As companies integrate artificial intelligence into their operations, it’s critically important that they also implement clear policies that ensure its responsible use and regulatory compliance. In alignment with our goal of ensuring ease of use of our productivity platform, we’ve outlined the key points we believe are necessary for an AI policy that could cover the use of our workplace copilot as well as more general AI guidance that can be applied more holistically.
We built our platform with a strong emphasis on transparency and individual control, and with full knowledge of the important enterprise requirements necessary for implementation. As an independent platform that works natively with many of the largest applications on the market, we uniquely apply specific governance and security measures that are required for some of the most rigid use cases, from health and human services to finance. To that end, we’ve outlined the characteristics of our platform that are relevant to each section of a general AI policy. We want to ensure that every customer, and potential customer, is clear on how we solve some of the most salient security and compliance considerations facing organizations today.
When implementing AI, corporate policy will likely address both potential risks and opportunities. A clear scope helps businesses identify which technologies fall under their AI governance framework. A policy should be broad enough to be applied to any third-party or publicly available AI tool, with specific carve-outs and descriptions for various use cases. (As always, please consult with your own legal team when drafting a policy.)
Organizations must prioritize transparent user consent and control mechanisms. Where AI interacts with individuals, either internally or externally, it must do so in a transparent manner. Users must ensure that individuals are aware when they are interacting with AI and what data the AI is collecting, processing, or using. Clear disclosures about AI's role in every interaction allow users to stay informed and in control.
Read AI demonstrates this through a multi-layered approach to privacy, including explicit recording notifications and easy opt-out capabilities for all meeting participants. This is a unique feature (even though in some states it’s a requirement) and we know the foundation of transparency builds long-term trust and adoption.
When it comes to data privacy, trust begins with control and visibility. AI systems should comply with major regulations, ensuring that personal information is anonymized and encrypted. At Read AI, we’ve observed that leading organizations are embedding strong privacy protocols into their AI implementations by offering granular controls over what data is collected, processed, and stored. AI tools should never be granted or assume automatic data access.
Specifically, AI systems must comply with all applicable data protection regulations. Enterprise organizations should require robust administrative controls while respecting individual privacy. A comprehensive approach includes customizable retention policies and granular workspace settings to meet various compliance requirements.
Organizations must also implement strict data processing protocols and security measures. This includes clear documentation of data handling procedures and limited access to sensitive information. AI tools should only process data users have permission to access, and data cannot be stored or used without explicit consent to protect user and customer data.Read follows all the required safeguards for both SOC2 and Type 2 and HIPAA Compliance. Read offers fully customizable data retention rules; controls for audio, video, and transcript access; Workspace-level integration management; and distribution controls. Read also documents all privacy features transparently and openly and enables granular user controls over data sharing and retention. Our Search Copilot tool also follows strict bottom-up sharing controls and governance. Read more about that here. At Read AI, only our proprietary, first-party model is used for data processing. Customer experience data is not shared by default. Read doesn’t train against customer data unless a customer opts in (only around 10-15% of customers currently opt-in). Read never stores content and we implement clear data deletion protocols and verification. Secure cloud infrastructure is standard, and the majority of data is stored in the U.S. (for those who opt-into HIPAA compliance, all data is stored here).
When drafting a policy, it should be stated that personal data must be anonymized where possible and stored securely with encryption standards, and regular audits should be conducted to ensure compliance with data privacy policies.
Protecting individual privacy while enabling collaboration requires careful balance. Implementing user-controlled sharing mechanisms ensures data protection while maintaining productivity. As part of any policy, a company should appoint an AI governance officer responsible for policy enforcement and updates, and to review the required logs for transparency and auditability.
Read AI provides individual control over content sharing (we believe this should not be a top-down process). We also offer granular permissions for data access and clear audit trails for shared content. Our customer support team can provide the details required for enterprise teams.
Though Read AI does not create AI-generated content from the open web, considerations for this type of tool are likely to be included in a general AI policy. Companies must have a clear process for addressing AI-related incidents and mitigating potential harm and AI should be monitored continuously to detect unintended behaviors and allow human intervention when necessary.
Organizations should also clearly outline which tasks can be fully automated and which require human intervention. For high-stakes decisions—like hiring or financial approvals—there should likely always be a human-in-the-loop system. These decisions can be made by a designated AI ethics committee that oversees AI deployment and ensures alignment with company values.
A key part of AI transparency is making sure all external communications—including marketing materials, customer service responses, and reports—are accurate and validated by humans. Tools like Read AI’s Search Copilot include citations for all generated outputs, so users know exactly where information is sourced from. Logging and monitoring systems ensure that AI operations remain transparent and accountable, minimizing risks while fostering innovation.
Policies should be regularly updated in response to technological advancements and regulatory changes. Also, to the extent possible, ethical AI principles should be embedded in corporate culture to promote responsible AI usage. At Read AI, we’ve learned that empowering users with transparency and control leads to stronger trust, collaboration, and productivity. By implementing responsible AI practices, companies can create an environment where innovation flourishes without sacrificing integrity.
For a product demo or to ask questions about Workspace controls, please contact our sales team.
We want every customer to clearly understand how we address the most important security and compliance challenges organizations face today.
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