The Future of Automation in Cybersecurity
We’re at a major inflection point when it comes to artificial intelligence (AI): It is no longer emerging, but instead part of our present reality. This is true across nearly every industry, but AI is particularly nuanced in cybersecurity.
As cyberthreats grow more sophisticated, security teams face immense pressure to manage an expanding attack surface. In response, the cybersecurity industry is turning to automation and AI to bolster defenses and streamline operations. However, AI is a double-edged sword.
For the cybercriminal, it’s creating a wider threat landscape by limiting the barrier to entry and increasing the speed at which they can launch attacks. It’s also enhancing the sophistication of those threats. While only about 20% of cybercriminals said they found value in leveraging AI for cyberattacks in 2023, that number skyrocketed to over 70% this year.
For the defender, AI is quickly becoming table stakes in the ongoing battle against cybercriminals, especially during a time of increased talent shortages and skills gaps. The challenge is effectively scaling automation for threat detection, rapid response time and accurate resolutions. The integration of these technologies raises complex questions about identity management, human oversight and the future of security practices. Let’s explore.
The Power of Real-Time Data in AI
Automation in cybersecurity is not new, but its role is becoming increasingly vital as businesses scale their digital infrastructure. Security teams are turning to AI and automation to handle repetitive, mundane tasks, detect threats in real-time and remediate issues faster than ever before.
Automation when done at scale is effective because the technology can help continuously monitor the threat landscape. As organizations adopt more devices, software and systems, automation ensures that security policies are enforced consistently across large environments. Add AI to the mix, and you can start to look for novel patterns, which can significantly bolster proactive defense. AI agents can then be deployed to quickly identify novel attack patterns or anomalies in network traffic, reducing the time it takes to respond to incidents.
However, while automation and AI help detect threats and accelerate efficiency, the real advantage comes from pairing AI with real-time data from the operational environment. Being able to find issues after they happen and using that information to ensure they don’t happen again is helpful, but being able to find issues as they happen and remediating those issues in real-time with the context of your actual operating environment as it looks like today is a superpower – and the future of cybersecurity.
Better insight into the operating environment will also help organizations assess the vendors who have access to their company information, opening them up to potential security threats they may not be aware of. These vendors are also making use of automated and AI-powered tools, and may not have the same guardrails or protections against improper use. If AI can’t be left to run wild within an organization, then the same goes for the vendors they invest in and trust with their data.
The Permanent Role of Human Oversight
While AI and automation are powerful tools, they cannot replace human oversight. The future of automation and AI in cybersecurity requires a symbiotic relationship between humans and AI. Despite the impressive capabilities of AI, systems should still be monitored by humans to ensure they are functioning correctly and that the context is accurately understood. If, for example, AI handles a workflow with multiple steps, and one step fails, it can compromise the entire process. This is why human oversight remains critical.
The ultimate goal of automation is not to replace humans; it’s to handle the “base load” of cybersecurity, freeing up experts to focus on more advanced challenges. This is particularly important for governance and ethical considerations.
The growing use of AI brings with it a new set of risks, especially in the realm of machine identity and authentication. It won’t be enough to trust traditional methods of securing systems; businesses must consider how to handle risks associated with the vast increase in automated software, including the potential misuse of AI.
Governance in automated systems is vital to ensure that AI-driven decisions are made transparently and in line with regulatory standards. Integrating human oversight into automation is crucial for creating a “feedback loop” where security teams can monitor AI behavior and adjust policies as needed. Systems must be designed with governance in mind so that security measures that can adapt to new threats are built in rather than tacked on after the fact.
AI’s Essential Role in an Uncertain Future
AI tools are getting more sophisticated, more complex and smarter every day. Conversations we’re having now could look different by the middle of next year, let alone within the next five years or a decade. However, one thing is for certain: The role of automation and AI in cybersecurity will continue to expand and evolve, but it will not be without challenges.
Organizations will continue to explore new ways to apply AI, learning from past implementations and fine-tuning systems. The key to success will be using AI not just as a tool, but as an enabler to increase the efficiency and scale of security efforts. Threats like post-quantum readiness and coding kill switches will introduce entirely new spheres of risk that will interfere with and break existing systems, or systems being currently implemented. These new and advancing threats may not be entirely possible to solve in the present, but future-proofing organizations require making the best of the tools currently available.
By combining the power of automation with the oversight of skilled professionals and real-time data, cybersecurity teams can build more resilient systems to defend against an ever-evolving threat landscape. Implementing the right checks and balances on these tools while having visibility into the data to understand where they’re performing — and where they’re not — will best position organizations to keep themselves secure. The future of cybersecurity is not about choosing between AI and human expertise, but rather how to harness both to create a more secure digital world.
