It’s nearly impossible to discuss technology investments without mentioning artificial intelligence (AI)—and that is especially true in cybersecurity. At the recent RSA Conference in San Francisco, AI was at the center of discussions, particularly as cyber threats evolve and bad actors increasingly use AI to bypass security defenses.
Despite AI’s potential in cybersecurity, the sector has seen declining funding and M&A activity. However, investors believe AI’s capabilities could help reinvigorate cybersecurity innovation, even as companies struggle to fully integrate AI-powered security measures.
Cybersecurity AI: Investment Trends
Cybersecurity AI is still in its early stages, both in terms of implementation and investment. A Crunchbase analysis of cybersecurity and AI startups shows that funding has not accelerated as quickly as other AI sectors.
- 2021: Peak investment year, with 130 funding deals totaling $2.3 billion.
- 2023: Declined to just over 100 deals, with $1.2 billion invested.
- 2024 (Year-to-Date): Roughly $700 million invested across 29 deals, with a major chunk going to SandboxAQ, which raised a $500 million round.
At its core, AI enhances automation, which has long been a part of cybersecurity. Security operations centers (SOCs) have leveraged automation to assist cyber teams facing talent shortages.
However, traditional automation is rule-based, requiring manual input from security professionals. This can leave security systems rigid and unable to adapt to new threats. AI-powered security tools, leveraging large language models (LLMs), could revolutionize SOCs by learning and adapting in real-time to emerging cyber threats.
Despite its promise, the real challenge is trust—will companies feel comfortable entrusting their security infrastructure to AI?
“The move from human- to rule-based security was driven by cost. With AI, it will be driven by speed and accuracy.” — Leo Casusol, Managing Director at Forgepoint Capital.
With 90% of web traffic now nonhuman, largely consisting of bots and digital interference, AI could play a critical role in distinguishing genuine threats from background noise.
Alex Doll, Founder of Ten Eleven Ventures, highlights that AI-driven analytics can help security professionals filter out irrelevant data, allowing them to focus on real security risks.
AI in Data Protection and Model Integrity
Another key role for cybersecurity in AI is data integrity—ensuring that AI models are trained on secure, uncorrupted data.
- Cranium, a New York-based startup, raised a seed round from KPMG and SYN Ventures to help enterprises monitor and manage their AI/ML environments, ensuring data integrity.
- As bad actors attempt to manipulate LLMs, cybersecurity measures will be critical to ensuring AI-generated insights remain reliable.
Despite AI’s promise, cybersecurity investors remain cautious. While AI holds the potential to enhance security, streamline operations, and improve threat detection, it still faces legal, ethical, and implementation hurdles.
“Before cyber finds its foothold in AI, artificial intelligence itself must first prove its impact—making businesses more efficient and employees more productive.” — Roger Thornton, General Partner at Ballistic Ventures.
Startups like TrojAI, Calypso AI, and Gretel are developing solutions to integrate AI-driven security into business operations. However, for widespread adoption, the real-world impact of these technologies must become clearer.
AI is poised to transform cybersecurity by improving automation, threat detection, and data integrity. However, challenges remain, and investors are still waiting to see how AI will truly revolutionize security operations. As AI continues to evolve, cybersecurity firms must strike a balance between innovation and risk management—ensuring AI is both a powerful security asset and a trustworthy solution.
