The Six Dimensions of AI Vendor Evaluation That Matter Most

Artificial intelligence is moving from pilots to enterprise-wide adoption. The right vendor decision determines whether AI becomes a growth driver or a source of cost, risk, and lock-in.

This article provides the evaluation framework: six dimensions and a scorecard you can apply in RFPs, pilots, and renewals. For common traps to watch during selection, see: The Four Classic Pitfalls in AI Vendor Selection. For the business and reputational consequences of getting it wrong, see: The Hidden Costs of Choosing the Wrong AI Vendor.

Definition: The vendor’s ability to deliver robust, enterprise-grade AI beyond prototypes.

Assess:

- Supported modalities (text, vision, speech, structured data).

- Model/tool quality against relevant benchmarks and realistic workloads.

- Extensibility (fine-tuning, RAG, guardrails APIs).

- Observability (drift, accuracy, latency, usage).

Note: For why demos often fail to translate to production, see the Pitfalls article (PoCs that never scale). Keep this section focused on how to evaluate depth rather than recounting failures.

Definition: How seamlessly the platform fits your systems, data, and workflows.

Assess:

- Native connectors (ERP/CRM/HR/data platforms) and standards (OpenAPI, REST/GraphQL).

- Identity/networking (OAuth/OIDC/SCIM, VPC, private networking, IP allowlists).

- Deployment options (cloud, on-prem, hybrid) and data residency.

- Lifecycle effort (initial integration, upgrades, change management).

Outcome: Lower lift to adopt and operate; fewer brittle customizations.

Definition: Controls that protect data and meet regulatory requirements from day one.

Assess:

- Encryption at rest/in transit, key management, tenant isolation.

- Attestations (SOC 2, ISO 27001) and sector controls (e.g., HIPAA), GDPR practices.

- Privacy features (segregation, zero-retention, redaction, DSR/RTBF workflows).

- Regulatory readiness (e.g., EU AI Act alignment) and auditability.

Tie-in: For consequences of gaps (fines, trust erosion), see Hidden Costs.

Definition: Consistent performance as usage expands across teams and regions.

Assess:

- Elastic scaling, multi-region HA/DR, capacity planning.

- Enterprise-fit quotas/rate limits and performance SLOs.

- Roadmaps for throughput/latency improvements and cost efficiency.

Result: Predictable service at growth inflection points.

Definition: The vendor’s commitment to ongoing success beyond a sale.

Assess:

- SLAs (uptime, response, escalation) and named CSM/TAM.

- Enablement (docs, training, sandboxes) and solution engineering.

- Partner ecosystem and professional services.

Signal: A repeatable success model, not one-off heroics.

Definition: Freedom to adapt and avoid lock-in as the landscape evolves.

Assess (solution-oriented):

- Portability of models, data, prompts/workflows.

- Interoperability and open standards.

- Modular architecture enabling component swaps.

- Contractual protections (export, exit assistance, escrow where relevant).

Note: The mechanics and risks of lock-in are covered in Pitfalls and Hidden Costs; keep this section focused on how to evaluate flexibility.

Operationalize the six dimensions with a weighted scorecard aligned to business priorities:

1) Define weights (e.g., security for regulated sectors; scalability/flexibility for fast-growth teams).

2) Convert each dimension into objective criteria and evidence requests.

3) Run structured pilots tied to KPIs and SLOs.

4) Require transparency (security docs, roadmaps, references).

5) Bake in exit and portability terms at contracting.

For pitfalls to anticipate during evaluation, see the Pitfalls article. For executive alignment on why the rigor matters, see Hidden Costs.

Use these six dimensions as your backbone for selection, renewal, and governance. Keep pitfalls in view to pressure-test vendors, and use the Hidden Costs narrative to align stakeholders on the business stakes.