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Yes—but only if you manage the provider as a critical supplier rather than as ordinary software. Classify the dependency by data sensitivity, operational impact, replacement time and regulatory exposure. Put security, data rights, service levels, incident duties and exit assistance in the contract; verify the provider’s controls independently; and test that you can move prompts, data and workflows elsewhere.
If an outage would stop an important process, the provider can change terms without useful notice, or your team cannot export and validate its work, do not make that service mission-critical yet. Keep the workload low-impact, add a tested second option, or retain a manual or self-hosted fallback.
What “depending on one AI provider” really means
Private AI can mean a hosted model service restricted to your organization, a dedicated tenant, or a provider operating models and data under a bespoke agreement. The privacy boundary may be stronger than a public consumer tool, but it does not remove supplier risk. The provider still controls infrastructure, model versions, APIs, support processes, subprocessors and often the logs needed to reconstruct a decision.
Dependency is therefore a business-risk decision, not a technology preference. A useful classification asks four questions:
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| Dimension | Questions to answer | Why it changes the decision |
|---|---|---|
| Data sensitivity | Will the service receive personal data, confidential business information, regulated records, source code, embeddings or customer communications? | More sensitive data requires stronger processing limits, location controls, access controls and deletion evidence. |
| Operational criticality | Which process stops after one hour, one day or one week without the provider? | A service used for optional drafting can tolerate an outage that would be unacceptable in payment, support, safety or production workflows. |
| Replacement time | How long would it take to move prompts, configurations, evaluations, integrations and staff to another provider? | Long migration time turns a temporary outage or price change into a business continuity problem. |
| Regulatory impact | Does the use affect employment, credit, health, safety, access to services or other legally protected interests? | Role-specific duties, documentation and human oversight may apply even when the provider calls the system “private.” |
Record the classification in your supplier register and assign an owner. A high-impact, hard-to-replace service deserves critical-supplier controls; a low-impact experiment may only need basic privacy review and a spending limit.
Business-dependency checklist
Map the failure you would actually experience
- List every workflow that calls the provider, including scheduled jobs, customer-facing features, internal search, summarization and agent actions.
- For each workflow, define the tolerable interruption at one hour, one day and one week. Include manual workarounds and their staffing cost.
- Inventory what leaves your environment: prompts, uploaded files, embeddings, outputs, conversation history, telemetry, evaluation sets and administrator activity logs.
- Estimate migration time and cost, including prompt rewriting, integration changes, re-testing, user training and legal review.
- Identify a fallback: a second provider, a local model, a queued-and-retry design or a documented manual process. “We could switch” is not a fallback until it has been exercised.
Set a dependency tier
| Tier | Typical use | Minimum operating posture |
|---|---|---|
| Low | Non-sensitive brainstorming or a pilot with no customer commitment | Approved data types, basic access control, spending cap and an owner. |
| Important | Internal productivity or a customer feature with a documented manual workaround | Contractual privacy terms, service targets, incident notice, export plan and periodic evaluation. |
| Critical | A process whose outage causes material revenue, safety, contractual or regulatory harm | Evidence-backed security review, recovery commitments, change notice, tested failover, executive ownership and a rehearsed exit. |
Do not use a provider’s “enterprise” label as the tier. Your own impact analysis determines the controls.
Security and privacy due diligence
Require evidence, not assurances
The Federal Trade Commission’s vendor guidance is blunt: “Put it in writing” and “Don’t just take their word for it.” Ask for current independent assurance or assessment evidence, the scope and date of that evidence, exceptions, remediation status and the process for updating controls as threats change. A security badge, sales presentation or generic policy page is not a substitute for evidence covering the service you will use.
Your review should address:
- Identity and access: SSO, multifactor authentication, role-based administration, privileged-access review, service-account handling and prompt-level authorization.
- Cryptography: encryption in transit and at rest, key ownership options, key rotation and protection of backups.
- Tenant isolation: separation of your data, model artifacts, logs and administrator actions from other customers.
- Vulnerability management: scanning, patch timelines, dependency management, penetration testing and disclosure handling.
- Incident response and recovery: detection, containment, customer communications, recovery-point objectives (how much data could be lost) and recovery-time objectives (how long restoration should take).
- Subprocessors: a complete, current list; each subprocessor’s function and location; notice and objection procedures for additions.
Ask direct data-use questions
Get unambiguous answers to whether customer inputs and outputs train any model, whether humans can review them, where processing and support occur, how long each category of log remains, and how deletion is verified in primary systems, caches and backups. Distinguish deletion of content from deletion of metadata such as account identifiers, timestamps and abuse records. If retention varies by product, region or support channel, write the variation into your data-processing documentation.
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Check that the provider can restrict administrator access, produce access logs, separate test data from production data and honor legal holds without silently retaining everything forever. Require notification when a subprocessor, processing location or model-training practice changes.
Contract terms that prevent surprises
Commercial terms are part of the security boundary. Attach a service description and data-processing terms to the agreement rather than relying on a web page that can change without negotiation.
| Contract area | What to specify | Questions to test before signing |
|---|---|---|
| Permitted processing | Purpose limitation, prohibited uses, geographic processing boundaries and instructions for each data class. | Can the provider use prompts or outputs for training, abuse analysis or product improvement? Can you opt out contractually? |
| Ownership and license | Your rights in inputs, outputs, prompts, fine-tunes, retrieval indexes, evaluation data and generated artifacts. | Can you reuse and export them after termination? Does the provider claim a continuing license? |
| Retention and deletion | Retention periods by data type, deletion deadlines, backup treatment and written deletion certification. | What evidence will you receive, and what is excluded for security or legal-retention reasons? |
| Incident notice | Notice deadline, required details, cooperation, evidence preservation and allocation of response costs. | Does the clock start at discovery, confirmation or a regulator’s notice? |
| Audit and assurance | Independent reports, questionnaire rights, targeted assessments for material risk and remediation tracking. | Can you investigate a serious issue without accepting an unrestricted audit prohibition? |
| Subprocessors | Disclosure, advance notice, objection and equivalent obligations downstream. | Can a new subprocessor change data location or access without practical notice? |
| Service levels and support | Availability target, latency or quota commitments, maintenance notice, support severity levels and recovery objectives. | Are credits the only remedy, or can repeated failure trigger termination? |
| Change and suspension | Notice periods for model, API, policy, price and location changes; safeguards against abrupt suspension. | What happens to queued jobs, stored data and customer access during a dispute or abuse investigation? |
| Termination and transition | Export formats, transition assistance, continued read-only access, deletion timing and survival of confidentiality duties. | Can you retrieve everything needed to rebuild the workflow before the account closes? |
Include a practical change-notice period. A provider that can retire a model, alter an API schema or move processing to another jurisdiction overnight can create more risk than an outage. Define what counts as a material change and give your business time to test and migrate.
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Compare model and service performance for your workload
A private deployment can still produce unacceptable answers or become too expensive at scale. Evaluate the service with your own representative, approved data and a repeatable test set; do not rely solely on a public leaderboard or a provider’s broad accuracy claim.
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| Capability | Evidence to collect | Decision implication |
|---|---|---|
| Accuracy and task fit | Task-specific evaluation results, error categories, refusal behavior and performance by language or document type. | A lower-cost model may be unsuitable if human correction erases the apparent saving. |
| Latency and capacity | Observed response times, concurrency limits, quotas, batch behavior and peak-period performance. | Design queues or capacity reservations when interactive limits would interrupt operations. |
| Availability and recovery | Published uptime history, maintenance practice, incident record and contractual recovery commitments. | Separate a marketing uptime figure from a remedy that supports your business continuity plan. |
| Version transparency | Model identifiers, deprecation windows, release notes, behavior-change notices and rollback options. | Unannounced behavior changes can invalidate evaluations and regulated documentation. |
| Safety and escalation | Abuse controls, content filtering, red-team information, human escalation and appeal handling. | Safety must be observable and adjustable for your use case, not merely asserted. |
| Integration and observability | Stable APIs, authentication, audit logs, metrics, tracing and alerting. | You need enough visibility to diagnose a bad output or outage without provider-only tooling. |
| Portability and cost | Export formats, compatible interfaces, token or usage pricing, support fees and migration effort. | Total cost includes concentration risk and the engineering work needed to leave. |
Keep a dated evaluation set and rerun it after model, prompt, retrieval, policy or data changes. Record both quality and failure severity; an average score can hide a rare but unacceptable error.
Use a repeatable governance method
The NIST AI RMF Playbook organizes work into Govern, Map, Measure and Manage, and states that it is based on AI RMF 1.0. Use those functions to assign owners and preserve evidence rather than treating the provider review as a one-time questionnaire.
Govern
- Name the business owner, technical owner, security reviewer, privacy counsel and compliance contact.
- Set risk appetite, approval thresholds, escalation paths and review frequency.
- Require records for contracts, assessments, incidents, model changes, evaluations and exceptions.
Map
- Describe the intended use, affected people, data flows, human decisions and downstream systems.
- Identify foreseeable misuse, discrimination, privacy loss, security compromise and availability harm.
- Map provider and subprocessor roles so that responsibilities are not lost between organizations.
Measure
- Test accuracy, robustness, privacy controls, security, resilience, transparency and human-oversight effectiveness.
- Track incidents, near misses, latency, quota failures, drift and unexplained output changes.
- Compare results with the documented acceptance criteria for each workflow.
Manage
- Prioritize mitigations by impact and deadline, then verify that they worked.
- Pause, restrict or retire a use when evidence no longer supports the risk decision.
- Review the provider after material changes, incidents, new data types or changes in law.
NIST’s trustworthiness dimensions include security, resilience, privacy, accountability and transparency. They are useful prompts for supplier questions, but they do not replace a contract or a workload-specific risk decision.
Regulatory duties depend on role and jurisdiction
Do not assume that a private arrangement removes regulatory obligations. Determine whether your organization is a provider, downstream provider or deployer, what the system does, and where affected people are located.
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For European Union exposure, the European Commission states that obligations for providers of general-purpose AI models entered into application on 2 August 2025, while Commission enforcement powers for those obligations enter into application on 2 August 2026. High-risk systems have separate timelines and duties. Your review may need to cover technical documentation, copyright-related obligations, transparency, risk management and fundamental-rights considerations, depending on the role and use case.
Ask the provider which obligations it accepts contractually and which evidence it will supply. Then document your own deployer responsibilities; a vendor’s compliance statement does not transfer every duty to the customer.
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Define the portable asset set
Before signing, list the artifacts required to recreate the service elsewhere:
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- System and developer prompts, templates, routing rules and safety policies.
- Source documents, metadata, embeddings, retrieval indexes and chunking settings.
- Fine-tuning data, adapters, model parameters and preprocessing code where applicable.
- Evaluation datasets, expected answers, scorecards and approval records.
- Conversation and job history, audit logs, usage records and configuration exports.
- Integration code, schemas, authentication assumptions, rate-limit handling and monitoring rules.
For each item, record format, owner, export method, frequency and whether the provider includes it in its standard API. “Export available” is insufficient if the export is proprietary, incomplete or available only after termination.
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Test a second path
- Create a small, sanitized copy of the production workflow and its evaluation set.
- Implement an adapter so application code is not tied to one provider’s request and response format.
- Run the same tests against a second provider, a self-hosted model or a manual process.
- Compare quality, latency, safety behavior, cost and staff effort; define acceptable differences in advance.
- Document the traffic-switch procedure, credentials, data synchronization and rollback steps.
- Repeat the test after major model or API changes, not only during procurement.
Portability rarely means identical outputs. It means the business can preserve required records, operate within an accepted quality range and continue serving users while the replacement is tuned.
Obtain deletion evidence
At exit, export the agreed asset set, disable access, revoke keys, confirm subprocessor deletion and obtain a dated certificate or equivalent evidence. Reconcile the provider’s deletion statement with your own inventory, including backups and support systems. Retain only the records you are legally required to keep.
Rehearse the failure scenarios
Run a tabletop exercise before declaring the provider critical. Include participants from operations, security, legal, communications and customer support. Walk through these scenarios:
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- Sudden price increase or quota reduction: Which workloads are throttled first, and what approval is needed to spend more?
- Model retirement or behavior change: How are evaluations rerun, prompts revised and regulated records updated?
- Data incident: Who receives notice, which logs are preserved, and how are affected people and regulators assessed?
- Regulatory restriction: Can you pause the affected use while keeping unrelated operations running?
- Provider acquisition or failure: Where are contracts, data and support obligations transferred, and how quickly can you invoke the exit plan?
The exercise is successful only when the team demonstrates export, traffic switching, output validation, customer communication and deletion—not when everyone agrees that a plan exists.
A practical approval sequence
- Classify the workload. Complete the data, criticality, replacement-time and regulatory-impact assessment.
- Set acceptance criteria. Define security evidence, quality thresholds, availability, latency, retention and recovery requirements.
- Review the provider. Validate controls, subprocessors, locations, model practices and independent assurance.
- Negotiate the contract. Put processing limits, rights, notice, service levels, audit, export and deletion in signed terms.
- Build technical guardrails. Minimize data, isolate credentials, log decisions, cap spend and design provider adapters.
- Run the portability test. Exercise a second path and record measurable gaps.
- Approve with an expiry date. Assign owners and schedule reassessment after incidents, material changes and at least annually for critical use.
No authoritative source establishes a universal percentage for private-AI provider lock-in, outage probability or provider failure. Your own dependency classification, contract evidence and exit test are more decision-useful than an invented benchmark.
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