Build, Buy, or Blend? A 2025 U.S. Framework for Enterprise AI Leaders

U.S. regulatory and market backdrop

Enterprise AI in the U.S. has moved beyond experiments. CFOs want measurable ROI, boards expect demonstrable oversight, and regulators expect controls aligned with existing risk frameworks. With a sector-driven and enforcement-led approach, U.S. references for procurement and vendor assurance are converging on NIST guidance and sector-specific rules.

Key anchors to watch

• NIST AI Risk Management Framework (RMF): the de facto federal guidance shaping procurement and vendor assurance.
• NIST AI 600-1 (Generative AI Profile): tighter expectations around hallucination testing, monitoring, and evidence.
• Banking and finance: SR 11-7, FDIC/FFIEC guidance, and OCC scrutiny for model-embedded processes.
• Healthcare: HIPAA plus possible FDA oversight for clinical algorithms.
• FTC and SEC: enforcement and disclosure expectations on transparency, bias, cybersecurity, and data use.

Strategic decision: build, buy, or blend

The right choice depends on the use case. Consider these strategic rules of thumb:

• Build when the AI capability is core to competitive differentiation, handles sensitive regulated data, or requires deep integration with proprietary systems.
• Buy when the use case is commoditized, speed-to-value is essential, or vendors provide compliance artifacts you lack.
• Blend for most enterprise workloads: buy a hardened platform for governance and scale, then build the last mile for retrieval, prompts, orchestration, and domain-specific evaluation.

A 10-dimension scoring framework

Use a structured scoring model to turn debates into evidence. Score each dimension 1–5 and weight by priority. Example dimensions and suggested weights:

1. Strategic differentiation — 15% (Build bias: AI capability is product moat; Buy bias: commodity productivity gain)
2. Data sensitivity & residency — 10% (Build bias: PHI/PII/regulatory datasets; Buy bias: vendor can evidence HIPAA/SOC 2)
3. Regulatory exposure — 10% (Build bias: SR 11-7/HIPAA/FDA obligations; Buy bias: vendor provides mapped controls)
4. Time-to-value — 10% (Build bias: 3–6 months acceptable; Buy bias: must deliver in weeks)
5. Customization depth — 10% (Build bias: domain-heavy, workflow-specific; Buy bias: configurable suffices)
6. Integration complexity — 10% (Build bias: embedded into legacy/ERP; Buy bias: standard connectors adequate)
7. Talent & ops maturity — 10% (Build bias: LLMOps in place; Buy bias: vendor hosting preferred)
8. 3-year TCO — 10% (Build bias: infra amortized, reuse across teams; Buy bias: vendor unit economics win)
9. Performance & scale — 7.5% (Build bias: millisecond latency or burst control required; Buy bias: out-of-box SLA acceptable)
10. Lock-in & portability — 7.5% (Build bias: need open weights/standards; Buy bias: comfortable with exit clause)

Decision rules:

• Build if Build score exceeds Buy score by 20% or more.
• Buy if Buy score exceeds Build score by 20% or more.
• Blend if results fall within the ±20% band.

Modeling 3-year TCO correctly

Compare like-for-like: don't put 1-year subscription against 3-year build costs. Typical 36-month build costs include engineering teams, cloud compute for training and inference, data pipelines, observability and eval tooling, compliance work (audits, SOC 2, HIPAA), and egress/replication fees. Buy TCO includes subscription baseline, usage fees, integration uplift, add-ons for RAG and safety, vendor compliance artifacts, and migration/egress costs at exit.

When to build (U.S. context)

Build is the better path when the model or system is core IP, when you cannot permit regulated data into vendor pipelines, or when custom integration into mission systems is essential. Expect ongoing compliance overhead, intense hiring competition for LLMOps talent, and hidden operational costs like red-teaming and continuous evaluation.

When to buy

Buy when the workflow is commodity, time-to-value is critical, or reputable vendors already provide strong compliance coverage (NIST mappings, SOC 2, HIPAA BAAs). Key risks are vendor lock-in, usage volatility from token pricing, and material exit/egress costs unless explicitly negotiated.

The blended operating model

Most U.S. enterprises will default to a blended approach in 2025. Buy platform capabilities for governance, multi-model routing, and audit trails. Build the last mile: retrieval, adapters, domain evaluation datasets, hallucination tests, and sector-specific guardrails. This balances scale with control over sensitive IP and regulatory evidence.

Due diligence checklist for VPs of AI

If buying vendors, verify assurance certifications, HIPAA BAAs where applicable, explicit data portability and egress terms, SLAs for latency and residency, and bias/safety deliverables. If building, operate under NIST AI RMF categories, design multi-model orchestration to avoid lock-in, invest in observability and evaluation pipelines, staff a dedicated LLMOps team, and apply strict cost controls.

A practical decision tree

• Does the capability drive competitive advantage within 12–24 months? Yes → Probable build. No → Consider buy.
• Do you have governance maturity aligned to NIST AI RMF? Yes → Lean build. No → Blend.
• Would vendor compliance artifacts satisfy regulators faster? Yes → Lean buy or blend. No → Build.
• Does 3-year TCO favor internal amortization? Yes → Build. No → Buy.

Example: U.S. healthcare insurer

Use case: automated claim review and explanation of benefits. PHI is involved, integration is tight with legacy claim systems, and regulation includes HIPAA and potential HHS/FDA oversight. Outcome: blend. Choose a vendor platform with HIPAA BAA and SOC 2 Type II for base LLM and governance, build custom retrieval, code adaptations, and evaluation datasets, and map oversight to NIST AI RMF for board audit evidence.

Key takeaways for VPs of AI

• Apply a scored, weighted framework to each use case to produce audit-ready evidence.
• Expect blended estates to dominate and keep last-mile control as enterprise IP.
• Align build and buy choices to NIST AI RMF, SOC 2, ISO/IEC 42001, and sector laws like HIPAA and SR 11-7.
• Model 3-year TCO including cloud egress and include exit/portability clauses in contracts up front.

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