AI Security Tools Got a Budget Line. The People Who Run Them Didn't.
October 26, 2026
Randy Hall, CEO— AI-assisted and reviewed prior to publication.
Most security leaders are funding AI security tools faster than they are funding the people who operate them. New budget data shows AI tooling now claims the largest share of net-new security spending, while median budget growth for everything else, including training, sits at zero. The result is a widening gap between what organizations buy and who can actually run it safely.
Is AI Security Tool Spending Outpacing Staff Training?
Yes, and the gap is measurable. According to the 2026 Security Budget Benchmark Report from IANS Research and Artico Search, AI for security was the top priority for allocating net-new budget dollars, with 69% of CISOs identifying it as their leading investment area, even as overall security budgets remained nearly flat.
That spending pattern is not evenly distributed. The same research found that AI security tooling now accounts for 3% of the average security budget on its own, and when combined with the rest of the software category, software represents 35% of the overall security budget, putting it two percentage points behind staff and compensation, according to TechTarget's coverage of the report. Tooling is catching up to headcount as a budget category. Training to operate that tooling is a separate line, and it is not catching up at the same rate.
Why Are CISOs Buying Tools Before Building the Team to Run Them?
Because the tools were available before the talent was, and procurement moves faster than certification cycles. Security leaders are under pressure to show the board they are addressing AI risk, and a purchase order is a faster answer than a training plan. That sequencing creates exposure the budget data does not fully capture.
The SANS 2026 Workforce Report found that 60% of CISOs named "not having the right staff" as their top challenge, ahead of the 40% who chose "not enough staff," with AI identified as the primary driver because rapid enterprise AI deployment has exposed gaps in what existing teams know how to secure. The report's lead recommendation is direct: organizations should build an AI security training program before the next AI tool deployment, not after, because the core finding was that most organizations deployed AI first and discovered the skill gap second.
That ordering problem matters because hiring your way out is not a reliable fix. The same SANS research notes that the market for highly skilled AI security practitioners is too small and too expensive to solve the gap through recruiting alone. If you cannot buy the skill on the open market at the pace you need it, you have to build it inside the team you already have.
What the Budget Data Actually Shows
The RH-ISAC 2026 CISO Benchmark reinforces the same pattern from a different angle. Nearly 90% of CISOs expect AI security spending to rise, largely by reallocating existing budgets rather than adding new dollars, and security budgets remain heavily concentrated on staff and compensation alongside off-premises software, underscoring the continued weight of talent and cloud tools in the spending mix. Reallocation, not expansion, is the operative word. Money is moving toward AI, but it is moving from somewhere else in the same flat budget, which means something else gets less.
| Budget category | Share of average security budget | What it funds |
|---|---|---|
| Staff and compensation | Largest single category | Headcount, including AI-literate roles |
| Software (including AI tooling) | 35%, two points behind staff | Platforms, detection tools, AI security products |
| AI tooling specifically | 3%, a new standalone line in 2026 | Tools to secure or monitor AI systems |
This is the trade-off a buyer actually faces. Every dollar that moves into an AI tooling line is a dollar that is not funding the certification, course time, or exam vouchers that would let someone on staff operate that tool with judgment instead of just a login. If you want a clearer picture of how a structured study plan fits around a working schedule, the curriculum overview and FAQ in Forge University's resources walks through what a realistic pace looks like.
The Operational Risk of a Tool Without a Trained Operator
A tool that nobody is formally trained to run is a liability dressed up as a control. AI security tools generate alerts, model risk scores, and policy recommendations, and someone has to interpret those outputs correctly under pressure. Without that training, the tool either gets ignored, misconfigured, or trusted more than it should be, and any of those outcomes defeats the purpose of the purchase.
ISACA built its response to exactly this problem. The 2025 ISC2 Cybersecurity Workforce Study found that 95% of respondents reported at least one skill need, a 5% increase from 2024, and 59% cited critical or significant skill needs, a 15% increase from the previous year, with AI topping the list of specific gaps. ISACA's answer was the Advanced in AI Security Management credential, which the organization describes as designed to equip cybersecurity leaders with the specialized skills needed to manage the evolving security risk related to AI, implement policy, and ensure its responsible and effective use across the organization. It builds on CISM and CISSP rather than replacing them, which matters for a budget conversation: it is a credential for people who already carry security management responsibility and now need to extend that judgment to AI systems specifically.
That design choice is worth noting for anyone building the business case internally. You are not funding a brand-new discipline from zero. You are extending a credential your senior staff likely already hold into a domain that your tool spending has already made urgent. The path from Forge University's CISM certification prep into AI-specific security management is a shorter and more defensible ask to a finance committee than standing up an entirely new hiring line.
Making the Case for Training Budget Alongside Tool Budget
The business case does not need to be complicated, but it does need to be made explicitly, because nobody is going to volunteer to shrink the tooling line on your behalf. Three points tend to land with finance and the board.
- The tool was already approved as a risk-reduction investment, so the training that makes it effective is part of the same risk case, not a separate ask.
- A credential tied to an existing team member's role, rather than a new hire, is a lower-cost and faster path to coverage than recruiting for a role the market cannot fill quickly.
- Flat overall budgets make reallocation, not expansion, the realistic frame, so the ask is to shift a portion of next year's software line into certification rather than request net-new funds.
If your team is ready to start closing that gap rather than just naming it, you can start training now and have the first credentialed staff member in place before the next tool renewal cycle comes up for budget review.
The Decision in Front of You
None of this argues against buying AI security tools. The threat surface those tools address is real, and waiting for perfect staffing before acquiring any capability is its own kind of risk. The argument is narrower: a purchase order without a corresponding training commitment is an incomplete decision, not a finished one.
The data is consistent across every recent survey cited here. Budgets are flat, AI tooling is absorbing the growth that exists, and skills are now the top concern ahead of headcount. The organizations that come out ahead over the next budget cycle will not be the ones that bought the most AI security tools. They will be the ones that paired every tool purchase with a named, credentialed person accountable for running it.