The Balancing Act of Leveraging AI is a Job for the Insurance Industry
The introduction of AI into everyday business operations has triggered the need to balance the anticipated benefits and rewards – which is serving as the catalyst for most – with the risk of moving too quickly, adopting without having a framework in place to properly oversee and govern the application of AI.
A failure to find this balance could negate any incremental value realized, only to replace it with the unnecessary costs, liabilities and longer-term impacts resulting from poorly or inadequately planned implementations and deployments. Striking this balance between risk and reward is a job made for the insurance industry given its existing propensity to manage, mitigate and transfer risk.
The decision to embrace AI is the responsibility of leadership, but one that a Board may also be liable for. In the same way that loss and risk control has become more proactive through education and awareness, so too must the same approach be taken with AI.
“We’re approaching a reality where it will be impossible for Board members to say: ‘I didn’t know’ when it comes to dealing with AI-driven exposures.”
Elliot Schreiber, NACD – Top 50 Governance Experts.
The role of risk management is perhaps more important than merely providing a policy than even before. Understanding the risks that adoption of AI presents for any organization seeking the potential benefits and efficiencies is paramount, and clients have every right to expect their insurance provider to initiate and drive this discussion.
The early adoption phase of AI still comes with a decent degree of unknowns, as every organization will adapt automation technology based on their existing business models while at the same time designing future state models based on what their new reality may look like. The journey from present state to future state or next state comes with significant risk for leadership and Boards that are uninformed and unaware of these implications.
The insurance industry has an opportunity to be a catalyst for this additional lens for understanding risk and the implications it might have on their respective books of business and the clients they serve. This industry is unique in that it already understands risk profiles by industry, type of exposure and business model – it has created expertise and product availability based on defined risks – AI is no different. This aggregate view of the global economy puts insurance at the heart of the AI balancing act, whether it wants to be or not.
The road to reward is paved with risk, and while it might not be the discussion an organization wants to have as it pursues much-needed cost savings through newfound efficiencies, it’s critical and necessary. Your insurance broker or risk manager should be an active part of these discussions.
The Board needs to get more operational given the nature of AI’s tactical impact. The Transition from an IT-driven mandate to business strategy increases the risk for leadership teams and Boards. AI should be on the agenda of every Board meeting so they can monitor and understand where the organization is piloting and experimenting.
These discussions must go beyond operational or situational risk – those issues that may arise in the day-to-day application of AI – and extend to systemic risks arising from policies and procedures that have a more permanent effect on how the organization does business going forward.
Once AI evolves from internal applications to external impacts to customers and stakeholders, it now represents liabilities that an organization’s C-Suite and the Board are accountable for, and “I didn’t know” isn’t good enough. Every leadership team and members of the Board must not only be aware of AI and the potential risks and rewards, but they must also truly understand it so they can factor this knowledge and insight into the decisions they make pertaining to how, when and why AI becomes more of a permanent part of their business model and day-to-day operations.
John Barker, JD, CCEP, CHPC, CHRC, CHC
