In today’s Tech Pulse, gain insight into how:

• Automation isn’t autonomy and why eliminating manual handoffs and approval bottlenecks is the real path to faster, safer vulnerability remediation.

• The biggest AI-driven cyber threat is still human nature, as attackers use AI to scale phishing, impersonation, and anxiety-fueled social engineering.

• Cybersecurity leaders need AI strategy, not just AI speed, using AI to prioritize business-critical risks, strengthen threat modeling, and build a faster learning loop.

Each of these articles is penned by members of Forbes Technology Council, key luminaries shaping the future of technology leadership.

Grab your coffee, and let's dive in!

Automation Isn’t Autonomy: Why Fast Patching Still Leaves Teams Exposed

Automation can speed up security tasks, but it doesn’t eliminate the human coordination that often slows remediation. True cybersecurity maturity comes from operational autonomy, where workflows move from detection to decision to action with minimal friction (and clear guardrails).

Here are the key takeaways to know:

🧭 Know the Difference: Automation accelerates execution; autonomy reduces manual coordination and handoffs across teams.

📈 Progress, But Not Peace of Mind: A survey of 209 IT/security pros found patching within six days rose from 15% (2023) to 59% (2026)—yet 56% still feel exposed to known vulnerabilities.

🧩 The Real Bottleneck is Between Tools: Even with automated scanning and patch deployment, prioritization, testing, approvals, and maintenance windows can stall remediation.

🚧 Autonomy Needs Guardrails: Examples include severity-based prioritization, phased rollouts to noncritical devices, and requiring admin approval only for high-risk changes.

🔍 Measure Maturity by Friction, Not Tools: Count manual handoffs, approval delays, and outdated governance, not just how many workflows are “automated.”

Read The Full Article >

The Biggest AI Cyber Risk Isn’t the Model—It’s the Person

Agentic AI like Anthropic’s Claude Mythos is raising alarms for its ability to discover (and even build) exploits at speed. The more enduring—and scalable—threat remains unchanged: humans are still the cheapest point of failure.

Here’s what to focus on:

🧠 Cybercrime Economics Favor Deception: It’s far cheaper to trick one person than to break a hardened system…AI just makes the lures faster, more localized, and more convincing.

🕳️ Finding a Flaw ≠ Landing a Breach: Even if AI can identify vulnerabilities, attackers still need access, privileges, delivery paths, and the right environment to weaponize them.

🛡️ Defenders Are Using AI Too: Security teams are leveraging agentic workflows and automated testing to close technical gaps faster—raising the cost of technical intrusion.

🎭 Anxiety Becomes an Attack Surface: Fear around new models can fuel phishing, impersonation, and extortion-style scams (e.g., fake zero-day claims, spoofed IT “emergency patch” alerts).

🤖 “Fight AI with AI” Defense: The takeaway: build unified, AI-native defenses that don’t rely on employees as the last line of defense against hyper-realistic deception.

Read The Full Article >

AI Speed Won’t Save You Without a Strategy

AI is accelerating both offense and defense—but leaders should resist “move faster” thinking unless they’re clear on where they’re going. The real advantage is using AI to sharpen judgment, align security to business risk, and build faster learning loops rather than just churn out more alerts.

Here’s what to pull forward:

🧨 AI Is Surfacing Flaws at Scale: Mythos identified 23,000+ potential open-source vulnerabilities, including 1,000+ rated high/critical by external firms.

📌 Attackers’ AI Use Is Familiar: Microsoft Threat Intelligence notes most malicious AI use still centers on generating text/code/media—phishing, translation, malware debugging and scripting.

🗺️ Start With Your Environment, Not Tools: Define assets at risk, likely adversaries, attack paths to disrupt and the metric that proves risk changed.

🧠 Use AI to Expand Judgment: Stress-test plans through “board/auditor/operator” perspectives and expose weak framing before execution.

🧩 Treat Vulnerability Discovery as a Threat-Modeling Signal: Don’t just prioritize tickets, ask what findings reveal about architecture complexity and secure-by-default engineering.

⏱️ Build a Faster Learning Loop: Use AI to shrink the time from new intel to updated controls, risk discussions, and testing priorities.

Read The Full Article >

Wrapping Up

If these articles sparked your interest, we have a network that you will absolutely love: Forbes Technology Council.

This exclusive, vetted community brings together the brightest minds in technology — founders, CEOs, CIOs, CTOs, CISOs, and other leaders of technology-focused teams.

Put yourself at the forefront of innovation with access to publishing opportunities on Forbes.com, a personalized, SEO-friendly Executive Profile, and the chance to network with other respected leaders in the field.

Join Forbes Technology Council today, and become part of a group driving transformation in technology.