How Security Leaders Mitigate Generative AI Risks While Encouraging Innovation

Imagine a tool that can predict cyberattacks before they happen, draft incident reports in seconds, or unmask hidden vulnerabilities in a sea of data. This isn’t science fiction—it’s the reality of generative AI (GenAI). But with great power comes great risk.

As organizations rush to harness GenAI’s potential, Security and Risk Management (SRM) leaders are walking a tightrope: enabling innovation while safeguarding against threats such as data leaks, biased outputs, and AI-driven cybercrime. How are they pulling this off?

Let’s dive into the strategies reshaping cybersecurity in the age of AI.

How SRM Leaders Reduce Generative AI Risks And Foster Innovation

Senior risk management leaders play an important role in navigating these complexities by implementing strategies that mitigate risks while fostering a culture of innovation.

Below are key approaches SRM leaders can adopt to effectively balance these dual objectives:

1. The GenAI Gold Rush: Adoption Is Here (But Security Is Playing Catch-Up)

By 2024, 90% of organizations had already boarded the GenAI train, with over half moving past experimentation into pilots or full-scale deployments, according to Gartner (2024).

Top use cases—data analysis (52%), personalized chatbots (49%), and research (48%)—show GenAI isn’t just a shiny toy; it’s a productivity powerhouse.

Yet here’s the catch: only 36% of SRM leaders feel confident in their cybersecurity team’s ability to secure these tools. Picture this: companies are building AI-driven fortresses with doors made of cardboard. Legacy security frameworks aren’t enough. GenAI’s quirks—like its knack for hallucinating false data or regurgitating sensitive information—demand tailored defenses.

2. Learning by Doing: Why Security Teams Are Their Own Guinea Pigs

How do you secure a technology you’ve never used? You experiment on yourself. Over 40% of cybersecurity teams are now actively using GenAI for threat detection, incident response, and policy audits. Teams that pilot GenAI internally boost their ability to secure enterprise-wide deployments by 28%.

Pro tip: Start small. Use GenAI to analyze phishing attempts or automate routine tasks. It’s like training for a marathon by sprinting first—build muscle where it matters.

3. The Influence Dilemma: Security Leaders Want a Seat at the Table

Here’s a paradox: 70% of SRM leaders say they influence GenAI decisions, but only 24% have final say on what’s allowed.

Without early involvement, security teams risk becoming the “Department of No”—shut out of critical conversations until problems arise.

The fix? Speak the language of business. Frame security as an innovation accelerator. For example, robust data governance isn’t a roadblock; it’s what lets marketers safely personalize customer interactions at scale.

4. Breaking Silos: The Dream Team for Secure AI

GenAI doesn’t respect departmental boundaries—and neither should security. Leading organizations are forming cross-functional “AI task forces” with IT, legal, compliance, and even frontline employees.

Collaboration isn’t just nice-to-have; co-creating policies with end users increases secure adoption odds by 23%.

Try this: Host a “GenAI Hackathon” where security and engineering teams jointly stress-test tools. It’s like a digital escape room—but with fewer zombies and more firewalls.

5. Talent Wars: Why Your Next Hire Might Be a Philosopher

Over 40% of SRM leaders admit their teams lack GenAI skills. But here’s the twist: technical wizardry matters less than critical thinking. Can your team spot flawed logic in an AI’s output? Detect subtle biases in training data?

Solutions:

• Recruit from unexpected fields (data scientists, ethicists).
• Partner with coding bootcamps to shape GenAI curricula.
• Prioritize adaptability over certifications—AI evolves faster than any degree program.

6. Winning Over the C-Suite: Speak Their Language

Boards lose sleep over AI misinformation (41%) and privacy risks (37%). CIOs fear “hallucinations” (56%) and sketchy data practices. To secure buy-in, translate security jargon into their priorities:

• “Our watermarking strategy reduces misinformation risks by 60%.”
• “Bias audits align with DEI goals—and prevent PR disasters.”

7. The Roadmap: Turning Risks into Rewards

To thrive in the GenAI era, SRM leaders must:

• Experiment fearlessly (but sandbox those experiments).
• Bake security into AI projects from Day 1—no more bolt-ons.
• Treat every employee as a security ally, not a liability.

Turning AI Risks into Measurable Human Resilience with Keepnet Human Risk Management

As GenAI accelerates the sophistication of phishing and social engineering attacks, Security and Risk Managers need more than policies—they need measurable, real-time visibility into human vulnerabilities.

Keepnet’s Extended Human Risk Management Platform delivers exactly that. With a dynamic Human Risk Score, organizations can monitor risk across every vector—email, SMS, voice, QR, and MFA phishing—and drill down into root causes by department, role, and behavior. This enables security leaders to proactively harden the most vulnerable entry points and present progress in board-friendly formats, such as trend graphs and industry benchmarks.

Keepnet also turns AI from a threat into a training advantage. Keepnet’s AI-powered phishing simulations mirror real-world attacks, utilizing voice cloning, deepfake scenarios, and natural language generation. Meanwhile, the Adaptive Security Awareness Training Software tailors micro-courses to each employee’s role and risk profile. The result? Teams that not only recognize advanced threats but also act on them, driving up report-to-click ratios and cutting repeat mistakes. Combined with automated re-simulation and instant in-the-moment education, Keepnet enables SRMs to transition from passive defense to continuous resilience.