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Most small businesses should define their AI governance process before buying a dedicated platform. Start by listing the AI tools and features in use, assigning an owner to each, and identifying the data and people affected. Consider specialist software only when the inventory, risk, or review workload is too difficult to manage reliably with existing tools.
Decide whether you need a dedicated platform
AI governance is the work of understanding how AI is used, setting appropriate rules, reviewing risks, and keeping records of decisions. A platform can help coordinate that work, but buying one is not the starting point—and software by itself does not guarantee legal compliance.
Begin with a practical inventory. Include standalone AI applications, models, experiments, agents, and AI features embedded in software from other vendors. For each use, record:
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- Business owner and purpose
- Who uses it and who may be affected by its output
- What data it receives, produces, or stores
- The vendor or provider
- Whether it informs decisions with significant consequences
This gives you a way to identify real gaps. A spreadsheet and existing approval tools may be sufficient when the inventory is small and reviews are straightforward. A dedicated platform becomes more worth evaluating when uses multiply, sensitive data or consequential decisions are involved, or keeping assessments and approvals current has become difficult.
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Use NIST as guidance, not a software mandate
NIST released the AI Risk Management Framework (AI RMF) 1.0 on January 26, 2023. It is voluntary guidance intended to help organizations incorporate trustworthiness considerations into AI design, development, use, and evaluation. NIST says the framework is being revised. Read NIST’s AI RMF overview.
The companion NIST AI RMF Playbook organizes suggested actions around Govern, Map, Measure, and Manage. NIST says organizations can use as many or as few of its suggestions as fit their context; it is not a checklist that every organization must complete. The Playbook supports shaping a proportionate process, not selecting a particular product, earning a certification, or proving legal compliance.
Its Manage guidance includes deciding whether an AI system achieves its intended purpose and whether development or deployment should proceed. It also suggests applying and documenting risk-management practices for third-party AI technology and other resources. For a small business, that makes vendor-provided AI features part of the governance question—not something to overlook because another company built them.
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Compare platforms against the work you need done
Write down the problems you want a platform to solve before comparing feature lists. Common gaps include not knowing which teams use AI, unclear data rules, missing approvals, inadequate vendor reviews, incomplete assessment records, or no practical way to monitor systems and handle incidents.
Score candidates against requirements your business can actually operate. Ask for demonstrations and written answers, not just claims on a product page.
| Capability | What to verify |
|---|---|
| Inventory and discovery | Can it register tools, models, embedded vendor features, and agents? How are records kept current, and who is responsible for updating them? |
| Risk intake and prioritization | Can staff submit a use for review, capture purpose and data, and route higher-risk uses for closer assessment? |
| Policies and approvals | Can you configure your own rules, approval steps, exceptions, and accountable owners? |
| Monitoring and incidents | Can teams record ongoing checks, changes, problems, and responses after approval? |
| Evidence and exports | Can you retrieve complete assessment and approval records in a usable format for internal review or an audit? |
| Integrations | Does it connect to the identity, ticketing, data, or collaboration systems you already use—and are those integrations included in the proposed scope? |
| Operating effort and cost | What setup, administration, training, support, and recurring work will the product require, in addition to its contract price? |
A longer feature list is not automatically better. A control that nobody has time to configure or maintain will not close a governance gap.
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Make vendors demonstrate a real workflow
Ask each candidate to show one representative AI use from beginning to end. The demonstration should follow your intended process and use realistic roles and sample data, rather than stopping at a dashboard or presentation.
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- Register a use, including its owner, purpose, vendor, and data.
- Complete the assessment and show how the system prioritizes or routes it.
- Apply a policy and record an approval, rejection, or exception.
- Show how the approved use is monitored and how a change or incident is handled.
- Export the resulting records and verify that they are complete and understandable outside the platform.
Use the demonstration to check where work happens, who must do it, and whether the records would help your business make and explain decisions. Vendor descriptions of capabilities are claims about their offerings, not independent proof of performance.
Check small-business fit, terms, and total cost
Before a pilot or purchase, get the commercial and operational details in writing. Confirm user and system limits, integration availability, implementation services, support, contract length, renewal terms, and how you can access or delete your data. Ask for the full recurring cost for the scope you plan to use.
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The public pages reviewed for the named products do not provide comparable prices. Credo AI describes centralized AI inventory, risk management, compliance, and monitoring; its Microsoft Marketplace listing describes it as an enterprise AI governance platform and directs buyers to contact sales for custom pricing. Holistic AI describes AI discovery and inventory, risk testing, policy and compliance enforcement, and audit reporting, and positions its offering for enterprise use on its product page. These descriptions do not establish that either product is affordable or well suited to a typical small business.
If you screen either vendor, ask for a reference from a business with a comparable number of AI systems, a complete quote for your intended scope, and a live demonstration of your workflow. Do not treat a vendor’s mapping to a framework as proof that your business meets applicable regulatory requirements.
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If a vendor appears to fit, agree on a limited pilot and define success measures in advance. Useful measures include how long it takes to register and review a use, whether required records are complete, whether staff follow the workflow, and how quickly the team can retrieve evidence. These are evaluation criteria to test in your own setting, not published performance results.
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At the end of the pilot, decide whether the platform solves a material problem better than a simpler process and whether your team can maintain it. If it adds administration without improving inventory, review, monitoring, or recordkeeping, it may be the wrong fit for your business.
Account for legal requirements separately
Applicable obligations depend on your jurisdiction, sector, and how the AI is used. Neither an AI governance platform nor alignment with a voluntary framework establishes compliance by itself. For regulated or consequential uses, verify requirements with qualified legal counsel or the relevant regulator before relying on a product’s compliance claims.
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