AI-powered browsers are quickly becoming co-pilots that can read, reason and sometimes even act on a user’s behalf. Professionals may be especially tempted to turn to AI browsers because they make work feel faster and smoother, especially when someone is juggling research, analysis or repetitive tasks. The promise of instant summaries, automated workflows and fewer clicks can be hard to resist.
However, cybersecurity experts are increasingly raising red flags concerning AI browsers’ security weaknesses. While their capabilities are impressive, these systems open up a fresh class of risks that traditional safeguards weren’t built to handle. Indeed, a recent Gartner report recommends businesses block AI browsers for the foreseeable future.
The members of the Senior Executive Cybersecurity Think Tank bring years of experience to this timely topic. With expertise in enterprise security, regulatory compliance and threat detection, they’re watching the evolution of AI browsers with a blend of anticipation and concern. Below, two of them explain the unique risks these systems introduce and the essential precautions all stakeholders—developers, regulators and end users—must take as AI-powered browsers gain traction in both enterprise and personal settings.
“Since AI browsers can act autonomously, they act as malicious malware if attacked successfully. It’s like built-in malware with no download required.”
Prompt Injection Can Turn an AI Browser Into a New Attack Vector
Eoin Keary, CEO of Edgescan Inc., has spent more than 20 years studying how hackers adapt to every new generation of technology. When he looks at AI-powered browsers, he sees a familiar problem taking on an unfamiliar shape.
“Injection attacks are not new; they’ve been around since ‘cybersecurity’ was coined as a phrase,” Keary says. “But AI browsers process natural language, so a new type of injection vector has evolved: prompt injection.”
When AI browsers interpret language and execute tasks autonomously, the door opens to subtle manipulations that legacy security tools aren’t designed to catch. Keary notes that security researchers view prompt injection as an unsolved problem.
“Attackers can hide malicious instructions in web pages, documents or other web elements,” he explains. “This could trick the AI system into executing harmful actions or unwanted functions.”
Keary warns that AI browsers expand the cybersecurity attack surface for both individuals and organizations. In fact, once compromised, an AI-powered browser becomes more than just a weak point in the system—it becomes a participant in the attack. Preventing exploitation may require rethinking how AI browsers operate at a foundational level, not just layering on more controls.
“Since AI browsers can act autonomously, they act as malicious malware if attacked successfully,” Keary says. “It’s like built-in malware with no download required.”
“When the browser starts making choices, security must shift from perimeter defense to decision integrity.”
Transparency Must Become a Design Imperative
Maman Ibrahim, Founder of Ginkgo Resilience LTD, has more than 20 years of global experience in cyber and digital risk and assurance in highly regulated industries. He focuses on a different but equally troubling dimension of AI browser risk: loss of visibility and control.
“When AI-powered browsers begin interpreting and acting without user prompts, boundaries between user intent, application logic and data flow start to blur,” he says.
Ibrahim explains that this opens the door to invisible prompt injections, data exfiltration through misunderstood permissions, and manipulation via personalized content pipelines. To counter those risks, Ibrahim argues that transparency must become a design imperative rather than a feature request. Humans need to understand why the browser did what it did and whether it acted within authorized boundaries.
“Developers need to embed provenance and explainability into every AI decision path,” he says. “Policymakers should treat agentic browsers like semi-autonomous systems, requiring new accountability models.”
At the same time, Ibrahim notes, users themselves can’t make any assumptions.
“End users must actively manage trust layers, knowing not just what they’re browsing, but also who’s doing the browsing,” he says.
As AI browsers increasingly make decisions, the loss of visibility starts to create real openings for mistakes or misuse. If no one can tell why a browser took a certain action, it’s harder to know whether that action was trustworthy in the first place. Ibrahim says this requires a significant security paradigm shift.
“When the browser starts making choices, security must shift from perimeter defense to decision integrity.”
Strengthening Security in the AI Browser Era
- Treat prompt injection as a critical risk. Attackers can embed malicious instructions in common web elements, so systems must be built and monitored with this evolving vector in mind.
- Assume AI-driven autonomy expands the attack surface. When a browser can act on its own, a single compromise can turn it into an active participant in an attack.
- Prioritize visibility and control in every workflow. When intent and data flow become blurred, organizations must strengthen oversight to avoid invisible manipulations or misuse.
- Embed provenance and explainability into AI decision paths. Clear reasoning trails help developers and users understand whether an AI-driven action was legitimate.
- Adopt accountability models suited to semi-autonomous systems. Policies should reflect that the browser is no longer a passive tool and may require new forms of governance.
- Encourage users to actively manage trust layers. People should understand not only what they are accessing online, but also which entity—them or the browser—is making decisions.
Charting a Safer Path for Autonomous Browsing
The rise of AI-powered browsers signals a major turning point in how people interact with the web. These tools promise efficiency and convenience, yet they also introduce risks traditional security frameworks aren’t equipped to handle. Prompt injection, loss of visibility and browsers that can act as semi-autonomous agents all challenge long-standing assumptions about what a browser is and how it should behave.
Looking ahead, the shift to decision-making browsers will require developers, policymakers and users to rethink trust at every layer. The next phase of security must focus not only on keeping threats out, but also on ensuring the integrity of whatever actions an AI system takes on a user’s behalf. As these tools continue to gain traction, building transparency, accountability and resilience into their design will determine whether AI-powered browsing becomes an asset or an uncontrolled liability.
