Protecting Trade Secrets: Make Sure Your Policies Reflect How Work Actually Gets Done
I recently read an article on Reuters about the rapid rise in trade secret litigation. While not a litigator, the article did make me think how corporate transactional counsel could proactively approach this issue. Trade secret protection is often treated as a legal checkbox. Policies are drafted, agreements are signed, and the issue quietly recedes into the background.
From a transactional and advisory perspective, that approach misses the point. The real value of trade secret policies is not how they perform in litigation, but how well they support the business as it operates, scales, hires, and collaborates. When policies align with reality, they reduce risk, improve discipline, and make the company easier to manage and easier to diligence.
Many companies encounter problems not because they lack policies, but because their policies were built for a version of the business that no longer exists.
Start by Knowing What Actually Deserves Trade Secret Treatment
Many companies treat “confidential information” and “trade secrets” as interchangeable. Operationally, that creates confusion.
Not all sensitive information needs the same level of protection, and trying to treat everything as a trade secret often leads to overbroad policies that no one follows. A more effective approach is to distinguish between:
Trade secrets — information that derives real economic value from not being generally known and that the business actively seeks to protect (for example, pricing models, proprietary algorithms, key customer data, or internal methodologies)
General confidential information — important business information that should be protected but does not rise to the level of a trade secret (for example, internal policies, non-public financial data, or routine commercial information)
This distinction matters because it allows companies to apply different controls to different categories of information, rather than relying on blanket restrictions that don’t match day-to-day workflows.
From a best-practices standpoint, companies that can clearly articulate what their trade secrets are better positioned to design realistic access controls, train employees effectively, and scale their operations without losing visibility into their most valuable information assets.
Policies Should Enable the Business, Not Describe an Idealized One
Modern companies are flexible by design. Employees work remotely or in hybrid arrangements. Teams collaborate across functions and geographies. Information moves quickly through cloud platforms, shared drives, and collaboration tools. Personal devices and AI tools are often part of everyday workflows.
Policies that assume centralized offices, tightly controlled networks, and uniform work patterns do not reflect this reality. More importantly, they do not help the business operate safely within it.
Good policy design starts with a simple premise: employees should be able to read the policy and recognize their actual work environment. When that happens, expectations are clearer, compliance improves, and management has fewer surprises.
Key updates to consider:
Clear restrictions on downloading, transferring, or using proprietary information outside approved systems
Explicit guidance on AI use, including prohibitions on inputting confidential information into public or unapproved tools
Tailored confidentiality and invention assignment agreements for different roles rather than one-size-fits-all forms
Remote and Hybrid Work: Treat It as the Default, Not the Exception
Remote and hybrid work is no longer a special accommodation. For many organizations, it is the baseline operating model.
Policies should address remote work directly and pragmatically, including:
How sensitive information may be accessed outside the office
Which systems and tools are approved for remote use
What security measures are expected in home or shared environments
What is not permitted, even in flexible work arrangements
When policies avoid the topic or treat remote work as an edge case, employees are left to make their own judgment calls. That inconsistency creates operational risk long before it becomes a legal issue.
Personal Devices: Acknowledge Reality and Set Guardrails
The use of personal devices for business purposes is one of the most common gaps between policy and practice. Many companies either prohibit it outright without enforcement or fail to address it at all.
A more effective approach is to acknowledge reality and set reasonable guardrails. Best practices often include:
Clarifying whether personal devices may be used for business
Defining what types of company information may be accessed on those devices
Requiring baseline security measures, such as passwords or encryption
Addressing ownership and control of company data when employment ends
This is less about strict enforcement and more about clarity. When expectations are clear, employees are more likely to comply, and the business is better positioned to manage transitions smoothly.
Cloud Collaboration: Manage Access as the Company Evolves
Cloud-based collaboration tools are essential to modern business operations. They also require ongoing attention as teams grow, roles change, and projects evolve.
From a best-practices standpoint, companies should:
Identify approved platforms for storing and sharing sensitive information
Use role-based access where appropriate
Periodically review who has access to what
Be thoughtful about data retention and duplication
These steps support efficient operations and reduce friction during financings, diligence processes, audits, and internal transitions. They also signal that the company treats its information assets intentionally rather than casually.
AI Tools: Draw Bright Lines Early
AI tools are now part of how many employees work, whether companies have formally approved them or not. Drafting, summarizing, analyzing, and brainstorming with AI has become routine in many roles.
The primary risk is not that employees are using AI. It is that they are doing so without clear guidance, making individual judgment calls about what information is appropriate to share.
Policies should draw bright, easy-to-understand lines. At a minimum, companies should be explicit that confidential, proprietary, or non-public information may not be input into public or unapproved AI tools. That prohibition should be stated clearly and plainly, not buried in general confidentiality language.
Good practice also includes:
Identifying whether any AI tools are approved for business use
Clarifying that public AI tools may retain, reuse, or train on inputs
Addressing ownership and permitted use of AI-generated outputs
Reinforcing that efficiency gains do not override confidentiality obligations
This approach does not require predicting every future AI use case. It establishes a stable framework: tools may change, but the rule around confidential information remains consistent.
Credibility Comes From Alignment, Not Length
Effective policies are not necessarily the longest or most detailed. They are the ones employees recognize as describing how the business actually operates.
From a governance perspective, credibility matters. Clear, realistic policies are easier to train on, easier to update, and easier to integrate into onboarding, offboarding, and operational reviews. They also reduce friction when the company faces a transaction, internal review, or unexpected issue.
Advisors, investors, and counterparties care less about perfect language and more about whether the company appears organized, disciplined, and intentional.
Final Thought
Trade secret policies are not just about guarding against worst-case scenarios. They are about supporting the business in the way it actually functions today.
Companies that periodically revisit and modernize these policies put themselves in a stronger operational position. They move faster, collaborate more confidently, and reduce uncertainty around their most important information assets. Cruxterra is here to help you do just that! Reach out: LetsGo@Cruxterra.com
