{"id":197894,"date":"2026-03-19T17:01:00","date_gmt":"2026-03-19T21:01:00","guid":{"rendered":"https:\/\/testing.news-you-need.com\/index.php\/2026\/03\/19\/security-challenges-rise-as-ai-adoption-outpaces-defenses\/"},"modified":"2026-03-21T04:25:38","modified_gmt":"2026-03-21T08:25:38","slug":"security-challenges-rise-as-ai-adoption-outpaces-defenses","status":"publish","type":"post","link":"https:\/\/testing.news-you-need.com\/index.php\/2026\/03\/19\/security-challenges-rise-as-ai-adoption-outpaces-defenses\/","title":{"rendered":"Security challenges rise as AI adoption outpaces defenses"},"content":{"rendered":"

Security challenges rise as AI adoption outpaces defenses<\/a><\/p>\n

https:\/\/siliconangle.com\/2026\/03\/19\/agents-quantum-cybersecurity-ai-security-challenges-rsac26\/<\/a><\/p>\n

Publish Date: 2026-03-19 17:01:00<\/a><\/p>\n

Source Domain: siliconangle.com<\/a><\/p>\n

Author: <\/a><\/p>\n

Using an unordered list, summarize the following article with between 4 and 8 key points.
\n\t\t\t\t\t\tSince OpenAI\u2019s ChatGPT burst onto the scene near the end of 2022, the past three years have been a time of all gas and no brakes. As the enterprise world begins to deal with the security challenges of unchecked AI adoption, it may finally be time to slow down the speeding car.
\nSigns of trouble on the road ahead are beginning to appear. Tests conducted by an AI security lab in cooperation with OpenAI and Anthropic found that AI agents tasked with creating simple LinkedIn posts from a company\u2019s database dodged guardrails to post sensitive information in public.
\nThe viral popularity of open-source AI agents such as OpenClaw, which drew 2 million users in a single week, has prompted security warnings, including one from China\u2019s cybersecurity agency, about the tool\u2019s inherent flaws. A report from IBM Corp. found that 60% of AI security-related incidents led to compromised data, 31% led to operational disruption, and 97% of compromised organizations had zero AI access controls in place.
\n\u201cThe challenges around data governance and compliance remain significant,\u201d said Christophe Bertrand, principal analyst for cyber resiliency, data protection and data management at theCUBE Research. \u201cScaling AI requires trust, and trust starts with trusted infrastructure, trusted and protected data, cyber resilient data that can be recovered, and compliant and governed data so organizations don\u2019t use data that creates business risk.\u201d
\nThis feature is part of SiliconANGLE Media\u2019s ongoing exploration of the latest trends in cybersecurity. Be sure to check out SiliconANGLE\u2019s extensive coverage of RSAC 2026, including interviews with RSAC, EY, StackHawk, NetApp, Dell, Capital One, Ping Identity, Cato Networks, XBOW and Elastic. (* Disclosure below.)
\nAgentic security challenges
\nThe rise of AI agents within the enterprise has captured the attention of many in the cybersecurity community. The primary concern is that traditional firewalls were created for human-to-app communication, yet the rapid adoption of solutions such as Model Context Protocol, or MCP, for agent-to-agent interaction has left security organizations unable to see or monitor data traffic.
\nApplication delivery provider F5 Inc. took steps earlier this month to address this growing security gap by introducing NGINX Agentic Observability. This solution can inspect MCP data directly in the traffic path, offering new visibility into which AI agents are interacting with which services in an effort to eliminate a blind spot for IT oversight.
\n\u201cAgentic is the single biggest issue right now,\u201d said Jimmy White, vice president of AI for F5, during an exclusive interview with SiliconANGLE. \u201cAgents can be many things to different people.\u201d
\nIndeed, the explosion of agents and their many different personas has led some cybersecurity firms to lean on identity as an enterprise solution. Ping Identity Inc. released Identity for AI in November, an approach designed to provide users with a single control plane that can manage the entire agent lifecycle. The solution introduces a security layer that can monitor agent activity while enforcing policy-based guardrails and least-privilege access.
\n\u201cThis is a pivotal moment supporting our mission to place identity at the heart of security \u2013 not just to drive more secure innovation, but to help organizations build for long-term trust,\u201d said Andre Durand, Ping Identity founder and chief executive. \u201cWe\u2019re at a critical inflection point, where AI is reshaping the landscape and eroding trust.\u201d
\nPreparing for the quantum era
\nWhile AI has been a central focus for the cybersecurity world, a technology that may still be years away from implementation is also receiving significant attention. It is quantum computing and the need for post-quantum cryptography, or PQC, that has emerged this year as a key area of focus.
\nThe reason for security\u2019s current interest is that RSA encryption, a public key cryptosystem that has been in use since the 1970s for secure data transmission, could become vulnerable to rapid decryption through the use of more advanced quantum computers. The security of everything from bank transactions to a company\u2019s stored proprietary data will be at risk.
\nThe pace of activity in quantum readiness within the cybersecurity industry picked up noticeably over the past year. One example can be seen in the collaboration announced in December between NetApp Inc. and F5 on high-performance data delivery solutions that leverage PQC. F5\u2019s BIG-IP has been designed to support hybrid key agreement and NIST-sanctioned algorithms for quantum-resistant secured communications, with additional support for PQC for NetApp StorageGRID clusters.
\nThe key step is to prepare the hardware now and identify where the most critical data resides, according to F5\u2019s White. \u201cWe\u2019re building our solutions into our hardware,\u201d White explained. \u201cPQC is more about protection; it\u2019s about protecting what we already have. A lot of companies don\u2019t understand what data they have at rest.\u201d
\nEmbracing auto-adaptive solutions
\nThis lack of understanding has been further compounded by uncertainty over how to respond when data, wherever it may be stored, is suddenly at risk. \u201cAlert fatigue\u201d and \u201ctool sprawl\u201d have emerged as two of the largest pain points for cybersecurity practitioners. Too many tools generating endless alerts have left security organizations wondering what\u2019s important and what\u2019s not.
\nThis is a serious problem for another reason: Malicious actors have changed their patterns to evade immediate detection. Security researchers have noticed that attackers increasingly are blending into normal enterprise activity by breaching legitimate tools and targets. Rather than taking action that could trigger a single alert, malicious actors execute a number of low-profile moves that can remain undetected for a significant period of time.
\nBecause many existing point solutions often fail to identify this behavior, security companies are turning to auto-adaptive threat prevention tools. Earlier this month, Cato Networks Ltd. unveiled Cato Dynamic Prevention, an engine designed to stop threats by correlating signals from months of activity.
\nAI itself holds promise in being able to help signal-weary security organizations spot trouble early. As SiliconANGLE has documented in its research, security is no longer a bolt-on function. Security teams are increasingly influencing infrastructure and application decisions across the enterprise, and they are using AI in the process.
\n\u201cAI can watch your behavior and say, \u2018You know, here\u2019s a feature that you need,\u2019 or \u2018I\u2019m going to self-tune a firewall, for example, based on your traffic,\u2019\u201d according to Jon Oltsik, principal analyst, cybersecurity, at theCUBE Research. \u201cThat\u2019s a real-time AI advantage that we\u2019ll get. It\u2019s not pie in the sky. This is happening now.\u201d
\nSecuring the intelligent edge
\nAs AI applications continue to expand, they are becoming more prevalent in a wide range of use cases, especially at the edge. This has opened a new area of concern for cybersecurity practitioners who must now secure the data flowing through AI pipelines in remote locations.
\nEnterprise vendors have responded to this concern by offering solutions that can mitigate the risks of edge deployments. An example of this can be seen in the rollout last year of Dell Technologies Inc.\u2019s NativeEdge, a software platform for the central management of edge operations. Dell\u2019s offering includes centralized control and zero-trust security in the automation of edge infrastructure deployments.
\nSecurity at the edge highlights an additional trend generated by enterprise implementation of AI. The AI factory \u2014 specialized infrastructure that combines high-performance GPUs, software and data pipelines \u2014 is now expanding to the edge as enterprises need real-time decision-making in places such as manufacturing facilities and retail stores.
\nAs noted by SiliconANGLE\u2019s research analysts, this represents the dawn of the hyperconverged edge where compute, storage, security and AI inference come together in one unified infrastructure. This is still a work in progress and reliably securing these environments will not be an easy task.
\n\u201cEnterprises are currently fighting a two-front war,\u201d said Zeus Kerravala, principal analyst at ZK Research, a division of Kerravala Consulting. \u201cOn one side, there is an aggressive push toward AI adoption; on the other, an infrastructure landscape so fractured across edge, cloud and on-premises sites that scaling becomes nearly impossible. The \u2018Age of AI\u2019 is quickly becoming the \u2018Age of Complexity.\u2019 The winners won\u2019t just be the companies with the best models, but those with the most resilient, observable and converged delivery platforms.\u201d
\n(* Disclosure: TheCUBE is a paid media partner for the RSAC 2026 Conference. Sponsors of theCUBE\u2019s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)
\nImage: SiliconANGLE\/ChatGPT<\/p>\n

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