’s turning out to be the case,” Wood said, referencing Sun Life Financial Inc. in an interview, fresh off a visit to Toronto for the Collision tech conference.
His observation turns age-old assumptions about innovation and who is open to embracing technology upside down. It comes as nearly every sector is grappling with advances in AI and considering how the technology can increase productivity and profitability.
How different industries are using AI
Wood has recently seen life insurance companies turn to AI to review 90-year-old policies and identity risks they could pose over the next decade or so when they are likely to be paid out.
Doctors have also adopted the technology, using it to transcribe exchanges with patients and cobble together appointment summaries that are so accurate, blind-testing has shown health-care providers would choose them over human-crafted summaries seven out of 10 times.
Wood suspects regulated sectors have moved faster than others on AI for a few reasons.
The first stems from the trove of data at their fingertips.
Many regulated companies are sitting on extensive databases, market research and development reports, clinical trial results and patient and insurance records that hold a lot of potential because the organizations are privately held.
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“The models have never seen them before, and as a result, you can use generative AI to be able to understand, read, connect the dots, find similarities, find differences across these very large collections of data,” Wood said.
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Balancing privacy and potential
Knowing the data’s value often also means understanding what it takes to protect it.
Some AI systems, for example, collect, use and train on any data input into them but many companies have policies promising not to disclose or share customer or patient information.
Regulated industries already know how to navigate these thorny issues in a way that won’t stymie or block organizations from implementing technology, making AI adoption faster, Wood said.
“They’ve already figured out … what data they have, what it can be used for, who it can be used by, what tools it can be used with, all those sorts of things,” he said.
That understanding gives them a head start compared with other organizations who haven’t confronted these issues before or who don’t believe there’s a way forward for them with AI.
“There is a kind of schism in some customers’ minds that in order to be successful with generative AI, you have to make some sort of negative trade-off when it comes to the privacy of the data that you’re using,” said Wood.
“I can understand where that comes from. Some folks have played a little, shall we say, fast and loose with the data that has been available to them.”
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But Wood insists there are ways to balance privacy and potential.
Many companies only use AI with anonymized or de-identified data, while others offer secure digital environments where staff can test AI without the fear of data leaking to the public or training future models.
Wood said AWS, Amazon’s cloud-computing subsidiary, does not use data from paid corporate customers to train underlying models and also gives them full control over where their data resides, how it moves and what network it is on. The company also doesn’t have internal or third-party staff reviewing their clients’ prompts.
The speed with which they navigate data privacy aside, the final reason Wood thinks regulated businesses have rushed toward AI adoption is because they’re keen not to be left behind by the latest technological whirlwind.
“They’ve had to sit on the sidelines a little bit as digital transformation has washed across other industries,” he said, offering the example of how media and entertainment companies have been pushed ahead by streaming platforms.
“They’re looking at generative AI not just as a way to kind of catch up, but as a way to leapfrog, significantly kick-start that digital transformation.”
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If we had less federal and provincial government regulations we could definitely see an uptrend in productivity.
Next the federal government should lead/force the provinces into an open market. Bring down trade barriers and this countries standard of living would rise along with productivity.
Next but not least is to reduce the size of the federal government relative to the economy. Examples of this are defending the CBC, eliminating the Status of Women ministry (do we really need it in this day and age), eliminate the all the economic diversification funds – Western, Ontario, Quebec and Martimes. They are just slush funds with little to show.
And although I could add many more suggestions, why not have just one business tax rate, no matter the size. This would encourage small businesses to become medium and medium sized to become large. After all it’s lage companies that pay the best wages and benefits while contributing greatly to their communities. A Microsoft anyone?
If we had less federal and provincial government regulations we could definitely see an uptrend in productivity.
Next the federal government should lead/force the provinces into an open market. Bring down trade barriers and this countries standard of living would rise along with productivity.
Next but not least is to reduce the size of the federal government relative to the economy. Examples of this are defending the CBC, eliminating the Status of Women ministry (do we really need it in this day and age), eliminate the all the economic diversification funds – Western, Ontario, Quebec and Martimes. They are just slush funds with little to show.
And although I could add many more suggestions, why not have just one business tax rate, no matter the size. This would encourage small businesses to become medium and medium sized to become large. After all it’s lage companies that pay the best wages and benefits while contributing greatly to their communities. A Microsoft anyone?