The potential for AI to permeate almost every aspect of business is now widely recognized, and compensation planning is no exception. Boards of companies seeking to integrate AI into their operations, long-term strategies, and products are now facing a new set of questions. Should AI metrics be incorporated into incentive plans, and if so, how?
While it is still early days for most boards to navigate the intersection of AI and executive compensation, some are considering incorporating AI-related goals into their compensation programs. “So far, this has primarily been in annual bonus plans rather than as part of long-term incentives,” said Noah Kaplan, managing director at F.W. Cook, noting that this approach generally falls into one of two buckets.
In some cases, AI efforts are part of a bonus plan that covers broader strategic objectives, and the board evaluates progress on internal AI projects and implementation efforts. Such evaluations are usually done qualitatively, rather than against pre-set quantitative goals. For example, one company established AI-related KPIs tied to key business priorities where executives focused on AI literacy and enablement, and used KPI scoring to modify bonus plan funding based on top-line and bottom-line performance.
In another example, AI-related goals appear as part of selected executives' personal performance goals within a bonus plan. “We have seen the development and implementation of AI-related tools serve as part of the bonus decision process for executives responsible for these initiatives,” Kaplan explains.
Although interest in incorporating AI-related considerations into compensation programs is growing, adoption remains limited and cautious. Typically, strategic and personal performance goals are given a relatively low weight of 20 to 30 percent within a company's bonus plan, and goals related to AI are only part of the goals covered by these categories.
“There are big questions among businesses about how to deploy this effectively,” Kaplan said. “Also, the limited adoption and modest weighting of standalone AI metrics when used suggests that most companies are using these metrics to signal that AI adoption and innovation is a key focus area, rather than seeking incentives or rewards for specific AI outcomes.”
beyond the bonus
Some companies with AI-related products and technologies are going further by using product development milestones and quantifiable commercialization goals as funding metrics in their incentive plans. Salesforce stands out in this category by having AI-related initiatives built directly into its FY27 performance stock options, with 50% of its funding based on annual recurring revenue from Agentforce and Data 360, and 50% based on “Agent Work Units,” which measure individual tasks performed by AI agents in production across the Salesforce platform. Salesforce's introduction of this new AI metric aims to understand agent activity and customer engagement, not just contract revenue.
“This is one of the only publicly available examples of AI being built directly into a long-term incentive plan, and a company selling AI-related products that has a way to quantify performance,” Kaplan says. “For the majority of companies working on integrating AI for internal purposes, the quantification is not very clean.”
Another reason why boards have yet to incorporate AI metrics into their incentive plans is that the technology itself introduces significant uncertainty into the already far from certain science of long-term planning. “AI is seen as a potentially disruptive and paradigm-changing technology for many businesses,” Kaplan explains. “And even using very traditional metrics like revenue, profit, and return on equity, it’s already difficult to set reasonable multi-year performance targets.”
While AI is becoming central to long-term corporate strategy, its transformative potential can make it difficult for boards and executives to predict what their business, or competitive environment, will look like in the years ahead.
In fact, the growing influence of AI could have far-reaching implications for executive compensation design, beyond the AI-related goals themselves. As companies lean more toward AI-driven strategies, the unpredictability surrounding future business models and performance may make setting traditional multi-year financial goals more difficult, Kaplan said. “An indirect consequence of this could be a return to metrics tied to stock prices and total shareholder returns, or a reconsideration of stock options as capital instruments, all of which are strategically agnostic and reward the creation of shareholder value without relying on accurate long-term forecasting.”
Adopt and sustain AI
Demand for executives with deep AI expertise is also driving compensation committee discussions, with companies considering the need to pay premiums for key talent and special retention grants for technology leaders deemed essential. While overall compensation levels are flat due to a broader softening in the labor market, executives with AI capabilities and experience who can lead implementation, commercialization, and transformation efforts remain in high demand.
“Beyond the extreme example of moonshot awards like the one Meta recently awarded, we’re seeing companies of all sizes pay a lot of money to hire such talent and really work on the affordability front to acquire the AI skills they need,” Kaplan says. “The main way is through the amount of annual salary, but in some cases companies are looking to benefit by offering targeted retention incentives to retain key talent.”
As spending on AI leadership, infrastructure, and enterprise-wide transformation efforts continues to increase, investors may begin to pressure companies to measure whether those investments are actually creating value.
“Once companies define how best to quantify the return on AI investments, that becomes a logical bridge to incorporating relevant metrics into compensation programs,” Kaplan says. “At that point, the qualitative goals currently found in bonus plans may turn into quantitative metrics that are more meaningfully integrated into incentive plans.”
