The AI That Works Is Beating The AI That Wows

Billy Biggs leads KnowledgeLake’s strategy and growth, bringing over 25 years of SaaS leadership.

The Department of Veterans Affairs cut average disability claims processing time from 141 days to 81, a 42% reduction, and pushed its backlog below 100,000 for the first time since 2020. There was no keynote for it. It was covered as a staffing story, not a technology one, and that’s the right read. The point was never the AI. It was that case files requiring real human interpretation now move faster through an agency that has lost nearly 2,700 claims examiners since January 2025. But the same coverage flagged a gap: 94% accuracy at the issue level, 83% at the claim level. As the son of a veteran, I know what sits behind that second number: a family waiting on a decision that shapes the next chapter of their lives. Speed is the easy part. The real test is whether you can trace, explain and stand behind every decision at the end of a mission-critical workflow.

​Two-Thirds Of Your AI Budget Never Gets Opened

Back-office functions—finance, HR, payroll, compliance, data entry—are not a rounding error. The Hackett Group puts median SG&A costs at 14.3% of revenue across the largest US public companies, the highest in five years and only 17.9% of them cut those costs last year. That is an enormous, mostly manual cost base that has sat in plain sight for decades, waiting for someone to act.

Now that AI has been applied, the results are not subtle. Deloitte found that organizations that moved past piloting intelligent automation cut costs by an average of 32%. The VA numbers are not an outlier. They are the pattern repeating itself, in function after function, at companies that never bothered to put out a press release about it.

This Is Where Value Selling And AI Meet

The Moat Isn’t The Model​

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