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AI has expanded the CISO’s job beyond using automation to defend systems. CISOs are increasingly involved in governing AI-enabled products, workflows, vendors and agents, while helping security teams use AI safely. Keeping up means combining security and AI literacy with clear accountability, cross-functional influence, risk communication and workforce development—not becoming a machine-learning researcher.
How AI is changing the CISO mandate
The CISO now has two connected but distinct responsibilities: helping the security function use AI, and helping the organization manage the risks of AI it builds, buys or puts to work. The first concerns security operations, such as reviewing events and correlating data. The second reaches into business processes, products, software development, vendor relationships and autonomous or semi-autonomous agents.
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A February 2026 Cisco summary of Splunk’s annual CISO Report says nearly all respondents reported responsibility for AI governance and risk management, and more than four out of five said they oversaw secure software development. The findings came from Oxford Economics’ survey of 650 CISOs conducted in July and August 2025 across nine countries and nine industry groups; they describe those respondents, not every organization. Cisco’s report summary and methodology provide the survey context.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsAI’s value and risk appear together in the same survey. Ninety-two percent of respondents said AI enabled their teams to review more security events, and 89% reported improved data correlation. Those are respondent reports, not controlled measurements of performance. At the same time, 86% feared agentic AI would increase the sophistication of social-engineering attacks.
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This broader remit does not mean the CISO should own every AI decision. Business leaders set objectives and acceptable risk; product and engineering teams design and operate systems; legal, privacy, compliance, procurement and finance may need to weigh in. Security can help establish decision rights, controls, monitoring and escalation. Deloitte’s analysis argues for named business, technical and risk-oversight owners for significant use cases, rather than an assumption that one executive can carry the whole accountability chain. Its survey is separate from the Cisco/Splunk survey: Deloitte reports that 49% of organizations in its survey had a CISO role in 2026, up from 31% in 2023. Deloitte’s analysis of the changing CISO role sets out its governance perspective.
Which CISO skills need to keep pace?
AI and model literacy
A CISO need not train models, but should be able to ask what data a system uses, where that data goes, what permissions the system has, which tools it can invoke, how its output is checked and where a person can intervene. The same questions apply whether the organization develops a model, embeds AI in a product or adopts a vendor’s service.
Governance judgment and accountability
For each significant AI use case, establish an inventory entry, a business owner, a technical owner and a risk-oversight owner. Define the permitted purpose, the approval required before launch, the conditions that require a pause, the evidence that must be retained and the route for escalating problems. This makes accountability actionable without turning security into the default owner of every business outcome.
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AI agents can act through connected tools and data, so ordinary questions about identity and least privilege need to include delegated activity. Ask which identity an agent uses, whose authority it represents, what it can reach, for how long, and how that access is revoked. An agent should not inherit broad permissions simply because its human operator has them.
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Secure-by-design collaboration
Work with product and engineering leaders while systems are being designed, not only at release review. Security input should cover data flows, access, dependencies, testing, logging, incident response and changes to models or connected tools. Deloitte quotes a CISO at a major American biopharmaceutical company describing the pace of vulnerability exposure: “Back in the day, if a vulnerability got introduced, you had at least weeks. These days it’s getting down to hours.” That observation is not a universal measurement, but it underscores why security decisions need to fit faster development and change cycles.
Executive risk communication
Translate technical controls into business consequences: what service, customer data or decision could be affected; how likely misuse or failure is; how quickly the organization could detect it; and what containment or recovery would look like. A concise risk explanation should distinguish a known control gap from a speculative scenario, and state who can accept the remaining risk.
Workforce development
Review work by task rather than assuming AI simply removes jobs or makes every role more productive. Identify tasks that can be automated, tasks that AI can assist but a person must validate, and tasks where judgment, investigation or accountability still require a human. Provide time and training for teams to use new tools safely and adapt responsibilities as systems change.
How to govern AI agents in practice
Deloitte recommends treating agent behavior as something to monitor and control, not merely approve at launch. Its suggested measures are analytical recommendations, not a binding standard; adapt them to each system’s permissions, impact and risk tolerance.
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- Watch tool use: alert on unusual tool calls, unexpected interactions or behavior that departs from the agent’s assigned goal.
- Detect privilege changes: monitor for privilege escalation and access beyond the agent’s expected scope.
- Track data access: log unusual or sensitive-data access, including the identity and authority under which it occurred.
- Set intervention thresholds: define in advance which events require a human review, suspension or other rapid intervention.
- Preserve useful records: retain logs that let responders reconstruct what the agent did, what it accessed and what instructions or tool interactions shaped its actions.
These controls are most useful when paired with an explicit decision about which actions an agent may take automatically and which require human approval. A control that only blocks known bad inputs may not be enough if the system can act unexpectedly; detection, containment and recovery also matter.
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Start with the organization’s actual AI use cases and the consequences of failure. A customer-facing agent with access to sensitive records calls for different permissions and intervention points than an internal assistant that only summarizes approved documents. Use a short review to turn broad principles into decisions:
- Map use cases: identify AI-enabled products, workflows, vendor services and agents, including what data and tools each can access.
- Name accountable owners: record business, technical and risk-oversight owners for significant uses, then make approval and escalation paths clear.
- Set action boundaries: specify what the system may do on its own, what needs human approval, and what conditions trigger a pause.
- Test the control loop: verify that monitoring, logs, incident response, containment and recovery work for the use case—not only that preventive controls exist.
- Match workforce plans to tasks: decide where to hire, upskill, redesign roles or keep human review, and revisit those choices as tools and risks change.
The workforce evidence argues against treating headcount as the only capacity measure. SANS Institute and GIAC’s 2026 report, based on 947 global respondents, says 60% of organizations named the skills gap as their leading workforce challenge, compared with 40% citing headcount shortages. The report also says 74% saw AI changing cybersecurity team size or role structures, while 16% cited workforce reduction. These findings suggest varied organizational responses, not inevitable job loss or proof that training alone prevents breaches. The report attributes a direct-impact breach to workforce skills gaps at 27% of organizations; that association does not establish that a particular training program would prevent such an incident. SANS and GIAC’s 2026 workforce report describes its sample and findings.
What a useful readiness test looks like
Your skill set is keeping pace if you can do more than name AI risks or tools. You should be able to ask the right technical questions, get accountable owners around the table, set boundaries for automated action, explain residual risk in business terms and develop a workforce that can operate the controls. The goal is not for the CISO to become the owner of all AI; it is for the CISO to make risk visible and governable while the people accountable for business outcomes make informed decisions.
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