Software vendors keep pitching our leadership team on AI-driven upgrades that promise massive operational transformations. How do we filter out the software theater and determine if an AI tool actually solves a core business issue?

Question

Tyler Smith · Accepted Answer

Most enterprise software companies have slapped an AI label on basic feature updates to justify price hikes and renewal upsells. If you listen to software sales reps, every department in your business is falling behind without their proprietary machine learning algorithms.

To filter out the theater, implement a strict evaluation rule for your leadership team: never buy an AI tool to solve an undefined problem. Machine learning should only be considered as a footnote to a documented operational bottleneck.

When a vendor pitches an AI platform, force the conversation through these operational checkpoints:

- What documented step in our core process does this software replace or accelerate? If the vendor cannot pinpoint the exact operational step their tool optimizes, end the demo.
- Can the tool function on our existing clean data without requiring months of custom integration? If it requires an expensive systems overhaul, the tool is a distraction, not an asset.
- Does the vendor accept financial risk? Ask for a sixty-day pilot tied directly to an operational measurable on your Scorecard. If the vendor insists on an annual contract upfront with no performance-based exit, their technology likely underdelivers.

Never let a vendor sell you AI for the sake of AI. If an upgrade does not directly expand gross margin, lower customer turnaround time, or protect operational capacity, kill it during your weekly Level 10 Meeting and keep your focus on your Rocks.