The Ultimate List: 80+ AI-Powered Cybersecurity Stats & Trends

Blog Overview: AI now sits on both sides of the cyber fight, defenders use it to detect and contain breaches faster than ever, while attackers use it to write phishing, clone voices, and, increasingly, run autonomous agents. This blog covers the latest 2026 statistics on the AI-in-cybersecurity market, enterprise adoption, AI-powered attacks, phishing, deepfakes, ransomware, and the fast-emerging risk of agentic AI. Every figure is sourced from recognized reports, so you can see exactly where the numbers come from, and what they mean for your security program.

As cyber threats evolve in complexity and scale, the need for advanced defense mechanisms has never been more urgent. Traditional cybersecurity strategies are increasingly inadequate against sophisticated attacks like zero-day exploits, ransomware, supply chain compromises, and AI-powered phishing attempts. In this context, Artificial Intelligence (AI) has emerged as a critical component of modern cybersecurity, offering both unprecedented opportunities for defense and new avenues for cyber threats.

As we move forward by adopting digital infrastructure, understanding the statistical landscape of AI’s integration into cybersecurity is crucial for organizations. Backed by data-driven research and key statistics, we’ll explore the current landscape of AI adoption—its role in preventing data breaches, the challenges organizations face, and the broader economic impact of this evolving technology. And in 2026, one shift stands above the rest: the arms race has moved from generative AI to agentic AI, where autonomous systems act, on both attack and defense.

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Artificial Intelligence (AI) In Cybersecurity Market Key Takeaways

As per the market research, the global AI in cybersecurity market size was estimated to reach USD 25.35 billion in 2024 and grew to an estimated USD 31.48 billion in 2025. It is now projected to reach USD 93.75 billion by 2030, growing at a CAGR of 24.4% from 2025 to 2030.

• Precedence Research values the market at USD 29.64 billion in 2025 and projects it to reach USD 167.77 billion by 2035, at a CAGR of 18.93%.
• Fortune Business Insights estimates the market at USD 34.09 billion in 2025, rising to USD 44.24 billion in 2026 and USD 213.17 billion by 2034 (CAGR 21.71%).
• A 2024 survey revealed that 54% of U.S. respondents identified this application as their primary AI-enabled cybersecurity strategy.
• The North America artificial intelligence (AI) in cybersecurity market size held the largest global share (≈34.9% in 2025, ≈35.5% in 2026) and is projected to reach roughly USD 14.95 billion in 2026, driven by the concentration of major vendors and heavy BFSI, healthcare and IT adoption.

The U.S. artificial intelligence (AI) in cybersecurity market size is estimated at USD 7.88 billion in 2025 and is projected near USD 7.60 billion in 2026 on its way to USD 45.69 billion by 2035, growing at a CAGR of roughly 18.9%, the U.S. remains the single largest national market.

As per MarketsandMarkets research, the market is projected to reach USD 50.83 billion by 2031, with software taking the largest share as more enterprises adopt AI-based detection and automated response.

• Geography: North America accounted for the largest share of global revenue roughly 35.5% in 2026.
• Type: The network security segment is projected to hold the highest share (≈32.4% in 2026), while application security grows fastest.
• Offering: The services segment held a leading revenue share of ≈34.9% in 2025.
• Technology: Machine learning led the technology segment, capturing over 47% of the total revenue.
• Vertical: Large enterprises are projected to hold ≈62.2% of the market in 2026, while BFSI remains the top spender.
• Application: Fraud detection and anti-fraud applications accounted for over 22% of the total market revenue.
• There are 3,194 Artificial Intelligence (AI) companies in Cybersecurity worldwide. The leading companies include Splunk, Palo Alto Networks, Darktrace, CrowdStrike, Ping Identity, ZeroThreat, and Fortinet.
• Over the past 10 years, an average of 221 new companies have been launched annually.
• Over the past few months, the banking sector has experienced a 280% surge in cyber-attacks, a threat that can be significantly mitigated with AI-driven defenses.

• 90% of organizations are actively implementing or planning to explore large language model (LLM) use cases, while only 5% feel highly confident in their AI security preparedness.
• The AI in cybersecurity market is projected to grow by $8.3 billion over the next five years, reflecting its rising adoption across industries.
• Approximately 61% of organizations report they cannot effectively respond to breach attempts without AI support.
• In recent years, more than half of cybercrimes have involved the use of AI and machine learning, highlighting the dual-use nature of these technologies.
• Up to 75% of security awareness professionals are expected to implement AI-based solutions into their daily operations.
• Currently, 63% of security breaches are detected more quickly when AI is integrated into cybersecurity systems.
• 69% of companies believe they cannot effectively respond to cyber threats without AI assistance.
• Reflecting a major shift in cyber warfare, cybercriminals are reportedly freeing up to 60% of their time through the use of AI-driven automation.
• 1 in 6 (16%) of all data breaches now involve attackers using AI, most commonly for phishing (37% of AI-enabled attacks) and deepfake impersonation (35%).

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Impact of AI on Cybersecurity – Key Statistics

• For the first time in five years, the global average cost of a data breach fell, to USD 4.44 million in 2025, down 9% from USD 4.88 million, driven by faster AI-powered detection and containment.
• Organizations that used AI and automation extensively cut their breach lifecycle by about 80 days and saved roughly USD 1.9 million per breach versus those that didn't.
• Mean time to identify and contain a breach dropped to 241 days, the lowest in nine years.
• AI-based solutions reduce IoT security risks by 60%.
• AI automates up to 80% of cybersecurity operations.
• AI-powered behavioral analysis reduces cyberattack success rates by 73%.
• AI predicts 85% of data breaches before they occur.
• 60% of cybercriminal groups now use generative AI for attacks.
• AI enhances dark web threat intelligence by 68%.
• AI improves Security Operations Center (SOC) efficiency by 95%.
• AI-driven spear phishing emails have a 92% higher success rate.
• AI-driven network security reduces breach likelihood by 83%.
• 80% of AI-driven security systems have been tested against adversarial AI attacks.
• AI-driven endpoint security reduces attacks by 72%.
• AI-based cloud security tools reduce misconfigurations by 65%.
• AI-powered email filtering reduces spam and malicious emails by 94%.
• AI-powered tools can crack 51% of passwords in less than a minute.
• AI improves zero-day vulnerability detection rates by 70%, significantly enhancing organizations’ ability to identify and mitigate previously unknown threats.
• AI helps reduce insider threats by 45%, enabling organizations to detect unusual behavior patterns and prevent internal security breaches more effectively.
• Companies using AI-driven security save an average of $3.81 million per breach, highlighting the significant cost advantage of proactive, AI-powered threat detection and response.

Adoption of AI in Cybersecurity

The adoption of AI in cybersecurity is accelerating across industries. Now is the time to get deeper into how organizations and security professionals perceive AI’s impact—its growing importance, practical applications, and potential to reshape the future of cyber defense.

• 55% of organizations are planning to adopt GenAI solutions within the year. This reflects a significant shift toward AI-driven cybersecurity strategies and widespread industry adoption.
• 48% of cybersecurity professionals express confidence in their organization's ability to implement an AI-based security strategy. While this data shows growing readiness, it also highlights a gap where many teams may still require additional resources or training.
• Only 12% of security professionals believe AI will fully replace their roles. This suggests that the majority view AI as an enhancement to human expertise, not a substitute.
• 68% of these businesses in the survey were currently using at least one AI technology, while 32% had plans to adopt AI in the future.
• Among businesses currently leveraging AI, 64% are utilizing a single type of AI technology, while 22% have adopted two types, and 14% are employing three or more AI technologies—indicating a growing trend toward multi-layered AI integration in cybersecurity strategies.
• Among businesses currently leveraging AI, natural language processing and generation is the most prevalent, with 38% of organizations adopting it. This is followed by machine learning at 27%, and computer vision, image processing, and generation at 25%.
• 65% of respondents say their organizations now regularly use generative AI, and broader McKinsey data shows around 78% of organizations use AI in at least one business function, up sharply year over year.
• Over 57% of employees now use personal GenAI accounts for work, and 33% admit entering sensitive data into unapproved tools.
• 14% of employees were found using GenAI tools on corporate devices, and 72% of them accessed those tools with personal emails or unauthenticated accounts rather than governed corporate ones.
• According to Gartner's 2026 CIO survey, only 17% of organizations have deployed AI agents so far, but more than 60% expect to within two years, the most aggressive adoption curve of any emerging technology tracked.
• 9% of businesses reported using AI-related hardware, while 8% are implementing RPA, showcasing a broad spectrum of AI technologies being integrated into operations.
• 38% to 60% of businesses adopted AI technologies primarily through the purchase of external software or ready-to-use systems.
• 21% of businesses reported developing machine learning technologies in-house.
• 34% of organizations chose to outsource development of AI-related hardware, making it the most commonly outsourced AI function.
• Among current AI users, 47% reported having no specific cybersecurity practices in place for AI technologies, while 13% were unsure about their organization's practices.
• Of those planning to adopt AI in the future:
  1. 25% stated their organization would not implement dedicated cybersecurity measures for AI.
  2. Another 25% were unsure whether such practices would be established.
• Among organizations without — or not intending to implement — specific AI-related cybersecurity practices:
  1. 14% admitted they had not considered the need or lacked sufficient knowledge.
  2. Another 14% believed that AI was not being used for sensitive applications, thus didn't require special security measures.
• A report from BlackBerry suggests that 95% of IT decision-makers believe that governments should take responsibility for regulating advanced technologies like ChatGPT.
• ChatGPT usage has surged by 634.1%, making it the fastest-growing AI application—despite also being the most-blocked by enterprises.
• 85% of organizations feel confident in their data security strategies to keep pace with the rapid evolution of AI.
• 35% of companies report they are already leveraging AI across various business functions.

The Hidden Risks Behind AI Adoption

As investments in AI surge, there's broad consensus that defensive AI will play a critical role in strengthening cybersecurity. While the technology offers promising advantages in threat detection, prevention, and response, it also introduces new risks and complex challenges that cannot be overlooked.

In 2026, the biggest of these is a governance gap: organizations are racing to adopt AI far faster than they are securing it.

In a recent survey conducted by the Cloud Security Alliance (CSA), respondents highlighted several key concerns regarding the use of AI in cybersecurity:

Confidence in current security measures remains notably low. Only 5% of respondents rated their confidence at the highest level—five out of five.

According to a survey by Lakera, a significant 86% of participants expressed moderate to low confidence in their existing security strategies’ ability to defend against advanced AI-driven attacks, reflecting widespread uncertainty about current preparedness.

• According to a Statista report, nearly 50% of global business and cybersecurity leaders cited the advancement of adversarial techniques, including phishing, malware development, and deepfakes, as their top concern regarding the impact of generative AI on cybersecurity.
• Meanwhile, 60% of organizations admit they are not adequately prepared to defend against AI-driven cyberattacks.
• In a striking indicator of rising caution, enterprises are now blocking 18.5% of all AI/ML transactions—a 577% increase over just nine months—highlighting escalating fears around AI data security and a growing hesitance to implement AI policies.
• 97% of organizations that suffered an AI-related security incident lacked proper AI access controls.
• 63% of breached organizations had no AI governance policies in place to manage AI or prevent shadow AI.
• Shadow AI, unsanctioned employee use of AI tools, was a factor in 20% of breaches and added about USD 670,000 to the average breach cost, pushing shadow-AI breaches to ~USD 4.63 million each.
• 60% of AI-related breaches led to data compromise and 31% caused operational disruption, as attackers targeted compromised apps, APIs and plug-ins across the AI supply chain.
• A staggering 77% of companies reported experiencing security breaches in their AI systems within the past year, underscoring the growing risks associated with AI integration.
• Additionally, over 95% of respondents believe that the use of dynamic content generated by large language models (LLMs) has made phishing detection significantly more difficult, raising new concerns around AI-fueled social engineering.

• As concerns around data security intensify, 63% of organizations have implemented restrictions on the type of data that can be input into generative AI tools, while 27% have taken a stricter stance by banning GenAI applications entirely. (Cisco)

• 55% of data leaders identify the inadvertent exposure of sensitive information by large language models (LLMs) as one of the most serious threats in today’s AI landscape.
• 57% report a significant surge in AI-powered attacks over the past year—highlighting the dual challenge of protecting data while combating increasingly intelligent threats.

• In a recent survey, 36% of respondents ranked AI-powered attacks as their top cybersecurity concern, reflecting growing anxiety over the offensive use of generative technologies.
• 51% of IT decision-makers believe that a major cyberattack will be publicly attributed to ChatGPT or similar AI tools within the next year.
• 51% of IT professionals believe that successful cyberattacks in 2024 could be attributed to ChatGPT or similar AI tools.
• 53% of IT professionals identify the biggest concern with ChatGPT as its ability to help cybercriminals craft more convincing and legally sound phishing messages.
• 71% of IT professionals suspect that nation-states may already be leveraging ChatGPT for hacking and phishing operations targeting other countries.
• 43% of cybersecurity experts have observed a rise in machine-driven cyberattacks, reflecting a growing trend in AI-powered threats.

• 36% of respondents said they haven’t used AI or ML for cybersecurity yet, but are now seriously exploring generative AI tools.
• 37% of data leaders report having a comprehensive strategy in place to stay compliant with current and emerging AI regulations and data security demands.
• 71% of organizations have already taken proactive steps to reduce risks associated with AI adoption.

• As per McKinsey report, 65% of respondents say their organizations regularly use generative AI—nearly double the figure from a survey conducted just ten months earlier.

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Technological Advancements

With the rapid evolution of AI technology, its integration into existing workflows is expected to significantly enhance operational efficiency and reduce costs. Rather than replacing cybersecurity professionals, AI is increasingly seen as a powerful ally, augmenting human expertise, automating routine tasks, and enabling faster, smarter decision-making in threat detection and response.

• In a recent survey by CSA, only 12% of professionals reported facing no challenges in threat investigation and response, emphasizing the need for tools like AI to support and enhance these critical security functions.
• Just 12% of security professionals believe AI will completely replace their jobs, while the majority see it as a way to augment their skills, assist in their roles, or automate routine tasks, freeing them to focus on higher-level responsibilities.

• Organizations are applying AI across various cybersecurity use cases, with the top areas being rule creation (21%), attack simulation (19%), and compliance violation detection (19%).

Data leaders are increasingly interested in AI's potential as a data security enabler. According to respondents, some of the key advantages of using AI in data security operations include:

1. Anomaly detection (14%)
2. Security app development (14%)
3. Phishing attack identification (13%)
4. Security awareness training (13%)

• Two-thirds of organizations now utilize AI and automation in their Security Operations Centers (SOCs)—a 10% increase compared to the previous year.
• Organizations without AI and automation in their security stack face an average breach cost USD 5.52 million, while those using AI and automation extensively average USD 3.62 million, a gap of about USD 1.9 million.
• Defensive AI is anticipated to have a major impact across cloud, data, and network security, enhancing protection and response capabilities across digital environments.

• 71% of security stakeholders express confidence in AI-powered security tools, believing they are more effective at blocking AI-driven threats than traditional solutions.
• 69% of enterprise executives agree that AI will be essential for responding to cyberattacks, underlining its growing strategic importance. In the telecom sector, a notable 80% of companies are relying on AI to detect threats and prevent attacks, reflecting industry-specific confidence in AI’s defensive capabilities. (Capgemini Research Institute)
• As per Gartner, by 2028, the use of multi-agent AI in threat detection and incident response is projected to grow from 5% to 70% of AI applications—primarily designed to assist cybersecurity teams, not replace them.

• Through 2025, the rise of generative AI is expected to drive a 15%+ increase in application and data security spending, as organizations invest more resources to secure AI systems.
• By 2026, roughly 40% of development teams routinely use AI-powered auto-remediation from AST vendors, up from under 5% in 2023, a shift now visibly underway.
• Global information security spending is projected to reach USD 244.2 billion in 2026, with the "AI-amplified" security market growing from ~USD 49 billion in 2025 to ~USD 160 billion by 2029.

Agentic AI: The New Attack Surface

The defining cybersecurity shift of 2026 isn't generative AI that writes text, but it's agentic AI that takes action. An AI agent plans multi-step tasks, calls tools and APIs, reads and writes data, and chains those actions together with limited human oversight.

That autonomy is exactly what makes agents useful, and exactly what makes them a security problem the industry never built defenses for. When an agent is compromised, it can traverse systems, exfiltrate data, and escalate privileges at machine speed, before a human analyst can react.

• Gartner projects 40% of enterprise applications will embed task-specific AI agents by 2026, up from less than 5% in 2025.
• In a widely cited Dark Reading poll, 48% of cybersecurity professionals named agentic AI and autonomous systems the single most dangerous attack vector of 2026.
• 92% of security professionals say they are concerned about the impact of AI agents on their organizations.
• The average AI-agent-related data breach now costs roughly USD 4.7 million, and prompt injection, a technique barely named three years ago, already affects more than a third of deployed agents.
• In a controlled red-team test, an autonomous agent gained broad access to an internal enterprise AI platform in under two hours, a stark preview of agent-speed attacks.
• In December 2025, OWASP published its first Top 10 for Agentic Applications (2026), reframing the threat model around identity and tool use rather than the network perimeter; the recurring theme is least privilege.
• Over 75% of enterprises are expected to use AI-amplified cybersecurity products by 2028, up from less than 25% in 2025.

The takeaway for security teams: testing has to move at the same speed as the attacker. According to Omdia's report, 95% of organizations rank pentesting as a top or high priority, yet on average they test only 32% of their attack surface per year, and 64% of security leaders say they prefer agent-led testing with human oversight. That gap between what needs testing and what actually gets tested is exactly where agentic AI pentesting earns its place.

This is the lane ZeroThreat is built for. Agentic AI pentesting uses controlled AI agents to validate real exploit paths, chaining multi-step actions, abusing business logic, and confirming what's actually exploitable rather than flagging theoretical CVEs, so teams get proof, not just a longer alert queue.

AI Phishing Statistics

• Phishing has overtaken stolen credentials as the most common initial breach vector, responsible for 16% of breaches at an average cost of USD 4.8 million.
• 40% of phishing emails targeting businesses are now generated by AI.
• Harvard Business Review suggests that 60% of recipients fall victim to AI-generated phishing emails, a rate comparable to traditional phishing attacks.
• Using large language models (LLMs), spammers can reduce campaign costs by 95% when creating phishing emails.
• Credential phishing attacks jumped 703% in the second half of 2024, while overall phishing email volume rose 202% over the same period.
• Deepfake-enabled phishing surged more than 310% between 2023 and 2025 as voice and video cloning went mainstream.
• As per IBM, the average cost of a phishing-related breach is $4.88 million.

AI Deepfake Statistics

• 61% of organizations reported an increase in deepfake attacks over the past year. (Deep Instinct)
• The volume of video and voice deepfakes shared online rose from roughly 500,000 in 2023 to an estimated 8 million in 2025.
• By 2024, a deepfake attack was occurring somewhere in the world roughly every five minutes, with crypto platforms absorbing a disproportionate share.
• Deepfake vishing (voice-phishing) attacks surged more than 1,600% in Q1 2025 versus Q4 2024 in the U.S., fueled by voice-cloning tools that need only seconds of source audio.
• Deepfakes were used in 35% of all AI-enabled breaches in 2025, second only to phishing.
• 75% of deepfake attacks involve impersonation of a CEO or other C-suite executives. (Deep Instinct)
• Generative AI is projected to increase losses from deepfakes and related attacks by 32%, reaching $40 billion annually by 2027. (Deloitte)
• U.S. fraud losses reached USD 12.5 billion in 2025, with AI-assisted attacks a significant contributor. (FTC)
• The single largest documented incident to date: the engineering firm Arup lost about USD 25 million after a deepfaked video call impersonated its CFO and colleagues.
• Gartner predicts that by 2026, 30% of enterprises will no longer trust standalone identity-verification and authentication tools in isolation.

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AI Ransomware Statistics

• 48% of security professionals believe AI will drive future ransomware attacks. (Netacea)
• Ransomware rose 37% year over year and is now present in 44% of all breaches. (Verizon DBIR 2025)
• Ransomware appears in 88% of breaches at small and medium businesses, which typically lack layered defenses and recovery readiness.
• The tide is turning on payments: 64% of victim organizations refused to pay a ransom, up from 50% two years earlier.
• The average cost of a ransomware attack on companies is $4.45 million. (IBM)
• Ransomware attacks increased by 13 times in the first half of 2023 as a share of total malware detections. (Fortinet)

Cybersecurity Risks

• 60% of IT professionals feel their organizations are unprepared to defend against AI-generated threats. (Darktrace)
• While 79% of IT security executives report taking steps to mitigate AI risks, only 54% of hands-on practitioners share that confidence. (Darktrace)
• Third-party involvement in breaches doubled to 30% (from 15% the year before), and exploitation of vulnerabilities as an initial access vector surged 34%. (Verizon DBIR 2025)
• The human element was involved in 60% of breaches, and stolen credentials remained the top single access vector at 22%.
• The U.S. saw a record-high average breach cost of USD 10.22 million in 2025, even as the global average fell, driven by regulatory fines and detection costs.
• 41% of organizations still rely on endpoint detection and response (EDR) to stop AI-driven attacks. (Deep Instinct)
• Prior research indicates that over 50% of organizations find EDR solutions ineffective against emerging threats.
• Despite these limitations, 31% of organizations plan to increase investment in EDR solutions. (Deep Instinct)

AI-powered Cybersecurity Prevention Tools

A promising trend from the recent 2025-2026 research shows that, despite adoption challenges, an increasing number of organizations believe AI is enhancing their security posture.

Specifically, AI is helping organizations better prioritize threats and vulnerabilities (56%, up from 50%), boost the efficiency of their Security Operations Center (SOC) teams (51%, up from 43%), and accelerate the speed of threat analysis (43%, up from 36%).

• Key barriers limiting the effectiveness of AI-based security technologies include interoperability issues (63%, up from 60%), challenges in applying AI-based controls enterprise-wide (59%, slightly down from 61%), and difficulties in creating a unified view of AI users across the organization (56%, down from 58%).
• A notable trend is the growing reliance on legacy IT environments, which has risen from 36% to 45%. Additionally, 70% of respondents report that integrating AI-based security tools with legacy systems remains a significant challenge.

The average IT security budget for 2025 is $36.8 million, with approximately 21% ($7.9 million) dedicated specifically to AI and machine learning investments.

More organizations are assessing AI’s effectiveness by measuring their SOC teams’ improved ability to detect and respond to threats, rising from 52% to 61% of respondents.

As shown, Looka and ChatGPT are the most frequently used tools, with 36% and 34% of respondents reporting usage, respectively.

To evaluate the effectiveness of AI-powered cybersecurity solutions, organizations track improved response times (45%), reduction in alerts within a given period (37%), and cost reduction (36%).

More organizations are adopting a unified approach to managing both AI and privacy security risks, increasing from 37% to 52% of respondents.

• 70% of cybersecurity professionals say AI is highly effective at detecting threats that would have previously gone unnoticed.
• 73% of cybersecurity teams want to shift their focus toward an AI-powered preventive strategy.
• 53% of security teams report their organization is still in the early stages of adopting AI cybersecurity tools.
• 65% of security teams face challenges integrating AI solutions with legacy systems.
• Only 18% of security teams say their organization has fully adopted and implemented AI cybersecurity tools.
• 63% of cybersecurity professionals primarily use AI to create rules based on known security patterns and indicators.
• 50% of organizations use AI to address cybersecurity skills gaps.
• Only 15% of stakeholders believe that non-AI cybersecurity tools are effective at detecting and stopping AI-generated threats.
• Enterprises with mature AI governance programs report roughly 45% fewer security incidents and resolve breaches materially faster than those without formal oversight, governance is now a performance multiplier, not a checkbox.

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Conclusion

We must accept that the future of consumer cybersecurity lies in adopting AI, especially when addressing the potential threats and cyber-attacks posed by social engineering and IoT malware. With AI at its core, cybersecurity is entering a new era—defined by faster response times, adaptive defenses, and unprecedented threat detection and mitigation levels.

AI-powered prevention tools are enhancing detection, accelerating response times, reducing false positives, and saving millions in operation costs. In 2026 that promise is measurable: for the first time in five years, average breach costs fell, and the organizations seeing the biggest savings are the ones that let AI detect and contain faster. Adoption is rapidly becoming universal across industries, driven by executive backing and recognition of AI’s vital role. Still, challenges remain in fully integrating AI within legacy systems and scaling adoption effectively.

AI in cybersecurity cuts both ways, the same automation that helps defenders also arms attackers, and agentic AI raises the stakes on both sides. With ZeroThreat, you don't have to choose between innovation and security.

As organizations seek to balance the promise and pitfalls of AI and ML in application protection, ZeroThreat helps you navigate this evolving landscape with precision. By combining AI-powered and agentic pentesting, business-logic and authenticated testing, advanced automation, near-zero false positives, and real-time defense, we empower security teams to embrace the future of AI with confidence.