Artificial intelligence isn’t just a buzzword in the insurance world – it’s already reshaping core workflows and reclaiming time across the value chain. From faster data reconciliation to smarter reporting, Canadian insurers and brokers are finding real, measurable value in AI adoption.
At Insurance Business’s Women in Insurance Summit, a panel of senior leaders shared how their organizations are deploying AI to reduce inefficiencies, eliminate tedious tasks, and empower teams to focus on what matters most: insight, strategy, and client relationships.
Their message of the panelists was clear: while there’s no shortage of excitement about AI’s potential, getting it right requires thoughtful execution, strong governance, and a people-first mindset.
AI is already being used to improve insurance operations, the panelists agreed.
At Gore Mutual, Jharna Deshmukh highlighted the efficiency gains made through AI-driven data reconciliation. Tasks like aligning operational and financial data – once slow, error-prone, and labor-intensive – are now automated using machine learning, which not only finds discrepancies but helps teams focus on what matters most.
“If anybody's worked with that data, they will understand how complex it is. It's like playing ‘spot the difference’. It's my favorite game, but imagine trying to find 10,000 or more differences. It's slow, tedious and frankly, very boring and mostly inaccurate,” Deshmukh said.
Amanda May, vice president at McCAM Insurance Brokers, offered a broker’s perspective, noting how AI-powered tools are enhancing the way data is extracted and analyzed from Excel reports. What used to take an entire day now takes a fraction of the time, enabling teams to surface new insights, identify time-wasting activities, and run operations more efficiently, she said.
This has sparked curiosity and engagement across her team, who now see AI as a way to improve both client service and their own workflows.
“What's really exciting is I'm able to give new metrics and data to the rest of the team, and now I've got more engagement from them, because they're curious,” May said.
Kate Della Mora, CEO of CFC Underwriting Canada, said that AI’s greatest strength may be in freeing up time across the value chain. Whether simplifying submissions between brokers and underwriters or scanning through complex documentation, the goal isn’t to replace human roles – but to streamline tasks so professionals can spend more time doing what they do best: building relationships, offering guidance, and selling.
Despite the growing appetite for AI, the road to implementation is far from smooth. Panelists emphasized that insurers must overcome both technological and organizational hurdles to fully realize AI’s benefits.
Data quality and privacy emerged as major concerns. Della Mora underscored the importance of regulatory compliance and governance in the use of sensitive information. In a heavily regulated environment like Canada’s, strict privacy laws demand rigorous data protection protocols – especially as insurers begin leveraging AI to manipulate and interpret vast datasets.
“The insurance industry is typically a decade or more behind in technology. So I think … we have to think about the data that each respective company has collected – how reliable it is, and how long have they been collecting it,” she said.
Della Mora also pointed out that many insurers are still catching up to modern tech standards, and AI tools are only as reliable as the information they’re trained on.
“AI is great, but it can be ‘garbage in – garbage out’, so we have to be hyper aware,” she said.
Deshmukh agreed that technology itself can be both a solution and a stumbling block.
On the technology side, data privacy remains paramount – particularly given Canada's strict regulatory framework. She noted that any use of AI must be underpinned by partnerships with vendors that can guarantee region-specific data hosting and strong governance controls from the outset.
Beyond data privacy, the overwhelming number of tools on the market presents its own challenge. With so many AI solutions available, it can be tempting for teams to adopt tools ad hoc. But Deshmukh warned that this “plug-and-play” mindset is often misaligned with long-term needs.
“Given a choice, everybody would want to just pick up something and start using it. That's not the right fit for any organization,” she said.
Looking ahead, panelists expressed cautious optimism about AI’s long-term role in reshaping the insurance landscape – moving it from a reactive industry to a proactive, predictive one.
Deshmukh shared her hope that AI will enable insurers to anticipate and prevent losses before they occur. Rather than simply responding to disasters like wildfires or floods, she envisions a future where AI systems combine economic trends, weather models, environmental data, and even human behavior to forecast risk and minimize exposure in real time.
Della Mora echoed that excitement, adding that she hopes AI will contribute to greater market stability. The insurance sector is known for its volatile cycles between hard and soft markets, and she believes that more sophisticated data modeling could help smooth those swings. With better tools to assess and price risk accurately, insurers could deliver more consistent outcomes for clients and the industry alike.
For May, the future of AI is about eliminating low-value work and unlocking higher-purpose roles. She highlighted the potential to remove repetitive tasks like manual data entry and redeploy staff into more strategic positions.
“This is a tool that is going to eliminate tedious jobs to create more meaningful ones,” she said.
