Driving AI innovation and risk management

Generative artificial intelligence (AI) has emerged as a new technology with the potential to completely reshape business practices and create new avenues for innovation. It will have a significant impact on almost every industry sector. Organizations have been quick to embrace it, as evidenced by a recent Gallagher survey of 1,000 business owners. In that survey, the vast majority—81 percent—indicated that they plan to maintain or increase investment in AI in the near term.

However, along with new efficiencies, AI tools will bring new risks to the fore for those who use them. AI risk will force enterprise risk management programs to incorporate effective management strategies, which will undoubtedly be a new process for most entities.

The main risks associated with the generative use of artificial intelligence

While we’re still evaluating all the risks associated with generative AI, we’ve identified a few high-risk categories that business leaders should pay close attention to, including:

• Bias and data fairness… AI models and their underlying assumptions have the potential to infuse bias into decision-making and perpetuate discriminatory practices.
• Privacy issues… More privacy laws related to the collection, storage and sharing of personally identifiable information will likely apply to the use of AI. Careful consideration of compliance obligations related to these matters should be a priority.
• Data quality… Relying on incomplete or incorrect data can lead to wrong analyzes and results.
• Intellectual property and data ownership… Proprietary rights and trade secrets may not be adequately protected, increasing the risk of consent and proprietary rights litigation.
• Regulatory risk… Several states have passed bills focused on compliance requirements for those who provide AI platforms and those who use them. Global privacy regimes have already adopted laws with a similar focus.

The Chief Artificial Intelligence Officer: A New Role

As modern risk management-oriented organizations use artificial intelligence to stay competitive, they may need to tackle a new role: the chief artificial intelligence officer (CAIO). The role will require a strong ability to balance innovation with AI risk management and may include:

• Strategic AI Leadership: Creating and implementing the overall AI strategy with a view to improving operational efficiency, improving customer experience and identifying new revenue streams.
• Risk management and compliance: Establishing a framework for the safe and responsible use of AI as it aligns with both organizational ethical standards and those generally expected by external parties. This should also extend to complying with regulatory requirements as they evolve.
• Government programs:Creating formal structures to oversee AI initiatives and projects. These SOPs should help ensure that the organization meets ethical and regulatory standards, with a focus on fairness, transparency, data security and prevention of unintended consequences.
• Internal cross-collaboration:Close coordination with multi-division and C-suite leaders. This should encourage collaboration between various stakeholders, including but not limited to legal, IT, privacy, operations, marketing, human resources, sales and risk management departments.
• Performance measurement and continuous improvement:Fostering a culture of continuous AI-centric innovation. Periodic evaluations of the performance of AI tools and the return on investment in AI resources, while staying abreast of new technologies that align with the organization’s current and future goals.

Where to start: New AI risk management guidelines

Several organizations have recently published suggested frameworks for risk-based standards in the implementation of AI programs:

While not all organizations may be ready for a CAIO at this time, they should carefully consider such an investment. This role will become more important as AI becomes a standard requirement to remain competitive. Most companies have already adopted AI in some form, and there is every indication that the use of AI will continue to grow rapidly. Litigation and regulatory risks have increased with the pace of AI engagement, driving the need for risk managers to stay on top of AI risk as it evolves.

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InsurTech Risk management through data-driven artificial intelligence