Intelligent Software. Enterprise Ready.
Enterprise AI sales pitches are calibrated for the boardroom, not the server room. Drawing on the candid admissions of implementation consultants, this piece examines what vendors say once procurement signs off — and how buyers can pull those truths forward before the ink dries.
Plenty of vendors have discovered that slapping 'AI-powered' on a legacy product converts better than rebuilding it. Here are five diagnostic signs that your AI strategy is really just a software upgrade wearing a new label — plus litmus tests your team can run this week.
The most valuable components of an enterprise AI stack are the ones nobody demos — routing layers, fallback logic, and observability pipelines that absorb failure before anyone notices. This piece argues that CTOs should evaluate vendors on how gracefully their systems degrade, not how impressively they perform.
The dominant narrative in enterprise AI sells consolidation: one vendor, one platform, one contract. The engineering reality points the other way — toward a composable stack of specialized components that can be upgraded, replaced, and governed independently.
A growing share of 'AI-powered' enterprise software is a foundation model behind a login screen, marked up several hundred percent. Buyers deserve better — and the demo room is where the truth comes out, if you know which questions to ask.
Flashy demos are easy; enterprise-grade AI is not. This checklist breaks down the seven measurable criteria — from SOC 2 attestation to total cost of ownership — that separate serious platforms from well-funded vaporware.
Roughly 70% of enterprise AI projects never survive to production, and the autopsy almost always reveals the same wounds. The fix isn't better models — it's a radically different procurement mindset from the C-suite down.