Enterprise
Evaluating enterprise AI and cloud software: a buyer's framework
A single enterprise software or AI contract can run six or seven figures a year for a decade. The people who sign those contracts need a way to compare vendors that goes beyond the demo.
Start with the decision, not the tool
Most failed AI deployments trace back to an unclear question. Before evaluating platforms, define the workflow being changed, the metric that will move, who owns the outcome, and what the current process costs. A vendor that cannot map its product onto that definition is selling a capability, not a result.
Questions for any AI or cloud vendor
- Data handling
- Where is data stored and processed? Is customer data used to train models? Can you require a specific region for residency? Is there a documented deletion process?
- Security posture
- SOC 2 Type II at minimum; ISO 27001; HIPAA business-associate agreements where health data is involved; FedRAMP for public-sector work. Ask for the most recent penetration test summary.
- Model governance
- Which underlying models are used, can they be pinned to a version, and what is the notification process when a model changes? How are hallucinations, bias and drift monitored?
- Pricing mechanics
- Per-seat, per-usage (tokens, API calls, compute hours), or platform fee plus usage. Model your cost at 3× expected adoption, because usage-based pricing punishes success.
- Exit
- Data export format, contract termination terms, and what happens to fine-tuned models or embeddings you paid to create.
Build, buy or partner
- Buy when the workflow is common across your industry and the vendor has more training data than you ever will.
- Build on foundation-model APIs when the differentiation is in your proprietary data and process, and you have the engineering capacity to maintain it.
- Partner with a systems integrator when the problem is organizational change rather than technology.
Measuring the result
Run a time-boxed pilot with a control group and a pre-agreed success threshold. Measure cycle time, error rate and cost per transaction, not user sentiment. Budget for the change-management and integration work, which routinely exceeds the software cost in year one.
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