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EN · AI Strategy & Transformation

How to assess whether an AI consultancy is vendor-neutral or platform-aligned

Expose incentives, conflicts, and excluded alternatives before accepting a technology recommendation or implementation bid.

Enterprise compares multiple AI platforms through a transparent decision lens, with commercial connections and balanced alternatives.
The AI Recommendation Independence Proof-8 makes incentives, alternatives, costs, and criteria visible before a recommendation. · Generated with OpenAI

A vendor-neutral AI consultancy is not one with no partnerships. It is one that discloses material economic relationships, separates advice from resale and implementation, compares options against verifiable requirements, and lets the buyer challenge the recommendation. A platform-aligned firm may bring speed, skills, support, and discounts; risk begins when incentives, exclusions, and exit cost remain hidden.

Before hiring, demand a reproducible decision: who set the criteria, which alternatives were tested, how each scored, who receives referral fees, resale margin, credits, or quota benefits, and what evidence would change the recommendation. Another qualified firm should be able to review the record without reconstructing the sales process.

AI Recommendation Independence Proof-8: a 32-point scorecard

Score each dimension from zero to four: zero is absent; one is an assertion; two is partial disclosure; three is current evidence with an owner and control; four adds a tested alternative and reassessment trigger. As an illustrative gate, proceed at 24 of 32, with no zero and at least three for incentives, options, lifecycle cost, and portability.

  • Commercial relationships — alliances, resale, commissions, rebates, credits, MDF, quotas, certifications, affiliates, and owned products are disclosed.
  • Scope and decisions — advice, selection, architecture, resale, implementation, evaluation, and approval have explicit ownership and separation.
  • Requirements and evidence — business outcome, users, data, risk, performance, integration, operations, and exit drive the choice.
  • Options and exclusions — at least three plausible paths, including do-nothing, hybrid, or substitution, are compared and exclusions justified.
  • Lifecycle economics — license, consumption, services, integration, operations, people, migration, egress, and retirement appear in scenarios.
  • Portability and reversibility — data, code, prompts, configurations, evaluations, logs, documentation, and interfaces can be transferred and tested.
  • Conflict controls — disclosure, recusal, independent challenge, team separation, and buyer approval match the risk.
  • Ongoing governance — incentive, price, product, region, or performance changes trigger a record, new analysis, and remedies.

Apply six kill criteria

  • The consultancy refuses to disclose material economic relationships.
  • A platform was chosen before verified needs and requirements.
  • The same team writes criteria favoring its resale offer and evaluates its own bid without safeguards.
  • Total cost omits licenses, use, migration, egress, operations, or exit.
  • Proprietary accelerators, data, configurations, or evaluations are neither portable nor replaceable.
  • Incentives can change without notice, documentation, reassessment, or a repricing right.

A failed criterion need not end the sourcing process. It may narrow the mandate to discovery, separate adviser from implementer, require independent review, reopen architecture options, or create a condition precedent. A generic impartiality statement does not repair a biased decision process.

Require eight reusable artifacts

  • Relationship and incentive register with entity, benefit, material value or range, owner, and review date.
  • Requirements-to-evidence matrix tied to outcome and risk.
  • Three-option decision record with exclusions, assumptions, and triggers.
  • Scenario-based total-cost model including migration and exit.
  • Portability or substitution proof for critical components.
  • Conflict mitigation and responsibility-separation plan.
  • Separate pricing for advice, licenses, resale, and implementation.
  • Post-award log for changes, exceptions, decisions, and reassessments.

Run a 90-minute conflict test

Give finalists the same requirements and request a recommendation with three options. Then disclose a new platform rebate, cloud credit, or certification target. Require them to recompute options, total cost, conflict, recommendation, and exit. Evaluate transparency, evidence discipline, and willingness to change position—not fluency in defending the preferred platform.

When alignment can create value

Deep specialization can shorten integration, unlock technical support, improve staffing, and reduce execution risk in an ecosystem the buyer has already selected. That is legitimate when the buyer understands the incentive, verifies fit, and preserves exit options. Absolute neutrality may be less useful than transparent, governed alignment; a wall of partner logos is not proof of independence either.

United States context

For federal acquisitions, FAR Subpart 9.5 requires agencies to identify and resolve organizational conflicts before award. Private buyers are not automatically governed by those rules, but the principles—prevent biased judgment and unfair advantage, document the analysis, and use proportionate mitigation—provide a strong review pattern. Add applicable state privacy, sector, competition, export, and contracting requirements with counsel.

Put independence into the RFP and contract

Give all bidders the same requirements and data. Require initial and continuing conflict disclosure, criteria set before bids, buyer access to evidence, unbundled pricing, proportionate audit rights, independent challenge for critical decisions, and reassessment when incentives or conditions change. Tie milestones to decision artifacts—not to closing a license transaction.

Connect the decision to adjacent diligence

Use https://makinai.co/insights/en/buy-configure-or-build-ai-solution to define the option set, https://makinai.co/insights/en/evaluate-ai-solution-architecture-proposal-before-hiring to test architecture, https://makinai.co/insights/en/how-to-assess-ai-vendor-lock-in-exit-plan to validate exit, and https://makinai.co/insights/en/how-to-evaluate-ai-consulting-proposals-scorecard to normalize bids.

When to involve MAKINAI

MAKINAI can structure independent criteria, normalize options and lifecycle costs, run the conflict test, and turn a recommendation into verifiable decisions, gates, and exit rights. Explore https://makinai.co/services/en/ai-strategy-transformation-consulting.

Sources and references

  1. FAR Subpart 9.5 — Organizational and Consultant Conflicts of Interest · U.S. General Services Administration

    Provides rigorous principles for identifying, avoiding, neutralizing, or mitigating conflicts that can bias judgment or create unfair advantage.

    2026-09-11
  2. GSA — Buy AI · U.S. General Services Administration

    Recommends starting with mission needs and requirements rather than specific technologies or vendor solutions.

    2026-09-11
  3. UK Government — Digital, Data and Technology Playbook · UK Government Commercial Function

    Supports whole-life value comparisons, lock-in prevention, and supplier- and technology-agnostic requirements and documentation.

    2026-09-11
  4. NIST AI RMF Core · National Institute of Standards and Technology

    Connects governance, context, measurement, and management of third-party and component risks to documented decisions.

    2026-09-11
  5. NIST SP 800-161 Rev. 1 — Cybersecurity Supply Chain Risk Management · National Institute of Standards and Technology

    Guides identification, assessment, monitoring, and mitigation of supplier, product, service, and component risk across the lifecycle.

    2026-09-11
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