AI is all around us. But is it the next flavor of the month or a seismic shift in how we do business in the future?  This question was asked at a roundtable discussion with various insurance industry executives a few months back. Surprisingly, not a single executive thought it was a “flavor of the month.” Rather, they all saw the potential in this game-changing technology.

While they agreed AI is a seismic shift, there were concerns about proving ROI and external use cases. This seems to be a common theme across insurance companies. According to Accenture, insurers are assessing AI from an ROI standpoint, particularly in the insurance claims process. As they do, they are confronting concerns about AI’s viability from a business and consumer point of view.

Concerns about AI in the insurance sector

Since risk management is in the very DNA of the insurance business, it is perhaps not a surprise that many insurers feel due diligence will be necessary before embracing a transformative technology like generative AI in insurance.

For starters, a global Workday study found that only 41% of surveyed insurance executives believe their organization has the skills to keep pace with emerging finance technology. Without the proper expertise in data science and other relevant fields, insurers may struggle to achieve their AI goals. In addition, claims adjusters and related personnel will require proper training to use AI for claims processing effectively. While useful, AI will not replace the human touch.

In addition, AI requires consistent access to a large volume of high-quality data to perform properly. Timely access, or even access at all, is not a given in an insurance context. As Risk and Insurance notes, data availability and ownership — already significant challenges in this sector — will become even more acute as insurers embrace AI.

For their part, consumers also harbor concerns about AI. Fifty percent of respondents to Insurity’s 2024 AI in Insurance Report oppose the idea of AI in claims management, and 45% don’t want it used in underwriting, either. As Insurity notes, consumers are especially skeptical about the notion of AI taking on more decision-critical roles in general.

Careful preparation is crucial to success with AI

When considering the question “How is AI used in insurance?” businesses must strive for a balance between innovation and due diligence. AI is a powerful tool, but it is still just that: a tool. Accordingly, insurers and the experienced professionals who work for them should consider AI a helper but not a replacement for human expertise and insight.

When it comes to implementing AI, it’s important for insurers to take a crawl, walk, run approach. Insurers should continue to explore low-risk, high-reward AI use cases to help claims adjusters do their jobs more efficiently. For example, AI could help detect and prevent fraudulent claims or offer predictive insights. Seeking partnerships with AI solution providers that integrate with internal apps is a strong approach as well.

To maximize ROI for AI investments, insurance companies should also ensure claims adjusters receive proper training on using it. Likewise, if they do not yet possess sufficient in-house expertise in related fields like data science, insurers should consider partnering with technology providers that have deep experience in the field. Insurers who carefully integrate AI into their claims processes will find themselves ideally positioned to maximize the ROI they seek.

Potential use cases for AI in insurance claims

The traditional claims process can be notoriously slow, burdening claims adjusters with reams of claims to manually review in a limited amount of time. According to a recent KFF study, even when patients received care from in-network physicians, insurer denial rates reached 49% in 2021. One insurer’s denials reached a staggering 80% in 2020.

Manual claims processes result in not just high rates of denial, but lengthy delays and errors, as well. Insurers could use AI to accelerate the claims process, simultaneously improving productivity, resolving a longstanding customer pain point and improving access to care. For example, healthcare providers and insurers could tap AI to handle unstructured data sets from multiple sources, significantly streamlining data entry. This step would increase accuracy, helping insurance claims adjusters make more accurate decisions and issue faster approvals.

Accenture notes that insurers are also considering whether and how generative AI in insurance could address looming workforce gaps in claims and underwriting. By leveraging AI to increase internal productivity and improve the insurance employee experience, insurers can build the capacity to navigate talent shortages with greater agility while improving their ability to retain talented claims adjusters.

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