Outsourcing Contract Checklist for AI and Software

Outsourcing risk is either handled in the contract or hidden in it. Vague scope, silent IP terms, unrestricted data use, and absent exit provisions do not cause problems until they cause expensive ones. This checklist covers the terms that matter in AI and software engagements. It complements how to negotiate an ai development contract and the AI procurement for CIOs whitepaper. This is general guidance, not legal advice; use qualified counsel.

Who should use this checklist?

Buyers of AI development, software engineering, staff augmentation, and embedded engineering services, and the procurement, legal, and security teams supporting them.

Is the counterparty verifiable and the law right?

1. The contracting entity is identified with registration details and jurisdiction.
2. Governing law and venue are in the buyer's jurisdiction where feasible.
3. Leadership accountable for the engagement is named and reachable in the buyer's hours.
4. For cross-border delivery, the relationship between the contracting entity and the delivery team is clear.

Reference: the cross-border engineering delivery model whitepaper.

Is scope defined as outcomes with acceptance?

1. Outcomes are stated with measures, not only deliverables or hours.
2. Acceptance criteria are explicit, including for AI systems the evaluation method and thresholds.
3. Assumptions and dependencies on the buyer (access, data, decisions) are listed.
4. Out of scope is written.
5. Engagement shape and roles are defined.

Reference: how to write acceptance criteria for ai.

Is IP assigned?

Term	Present?
Assignment of all custom work product to the buyer on creation or payment
Definition of work product covering code, prompts, evaluation datasets, configurations, documentation, and models trained on buyer data
Vendor pre-existing IP identified and licensed with rights sufficient to operate and modify
Third-party and open-source components disclosed with license compliance
Moral rights waivers where applicable
Buyer-owned repositories and infrastructure from day one

Reference: the ip protection checklist for offshore development.

Are data terms complete?

1. Data in scope, purpose limitation, and permitted processing.
2. Model-provider restrictions: which providers may receive which data, under what terms; no training on buyer data.
3. Residency and transfer rules.
4. Retention and deletion with certification.
5. Breach notification timelines and cooperation.
6. Subprocessor disclosure and approval.
7. Alignment with applicable regulation (data protection, sector rules).

Reference: ai data privacy compliance and data security offshore ai.

Are security obligations specific?

1. Access controls: identities, MFA, least privilege, time-bound access, no shared accounts.
2. Device and network requirements.
3. Secrets handling.
4. Security testing obligations for delivered systems, including AI-specific testing.
5. Audit rights and evidence provision.
6. Incident cooperation.

Reference: the LLM security checklist.

Is change governed?

1. A change control process with impact assessment and approval.
2. For AI systems, re-evaluation requirements on model, prompt, or retrieval changes.
3. Notification of material changes to team, subprocessors, or tooling.
4. Key personnel provisions and continuity commitments.

Are commercial terms clear?

1. Pricing drivers explained; volume and scope assumptions stated.
2. No outcome or timeline guarantees offered or accepted in place of acceptance criteria.
3. Payment milestones tied to acceptance where fixed scope applies.
4. Rate cards and escalation for time-based engagements.
5. Expenses and tooling responsibilities.

Reference: ai project cost estimate and time and materials vs fixed price ai projects.

Is exit designed in?

1. Termination rights for convenience and cause with notice periods.
2. Transition assistance for a defined period.
3. Delivery of documentation, runbooks, and training.
4. Export of code, data, prompts, configurations, evaluation sets, and infrastructure definitions.
5. Access revocation and data deletion with certification.
6. License continuity for anything needed to operate.

Reference: the ai project handoff checklist.

Are liability and warranty proportionate?

1. Warranties on workmanship, non-infringement, and compliance with specifications.
2. Indemnities for IP infringement and data breaches caused by the vendor.
3. Liability caps proportionate to the engagement and data sensitivity, with carve-outs for confidentiality, IP, and data breaches.
4. Insurance requirements where appropriate.

Are service levels defined where applicable?

1. Availability and support commitments for operated systems.
2. Quality commitments for AI systems framed as measured thresholds and monitoring, not guarantees.
3. Response and resolution times by severity.
4. Reporting cadence.

Reference: ai sla expectations.

How should gaps be handled?

Counterparty, governing law, IP assignment, and data terms are gates; do not sign without them. Security, change control, and exit terms should be negotiated to acceptable form before signature. Commercial and service-level terms are refined per engagement. Record any accepted gaps with rationale.

How FISTA Solutions contracts

FISTA Solutions Inc. contracts as a Delaware-registered entity under US law, assigns all custom work product to clients, keeps code and infrastructure in client accounts, restricts data use and model-provider access in writing, accepts specific security obligations with audit rights, governs change with re-evaluation for AI systems, and provides transition assistance and full export on exit. Engagements run through forward deployed engineers, staff augmentation, AI enablement, and AI agents. The record behind the approach is 150+ projects for 50+ companies across 12+ countries.

This checklist is general guidance, not legal advice. To discuss contract terms for an engagement, message FISTA on WhatsApp, or read red flags outsourcing ai for the warning signs in vendor terms.