AI Security Tools Are Creating GTM Categories That Didn't Exist 12 Months Ago

New Categories, New GTM Problems

Twelve months ago, "AI governance and risk" was a compliance discussion at conferences. Today it is a purchasing category with dedicated budget lines, vendor shortlists, and RFP requirements. The speed at which AI security tools are creating new market segments is outpacing the ability of most companies to position themselves within them.

The cybersecurity market is large and growing. VerticalIQ reports that global cybersecurity revenue reached $183.1 billion in 2024 and is projected to grow at a 10.5% CAGR to $273.6 billion by 2028 (VerticalIQ, 2026). The aggregate number, however, obscures a more important structural shift: the growth is not evenly distributed across existing categories. It is concentrated in new categories that are being defined in real time by the companies building them — most visibly AI TRiSM (AI Trust, Risk, and Security Management), which Gartner formally named and first covered in a dedicated Market Guide (Gartner, 2025).

The Four Categories Emerging Now

1. AI-Powered Threat Detection

Machine learning models that identify threats through behavioral pattern analysis rather than signature matching. This category existed in prototype form for years, but the combination of transformer-based architectures and affordable inference compute has made it commercially viable at mid-market price points. The talent constraint is real — the 2024 ISC2 workforce study documented a global cybersecurity workforce gap of 4.8 million professionals, up 19% year-over-year, with 90% of organizations reporting skills shortages (ISC2, 2024). Automation and AI-driven detection are pulled into that gap.

The GTM challenge: buyers understand "threat detection" but not "AI-powered threat detection" as a distinct purchase. Positioning requires educating the buyer on why the approach is categorically different — not incrementally better — than legacy signature-based systems.

2. Automated Compliance Monitoring

Continuous compliance monitoring that replaces periodic manual audits with real-time evidence collection. SOC 2 Type II, CMMC Level 2, ISO 27001, and HIPAA frameworks are the primary drivers. The regulatory tailwind is significant — VerticalIQ notes that CISA's 2024 rulemaking requires covered entities to report cyber incidents within 72 hours and ransomware payments within 24 hours, and the U.S. SEC's 2023 rule requires material cybersecurity incident disclosure within four days (VerticalIQ, 2026). Compliance is no longer a once-a-year event.

The GTM challenge: compliance is a "must-do" purchase, which means buyers are highly motivated but also highly risk-averse. They will not adopt an unproven vendor for a function that carries personal career risk if it fails — a pattern Gartner documents directly, finding that 68% of B2B buyers research intensively specifically to reduce perceived decision risk (Gartner, 2023).

3. AI Governance and Risk

A category that barely existed before the EU AI Act and the wave of AI executive orders that followed. Companies deploying AI systems now need governance frameworks, risk assessment tools, and audit trails for their models. Gartner's AI TRiSM Market Guide projects that by 2028, 25% of large organizations will have dedicated AI governance teams, up from less than 1% in 2023 (Gartner, 2025). The implication: the buying committee for this category is being formally constituted right now, inside customer organizations.

The GTM challenge: the buyer often does not yet know they need this. Market education and category creation must happen simultaneously. The company that defines the category's vocabulary often captures first-mover positioning advantage Sagentix Phase 01 Market Intelligence, 2026.

4. Deepfake and Synthetic Media Detection

Generative AI has made synthetic media — fake audio, video, and images — trivially easy to produce. Detection tools are emerging to serve financial services (identity verification), media companies (content authentication), and government agencies (national security). This is a pure category-creation play, and the threat is no longer abstract: Veriff documents a 2,137% rise in deepfake fraud attempts against financial-services firms since 2022, with incident losses of up to $680K per event (Veriff, 2025).

The GTM challenge: the threat is well understood in the abstract but poorly quantified. Buyers agree deepfakes are a problem but struggle to calculate the ROI of detection tools. Positioning requires making the threat concrete and the cost of inaction measurable.

Why Evidence-Based Positioning Is Non-Negotiable in New Categories

In mature markets, buyers have existing mental models. They know what a firewall does. They understand endpoint detection and response. The vendor's job is to differentiate within a known frame.

New categories have no established frame. The buyer's mental model is incomplete or absent. This creates two simultaneous requirements that most companies handle poorly:

Requirement 1: Educate the market on the category. This demands thought leadership, published research, speaking engagements, and content that explains the problem space — not the product. Gartner research finds that B2B buyers value third-party interactions 1.4× more than digital supplier interactions, which is why category-educating content produced by the vendor is only half the job; third-party validation carries more weight (Gartner, 2023).

Requirement 2: Establish credibility as a category leader. While educating the market, the company must simultaneously position itself as the authoritative voice in the space. This requires evidence — published case studies, third-party validation, compliance-aligned messaging, and quantified outcomes. In enterprise B2B, buying groups now include a median of six to ten stakeholders, each arriving with four to five independent pieces of information (Gartner, 2023). Evidence needs to survive each reader's private review, not just the pitch meeting.

The tension is real: you cannot rely on the category's reputation to validate your company, because the category has no reputation yet. Your company's evidence IS the category's credibility.

The Window Is Open but Time-Limited

Category creation follows a predictable lifecycle:

Phase 1 — Emergence (now). A handful of companies are building solutions. Buyers are early adopters or companies under regulatory pressure. The category vocabulary is not yet settled. First movers who define the language capture disproportionate mindshare.

Phase 2 — Validation (12–24 months). Analyst firms begin covering the category. Gartner publishes a Market Guide (as it did for AI TRiSM in February 2025). Budget line items appear in enterprise planning cycles. The category is real but the competitive landscape is still forming (Gartner, 2025).

Phase 3 — Consolidation (24–48 months). Incumbents enter through acquisition or internal development. The category converges on standard definitions. Differentiation shifts from "we invented this" to "we do it better." Late entrants compete on price.

For companies building in AI security today, the strategic window is Phase 1. The economics of category creation are most favorable now — when the field is open, the vocabulary is unset, and evidence-based positioning can establish durable first-mover advantage Sagentix Phase 02 VP Design, 2026.

In 24 months, these categories will have established leaders, defined vocabulary, and Gartner Magic Quadrants. The companies that defined the terms will be in the upper right. The ones that waited will be explaining why they are different from the leaders.

What This Means for GTM Strategy

Companies entering new AI security categories need a GTM approach calibrated to category creation, not category competition:

• Market intelligence must quantify the new category — bottom-up sizing with named data sources (VerticalIQ, BLS, government rulemaking records), not "AI security is a huge market" generalities. Investors and boards need evidence that the specific subcategory is large enough to justify the bet (VerticalIQ, 2026).
• Competitive positioning must acknowledge the category is new. Mapping yourself against legacy players is a positioning error. You are not competing with traditional SIEM vendors — you are creating an adjacent category. The competitive matrix should include emerging players and substitutes, not incumbents in a different market (Porter, 1980).
• Messaging must educate and differentiate simultaneously. Every piece of content should advance the buyer's understanding of the category while establishing your company as the credible authority within it. Thought leadership and sales enablement are the same asset.
• Pricing must signal premium positioning. In a new category, low pricing signals low value. Buyers are paying for risk reduction, and risk reduction commands premium economics. Price anchoring against the cost of a breach or regulatory fine — not against competitor pricing — is the correct frame (Nagle & Müller, 2018).

The double-digit CAGR in cybersecurity is not evenly distributed. It is concentrating in categories that did not exist twelve months ago. The question for companies building in these spaces is not whether the market is real. It is whether they will define it — or be defined by it.

References

• Gartner. (2023, June 8). Gartner marketing survey finds B2B buyers value third-party interactions more than digital supplier interactions [Press release]. Gartner, Inc. https://www.gartner.com/en/newsroom/press-releases/2023-06-08-gartner-marketing-survey-finds-b2b-buyers-value-third-party-interactions-more-than-digital-supplier-interactions
• Gartner. (2025, February 18). Market guide for AI trust, risk and security management. Gartner, Inc. https://www.gartner.com/en/documents/6185655
• ISC2. (2024). 2024 ISC2 cybersecurity workforce study. International Information System Security Certification Consortium. https://www.isc2.org/Insights/2024/10/ISC2-2024-Cybersecurity-Workforce-Study
• Nagle, T. T., & Müller, G. (2018). The strategy and tactics of pricing: A guide to growing more profitably (6th ed.). Routledge.
• Porter, M. E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. Free Press.
• Sagentix. (2026). GTM methodology: Category-creation playbook [Internal methodology documentation]. Sagentix Advisors Inc.
• Veriff. (2025). The growing threat of deepfakes in financial services – and why a "trust infrastructure" is the future. Veriff. https://www.veriff.com/identity-verification/the-growing-threat-of-deepfakes-in-financial-services-and-why-a-trust-infrastructure-is-the-future
• VerticalIQ. (2026). Cybersecurity services industry profile (NAICS 541690). VerticalIQ.