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Key Takeaways
1. AI needs guardrails. Leaders must establish clear rules for what employees can and cannot put into AI tools.
2. Don’t outsource judgment. AI can accelerate analysis and execution, but important decisions still require human expertise, context, and accountability.
3. Safe AI is a leadership issue. The goal isn’t to restrict AI; it’s to create enough governance that people can use it productively without exposing the organization to unnecessary risk.
Artificial intelligence has moved from “interesting experiment” to “board-level priority” with remarkable speed. While CEOs and executive teams now believe AI can materially improve efficiency, decision-making, and growth, they share a quieter concern:
How do we use AI safely so we don’t put our most sensitive data, IP, and competitive advantage at risk?
The good news is that companies can unlock real value from AI without putting proprietary information at risk — and they can do so without rushing into a costly, permanent hire before they’re ready.
Here’s how.
What is the Biggest Risk of Using AI in a Business?
The answer is simple: unstructured adoption. Across industries, AI is being used without the necessary guardrails.
- Employees are providing confidential data while using consumer AI tools.
- Teams are automating decisions that shouldn’t be automated.
- Vendors are retaining or training on company information.
- There is no clear accountability for AI-related decisions.
C-suite leaders are wondering: Do we need to hire someone to lead this? To figure that out, start with our list of the EXACT AI prompts for better executive hiring to understand what to ask AI so you can decide whether you need a permanent hire, fractional, or interim executive.
How Can I Establish Safe AI Boundaries for My Company?
Start by answering a few core questions:
1. What Company Data Can Be Safely Shared with AI?
Not all data is created equal. High-performing organizations clearly break data into three categories:
- Approved: Public information, general research, non-sensitive content, and appropriately anonymized or aggregated data.
- Restricted: Internal business information that may be used only with approved enterprise tools and appropriate controls.
- Prohibited: Trade secrets, highly confidential intellectual property, sensitive customer information, credentials, certain employee data, and other information the organization has determined should not be entered into an AI system.
AI rarely needs direct exposure to pricing logic, trade secrets, customer contracts, or sensitive IP to deliver value. Aggregated, anonymized, or abstracted data is often more than sufficient.
2. What Decisions Should AI Be Allowed to Make?
AI excels at:
- Drafting and summarizing
- Pattern recognition
- Research and analysis
- Process acceleration
Companies err by allowing AI to make final decisions in areas like pricing, legal terms, or strategic direction. The safest and most effective approach is positioning AI as a copilot, with humans firmly in control.
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3. Which AI Tools Should I Allow Employees to Use?
Before approving an AI platform, leaders should understand:
- What contractual protections apply
- How company data is stored
- Whether inputs are retained
- Whether data is used to train models
- Where information is processed
- What security controls are available
- What administrative and access controls exist
- How the vendor handles deletion and retention
The right infrastructure dramatically reduces the risk of unintended data exposure.
4. Should I Allow AI to Train on My Company’s Proprietary Information?
For most business applications, a retrieval-based approach is the right way to operate, versus training an AI model on proprietary documents.
The distinction is important: Training changes a model. Retrieval gives a model controlled access to information. AI pulls only the relevant information at the moment it’s needed, without permanently “learning” or storing it.
This allows executives to benefit from AI-powered insight while keeping core knowledge securely inside the organization.
Retrieval-based AI retrieves relevant information from an organization’s approved knowledge sources when it needs that info. This allows employees to get useful answers from company information without treating that information as permanent training data.
5. What Should an AI Governance Policy Include?
A useful AI policy should be specific enough that employees know what they can actually do.
At minimum, an effective AI policy should address:
- Approved AI tools: Which platforms employees may use for company work.
- Data restrictions: What information may and may not be entered into AI systems.
- Human oversight: Which outputs require review before they are acted upon or distributed.
- Accountability: Who owns decisions and outcomes when AI is involved.
- Security and privacy: How sensitive information must be handled.
- Verification: When AI-generated facts, analysis, or recommendations must be independently checked.
- Monitoring: How the organization will identify misuse, unexpected behavior, or emerging risks.
- Training: How employees will learn the organization’s rules and expectations.
Who Do I Need to Lead AI Strategy for My Company?
Few companies employ an executive who owns AI strategy, governance, implementation, and adoption. That’s a big problem with the speed at which AI is being adopted across industries and inside companies.
While hiring a permanent AI or technology leader may ultimately make sense, that can take months and your company needs to make decisions about AI today.
That’s why a RED Team interim executive is the right answer.
An experienced interim CIO or CTO can step in quickly to assess your current AI landscape, identify high-value opportunities, establish appropriate guardrails, and build an AI roadmap aligned with the business strategy. More importantly, our interims are operational leaders who go beyond recommending solutions to lead the implementation.
A strong interim executive can help your organization:
- Assess AI readiness across technology, data, people, and processes
- Identify practical use cases where AI can improve productivity, decision-making, or growth
- Establish AI governance and clear policies around data, security, privacy, and human oversight
- Evaluate AI vendors and platforms based on business requirements and risk
- Lead implementation and adoption so AI moves beyond experimentation
- Build internal capability and prepare the organization for its long-term leadership needs.
When the technology is moving faster than your organization’s leadership capacity, the right interim executive can close that gap quickly and with accountability for results.
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Frequently Asked Questions
An interim AI executive translates AI opportunities into a practical business strategy and leads execution. Depending on the organization, that may include assessing existing AI use, identifying high-value applications, establishing AI governance, evaluating technology vendors, addressing data and security requirements, developing an implementation roadmap, and leading adoption across the organization. The interim executive owns the work rather than simply delivering recommendations.
A company should consider an interim executive when it needs AI leadership, strategy, governance, or implementation expertise but does not yet have the right permanent executive in place. An interim CIO or CTO can quickly assess the organization’s AI readiness, prioritize opportunities, establish guardrails, and lead implementation while the company determines its long-term leadership needs.
The right interim executive depends on the organization’s AI objectives and existing leadership structure. An interim CTO or CIO may lead technology strategy, infrastructure, security, and implementation. An interim CDO may be appropriate when data, analytics, and AI are closely connected. In some organizations, an interim CEO or COO may be needed to ensure AI initiatives translate into operational and commercial results.
Yes. An experienced interim technology or data executive can establish practical AI governance covering data privacy, security, approved tools, intellectual property, human oversight, and accountability. They can also evaluate how employees are already using AI and identify risks that may not be visible to senior leadership. This allows companies to pursue AI opportunities while putting appropriate controls around sensitive information and consequential decisions.
Both will develop strong plans for your company’s AI policies, guidelines, and adoption. But only the interim executive will stick around to implement those plans, becoming a fully accountable member of the leadership team for a defined period of time or until the project is completed.
