AI is becoming a leading priority for new security spending, but surveyed CISOs generally expect it to expand team capacity and change skills—not trigger broad headcount cuts. In a Dark Reading interview, IANS’ Nick Kakolowski describes how security leaders are adapting to business adoption of AI, automating routine work and tying budget requests more closely to business conditions. The figures below come from IANS and Artico Search’s 2026 benchmark and describe respondents’ expectations, not guaranteed outcomes.
What AI is changing in CISO budgets
Security budgets are growing modestly even as AI becomes a prominent destination for new dollars. IANS and Artico Search’s 2026 Security Budget Benchmark Report, based on responses from more than 500 security executives, reports average security-budget growth of 5%. In that survey, 45% of organizations said their budgets were flat and 10% reported a decrease. The figures describe the survey respondents; the accessible release does not establish a complete sampling frame, geography or weighting methodology.
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| Benchmark finding | 2026 result |
|---|---|
| Average security-budget growth | 5% |
| Organizations reporting flat security budgets | 45% |
| Organizations reporting a security-budget decrease | 10% |
| CISOs naming AI for security the top priority for net-new security dollars | 69% |
| AI security tooling as a share of the average security budget | 3% |
| Software as a share of the average security budget | 35%; two points behind staff and compensation |
These results show a tension rather than a contradiction: AI can be a top priority for additional security dollars while still representing a small share of the total budget. The report also says increased business or operational risk was cited by 48% of CISOs with growing budgets, compared with 3% who cited a major industry breach. In the 2027 outlook, 64% expect a budget increase and 8% anticipate a cut; these are expectations, not actual future results. See the IANS and Artico Search benchmark release.
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Security leaders may be responsible for AI-related risk without controlling all the money used to address it. The benchmark’s report page says 76% of organizations still lack a distinct AI budget line. It reports that 38% fund AI security entirely through IT, data or innovation budgets; those organizations had the weakest reported rate of AI-funding increases, at 31%.
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| Budget approach | Reported AI-funding increase rate |
|---|---|
| Distinct AI budget line or subcategory | Approximately 70% |
| AI embedded in the security budget | 42% |
| AI funded through IT, data or innovation budgets | 31% |
The report page presents these as benchmark survey results, not proof that a particular budgeting structure causes higher investment. It also charts average security-budget growth at 17% in 2022, 4% in 2025 and 5% in 2026. Those historical figures should not be confused with a separate 33% reported for organizations citing AI investment as a primary growth driver. The benchmark is summarized on the IANS report page.
Why Kakolowski sees teams changing, not simply shrinking
Kakolowski describes organizations at different stages of AI maturity, while business leaders press ahead with adoption. In his account, the CISO’s role is shifting from simply resisting AI toward securing its use across the business. That can alter team organization and how organizations define security maturity.
He says AI can help teams take on work they otherwise lack the bandwidth to do, and that CISOs may use the AI discussion to direct resources toward operational or technology debt. This is a capacity and work-design argument, not a claim that every deployment produces savings or that all teams will be reorganized in the same way.
The benchmark reflects that distinction: 91% of surveyed CISOs expect AI to make security teams more productive over the next 12 months, 81% expect demand for new security roles and skills, and 69% do not expect AI to reduce existing security headcount. These are expectations rather than measured outcomes or causal evidence. IANS Faculty member Steve Martano summarized the pattern this way: “More AI and automation embedded in security workflows has not led to massive layoffs, but it has led to the repurposing of team members and a change in hiring and resourcing,” according to the benchmark release.
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Which security work may be automated—and what staff may do instead
Kakolowski points to automation of tier-one security operations center tasks and some tier-two work. In his account, that can let less experienced employees build skills and allow experienced staff to spend more time on nuanced decisions. It is a description of a possible division of work, not a guarantee that automation will eliminate particular roles or that every organization will adopt the same model.
- Routine work: Tasks with clearer patterns may be candidates for automation, subject to the organization’s tools, controls and risk tolerance.
- Early-career development: Entry-level employees may need opportunities to learn and take on more complex work as some routine tasks are automated.
- Experienced practitioners: Senior staff may be redirected toward ambiguous judgments and broader security problems that are harder to reduce to repeatable steps.
The practical workforce question is therefore not only how many people a team needs, but also which skills it must develop and how work is divided as AI enters security workflows.
How AI changes education and hiring expectations
The benchmark’s finding that 81% of surveyed CISOs expect demand for new security roles and skills signals anticipated change in capabilities, not a specific list of job titles or a universal hiring plan. Kakolowski’s account suggests that organizations may need to reskill less experienced workers as routine tasks shift, while experienced employees handle more complex decisions.
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For people preparing to enter security, the implication is to build durable security fundamentals alongside the ability to use and evaluate AI-enabled tools. For employers, training plans should reflect the tasks actually being automated and preserve a route for junior staff to gain experience; otherwise, reducing routine work without replacing its learning value could make skills development harder. That is a workforce-planning implication of the interview, not a quantified finding from the benchmark.
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How CISOs can make a stronger budget case
Kakolowski says security spending is increasingly tied to business conditions and revenue growth, rather than being driven only by threat headlines. He argues that CISOs need cross-functional relationships to understand where the organization is headed and build funding requests accordingly. His formulation is: “So instead of these swings in security budget growth, we’re actually really seeing it be much more tied to the macro environment and to the specific business revenue environment.” The statement appears in the Dark Reading interview.
IANS Faculty guidance recommends framing security proposals around growth, innovation, risk appetite, AI initiatives and measurable returns. A useful planning framework—an editorial synthesis of that guidance and the benchmark’s funding categories—is to make each request answer five questions:
- What is being funded? Distinguish AI-enabled security tools from security for the organization’s adoption of AI.
- Who controls the budget? Identify whether the relevant funds sit with security, IT, data, innovation or another function.
- What result is expected? Define whether the objective is more team capacity, lower risk or enabling a business initiative.
- How will value be shown? Set out expected costs, money saved, measurable returns and the organization’s risk appetite.
- What is the fallback? Present a “good” plan and a “good enough” option so executives can see the trade-offs if full funding is unavailable.
Martano’s warning is that without evidence of savings and return on investment, executives may simply assume AI will solve the problem: “If you don’t come armed with that data, particularly on the money saved and the ROI, the response is going to be, ‘we’ll just use AI to solve it,’ and that’s going to be it.” The guidance is described by IANS.
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What the findings do—and do not—establish
The benchmark and interview capture current market sentiment and survey expectations. They do not prove that AI caused budget changes, increased productivity or prevented layoffs. The accessible benchmark release describes more than 500 executives at organizations of different sizes and industries, but does not provide the full sampling frame, geography or weighting methodology. Kakolowski’s interview transcript was edited for clarity and length; Dark Reading points readers to the video for the full experience.
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