CYBASE RISK MANAGEMENT | EXECUTIVE INSIGHTS
WHO'S IN CHARGE OF YOUR AI? | SERIES OPENING
First article in the companion executive-focused series running alongside "When AI Goes Wrong".
The questions every executive should be asking before AI makes a decision they have to answer for.
AI is no longer just an IT initiative.
It is answering customer questions, screening job applicants, generating marketing content, analyzing financial data, scheduling appointments, and making recommendations that influence business decisions.
Some of these tools were formally approved by your organization. Others may have been introduced by individual departments or employees looking for ways to work faster.
Some are embedded in software your organization has used for years.
Here is the question:
How much do you actually know about the AI operating inside your organization?
More importantly, how much should you know?
You do not need to be an AI expert. But you do need to know what you are responsible for.
What should executives understand about AI?
Executives are not expected to understand every algorithm, model architecture, or technical configuration.
But if AI is influencing decisions within your department, you should understand:
- What the system does
- What information it can access
- What decisions it can make
- Which actions require human approval
- What happens when the system produces an unexpected result
This is the foundation of practical AI accountability.
It is also increasingly relevant to cyber risk management for executives, board cybersecurity oversight, and executive cybersecurity training. The issue is not whether every leader can explain how a model works. The issue is whether leadership understands the business consequences of the system’s behavior.
Five questions to ask now
Can you answer these questions for the AI tools operating in your department?
- Can you identify which AI tools are being used in your department?
- Do you know what company or customer information those tools can access?
- Are AI-generated recommendations reviewed by a human before action is taken?
- Can AI initiate transactions, communicate with customers, or change business records without approval?
- Who has the authority to stop an AI system when it behaves unexpectedly?
If you are struggling to answer these questions, you may have less visibility into your department’s operations than you realize.
That is not just a technology issue.
It is a business risk.
Why departmental AI decisions become enterprise decisions
Your department is not operating in isolation anymore.
Imagine your marketing team introduces an AI-powered customer engagement tool.
The tool works beautifully. It responds to customers, personalizes offers, and improves response times.
But during a customer interaction, the AI offers an unauthorized refund.
Now consider what happens next.
- Finance needs to understand the transaction.
- Customer Service needs to address the customer.
- Legal may need to evaluate the organization’s obligations.
- IT needs to investigate the system.
- Communications may need to prepare a response if the issue becomes public.
- Operations may need to determine whether other workflows are affected.
A decision that started in Marketing has suddenly become an organization-wide problem.
Who approved the AI tool?
Who defined its authority?
Who decided what would happen if it made a mistake?
These questions should be answered before deployment, not during an incident.
That does not mean every AI purchase requires executive approval. It means the level of leadership involvement should match the potential business impact.
Your executive AI responsibility: four levels of involvement
Not every AI configuration requires a board discussion or executive sign-off.
However, executive involvement should increase when AI introduces significant business risk. Particularly when it affects customers, employees, sensitive information, financial transactions, or critical operations.
Use this four-level framework to determine where your responsibility begins.
1. Visibility
Know what AI tools are operating in your department, who owns them, and what business processes they support.
Visibility includes more than a list of approved software. It should also account for:
- AI features embedded in existing platforms
- Department-level tools and pilots
- Vendor-operated systems
- Employee-adopted tools that may handle company information
- AI systems that make recommendations or take actions
You cannot provide meaningful oversight for systems you cannot identify.
2. Oversight
Understand the risks, safeguards, human approval requirements, and limitations of the technology.
You do not need to review technical specifications line by line. You do need to know:
- What the system is allowed to do
- What it is not allowed to do
- Which data it can access
- When a human must review or approve an action
- How the system’s performance is monitored
- What controls limit unintended behavior
Oversight turns AI use from an informal convenience into an accountable business process.
3. Cross-functional decisions
Participate when AI affects other departments, shared information, financial exposure, or organizational commitments.
Cross-functional review may be appropriate when an AI system:
- Communicates externally on behalf of the organization
- Handles customer, employee, health, financial, or confidential data
- Changes records or initiates transactions
- Influences hiring, pricing, eligibility, or service decisions
- Connects to systems used by multiple departments
- Creates legal, regulatory, contractual, or reputational exposure
The goal is not to create unnecessary delay. It is to prevent one department from making a decision that quietly creates obligations for the rest of the organization.
4. Incident readiness
Know your authority, your responsibilities, and the decisions you will be expected to make when AI fails.
Incident readiness means your leadership team has already discussed:
- Who can restrict or stop the system
- Which functions should continue
- Who must be notified
- What information decision-makers need
- How customer, employee, and partner impacts will be addressed
- When legal, compliance, insurance, or communications teams should be engaged
The objective is not to slow innovation by requiring executives to approve every technical decision.
It is to establish clear accountability before technology introduces consequences the business is not prepared to manage.
The question nobody wants to answer: What happens when your AI goes wrong?
Let us return to the customer service example.
Your organization discovers that an AI customer service agent has been manipulated into issuing unauthorized refunds. The system has already processed several transactions.
Your team has three immediate options:
- Shut down the AI system and potentially disrupt customer service.
- Keep it operating with additional human oversight while investigating.
- Restrict the system’s transaction authority while preserving other functions.
Which option do you choose?
Who has the authority to make that decision?
What information do you need before deciding?
How will your decision affect Finance, Operations, Legal, Customer Service, and your customers?
There may not be one universally correct response. The right course depends on the severity of the incident, available safeguards, business impact, and your organization’s obligations.
But your leadership team should already know how to work through those decisions together.
The first time your executives discuss their AI incident responsibilities should not be during an actual incident.
Executive AI readiness check
0/5
Check each question your leadership team can confidently answer.
- ☐ Do we have a complete inventory of AI tools, including those embedded in existing software?
- ☐ Which AI systems can access sensitive information or take action without human approval?
- ☐ Who approves AI use cases that create risk for multiple departments?
- ☐ Can we quickly restrict, override, or shut down an AI system without unnecessarily disrupting operations?
- ☐ Have our executives practiced responding to an AI-related business incident together?
Discussion checklist only. This is not a formal AI maturity or compliance assessment.
Use the questions to start a leadership conversation. Depending on your industry, systems, and obligations, you may need additional review from legal, compliance, privacy, security, risk, or operational experts.
The purpose is simple: identify where visibility, authority, and coordination are unclear before those gaps affect a customer, employee, transaction, or critical operation.
Turn AI responsibility into practiced readiness
You do not need to know everything about AI.
But you should know enough to:
- Ask the right questions
- Challenge assumptions
- Establish accountability
- Confirm decision rights
- Make informed decisions when the technology does not perform as expected
Because when AI creates a business crisis, the response will not belong to IT alone.
It will belong to leadership.
PUT YOUR LEADERSHIP TEAM TO THE TEST
Do not wait for an AI incident to find out who is in charge.
CyFireAI helps organizations practice business-critical decisions through realistic, role-based AI and resilience tabletop exercises. Teams can work through pressure, clarify responsibilities, and identify gaps without affecting production systems.
Experience a fire drill before the real thing happens.
Start with Fire Drill Fridays
Join a free, 30-minute interactive session designed to challenge how you think about AI risk and business decisions.
Always free · 30 minutes · Choose your Friday
Explore the executive readiness approach and bring the five-question check to your next leadership meeting.
Angel Mosley | Founder & CEO, CyBase Risk Management<br> AI Risk • Executive Preparedness • Organizational Resilience