Tech Explained: AI Dominates 2026 Cybersecurity Predictions in Simple Terms

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.

Caccia anticipates three changes after the first high-profile AI attack makes headlines: security budgets will free up considerably as executives recognize the urgent threat; the number of enterprise buyers will surge as competitors rush to protect themselves from similar attacks; and deal cycles will move three times faster than current cycles.

“The need for additional security investment will unlock budgets that theoretical risk assessments have constrained,” he said. “This will create a new market dynamic where AI security moves from ‘nice to have’ to ‘business critical’ overnight.”

Poor decisions by AI agents will lead to spate of operational disasters.

WitnessAI’s Chief Product Officer, Dan Graves, predicted that throughout 2026, enterprises will experience significant operational incidents caused by well-intentioned agents making poor decisions with serious unintended consequences. “These agents won’t ‘go rogue’ in a malicious sense,” he told TechNewsWorld. “They’ll simply lack the judgment and foresight to understand the full impact of their actions. This will lead to deleted code bases, downed systems, and other ‘helpful’ disasters.”

Graves explained that the problem stems from agents operating like children, smart at specific tasks but lacking emotional intelligence and long-term thinking. “When tasked with improving code, an agent might decide the most efficient approach is to delete the entire existing project and start from scratch, which might be logical from a narrow perspective, but catastrophic in practice,” he said.

“Companies will discover that preventing malicious attacks is only half the battle when their own helpful agents can cause equivalent damage simply by trying to do their jobs,” he noted. “The agents will have been following their instructions perfectly. They just interpreted ‘make this better’ or ‘optimize this process’ in ways that no human would have chosen. This will reveal the gap between computational logic and human judgment that no amount of training data can currently bridge.”

Agentic AI will shift the threat landscape and evolve tactics, techniques, and procedures.

Already a key component of many threat campaigns in 2025, agentic AI will further reshape the threat landscape in 2026 as threat actors continue to integrate AI tools into their attack methodology, predicted Alex Cox, TIME director and artificial intelligence working group lead at LastPass, a password manager and identity security company in Boston.

“Defenders will likely see threat actors use agentic AI in an automated fashion as part of intrusion activities, continue AI-driven phishing campaigns, and continued development of advanced AI-enabled malware,” he told TechNewsWorld. “They’ll use agentic AI to implement hacking agents that support their campaigns through autonomous work.”

In 2026, attackers will shift from passive use of AI in preparation activities to automation of campaigns and the evolution of tactics, techniques, and procedures using AI,” he added.

Zero-day exploits will become dramatically more common.

As AI accelerates aspects of vulnerability research, exploit development, and testing, zero-day exploits will become dramatically more common in 2026, predicted Brennan Lodge, fractional CISO at DeepTempo, a behavioral threat detection company in San Francisco.

“Offensive teams, particularly state-backed groups, will combine automated reasoning with large-scale code generation to chain subtle weaknesses into reliable, high-impact attacks,” he told TechNewsWorld. “As this capability matures throughout 2026, zero-days will shift from rare, high-effort tools to scalable offensive assets that can be deployed across research environments, supply chains, and cloud infrastructure.”

“For defenders, this means you cannot wait for a CVE to show up before you look for suspicious behavior,” he warned. “You will need models that can spot early signs of setup activity. By the time a zero-day is visible, the attacker is already where they wanted to be.”

“The result will be a growing emphasis on deep learning systems that evaluate how activity unfolds over time, allowing defenders to identify attacker intent during initial setup and access phases before any exploit becomes observable further down the attack chain,” he said.

The AI and cybersecurity domains will converge.

“The most meaningful shift of 2026 will be cultural,” contended Anurag Gurtu, CEO of Airrived, a developer of an enterprise agentic AI platform for cybersecurity in Dublin, Calif. “Cybersecurity and AI will cease to be separate domains.”

“Security operation Centers won’t just use AI,” he told TechNewsWorld. “They will operate with AI.”

He explained that agentic systems will automatically suppress alerts; run investigations in seconds; correlate exposures across the cloud, identity endpoints, and the network; generate remediations; validate changes; and maintain continuous controls.

By the end of 2026, he predicted that large enterprises will see 30% or more of SOC workflows executed by agents, not humans.

“This is the year AI transitions from a co-pilot to a co-worker,” he said.