The likelihood that AI will infiltrate nearly every facet of business is now widely acknowledged, and compensation planning is no exception. The boards of companies striving to integrate AI into operations, long-term strategy and products now face a new set of questions: Should AI metrics be embedded in incentive plans, and, if so, how?
While it’s still early days for most boards navigating the intersection of AI and executive pay, some are exploring incorporating AI-related goals into their compensation programs. “Where we’ve seen this so far is principally in annual bonus plans rather than as part of long-term incentives,” says Noah Kaplan, a managing director at FW Cook, noting that the approach generally falls into one of two buckets.
In some cases, AI initiatives are incorporated within the part of the bonus plan covering broader strategic goals, with boards evaluating progress on internal AI projects or adoption efforts. Such assessments are generally performed on a qualitative basis, rather than against pre-established quantitative targets. For example, one company has established AI-related KPIs tied to critical business priorities that focus executives on AI literacy and enablement, with scoring of the KPIs used to modify bonus plan funding that is based on top- and bottom-line performance.
In others, AI-related goals appear as part of select executive’s individual performance goals within the bonus plan. “We have seen cases where the development or deployment of AI-related tools served as part of the bonus determination process for the executives charged with those initiatives,” Kaplan explains.
While interest in integrating AI-related considerations into compensation programs is growing, adoption remains both limited and cautious. Strategic and individual performance goals are generally assigned a relatively low weighting of 20 percent to 30 percent within companies’ bonus plans, and goals tied to AI make up only a portion of what is covered by these categories.
“There are real questions among companies about how to roll this out in an effective manner,” says Kaplan. “And limited adoption of standalone AI metrics and the modest weighting where used, indicate that rather than seeking to incent or reward for specific AI outcomes, most companies are using these metrics to signal that AI adoption and innovation are an important area of focus.”
Beyond the Bonus
Some companies with AI-related product or technology offerings go a bit further, employing product development milestones or quantifiable commercialization goals as incentive plan funding metrics. Salesforce stands out in this category by incorporating AI-related measures directly into its FY27 performance stock option award, with funding based 50 percent on Agentforce and Data 360 annual recurring revenue, and 50 percent on “Agentic Work Units,” which measures discrete tasks executed by AI agents in production across the Salesforce platform. Salesforce’s introduction of this new AI metric is intended to capture agentic activity and customer engagement rather than simply contracted revenue.
“That’s one of the only disclosed examples of AI being directly incorporated into a long-term incentive plan, and it’s a company selling an AI related product for which there’s a way to quantify performance,” says Kaplan. “Quantification is less clean for the majority of companies that are working to integrate AI for internal purposes.”
Another reason boards have yet to embed AI metrics into incentive plans is that the technology itself introduces enormous uncertainty into the already-far-from-certain science of long-term planning. “AI is viewed as a potentially disruptive and paradigm-changing technology for many businesses,” Kaplan explains. “And setting reasonable multi-year performance goals—even using very conventional metrics like revenue, profit or return on capital—is already challenging.”
While AI is increasingly central to long-term corporate strategy, its transformative potential can make it difficult for boards and management teams to predict what the business—or the competitive landscape—will look like several years from now.
In fact, the growing influence of AI may have broader implications for executive compensation design beyond AI-related goals themselves. As companies lean further into AI-driven strategies, the unpredictability surrounding future business models and operating results could make traditional multi-year financial goal setting more difficult, says Kaplan. “An indirect consequence of this may be a shift back toward metrics tied to share price or total shareholder return, or a re-examination of stock options as an equity vehicle, all of which are strategically agnostic and reward for shareholder value creation without relying on precise long-term forecasting.”
AI Recruitment and Retention
Demand for executives with deep AI expertise is also prompting conversations in compensation committees, as companies weigh the need to pay a premium for critical talent or consider special retention grants for technical leaders viewed as indispensable. While overall compensation levels have flattened in tandem with a broader softening of the labor market, executives with the AI capability and experience to lead implementation, commercialization and transformation efforts remain highly sought after.
“Beyond the extreme examples of moonshot awards like those recently granted by Meta, we’re seeing companies of all sizes paying big dollars to recruit such folks, and really pushing themselves in terms of affordability to acquire the AI skills they need,” says Kaplan. “The principal path is through the quantum of annual pay, but in some cases companies are leaning in by providing targeted retention awards to help lock in key talent.”
As spending on AI leadership, infrastructure and enterprise-wide transformation efforts continue to escalate, investors may begin pressing companies to measure whether those investments are actually creating value.
“As companies get clarity around the best way of quantifying returns on AI investment, it will serve as the logical bridge to incorporating related metrics into compensation programs,” says Kaplan. “At that point, the qualitative goals that we are currently seeing in bonus plans will likely morph into quantitative metrics that are more meaningfully integrated into incentive plans.”
