Generative AI is Coming For Insurance: Celent Report

IIR talks with Celent Analyst Andrew Schwartz about the competitive opportunities and threats from Gen AI to insurers and how to navigate them.

(Image credit: Georg Eierman/Unsplash.)

Celent’s report “Generative AI – Mitigating Risk to Realize Success,” introduces the topic saying, “Generative AI is coming for insurance.” The phrase implies both opportunity and threat, which author Andrew Schwartz, an Analyst in Celent’s North American Property & Casualty Practice, fleshes out abundantly in the report. Schwartz notes the sudden and powerful impression made on the world by the debut of Chat GPT in Nov. 2022 and says, “Artificial intelligence is revolutionizing the way we live and work, and it will profoundly reshape our world by transforming jobs and fostering new industries. From this point forward, it will have a transformative, disruptive impact on insurance operations and technology.”

Andrew Schwartz, Analyst, North American Property & Casualty Practice, Celent

Generative AI—Gen AI for short—has been a focus for Schwartz to such an extent that he’s become a go-to source on the topic for Insurance Innovation Reporter. With the publication of this extensive report, we sought to have an exchange with Schwartz to call out some of the aspects of Gen AI that we find most interesting and most relevant to our readers.

Insurance Innovation Reporter: You call generative AI a “game-changer.” Does that mean the technology is capable of a degree of change that becomes qualitative?

Andrew Schwartz, Analyst, North American Property & Casualty Practice, Celent: Absolutely. In the insurance landscape, this represents a Promethean moment. Generative AI is not just about incremental advancements; it’s a transformative force, offering the potential to herald in a new era of precision and efficiency in risk assessment, claims processing, and customer engagement.

IIR: Just how much potential does AI have to change the game? How should we judge hype vs reality when it comes to claims about Gen AI’s potential? Is it hard to see the boundaries of Gen AI’s potential?

AS: The potential is vast, akin to an uncharted ocean with depths yet to be explored. While its allure is undeniable, discernment is crucial. The boundaries of Gen AI are fluid, evolving with each technological breakthrough, making it imperative to approach its capabilities with both optimism and a critical eye.

IIR: Does the potential of Gen AI differ by line of business within the insurance sector, or is it more of a universally useful technology? Could a particular insurance segment safely ignore Gen AI as a competitive threat?

AS: Gen AI’s versatility ensures its relevance across various insurance lines, from property to casualty to life. However, its transformative potential is particularly pronounced in areas like customer service, risk assessment, and policy personalization. Ignoring its rise in any segment would be overlooking a seismic shift in the industry’s landscape.

IIR: Where would we find some of the clearest use cases for Gen AI in insurance?

AS: Gen AI shines in areas such as enhancing customer service through tailored interactions, refining risk assessment models for more accurate policy pricing, and personalizing policy offerings based on individual client needs. Envision a scenario where a client’s query is addressed in real-time, with policy recommendations tailored to their unique profile.

IIR: To the extent that Gen AI is indeed a competitive concern, how quickly will its impact be felt? Should we consider the explosive adoption of ChatGPT as an indication of how fast Gen AI could bring change to the insurance industry, at least in some areas?

AS: The rapid ascent of platforms like ChatGPT indeed offers a glimpse into the transformative potential of Gen AI. Such tools have demonstrated that when the technology meets a specific need, its adoption can be swift and pervasive.

The pace at which ChatGPT and similar platforms have been integrated into various sectors underscores the industry’s readiness for Gen AI’s capabilities. While the insurance sector, with its intricate processes and regulatory considerations, might experience a more measured transformation, certain areas, especially those prioritizing immediate interactions and data-driven insights, could see quicker shifts.

In essence, while the broader implications of Gen AI in insurance will manifest over a longer horizon, specific facets of the industry, inspired by the likes of ChatGPT, might undergo rapid changes. It’s a testament to the duality of Gen AI’s influence: both as a catalyst for swift advancements in targeted areas and as a foundational force for long-term industry evolution.

The influence of Gen AI on the insurance sector is undeniable, but its full impact will unfold over time. While early adopters are already witnessing enhancements in certain processes, the broader, industry-wide transformation will be more gradual. It’s essential to view Gen AI not just as a fleeting trend but as a sustained evolution, one that might reshape the industry at a pace distinct from previous technological shifts.

IIR: When e-commerce first appeared, some thought it would be the end of insurance intermediaries. How might the impact of Gen AI differ? Are we likely to make similar mistakes in our predictions, or are there obvious ways that Gen AI will change insurance?

AS: Gen AI is set to enhance, not replace. It will introduce efficiencies and automation, particularly in customer service and personalization, but the nuanced expertise of intermediaries remains invaluable. Predicting its trajectory requires both historical reflection and forward-thinking vision.

IIR: Since the launch of ChatGPT, the industry seems to have had a lively sense of how risky Gen AI could be. As important as caution may be, do you think that an excess of care could result in losing a step to competitors when it comes to this technology’s benefits? How should one strike the balance between caution and creativity?

AS: The dance between innovation and prudence is delicate. While caution is paramount, excessive risk aversion may stifle progress. The equilibrium lies in informed, strategic integration, ensuring that creativity is not sacrificed at the altar of caution.

IIR: What are some of the clearest use cases for Gen AI in insurance?

Gen AI shines in areas such as enhancing customer service through tailored interactions, refining risk assessment models for more accurate policy pricing, and personalizing policy offerings based on individual client needs. Envision a scenario where a client’s query is addressed in real-time, with policy recommendations tailored to their unique profile.

(Source: Celent. Click to enlarge.)

IIR: What can one expect—starting with such low-hanging fruit—in terms of investment and return on Gen AI?

AS: Initial dividends manifest in operational efficiencies, particularly in customer service and risk assessment. Over time, as the technology matures, returns will extend to realms like enhanced customer retention and innovative policy offerings.

IIR: What are some of the limitations and potential pitfalls of Gen AI? The most enthusiastic talk about the technology as if it had some God-like quality. How would you bring us back down to earth both about Gen AI’s potential and its risks?”

AS: Generative AI, while revolutionary, is not without its constraints. Let’s temper our enthusiasm with a dose of reality:

Lack of Common Sense: Gen AI can sometimes produce results that, while syntactically correct, may lack practical or “common sense’ understanding. For instance, it might provide an answer that, while technically accurate, doesn’t align with real-world logic or expectations.

Limited Creativity: While Gen AI can generate responses based on vast amounts of data it has been trained on, it doesn’t truly “create” in the human sense. Its outputs are reflections of patterns it has seen before. So, if you’re looking for groundbreaking, out-of-the-box thinking, Gen AI might not always be your muse.

Complex Sequential Tasks: Gen AI can sometimes be challenged by tasks that require a deep understanding of sequences or intricate decision-making processes. It’s like expecting a sprinter to suddenly excel in a marathon; they’re both runners, but the demands of the race are different.

Accuracy Isn’t Guaranteed: Just because Gen AI can provide an answer doesn’t mean it’s always the right one. It has the potential to produce highly accurate responses, but it can also craft well-articulated yet entirely incorrect answers.

The following chart encapsulates the multifaceted challenges posed by Gen AI. From potential biases and ethical dilemmas to the very real threats of misinformation and regulatory breaches, it underscores the imperative for vigilance. Additionally, the risk of intellectual property violations and the potential misuse by nefarious actors highlight the need for robust safeguards. As we navigate the Gen AI landscape, it’s crucial to be cognizant of these pitfalls and proactively address them.

(Source: Celent. Click to enlarge.)

IIR: We’ve discussed how one should approach the inherent risks of Gen AI; a different question is how one must anticipate and work with how regulators evaluate those risks. What do insurers need to know, and how should they be thinking about that?

AS: Navigating the regulatory environment requires both foresight and adaptability. Engaging in proactive dialogues with regulatory bodies ensures that one remains at the vanguard of emerging guidelines, facilitating both compliance and innovation.

(Source: Celent. Click to enlarge.)

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Anthony R. O’Donnell // Anthony O'Donnell is Executive Editor of Insurance Innovation Reporter. For nearly two decades, he has been an observer and commentator on the use of information technology in the insurance industry, following industry trends and writing about the use of IT across all sectors of the insurance industry. He can be reached at or (503) 936-2803.

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