RESEARCH REPORT

In brief

In brief

  • Insurance organizations are only realizing a fraction of the potential of AI—and ultimately their employees.
  • By building the capabilities needed for AI and people to work together seamlessly, they will amplify the best qualities of both.
  • But only 35% of insurers have inclusive design or human-centric design principles in place to support human-machine collaboration.


Reimagine the business through human and AI collaboration

Insurance leaders are already adopting artificial intelligence (AI) tools and practices that speed up the automation of basic tasks in existing workflows. But this will soon be table stakes. The true potential of AI in insurance lies in using it as a collaboration tool with humans: to not only efficiently execute tasks but also transform what businesses actually do.

In some cases, AI can approach problems from a different angle to people: its judgment isn’t clouded by decades of previous experience or inherent biases, and it hasn’t yet learned what not to try. But this huge advantage requires human assistance to really take off, in the form of people partners helping to steward, direct and refine what the AI comes up with.

For instance, a carrier in Japan is developing an AI platform that provides P&C agents with sales support. Where the sales reps used to seek leads based on their own relationships and experiences, they now get next-best-action recommendations from the AI engine. The system improves based on agent feedback, creating a virtuous circle of human and machine feedback.

How can businesses today begin building this capability? To facilitate true human and AI collaboration, they need to find ways to replace a “command and response” relationship between human and machine with an experience that is interactive, exploratory and adaptable.

This starts with effective communication. Because of advancements in natural language processing (NLP), machines are beginning to better understand the context of language, instead of just the content.

Understanding physical context is also game-changing for AI’s ability to work with humans in extended reality (XR) environments. Image recognition and machine learning allow AI to not just see its surroundings, but understand them.

It goes the other way as well, with humans being better able to understand machines. Explainable AI allows people to open previously “black-box” AI systems to get at how the machine made a particular decision. In insurance, explainable AI should be able to tell a person why their claim was flagged as potentially fraudulent or the reason for an unexpected premium hike.

Building bridges between AI and employees

79%

of insurance executives believe collaboration between humans and machines will be critical to innovation in the future

21%

of insurance organizations report they are preparing their workforce for collaborative, interactive, and explainable AI-based systems

Fostering human-machine collaboration requires contextual comprehension between people and machines.

Reinventing the relationship between humans and machines

Once enterprises enable the full scope of human-AI collaboration, they can jump on the new opportunity before them—employing AI to reimagine everything—from the way their organizations are structured, to the way they approach work, to the value their enterprise creates.

Ultimately, better human machine interactions will lead to businesses being able to reinvent and constantly improve the offerings and experiences their customers want. When steps are taken to improve communication between machines and humans, the result is that AI becomes much more than just another tech tool. It’s an agent of change in the business.

Emmanuel Viale

Managing Director – Accenture Technology Labs


Andrew Starrs

Group Technology Lead – Banking


Abizer Rangwala

Managing Director – Technology Strategy, Insurance

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