AI roadmap – How insurance firms can prime themselves for the future

Report shows Canadian executives are ready to integrate AI, but how can they start?

AI roadmap – How insurance firms can prime themselves for the future


By Gia Snape

A vast majority (90%) of global business leaders in a wide array of industries have named artificial intelligence as the emerging area of innovation that has most influenced their organization’s long-term strategy, according to Accenture’s latest Technology Vision report.

Nearly two-thirds surveyed also said they anticipate dedicating more resources to AI in the next three to five years. 

The results show that Canadian insurance executives understand the important role that AI will play in the future of their work, and that they are willing to make the necessary investments to integrate AI, said Krish Banerjee (pictured), Canada managing director of data, analytics & applied intelligence at Accenture.

Speaking to Insurance Business, Banerjee shared four ways insurance companies can prepare for widespread disruption by AI:

  • Start with people

An organization’s workforce should be in its first line of priorities as it prepares to incorporate new technologies, Banerjee stressed.

“As insurers plan for further adoption of AI, they will need to radically rethink how work gets done. To that end, helping employees keep up with technology-driven change will be the biggest factor in realizing the full potential of AI,” he said.

 But companies should put overt emphasis on technical skills.

“Domain experts, who understand how data is applied in the real world, will be just as important as data scientists,” Banerjee added.

  • Create a robust, responsible AI compliance strategy

While regulations still vary widely around the world, organizations should take it upon themselves to put up robust and responsible governance structures for AI use.

“Responsible AI principles should be defined and translated into an effective governance structure for risk management and compliance, with organizational principles and policies and applicable laws and regulations,” Banerjee said.

  • Experiment with low-risk knowledge and creative work use cases

Organizations that want to ease their way into wider AI usage can experiment with different use cases, Banerjee suggested.

“For example, generating insights from internal company reports or publicly available information, while also exploring where the technology can lead to breakthrough innovation,” he said. “The potential business value of each use case should play a central role in defining an organization’s AI roadmap.”

  • Adopt a disciplined approach to data

Having a “strategic and disciplined approach to acquiring, growing, refining, safeguarding, and deploying data” is critical, especially when leveraging generative AI.

Banerjee added: “Foundation models will need to be customized with domain-specific data, semantics, knowledge, and methodologies.”

Three key areas AI can drastically change insurance  

AI is introducing a new dimension of human and machine collaboration that can radically change how work is accomplished.

The underpinnings of generative AI, popularized by ChatGPT, will transform some 40% of working hours across industries, Accenture’s research shows.

“Banking, insurance, and energy are among the industries whose work is most likely to be transformed because of their higher potential for automation,” said Banerjee. 

According to the MD, customer experience, process efficiency, and effective decision-making will be key areas in insurance that will be greatly improved by AI.

“Our research has found a third of all claimants say they were not fully satisfied with their most recent claims experience. This is a clear pain point in the speed of settlement. AI can improve settlement time by enabling digital and self-service claims processing that dramatically enhances customer experiences and accelerates processing,” he said.

“We’re already seeing many leading insurers invest in creating omni-channel environments that use chatbots, rich text messaging and guided scripting for agents.” 

Incorporating AI and automation will cut time spent by underwriters on non-core and administrative tasks, while boosting their risk selection and pricing accuracy.

In claims, AI can provide insights that help prevent leakage, resulting in more accurate payouts and increased customer satisfaction. 

What risks and challenges come with adapting AI technologies?

While AI-led technology will accelerate developments in many areas in insurance, like any emerging technology it will also introduce new areas of risk.

As AI adoption becomes more widespread, insurance companies will face greater scrutiny in their data privacy and security, ethical concerns, and shifting customer and employee expectations, Banerjee warned,

 “For insurance companies to be successful, businesses will need to be intentional and responsible about the use of AI and data from the get-go,” he said.

“Companies will need to weave in legal, compliance, and policy teams while building AI-led solutions. When AI is designed and put into practice within an ethical framework, it accelerates the potential for responsible human-AI collaboration and unlocks new sources of business growth.”

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