AI Security in 2026: What Business Leaders Need to Pay Attention To

Image source: Midjourney

At HiveStir, we spend a lot of time thinking about how teams move faster with AI without breaking things they cannot easily fix later. Trust. Security. Long-term viability.

That focus is what led me to a recent webinar, “AI Security in 2025: What We Learned and What’s Coming in 2026,” hosted by Prescient Security Co-Founder Sammy Chowdhury and featuring Kevin McDonald, COO and CISO at Alvaka.

The conversation quickly moved beyond technical controls. It centered on how AI is reshaping organizational risk, where leadership teams are underestimating exposure, and why familiar approaches to security, governance, and compliance are starting to fall apart as AI becomes more autonomous.

What follows are the takeaways that stuck with me most, especially from the perspective of someone actively building with AI and thinking about what happens when it scales.

AI Security in 2026 Is Already Embedded in the Business

AI has crossed a quiet but important line.

It is no longer limited to research teams or experimental pilots. It is embedded in everyday work, shaping decisions, writing code, supporting customers, and influencing outcomes across departments.

Kevin McDonald emphasized that leadership teams increasingly see AI as essential for efficiency and competitiveness. That pressure is pushing adoption forward faster than governance models, security architecture, and operating assumptions can keep up.

The pattern is familiar. The difference is speed. Control is lagging behind.

This Is No Longer “Just a Tool”

One of the most interesting moments in the webinar came when Kevin reflected on how quickly the industry narrative has shifted.

Not long ago, the conversation focused on minimizing AI, reframing it as “just large language models.” That framing is fading. What matters now is behavior.

Agentic AI systems operate autonomously. They move at machine speed, share data across systems, and take action with minimal human involvement. That shift, from AI as a tool to AI as an actor, fundamentally changes the risk profile.

Shadow AI is becoming common. Employees introduce tools or agents without formal review, usually with good intentions. But security teams can no longer rely on being “the department of ‘no.’” AI will be used whether controls are ready or not.

That reality forces a mindset shift. Security teams increasingly have to enable the business while still maintaining visibility and accountability.

Insurers are seeing the same thing. In PwC’s Banana Skins research, AI went from not appearing as a top risk in 2023 to ranking just behind cybercrime by 2025. In many cases, AI is making cybercrime easier to execute.

Whether leadership planned for it or not, AI is already reshaping organizational risk.

The Expertise Gap Is Getting Wider

Another theme that kept resurfacing was how quickly the knowledge gap is growing.

AI capabilities are advancing faster than most organizations can build expertise. This is not limited to security teams. Leadership, legal, and compliance functions are struggling as well, especially when it comes to agentic systems that challenge long-held assumptions about control and oversight.

Even well-resourced enterprises are falling behind. Estimates shared during the session suggested that fewer than 10 percent of organizations are truly prepared to manage the security implications of advanced AI.

At the same time, many companies are still addressing basic cyber hygiene. They are being asked to secure autonomous agents, evaluate AI-generated code, and defend entirely new attack surfaces all at once.

Research discussed during the webinar indicated that AI-generated code may be significantly less secure than code written by humans. Falling behind is becoming more expensive by the month.

Security Models Built for Humans Are Straining

Zero Trust remains foundational, but it was designed for people and their devices.

AI agents do not behave like human users. They operate continuously, move across systems in unexpected ways, and are often granted implicit trust so they can execute tasks independently.

That trust creates exposure.

Kevin summarized it clearly during the session. Zero Trust was built for humans and their devices. Agentic AI operates outside those assumptions. When agents are given implicit trust, Zero Trust no longer holds.

Organizations are already seeing examples where agents misunderstand permissions or access data through unintended paths. Combined with weaknesses in AI-generated code, this creates growing architectural debt.

Security models designed for human behavior cannot simply be extended to autonomous systems. Securing AI requires rethinking identity, access, permissions, and oversight from the ground up.

Governance Has Moved to the Center

One of the clearest messages from the webinar was that strong AI security depends on governance, not just technical controls.

Policies alone are no longer enough. As AI systems become more autonomous and interconnected, governance has to show up in daily operations, not just in documentation prepared for audits.

There are governance frameworks organizations can adopt, including ISO 42001, the EU AI Act, CIS Security Controls, and mappings to existing standards like SOC 2. But for many companies, the real challenge is not adopting frameworks. It is making sure those frameworks connect to day-to-day operations, where policy, governance, and enforcement are not theoretical, but actively have a seat at the table.

This idea closely aligns with recent thought leadership from Brenda Bernal, CEO of Compliagence. In her piece, From Audit Ready to Always Ready: Why AI Companies Need Continuous Compliance to Scale, she explains why traditional compliance models fall short in AI-driven environments:

“Audit-ready compliance worked when systems were stable. AI is not. Growing AI companies are shifting to an always-ready model, where governance is continuous, embedded, and designed to move at the same speed as innovation.”

The full article can be found here: https://compliagence.ai/insights/from-audit-ready-to-always-ready-why-ai-companies-need-continuous-compliance-to-scale.

In fast-moving AI environments, governance cannot be a point-in-time exercise. It has to be built into how systems are designed, deployed, and monitored.

What Leaders Should Expect in 2026

Looking ahead, several trends feel unavoidable.

Executive accountability will increase as regulators focus more on leadership decisions. Ethics and bias risks will grow as AI influences more outcomes. Agentic AI capabilities will advance faster than most organizations expect. AI-enabled identity deception and deepfake attacks will increase. Pressure to move quickly will lead to shortcuts that undermine data trust. Many early-career roles will be automated, creating long-term knowledge gaps.

Organizations that succeed will not simply be the fastest adopters. They will be the most intentional.

The Human Advantage Still Matters

Despite AI’s growing capabilities, several human skills remain essential.

Judgment. Creativity. Context. The ability to synthesize information and guide outcomes when AI produces options.

Kevin emphasized that humans are not being removed from the loop. Their role is becoming more important as they are part of the AI loop. Leaders who invest in these skills will make better decisions in environments where AI proposes and humans choose.

Closing Thoughts

AI is not slowing down, and the pressure to move quickly is not going away.

What this conversation reinforced for me is that the real differentiator is not whether organizations adopt AI, but how they do it. Teams that pair speed with intention, supported by governance, adaptable security models, and human judgment, are the ones that will scale successfully.

At HiveStir, we are building with that awareness in mind. AI can be a powerful accelerator, but only when the systems around it are built to evolve just as quickly.

The leaders who get this right in 2026 will not be the loudest or the fastest. They will be the ones who built foundations strong enough to support everything AI makes possible.

Need support turning AI ambition into something that actually scales?

If your focus is AI governance, compliance, or continuous readiness, the team at Compliagence helps AI-driven companies move from audit-ready to always-ready.

If you are looking to apply AI to marketing, growth, or strategy in a responsible way,

HiveStir helps teams put AI-powered products and programs in place that support long-term outcomes.