Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI is moving from experimentation to execution. What started as copilots is quickly evolving into autonomous AI agents that can make decisions, execute tasks, and operate across enterprise environments. As organizations accelerate adoption of agentic AI, they’re expanding their attack surface in ways traditional security models weren’t built to handle.

Organizations are not choosing between AI adoption and data security. Rather, they are discovering, often after the fact, that these two priorities are pulling in opposite directions. The engineering team has been using GitHub Copilot for six months. Finance is running variance analysis through ChatGPT. Legal is pasting contract language into Gemini for redlining. According to Cyberhaven Labs research, 39.7% of the data employees share with AI tools is sensitive.

Speakers made it clear that agentic AI is already operating across enterprise workflows. Learn why identity must govern ownership, permissions, actions, and accountability.

Adversaries are using AI to launch cyber attacks in record time, forcing security teams to measure responses in seconds instead of hours or days. Detecting these attacks is increasingly difficult. Phishing campaigns built by large language models (LLMs) achieve click-through rates 4.5x higher than traditional methods.1 Public sector organizations are at an inflection point with cybersecurity. Most security stacks in place today weren’t built for this level of speed.

There isn't a CIO on the planet not worried about AI spend right now. CFOs are increasingly nervous, too. For fear of falling behind, many companies have pushed their employees to use AI as aggressively as possible. The edict was clear: "Move fast, we'll figure out the bill later." And for the most part, it worked: AI has been genuinely transformational for the teams that leaned in. But the costs are real: we’ve heard countless horror stories of huge bills and painful overages on token spend.

The era of "typing into a box" is over. For years, we viewed artificial intelligence as a digital assistant—a sophisticated autocomplete tool that waited for human input. But according to Martin Kraemer, KnowBe4’s CISO Advisor for Europe and the Middle East, that dynamic has shifted. We have moved from asking AI questions to giving AI jobs. In a recent webinar, Martin explores the transition from AI tools to AI agents.

An account-takeover campaign against Instagram shows why agentic AI inherits every business logic blind spot we already had and then hands it a megaphone. Over the past weekend, a number of Instagram users, including the long-dormant Obama-era White House handle and a U.S. Space Force senior enlisted leader found their accounts hijacked. As reported by TechCrunch, the entry point wasn’t a stolen password, a phishing kit, or a zero-day in Instagram’s code.

In our view, The Gartner Hype Cycle for Agentic AI, published in April 2026, contains a passage that we at 1Password feel should be a wakeup call for any organization building an agent program.