AI Dominates Cybersecurity Predictions for 2026
Artificial intelligence was an inescapable technology in 2025 and will be even more so in 2026, particularly in cybersecurity.
While generative AI has posed significant challenges for infosec pros, the spread of agentic AI in the new year will further burden already-stressed security teams. On the flip side of that coin, though, is the promise of AI-powered applications that can improve cybersecurity for all organizations.
With those developments in mind, here are what some cybersecurity experts see in their tea leaves for 2026.
White Hats will gain advantage over black hats.
While threat actors are quickly accelerating their tactics with AI-enabled scale, defenders are poised to regain the advantage in 2026, predicted Nicole Reineke, a senior product leader for AI at N-able, a global IT management and cybersecurity software company.
“Defenders can see the whole board,” she told TechNewsWorld. “Unlike attackers, who often operate alone, with limited creativity, security vendors can aggregate patterns across thousands of attempted intrusions to better understand popular tactics and strategies.”
“This cross-actor visibility allows defenders to proactively identify emerging techniques long before individual organizations are targeted,” she continued. “In 2026, this network-level intelligence will become one of the most powerful differentiators in cyber resilience, enabling defenders to predict and neutralize attacks before they begin.”
Russ Ernst, CTO of Blancco Technology Group, a global company that specializes in data erasure and mobile device diagnostics, explained that AI’s inherent ability to detect patterns in large datasets improves security threat detection and identifies vulnerabilities in real time. “This helps organizations meet increasingly complex compliance requirements, and will minimize costly breaches, data leaks, and regulatory penalties,” he told TechNewsWorld.
“By embedding AI into IT asset management, enterprises can detect and isolate rogue or untracked devices before they become attack vectors while securing configuration baselines, including security settings, permissions, and configurations for systems and components,” he continued.
“Leveraging AI for better organization-wide security protections will lighten the load on cybersecurity teams already stretched thin, improve data security, and assist with increasingly complex data privacy laws and regulation compliance,” he added.
Agentic AI will revolutionize DevSecOps.
The next wave of AI development will revolve around agentic architectures, AI that can plan, reason, and act across systems, explained Ensar Seker, CISO of SOCRadar, a threat intelligence company in Newark, Del. “In DevSecOps, this means AI that not only flags vulnerabilities, but also files a Jira ticket, forks the repo, fixes the issue, and raises a pull request, without human intervention,” he told TechNewsWorld.
“This isn’t science fiction,” he asserted. “It’s already happening in prototype environments, and by 2026, security teams will increasingly rely on agentic AI to handle low-level security debt while focusing on strategic risks.
Shadow AI will run rampant.
“In 2026, Shadow AI will continue to run rampant in organizations and lead to the loss of more personally identifiable information and intellectual property,” predicted Joshua Skeens, CEO of Logically, a managed security and IT solutions provider headquartered in Dublin, Ohio.
He explained that as the race continues for businesses to find ways to increase efficiency and reduce costs by leveraging AI, many continue to look past the risks that this is creating in their organizations. “Employees are citing growing frustration with generic directives to use AI to do more, but most don’t understand where to begin, what to do, and most importantly, what not to do when leveraging AI,” he told TechNewsWorld.
“Most businesses are unaware of whether their employees are using ChatGPT, Grok, or other similar platforms, let alone if they are entering sensitive information into these platforms,” he continued. “The detection of Shadow AI will be key for businesses in 2026 who want to not only reduce risks but also to better understand what their employees are and are not doing with AI.”
“To be successful and secure with AI, businesses must first establish clear guidelines, educate and train their employees, and then grant them access,” he added. “We don’t give our kids the keys to the car and then come back months later and train them how to drive.”
Shadow AI is more than unauthorized use of popular AI tools, noted Gene Moody, field CTO of Action1, a cybersecurity and IT operations company in Houston.
“As AI adoption surged from 2023 to 2025, teams across the enterprise quietly deployed private or third-party LLMs outside official oversight,” he told TechNewsWorld. “By 2026, these shadow models will represent a significant and largely invisible attack surface, introducing unmonitored data flows, unknown training retention, and inconsistent access controls.”
“Many organizations will discover that sensitive information is already circulating through unapproved AI systems, creating compliance gaps and persistent leakage channels,” he continued. “The proliferation of these unsanctioned models will push enterprises to mandate registration of any AI workflow touching corporate data, impose governance over model endpoints, and offer approved, hardened alternatives to prevent teams from pursuing unsupervised experimentation.”
“Shadow AI will continue to appear when sanctioned tools feel slow or restrictive, and bans alone won’t stop it,” added Chris Faraglia, lead solutions architect at Sembi, a software quality and security management company in Austin, Texas.
“The practical solution is embedding policy within the integrated development environment, testing tools, and chat platforms, while logging usage like any other control to maintain speed safely without creating new insider risk,” he told TechNewsWorld.
Expect bump up in security spending in wake of first major AI-driven attack.
“In 2026, we’ll see the first major AI-driven attack that causes significant financial damage, prompting organizations to dramatically augment their compliance budgets with security spending,” predicted Rick Caccia, CEO of WitnessAI, an AI security and governance company in Mountain View, Calif.
He explained that currently, enterprise AI spending remains largely compliance-focused as companies prepare for regulatory requirements, given the absence of active threats. “This mirrors the cybersecurity landscape before 2009, when organizations spent on SIEM technology primarily for compliance purposes rather than security protection,” he told TechNewsWorld.
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