AI-Driven Phishing Defenses Increase Costs for Security Teams

email security

IRONSCALES' new research reveals a dual-use AI paradox in email security: AI-powered defenses accelerate security team response times, yet AI-generated phishing attacks simultaneously inflate the total cost of protection [1]. This treadmill dynamic plays out against a cybersecurity market projected to grow from ~$195B in 2024 to ~$338B by 2029 at an 11.6% CAGR [2]. For enterprise buyers, the findings sharpen the question of whether AI-native platforms can deliver net cost efficiency, not just speed gains.

What is Covered in this Article

  • Cybersecurity market growth trajectory and investment scale [2]
  • AI-powered defenses accelerating security team response times [1]
  • AI-generated attacks inflating total defense costs [1]
  • IRONSCALES research quantifying the offensive-defensive AI paradox [1]
  • Accelerating enterprise deployment of cybersecurity technologies [4][3]

The News: IRONSCALES published new research quantifying how AI is reshaping both sides of the phishing threat market [1]. On the defensive side, AI-powered tools made security teams measurably faster at detecting and responding to phishing threats [1]. On the offensive side, AI-generated phishing attacks drove up the total cost burden on security organizations, offsetting some of those efficiency gains [1]. The findings arrive as enterprise deployment of cybersecurity technologies accelerates broadly, with widespread organizational adoption reaching 77.9% by 1H 2026 [3]. The research frames a critical challenge for security leaders: faster response alone does not guarantee lower costs when the attack surface is expanding at pace.

AI Phishing Defenses Speed Up Teams But Drive Up Total Defense Costs

Analyst Take: IRONSCALES' research surfaces a tension that will define email security buying decisions for the next several years [1]. AI is simultaneously the most powerful tool defenders have and the primary engine inflating the cost of staying protected [1][1]. Vendors that can resolve this paradox, delivering speed and net cost efficiency together, will capture disproportionate share in a market on a steep upward curve [2].

A Market Expanding Fast Enough to Absorb, But Not Excuse, Rising Costs

The global cybersecurity market is projected to grow from approximately $195B in 2024 to $338B by 2029 at an 11.6% CAGR [2]. That trajectory reflects sustained enterprise urgency to fund defenses against increasingly sophisticated threats. But market growth does not insulate buyers from cost pressure at the organizational level. When AI-generated phishing attacks raise the total cost of defense [1], security leaders face a compounding problem: budgets grow, but so do the demands placed on them. The net result is a procurement environment where buyers scrutinize total cost of ownership more carefully, not less. Vendors must demonstrate measurable return, not just capability.

The Speed-Cost Treadmill: What IRONSCALES' Research Reveals

The core finding from IRONSCALES is structurally important [1]. AI-powered defenses made security teams faster at detecting and responding to phishing threats [1], which is a genuine operational win. Faster response reduces dwell time, limits blast radius, and frees analyst capacity. But AI-generated attacks simultaneously made overall defense more expensive [1], creating a treadmill effect where efficiency gains on the response side are partially consumed by the rising cost of staying current on the attack side. This dynamic pressures organizations to continuously invest in smarter, more adaptive protection rather than treating any single deployment as a solved problem. It also raises the bar for what an AI-native platform must prove to enterprise buyers.

Deployment Momentum Validates Demand, But Raises the Stakes for Differentiation

Enterprise adoption of cybersecurity technologies is accelerating. Security decision-makers reported widespread organizational deployment at 69.9% in 2H 2025 [4], rising to 77.9% by 1H 2026 [3]. That momentum confirms buyers are moving from evaluation to broad rollout, which compresses the window for vendors to establish differentiation before purchasing patterns solidify. For IRONSCALES, the research it has published positions the company as a credible voice on the AI paradox it is trying to solve [1]. The challenge is converting that credibility into a clear value proposition: not just that its platform is fast, but that it bends the cost curve in a way that AI-generated attack volume cannot easily reverse [1][1].

What to Watch

  • Net cost efficiency claims: whether IRONSCALES and peers publish quantified total-cost-of-ownership data that moves beyond speed metrics alone [1]
  • Attack volume escalation: how quickly AI-generated phishing attack rates increase through Q4 2026 and whether defense costs track proportionally [1]
  • Enterprise deployment saturation: whether widespread adoption rates plateau above 77.9% or continue climbing into Q3 and Q4 2026 [3]
  • Competitive positioning: how rival email security vendors respond to the cost-speed paradox narrative with their own research or pricing adjustments [2]

Sources

1. Ironscales News, Ironscales, August 2026

2. 1H 2026 Cybersecurity Market Sizing & Five-Year Forecast, Futurum Research, June 2026

3. 1H 2026 Cybersecurity Global Enterprise Decision Maker Survey Report, Futurum Research, June 2026

4. 2H 2025 Cybersecurity Global Enterprise Decision Maker Survey Report, Futurum Research, December 2025


Declaration of generative AI and AI-assisted technologies in the writing process: This content has been generated with the support of artificial intelligence technologies. Due to the fast pace of content creation and the continuous evolution of data and information, The Futurum Group and its analysts strive to ensure the accuracy and factual integrity of the information presented. However, the opinions and interpretations expressed in this content reflect those of the individual author/analyst. The Futurum Group makes no guarantees regarding the completeness, accuracy, or reliability of any information contained herein. Readers are encouraged to verify facts independently and consult relevant sources for further clarification.

Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.

Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum as a whole.

Read the full Futurum Group Disclosure.


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Author Information

FuturumAI

This content is written by a commercial general-purpose language model (LLM) along with the Futurum Intelligence Platform, and has not been curated or reviewed by editors. Due to the inherent limitations in using AI tools, please consider the probability of error. The accuracy, completeness, or timeliness of this content cannot be guaranteed. It is generated on the date indicated at the top of the page, based on the content available, and it may be automatically updated as new content becomes available. The content does not consider any other information or perform any independent analysis.

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