5.2.5 Licensing models

Deconstructing Commercial Licensing Structures

Commercial AI security tools are typically offered under several distinct licensing models. Each has profound implications for how you conduct engagements, manage budgets, and scale your team’s efforts. Let’s break down the most common structures you will encounter.

Per-User / Per-Seat Licensing

This is the most traditional software licensing model. You pay a fixed fee for each named user who needs access to the platform. It’s simple, predictable, and easy to budget for.

• Strengths: Cost predictability is the primary advantage. You know exactly what your expenditure will be for a given team size over the subscription period.
• Weaknesses: This model lacks flexibility. It can be cost-prohibitive for teams that rely on part-time specialists or external consultants for specific engagements. Scaling up or down quickly to meet project demands becomes a procurement bottleneck.

Per-Model / Per-Endpoint Licensing

A model increasingly common in the AI/ML space, where licensing is tied to the number of machine learning models you are actively testing or monitoring. The vendor’s definition of a “model” is critically important here.

• Strengths: Aligns costs directly with the assets you are protecting. If you have a small, fixed number of high-value models in production, this can be very cost-effective.
• Weaknesses: This can severely restrict exploratory testing. Does a fine-tuned version count as a new model? What about a quantized variant or a model still in a staging environment? Ambiguity in the license agreement can lead to compliance issues or stifle the red team’s mandate to test systems pre-production.

Usage-Based / Consumption-Based Licensing

Here, you pay for what you use. Costs are calculated based on metrics like the number of API calls to the tool, the volume of data processed, the quantity of adversarial tests run, or the compute hours consumed.

• Strengths: Offers maximum flexibility. It’s ideal for teams with highly variable workloads, allowing you to pay for intensive testing only when you need it. It lowers the barrier to entry, as you can start small and scale your usage.
• Weaknesses: The primary risk is unpredictable and potentially runaway costs. A large-scale fuzzing campaign or an automated prompt injection attack could generate a massive, unexpected bill. This model requires diligent monitoring and may create a culture where red teamers are hesitant to run comprehensive tests for fear of exceeding the budget.

Subscription Tiers (SaaS)

Most modern tools are sold as a Software-as-a-Service (SaaS) subscription, often with tiered packages (e.g., Basic, Professional, Enterprise). Higher tiers unlock more advanced features, higher usage limits, and better support.

• Strengths: Provides a clear path for growth. You can start with a lower-cost tier to evaluate the tool and upgrade as your team’s needs and maturity evolve.
• Weaknesses: Critical red teaming features, such as advanced attack libraries, custom test creation, or detailed reporting and integration capabilities, are often locked behind the most expensive enterprise tiers. A lower-tier subscription might prove insufficient for a serious red teaming engagement.

Comparative Analysis of Licensing Models

The right choice depends entirely on your team’s structure, objectives, and the nature of the AI systems you are tasked with evaluating. The following table provides a strategic overview to guide your decision-making process.

Model Type	Best Suited For	Red Team Pros	Red Team Cons & Watch-outs
Per-User / Per-Seat	Stable, internal teams with a fixed size and consistent workload.	Predictable budget, easy to manage. Encourages deep tool expertise among licensed users.	Inflexible for bringing in external experts. Poor value if users are not active full-time.
Per-Model / Per-Endpoint	Organizations with a few, well-defined production models.	Cost is directly tied to the protected assets. Can be economical for focused testing.	Restricts testing of pre-production, experimental, or fine-tuned models. Vague definitions can cause contract disputes.
Usage-Based / Consumption	Teams with fluctuating workloads or project-based engagements.	High flexibility, pay only for what you use. Low initial commitment.	High risk of unpredictable costs. May discourage intensive, large-scale testing due to budget anxiety.
Subscription Tiers	Teams of all sizes, allowing for a phased adoption and growth.	Scalable, clear upgrade path. Allows you to match features to team maturity.	Essential red teaming features may be locked in expensive tiers. “Feature-gating” can limit effectiveness.
Enterprise / Site License	Large organizations with extensive AI development and multiple teams.	“All-you-can-eat” model removes friction. Encourages broad adoption and experimentation.	Highest upfront cost. Requires significant negotiation and may include terms that are hard to change.