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Business leaders are concerned about potential “catastrophic cyber-attacks” driven by generative AI (GenAI). As a result, companies are attempting to fight fire with fire, plunging headfirst into leveraging GenAI solutions without first establishing essential, foundational cybersecurity strategies.

With a lack of focus and investment in cybersecurity fundamentals like patching, vulnerability scanning, penetration testing, endpoint protection and more, businesses could be blinded by the GenAI hype and fall victim to the most basic risks. As we enter the age of advanced tech, it’s critical that companies leverage AI to master the basics before sweating over GenAI use cases.

The Hype Cycle Model

Gartner’s Technology Hype Cycle model offers an interesting perspective on the state of AI in cybersecurity. With the advent of GenAI, the hype cycle kicked off with the Innovation Trigger. Early on, the conversation revolved around the endless possibilities of GenAI revolutionizing how businesses monitor, respond and remediate cyber-attacks – but no real solutions existed.

Next, the peak of inflated expectations is when product usage increases, but there’s still more hype than proof that the innovation can deliver. What’s worse is the product usage could create new risks. In fact, 47% of executives are concerned that adopting GenAI will usher in new attacks targeting AI models, data or services. Right now, we are approaching the Trough of Disillusionment, where interest in the technology wanes as implementations fail to deliver value. With the average cost of a data breach reaching $4.45 million globally, and $9.48 million in the US this year, many companies are not getting results from GenAI investments.

Simply adopting GenAI solutions does not mean companies are secure. In fact, the rush toward GenAI can complicate the work of security teams, distracting them from what matters – the fundamentals. AI solutions that address the basics of cybersecurity should be every organization’s top priority. It’s critical to build a strong foundation before diving into GenAI use cases.

Three Ways to Build a Foundation with AI

Although technology is rapidly evolving, one thing remains the same: Criminals are slipping through the cracks. Unpatched vulnerabilities, weak endpoint protection, or untested software continue to be obvious entry points for hackers. The bad guys will always take the easy win – and no organization is too small to skirt these threats.

Before considering GenAI for more complex risks, businesses can leverage AI to develop a strong cyber foundation in the following ways.

  1. AI to Develop a Single Pane of Glass for all Cyber Risks

Regular, proactive vulnerability scanning is a best practice but can be a monumental challenge for many businesses without AI. It starts with running discovery scans to identify and map out all organizational assets at risk. From there, it will be easier to get a complete picture of which assets are at risk, which vulnerabilities need to be patched, which networks might be targeted, and more. As vulnerability scanning becomes an ongoing practice, monitoring trends, and reporting on security program effectiveness across the enterprise network infrastructure becomes more efficient.

According to a recent study, security professionals waste nearly 33% of their time each day investigating and validating false cyber incidents. It is essential for AI tools to create efficiencies for security teams, offering all information on vulnerabilities, potential security incidents, and remediation efforts in a single platform. That single pane of glass is important to stay one step ahead of the latest cyber threats.

  1. AI to Supercharge Penetration Testing

It’s important to test cyber defenses using the same techniques as modern cybercriminals. From websites, mobile applications, cloud databases, large language models, and even employees, pen testing offers clear insights into what defenses are failing, and how humans can fill the gaps. But data shows that more than 75% of ethical hackers believe very few organizations have effective network detection, and response capabilities in place to stop an attack in real time.

With AI, this process becomes more efficient, allowing humans to analyze data, identify vulnerabilities, validate findings, and conduct reconnaissance before cybercriminals break through defenses. This helps organizations identify, notify, and respond to various incidents, policy violations, and network intrusions in a systematic manner.

  1. AI to Unify Cybersecurity and Compliance

Most companies believe solid compliance means they are secure. This is far from the truth. With the typical large company working with upwards of 10 cybersecurity vendors, and AI solutions accelerating that trend, gateways for risk are increasing. Security teams stitching together different cyber and compliance solutions results in more cost and complexity without truly improving security.

As AI solutions enter the market, the companies with the best cyber posture will recognize the connection between cyber and compliance and adopt solutions that offer unprecedented visibility and actionable intelligence across these important risk categories. AI can be the glue between cybersecurity and compliance that organizations need to adapt to the rapidly changing threat landscape.

Breaking out of the Cycle

Precisely 74% of IT and security leaders believe their organizations would more successfully defend against cyberattacks if they devoted more resources to preventive cybersecurity measures. Companies are throwing complex GenAI solutions at the problem, but the hype of it is outweighing the results. By devoting resources to AI that contribute to preventative cybersecurity fundamentals, organizations can improve their cyber posture into 2024 and beyond.