How is AI shaping the cybersecurity strategies of tomorrow?

AI is not just transforming industries—it’s rewriting the rules of cybersecurity. The rise of generative AI (gen AI) offers unprecedented opportunities for innovation and efficiency, but it also introduces new risks that threaten to outpace traditional security approaches. To put things into perspective, Accenture’s Cyber Intelligence research reported a staggering 223% increase in the trade of deepfake-related tools on dark web forums between Q1 2023 and Q1 2024—a clear signal that the stakes are rising.¹

The challenge? Striking a balance between AI’s enormous potential and the need to safeguard against evolving cyber threats. There’s no magic solution, no "one-click" fix. Instead, achieving AI’s full potential requires an ongoing, adaptive security strategy that can evolve as fast as the technology itself. In this post, we’ll explore how AI is reshaping cybersecurity and outline what businesses need to do to stay ahead of the curve.

Why a comprehensive AI security strategy is now non-negotiable

In just a few years, AI has gone from experimental to essential. Companies are rolling out gen AI solutions at breakneck speed, but this rapid growth adds increased layers of complexity to their tech environments. This underscores the critical need for robust AI asset management, data governance, and strong security frameworks. As companies scale AI, they're also uncovering new vulnerabilities. The message is clear: Prioritize AI security now, or risk being caught off guard by emerging threats.

Forward-thinking leaders who have laid the groundwork with secure AI infrastructures, enabling scalable innovation with trusted and monitored AI capabilities, are in a good position, but they can’t afford to be complacent. According to the Accenture 2024 Pulse of Change Index, 56% of executives say their companies will scale gen AI in the next six months. Yet, only 45% feel confident they can defend against AI-driven cyberattacks in the next year. That’s a significant gap—and one that underscores the urgent need for a more comprehensive AI security strategy.

Compounding this is the evolving regulatory landscape. Regulations like the EU AI Act—the first European Union regulatory framework for AI—as well as a slew of other regional regulations (e.g., Utah, Colorado AI acts, China’s AI Regulation) are coming into force. Businesses must shift from reactive to proactive compliance. A systematic approach to AI governance is essential to navigate these complex regulations and stay ahead.

On top of regulatory pressures, leaders must also navigate the growing proliferation of AI-based security tools. The focus should be on core capabilities that reduce risk and provide scalability through modular, flexible solutions—ensuring investments don’t lead to unnecessary technical debt.

But it’s not just about the right tools. Upskilling security teams to leverage AI effectively in their defense strategies is just as crucial. This ensures organizations remain compliant with evolving regulations and stay competitive in a rapidly changing technological landscape.

Securing AI: Critical strategies for success

Based on our research and experience working with leading organizations, we’ve identified several key strategies for mitigating AI-related risks:

Strengthening core security capabilities

To navigate the complexities of AI securely, it's vital to establish or reinforce your core security capabilities. A unified security foundation, built on a common data model and integrated operations, allows AI to blend seamlessly into enterprise processes. Key areas like Security Operations, Managed Extended Detection and Response (MXDR), and Identity and Access Management (IAM) are essential for mitigating risks and maximizing security benefits.

Laying foundational guardrails & building multi-layered defense

As AI-enabled applications scale across the workforce, the demand for robust, rapidly deployable security solutions grows. One effective starting point is AI firewalls. With AI models proliferating, these firewalls act as a solid first line of defense, securing interactions, preventing data leakage, and blocking malicious or unauthorized uses. They can be customized to fit evolving organizational policies and risk appetites.

However, AI firewalls are only one piece of the puzzle. A holistic, defense-in-depth strategy is essential, integrating secure architecture, data protection, access controls, and continuous monitoring. Relying solely on one solution leaves systems open to a wide range of vulnerabilities that can surface in other areas of AI architecture, such as orchestration layers, RAG databases, or API integrations.

Leveraging enriched risk context

Our understanding of AI-related risks has evolved dramatically over the past year, thanks to emerging regulations and thought leadership across the globe. Risk management leaders now have more tools to craft precise strategies, fine-tuning security controls with greater precision and broader coverage.

Incorporating enriched risk context—such as through red teaming or adversarial testing—enhances security by rigorously testing AI models against real-world attack scenarios, uncovering weaknesses and building more robust defenses. This approach ensures that risk assessments evolve in step with the rapidly changing security landscape.

Preparing for and embracing autonomous agents

As organizations look to unlock value with autonomous agents, security leaders are facing an even more complicated architecture and operating environment. Issues like increased data flows, new user roles and securing integrations must be addressed through context-specific controls. Engaging security teams early in the development process helps embed these controls and test components systematically, reducing unknown risks. A security program with operationalized AI design and testing capabilities is well positioned to address agent-driven risks.

AI agents offer a unique opportunity for security leaders to enhance defenses. When adopting an agent-based security approach, it’s vital to identify use cases that cut across multiple workstreams and align well with this method. Leveraging the full capabilities of your security platform, AI agents can be integrated to strengthen your overall security framework. By deploying AI agents in key areas like threat detection, incident response and compliance monitoring, organizations can create a unified, agile security stance. This approach not only facilitates comprehensive AI-driven workflows but also streamlines processes, making the entire system more efficient. The result is a more resilient and effective security infrastructure that is better equipped to defend against emerging threats.

Enhancing human-AI collaboration

According to Accenture’s research on gen AI’s workforce impact, up to 71% of tasks performed by information security analysts can be automated (28%) or augmented (43%) with AI². However, the shortage of AI-skilled security professionals remains a persistent issue.

To address this, security leaders must adopt a holistic AI talent strategy that not only focuses on targeted training but also empowers teams to fully engage with generative AI technologies in a culture of innovation and experimentation. This can include partnering with educational institutions to create AI-specific training programs, offering certification incentives or developing internal AI training academies. The synergy between human expertise and AI is crucial for driving informed decision-making and optimizing security operations. By integrating generative AI, security professionals can shift their focus to higher-level, strategic initiatives, highlighting the pivotal role of human-AI collaboration in shaping the future of security practices.

In conclusion

AI introduces new vulnerabilities—like data poisoning, model theft and adversarial attacks—that can disrupt operations, erode trust and jeopardize compliance. Integrating AI into cybersecurity strategies is no longer optional; it’s essential to staying ahead in today’s complex digital environment.

By adopting a multi-layered defense strategy, leveraging enriched risk context and fostering collaboration between humans and AI, organizations can create robust security frameworks that not only mitigate risks but also drive innovation. The journey toward secure AI deployment is ongoing, requiring a proactive, adaptive approach to ensure advancements remain safe, sustainable and competitive.

If your organization embraces these strategies, it will be well-prepared to navigate future challenges, safeguarding your digital assets and maintaining their competitive edge in an AI-driven world. Now is the time to act.

We would like to thank Periklis Papadopoulos for his significant contributions to this blog post.

For more insights you can explore our recent article, “Managing Cybersecurity in the Age of Artificial Intelligence” in Ivey Business Journal

Sources

¹ Accenture Cyber Threat Intelligence Research

² Accenture Research Modelling and Analysis