The evolution of artificial intelligence (AI), including the new wave of generative AI (Gen AI), is transforming numerous industries. Whether it’s automated claims, assessing risk, personalisation of products and services, or fighting cyber crime, insurance organisations are increasingly looking towards AI to help tackle complex and time-intensive tasks, and to streamline processes.

There is an urgent need to pick up the pace in adoption of artificial intelligence. Despite the use of AI in a handful of areas and pilots taking place elsewhere, insurance companies are not gaining an advantage on competitors by using this technology more widely. Doing so could enable businesses to work faster, more flexibly and develop more sophisticated models in response to the evolving insurance market.

So, how can insurers adopt AI effectively and unlock its full potential?

This report is intended to support insurance leadership teams in using AI to transform their organisations. It brings together insights from KPMG professionals and industry leaders from Zurich Australia, Generali Italia, PassportCard, and Prudential who share their perspectives on how to unlock AI's full potential.

Key findings impacting insurance organisations

Insurance organisations are increasingly investing in this space, but projects are taking too long to get into production.

Despite the natural risk-adverse approach, insurance businesses are ahead of the global average when it comes to investing in AI use cases across the business. However, the slow pace of implementation is creating significant delays in progress compared to other industries.

A careful balance of innovation and navigating risks are expected to be crucial.

AI offers untapped potential for those that are willing to embrace change, but it also brings new and concerning risks that should be considered as insurance organisations further develop their AI strategy. By undergoing an internal maturity assessment, organisations can have better clarity on current capabilities and identify areas to prioritise. KPMG firms’ tested maturity assessment framework enables organisations to do this effectively.

Successful organisations will likely still be data-driven and people-led.

Before starting on AI transformation, business leaders should have a clear and robust transformation plan in place, and focus on having a solid digital foundation and clean data to help improve the output. Upskilling and empowering colleagues and teams to better understand the bridge between AI and data can support longer-term success, and provide additional value by leveraging AI as an assistant.


of insurance organisations see AI as the most important technology for achieving their ambitions over the next three years.1
of insurance CEOs interviewed said it would take three to five years for generative AI to provide a return on investment with increased profitability, fraud detection and cyber-attack listed as the top benefits.2

How are insurers approaching AI?

AI offers huge potential benefits for insurers, with the AI market size estimated to grow to US$79 billion by 2032.3

Leadership teams acknowledge that AI could completely transform their operating models and ultimately, the customer experience. However, insurance companies appear to be approaching the technology strategically and with cautious optimism.

Many insurers have already started introducing machine learning (ML) or other AI technologies to help improve specific business processes, such actuarial models and fraud prevention processes. In customer service, AI is being leveraged to confirm identity through voice recognition, to provide a timely response to online queries through use of chatbots, and to generate more sophisticated ‘next best actions’ for customer service agents.

With enough training data, algorithms can better analyse risk and predict outcomes, adding accuracy to risk models and pricing structures. Both traditional and Gen AI could empower organisations to enhance actuarial models, deliver personalised insurance cover, or even increase the pace of insurance claims. But the process of doing so appears to be slow, with testing and implementation processes often taking several months to complete.

There is also growing recognition among insurers that a successful AI journey will likely be intrinsically linked to the maturity of their digital transformation. AI thrives on quality data and is best supported by cloud-based infrastructure and agile operating models; firms that are yet to fully embrace this are becoming aware of the urgency to do so.

We’re seeing significant interest in AI with many insurance organisations trialling proofs of concept within niche areas. There is still hesitancy around wider deployment, exacerbated by challenges around the speed at which AI is evolving, data quality, bias, and regulatory compliance. This has resulted in many businesses taking a measured approach.

Caroline Leong
Global Insurance Claims Lead, KPMG International
Operations Advisory Partner, KPMG Australia

Navigating AI’s risks in the insurance industry

While the opportunities aligned with AI are significant, the associated risks are also increasing. Eighty-five percent of insurance CEOs believe that generative AI is a double-edge sword, in that it may not only aid in the detection of cyber-attacks but also provide new attack strategies for adversaries.4 Organisations should be mindful of this when developing and integrating AI solutions:

  • Confidentiality risks
  • Generative AI services ‘hallucinating’ or creating inaccurate outputs
  • Data poisoning
  • ESG regulatory and reputational risks, given AI’s power demands
  • Cultural risks over whether staff are happy to work alongside AI systems

However, avoiding AI altogether may also expose insurers to the risk of missing out on potential opportunities and benefits, and losing competitive advantage. Doing so presents opportunity risks through reducing organisational knowledge, cutting abilities to develop new products and processes, and the risk of being overtaken by more technologically confident peers.

I expect that the mechanisms for interacting with customers in the future will change a lot. AI will enable change across the organisation and drive large-scale transformation. But there will still be a need for human empathy — when people are in a time of need or crisis, they want to speak to a human — I don’t think that is going to change.

John Kim
Chief Data Officer
Zurich Australia

Case study: Client zero

The need for human thought and oversight, data analysis, critical thinking and decision-making is not disappearing. And so, while clients are looking for support, they’re also interested in the lessons learned along KPMG firms’ AI journey.

KPMG professionals are approaching this new future as ‘client zero’ and ‘walking the talk’, following the same advice that KPMG professionals provide to clients — designing and implementing an AI strategy that aims to prioritise human centricity in the way KPMG firms adopt innovation, and to enhance the KPMG workforce of the future. KPMG professionals align to regulatory and voluntary standards, such as the EU AI Act and the ISO 42001.

Learn how KPMG Australia navigated risk to design, build and deploy our Gen-AI agent – KymChat.

How KPMG insurance and AI professionals can help


By combining deep insurance industry and functional knowledge with the right technologies, KPMG firms can help you to unlock business value and harness the full power and potential of AI with speed, agility, and confidence.

KPMG firms have worked with global insurance firms to help deliver meaningful AI transformation, combining industry knowledge and actionable insights with leading technology alliances, developing robust frameworks and AI accelerators.

KPMG professionals are experienced in developing proof-of-concepts and scaling these into integrated digital solutions. And these processes have been used internally to review and enhance KPMG firms’ capabilities.

KPMG insurance professionals can offer:

  • AI 360 assessment of internal capabilities and support to integrate AI into your strategy.
  • Development of use cases and AI operating model aligned with your business objectives.
  • AI risk assessment and development of control and governance frameworks for AI.
  • Creation of a data foundation for AI integration, and support with developing models and tuning.
  • AI concept development with our global alliance partners to develop a scalable solution.
  • Workforce impact assessment and analysis on the impact of transformation on the organisation.

Contact KPMG's AI & insurance specialists

References

  1. KPMG Global Tech Report 2023’, KPMG International, December 2023. 
  2. KPMG Insurance CEO Outlook’, KPMG International, December 2023.
  3. Artificial Intelligence (AI) In Insurance Market Size, Share, and Trends 2024 to 2034, Precedence Research, July 2023.
  4. KPMG Insurance CEO Outlook’, KPMG International, December 2023.