Companies Buy AI Licenses, Employees Use Them to Find Lunch

AI cut one company's time-to-hire from 56 days to 39, with more than 90 percent of hiring managers approving the process — but the tools weren't the reason. How employees were brought along was.

That's the argument from Jonathan Starling, Learning and Development Expert and HIC C-Level AI Cohort Graduate, whose implementation results offer a counterpoint to a pattern now visible across corporate America: companies buy AI, employees don't transform anything.

The pattern is expensive. Most AI rollouts start with a purchase order, according to a recent Inc. commentary by Netta Jenkins, founder of leadership performance firm HIC and author of Supercharged Teams. A company buys hundreds of licenses, sends a launch email, and watches logins climb. Three months later, someone in finance asks what the company got for the money. Nobody has a good answer.

What are employees actually doing with corporate AI?

At a recent AI adoption event in New York, a recurring theme emerged: employees were using their company's AI tools to find lunch spots and proofread emails. Useful, perhaps — but not the business transformation executives had in mind.

Jenkins puts the gap bluntly: a lot of companies are paying premium prices for a search engine. Login counts climb while high-value work stays untouched.

The question she raises is direct: how can organizations move beyond basic AI usage and get employees applying the technology to meaningful business challenges?

Who says people matter more than tools?

Starling does. He recommends starting with people, not technology. His approach focuses on four things:

• Building trust
• Equipping managers
• Redesigning workflows
• Measuring business outcomes — not simply counting logins

The distinction matters. Logins are an adoption metric that says nothing about business impact. Business outcomes are the number finance eventually asks for.

Starling's framework was sharpened through HIC's C-Level AI Cohort, a program whose graduates include executives applying AI to operational problems rather than novelty use cases.

What kind of results does proper enablement produce?

The business impact can be significant, Jenkins reports.

According to Starling, with proper planning and employee enablement:

• Product launch and sales enablement timelines can be cut in half
• Customer success managers can move from manually digging through accounts to identifying upsell and cross-sell opportunities almost instantly
• AI-powered sourcing and screening can compress hiring cycles by 17 days — from 56 to 39 — while winning approval from more than 90 percent of hiring managers

"In one implementation, AI-powered sourcing and screening reduced time-to-hire from 56 days to 39, with more than 90 percent of hiring managers approving the process," Starling said. "An internal engagement survey rated AI adoption 80 percent favorable."

That 80 percent favorable rating is the quiet headline. Adoption surveys in forced rollouts rarely score that high; employees who feel equipped tend to rate the technology they use.

What's the takeaway for buyers?

The tools weren't the reason for these results. How employees were brought along was.

For executives weighing their next license renewal, the math is straightforward: a rollout measured in logins bought three months of lunch-spot searches, while a rollout measured in business outcomes cut a hiring cycle by nearly a third. The license cost is the same either way.