AI’s True ROI: Betsy Tong Questions If More Time Equals Better Results

In a recent LinkedIn post, Betsy Tong challenges a common assumption about the return on investment for artificial intelligence, arguing that simply saving time doesn’t automatically translate to improved business outcomes. Tong highlights a survey by BCG, which found that while 42% of regular AI users claim to save at least a full day per week, a significant 66% reported being unsure what to do with the extra time.

This disconnect, according to Tong, means that increased efficiency doesn’t always lead to tangible business improvements.

“More time didn’t automagically become a better result. More customers served. Faster decisions. Less spending. More revenue. Better quality.”

Tong illustrates this point with a hypothetical scenario involving an analyst. She explains that while AI could cut the time to create a business case from two months to two hours, the bottleneck doesn’t disappear. If the review and approval process still requires multiple people and remains unchanged, the company’s overall output doesn’t increase.

The Bottleneck of Approval Processes

Betsy Tong points out that in her example, the analyst’s increased speed exacerbates the problem for the review team.

“It still takes 9 people to review and approve. Their approval pending queue got longer. Their overload just grew.”

This situation, as Tong describes, leads to a scenario where the individual is more efficient, but the company as a whole does not benefit from faster decision-making or increased output. The extra time generated by AI is absorbed into existing backlogs, rather than being redirected to higher-value activities.

Rethinking AI Implementation and Measurement

To address this potential pitfall, Tong advises organizations to ask critical questions before adopting AI solutions. She suggests a shift in focus from simply measuring time saved to understanding the impact on actual business results.

Key Questions for AI ROI Assessment

Tong poses several crucial questions that businesses should consider:

• What work stops when AI is implemented?
• What specific results are expected to change?
• Who will benefit from higher quality output?
• Who is responsible for checking AI exceptions?
• What concrete numbers will prove the success of the AI implementation?

By posing these questions, Tong aims to encourage a more strategic approach to AI adoption, ensuring that the technology leads to genuine business value rather than just creating a larger backlog of work.

“Did AI create better work, or just a bigger backlog?”

In essence, Betsy Tong’s insights on LinkedIn serve as a critical reminder for leaders to look beyond the immediate time savings offered by AI and to meticulously plan for how that freed-up time will be leveraged to drive meaningful business improvements and measurable ROI.