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Method · Procurement and acceptance

Agentic AI RFP requirements and acceptance evidence

A useful agentic AI RFP asks vendors to prove how the whole operating system works—not only describe a model, demo, or feature list. Requirements should connect to acceptance evidence, owner decisions, and an exit path.

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Direct answer

What should an agentic AI RFP require?

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It should define the business process and measurable outcome, system and data boundaries, agent and human roles, authority limits, identity and tool controls, model and supplier transparency, evaluation scenarios, telemetry, security, privacy, incident and recovery obligations, service ownership, cost reporting, portability, change control, and evidence-based acceptance criteria.

  • Require vendors to distinguish existing capability from roadmap claims.
  • Tie every material requirement to a demonstration, document, test, trace, or contractual acceptance condition.
  • Preserve the buyer’s ability to replace models, tools, providers, or implementation partners.

Source basis: reviewed official references are listed on this page and in the source ledger. Interpretation and implementation guidance retain the stated assurance boundary.

Procurement workflow

Move from marketing claims to a decision record

The procurement package should make comparison repeatable.

  1. Define the process and baseline

    Document volume, time, quality, cost, exceptions, risk, existing controls, and non-AI alternatives.

  2. Define system and authority boundaries

    State data, tools, environments, users, agents, permissions, prohibited actions, human approval, and stop authority.

  3. Define required evidence

    Specify architecture, AIBOM, security, privacy, evaluation, observability, incident, operations, and financial records.

  4. Design a comparative evaluation

    Use buyer-owned scenarios, thresholds, cost normalization, adversarial tests, and human review across shortlisted options.

  5. Write acceptance and exit criteria

    Make payment and scale decisions depend on evidence; include portability, transition assistance, data return, and deletion.

  6. Run an independent scale gate

    Issue go, conditional go, remediate, rebid, replace, or stop based on technical, economic, operational, and governance evidence.

Requirement map

Minimum RFP sections

Adjust depth to consequence, scope, and procurement rules.

SectionRequirement focusAcceptance evidence
Business outcomeProcess scope, baseline, users, value hypothesis, exclusions, non-AI alternativesBuyer-approved baseline and measurable success criteria
ArchitectureAgents, orchestration, state, memory, models, tools, APIs, environments, dependenciesCurrent diagrams, ADRs, AIBOM, integration demonstration
Identity and authorityAgent identity, delegation, least privilege, least agency, approvals, overrides, stopsPolicy configuration, access test, authority scenarios, audit trace
Data and privacySources, provenance, residency, retention, training use, retrieval, memory, deletionData flow, handling schedule, test evidence, deletion procedure
SecurityThreat model, prompt injection, tool misuse, code execution, supply chain, inter-agent messagingOWASP mapping, test results, findings, remediation, sandbox evidence
EvaluationScenario suite, rubrics, thresholds, human review, drift, regression, red teamingBuyer-run results, repeatable harness, version-linked scorecard
ObservabilityTrace coverage, model/tool events, content capture, cost, redaction, retentionPortable trace export, dashboards, telemetry dictionary, gap statement
Operations and incidentsSLOs, support, ownership, change, rollback, incident notification, recoveryRunbooks, exercise results, escalation roster, incident template
Commercial and exitCost units, consumption limits, IP, portability, transition, data return, lock-inTCO model, export demonstration, exit plan, contract schedules

Editable procurement record

Download the RFP requirements template

Use the Markdown template as a starting point and obtain procurement, legal, security, accessibility, records, and domain review.

Markdown

Agentic AI RFP Requirements

Editable requirement, supplier response, acceptance evidence, owner, status, and contract-treatment fields.

Download MD

Templates are planning aids. They are not certifications, legal advice, security guarantees, or substitutes for client-specific validation.

Primary-source basis

Official source ledger

Each record includes publisher, source type, status, reviewed date, summary, and use boundary.

National Institute of Standards and Technology · Official Framework Hub

NIST AI Risk Management Framework

NIST's voluntary framework for incorporating trustworthiness considerations into the design, development, use, and evaluation of AI systems.

Status
Current With Revision Underway
Published
2023-01-26
Reviewed
2026-08-01

Use boundary: Use as risk-management guidance; do not describe alignment as certification or legal compliance.

Open official source

National Institute of Standards and Technology · Official Profile

NIST AI 600-1: Generative AI Profile

A cross-sectoral companion profile for applying the AI RMF to risks that are distinctive to or intensified by generative AI.

Status
Current
Published
2024-07-26
Reviewed
2026-08-01

Use boundary: Use as a companion profile, not as proof that an implementation is compliant or safe.

Open official source

International Organization for Standardization · Official Standard Page

ISO/IEC 42001:2023 — AI management systems

Requirements and guidance for establishing, implementing, maintaining, and continually improving an AI management system within an organization.

Status
Current
Published
2023-12
Reviewed
2026-08-01

Use boundary: Do not claim certification unless an accredited audit and certification process has been completed.

Open official source

OWASP GenAI Security Project · Official Security Taxonomy

OWASP Top 10 for Agentic Applications

A community-developed taxonomy covering ten major agentic application risk areas, from goal hijacking and tool misuse through memory poisoning, cascading failures, and rogue agents.

Status
Current
Published
2025-12-09
Reviewed
2026-08-01

Use boundary: Use as a threat-oriented taxonomy and mitigation aid, not as a certification or guarantee of security.

Open official source

Model Context Protocol · Official Protocol Specification

Model Context Protocol Specification — 2026-07-28

The reviewed MCP specification defines an open protocol for connecting language-model applications with contextual resources, prompts, and tools through host, client, and server roles.

Status
Current Reviewed Version
Published
2026-07-28
Reviewed
2026-08-01

Use boundary: MCP is an interoperability protocol, not a complete agentic control plane, governance program, or security guarantee.

Open official source

OpenTelemetry · Official Specification Hub

OpenTelemetry semantic conventions for generative AI systems

Official semantic-convention material for interoperable telemetry describing generative AI operations.

Status
Evolving
Reviewed
2026-08-01

Use boundary: Record the exact convention version implemented because names and stability levels can evolve.

Open official source

Executive Office of the President, Office of Management and Budget · Official Federal Policy

OMB Memorandum M-25-21

Federal agency guidance issued April 3, 2025, that rescinds and replaces OMB Memorandum M-24-10 and establishes requirements for agency AI innovation, governance, transparency, and high-impact AI risk management.

Status
Current
Published
2025-04-03
Reviewed
2026-08-01

Use boundary: Applies to covered federal agency use; it is not a universal private-sector compliance standard.

Open official source

Official-source citations establish provenance and scope. They do not establish LongTermIntelligence.com certification, endorsement, legal advice, client outcomes, or a guarantee that a control is effective.

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