PowerPlan AI contract — TermScout contract intelligence report

PowerPlan AI Addendum Review & Analysis

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AI Certification (Beta) Overview:

When TermScout certifies a contract, it means that agreement has met our rigorous standards and made the below commitments to their customers as it relates to their AI product or services.

Receiving Termscout's AI Certification (Beta) means that the product is on the cutting edge of AI development and shows they're committed to establishing trust and transparency with their customers and being a responsible corporate citizen when it comes to their AI development and functionalities.

Termscout acknowledges that presently AI is something of a moving target, but at this point, we believe responsible vendors make these minimum commitments and are continuously evaluating their practices.

AI Commitments Overview:

Review the AI-related commitments and view source language citations below.

PowerPlan has established guardrails related to the use of their AI offering.
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PowerPlan addresses how they use Customer data related to their AI offering.
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PowerPlan addresses how they retain Customer data as it relates to their AI offering.
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Customer retains ownership of input data submitted to PowerPlan as it relates to their AI offering.
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PowerPlan commits to notifying Customer of a security breach impacting the Customer's data.
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PowerPlan commits to complying with applicable AI laws
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In conversations between TermScout and PowerPlan, PowerPlan has indicated their ongoing commitment to adopting contractual best practices related to AI as they're developed.
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AI Certification (Beta) Guiding Principles:

Termscout's AI Certification (beta) covers five major categories outlined below. Termscout believes while there are other important principles related to AI, these five categories cover the major obligations related to AI found in vendor contracts today and expect over time this will expand to fully realized compliance index.

1. Use Restrictions: Limiting harmful or unintended uses of AI Systems.
2. Transparency and Explainability: Ensuring users understand how AI works and its limitations.
3. Data Usage and Ownership: Clarifying rights around training data and generated content.
4. Security and Incident Response: Protecting data and systems from breaches or misuse.
5. Regulatory Compliance: Ensuring alignment with evolving laws.

AI Certification (Beta) Program:

If you are interested in being part of the AI Certification (Beta) Program and joining a standing group of select customers who has ongoing conversations with us about these standards and how they should evolve over time, please contact us at sales@termscout.com

Frequently Asked Questions

Find quick answers to the most common questions about our platform, process, and agreements.

Procurement teams often escalate agreements when vendors reserve the right to modify core terms, service functionality, or AI usage policies without meaningful customer approval or advance notice. Concerns increase when those changes could affect data handling, pricing structures, security obligations, or operational dependencies after implementation. Enterprise buyers generally expect material changes to follow defined notification and review processes rather than discretionary vendor updates that shift risk unexpectedly over time.

Agreements containing broad modification rights frequently trigger additional legal and security review because they complicate long-term governance and operational predictability. Procurement teams may hesitate to approve vendors if future contract obligations can change outside negotiated controls. This becomes particularly sensitive in AI SaaS environments where evolving models, data practices, or service capabilities could materially alter the customer’s risk posture after deployment. Stable governance expectations are often treated as part of the vendor evaluation process itself.

Buyers typically react negatively when agreements allow vendors to revise privacy practices, acceptable use standards, AI training rights, or pricing terms through simple website updates or policy notices. Clauses that lack customer termination rights, review windows, or limitations on material operational changes are more likely to appear out of market. Procurement and legal teams increasingly expect tighter controls around modifications that could affect compliance obligations or internal approval assumptions established during onboarding.

Enterprise organizations often integrate AI SaaS vendors into regulated workflows, internal controls, and security review frameworks. If vendors can materially change operational terms without structured customer consent, internal governance assumptions may become unreliable after implementation. Buyers therefore evaluate unilateral change language as part of broader vendor trust and accountability analysis. Agreements that preserve transparency, customer visibility, and predictable escalation processes generally move through procurement review more efficiently than agreements built around broad vendor discretion.