Avoiding AI Pitfalls in Networking: A Guide for IT Leaders

Tabby Worthington
AI governance, AI pitfalls, ajay malik, Business Continuity, Go Beyond the Connection Podcast, greg davis, it strategy, Reliable networking

Why Avoiding AI Pitfalls in Networking Is Critical

AI has enormous potential to transform IT operations, but it’s not a silver bullet. For every success story, there are projects that overpromise, underdeliver, or even damage trust when outcomes don’t materialize. In this segment of Go Beyond the Connection, Ajay Malik (StudioX AI) and Greg Davis (Bigleaf Networks) share a pragmatic roadmap for avoiding AI pitfalls in networking—and ensuring that investments in AI deliver measurable reliability.

The Most Common AI Pitfalls

Malik points out that many AI initiatives stumble for predictable reasons. IT leaders should be on guard against:

Vendor hype: Choosing AI tools based on buzzwords or flashy demos rather than proven results.
Scaling too soon: Expanding pilots before measurable outcomes are validated, leading to wasted spend and eroded credibility.
Ignoring model drift: Treating AI as “set and forget,” which often results in performance degradation and unreliable insights.

Each of these pitfalls can undermine executive trust and stall broader AI adoption.

Key Takeaways for IT Leaders

Start small: pilot AI projects, measure rigorously, then scale.
Maintain ongoing governance to keep AI reliable over time.
Partner with vendors who emphasize measurable business outcomes, not just innovation theater.

“The danger isn’t AI itself—it’s adopting AI without accountability.” — Ajay Malik

Highlights from the Segment

Ajay Malik describes how IT teams can build guardrails for AI adoption that protect long-term reliability.
Greg Davis shares examples of customers who avoided costly mistakes by focusing on business outcomes first.
Both emphasize the importance of executive alignment and measurement frameworks before scaling any AI investment.

Closing: Building Trust Through Accountability

AI can be a powerful ally in network management, but only if it’s applied responsibly. By avoiding hype-driven decisions, ensuring governance, and proving outcomes before scaling, IT leaders can turn AI into a strategic advantage.