How Leaders Measure AI Outcomes in IT and Networking

Tabby Worthington
AI outcomes, ajay malik, customer experience, Executive decision-making, Go Beyond the Connection Podcast, greg davis, IT leadership, Measuring reliability

Why Measuring AI Outcomes in IT Matters

AI demos may look impressive, but executives aren’t swayed by flashy presentations. For business leaders, the only question is whether AI improves the outcomes they track every quarter: uptime, customer satisfaction, and operational efficiency. In this segment of Go Beyond the Connection, Greg Davis (Bigleaf Networks) and Ajay Malik (StudioX AI) explain why measuring AI outcomes in IT is the difference between hype and long-term value.

Executive Metrics That Matter

Business leaders view AI through the lens of risk and return. Davis and Malik highlight the top three outcomes executives expect to see:

Uptime: The most direct measure of reliability, and a non-negotiable expectation.
Customer Experience (CX): Fewer support tickets, smoother digital interactions, and higher NPS.
Operational Efficiency: AI should lower costs by deflecting tickets and reducing mean time to resolution (MTTR).

When IT leaders report on AI projects, these are the outcomes that resonate in the boardroom.

Key Takeaways for IT Leaders

Executives see AI as a business tool, not a technical experiment.
Outcomes like uptime and NPS should be built into every AI evaluation.
Reporting on AI should use the language of finance and customer success, not just technical jargon.

“Demos don’t matter if uptime and customer experience don’t improve.” — Greg Davis

Highlights from the Segment

Greg Davis explains how CEOs frame AI adoption as risk mitigation and trust-building.
Ajay Malik shares how aligning AI with measurable KPIs makes it easier to secure executive buy-in.
Both stress that winning budget requires clear proof of business outcomes, not abstract performance metrics.

Closing: Framing AI in Executive Terms

If you want to sell AI internally, don’t focus on features—focus on outcomes. By presenting reliability, CX, and cost savings in executive language, IT leaders can turn AI from a technical curiosity into a trusted business strategy.