Your Company Is Measuring the Wrong Thing About AI | Opinion

Companies are rushing to incorporate AI, yet many are measuring the wrong metric: whether personnel are utilizing the tools, rather than whether the business is truly enhancing. Boards and executives ought to seek proof that AI boosts productivity, sharpens judgment, safeguards institutional knowledge, and generates concrete financial value, not merely evidence that staff are logging in.

This issue extends beyond technology divisions. AI is already altering how individuals work, how customers engage with firms, and how leaders allocate resources. According to Boston Consulting Group (BCG), 50 to 55 percent of U.S. roles could be influenced by AI within the next two to three years, while 10 to 15 percent could potentially vanish over an extended period.

The fundamental business inquiry is not if work will change; it is if organizations will handle that evolution intelligently. I am apprehensive that many are beginning at the incorrect point. Executives purchase a tool because AI is trendy, then prompt employees to discover something to do with it. That is the wrong approach. AI should initiate with a business issue, a baseline, and a definition of success.

The difference is vital as automating a task does not inherently enhance a business. Saving five hours is insignificant if those hours merely vanish into additional meetings. An expeditious report is not beneficial if it contains more errors. And downsizing based on projected productivity gains can erode institutional knowledge before those gains ever come to fruition.

I have witnessed AI functioning remarkably well when it is viewed as a thought partner rather than an oracle. In financial modeling, for instance, I desire humans to construct the main model, comprehend the assumptions, and challenge the business logic. AI can then aid in testing formulas, incorporating intricate updates, summarizing changes, and expediting iteration.

The technology streamlines the work; human discernment refines it. That human component is becoming increasingly crucial, not less. As BCG's research underscores, many occupations are likely to be restructured rather than eliminated. The opportunity lies in shifting personnel from repetitive, reactive duties to judgment, creativity, relationships, and strategic problem-solving.

When executed properly, AI can make a workforce more proficient. Employees can acquire new skills, companies may diminish certain forthcoming hiring requirements, and productivity gains can be reinvested into growth. When executed improperly, the reverse occurs. Companies applaud adoption while workflows become disjointed, employees receive insufficient training, multiple tools duplicate each other, and tacit knowledge leaves the organization.

The organization may appear leaner on paper but weaker underneath. That is not transformation; it is hollowing out the business and labeling it efficiency. Boards and CFOs need a superior benchmark: an AI value scorecard established prior to implementation and examined post-deployment. Financial measures should encompass total expenditure, revenue impact, margins, cash flow, payback, and return on investment.

Operational measures should include cycle time, error rates, rework, cost per output, and whether AI is integrated into genuine workflows instead of being merely utilized. Human measures should monitor training, employee sentiment, retention, skill development, and, most crucially, where the time generated by AI ultimately goes.

Risk and discernment should also reside on the scorecard. Executives should be aware of how frequently AI output necessitates correction, whether decisions improve, and whether security, compliance, or precision issues arise. These are not secondary concerns. They impact profitability, customer trust, succession planning, and long-term enterprise value.

The prospect is evident. AI can eliminate monotonous work, provide employees with more time for strategic duties, refine processes, and convert productivity gains into growth. However, the ramifications of getting it wrong are equally severe. Businesses can pursue adoption metrics, prematurely cut costs, lose vital expertise, and become more reliant on systems they do not adequately grasp or evaluate.

Boards and executives must cease treating AI adoption as the culmination. Before endorsing a significant AI investment, establish the baseline, define the business outcome, assign quantifiable financial and operational targets, and decide how human impact will be monitored. Then automate the dashboard and examine the results regularly.

Remember that AI does not create value simply due to its usage. It generates value when people employ it to construct a superior business. Heather Hall, CPA and CGMA, is the founder of Sapphire CFO Solutions, where she counsels companies and boards on financial strategy, governance, operational expansion, and technology investment. The perspectives presented in this article are the author's own.