What is the Role of AI in Cybersecurity?
At this point in time (May 22, 2024) many people view AI as something to fear. The unknown element paired with the fact that AI is more adept than humans in many areas makes people uneasy.
This is a normal reaction – people view the unknown as something to fear.
- Remember how nervous people were to use credit cards instead of checks?
- Go farther back and you’ll see the commotion that took place when cars began replacing horses.
With AI fully integrating into society now, the need for stronger AI cybersecurity is obvious.
AI is actually providing a way for humans to better execute their cybersecurity needs, because it offers a more efficient way to safeguard personal data from threats.
How Can AI in Cybersecurity Help?
Just as always, the concern is with how we share our personal data with the companies and people we interact with digitally.
From banking to social media, we leave a “trail of breadcrumbs” that make it quite simple for anyone with access to take and use our info. AI can help reduce the scams that hackers attempt to develop with our data.
Here’s how:
- Threat Detection: AI algorithms analyze patterns and learn from them to identify potential threats before they become actual ones. This proactive approach prevents many scams from happening in the first place.
- Handling Big Data: With the colossal amount of data generated daily, it’s impossible for humans to monitor everything. AI systems can process vast volumes of data quickly, spotting anomalies that may indicate a security issue.
- Adaptive Learning: AI systems continually learn and adapt to new potential risks. They evolve with the threat landscape, which means they’re always a step ahead of hackers.
- Automated Responses: Upon detecting a threat, AI systems can automatically take countermeasures without human intervention, significantly reducing response times.
Examples of AI in Cybersecurity
Because this tech is not actually new, you’re already experiencing the positive effects of AI supporting cybersecurity via your credit card companies and financial institutions who are actively onboarding tech to keep your data safer.
- A financial institution used AI to detect and prevent fraud, seeing a reduction in false positives by 25%.
- An e-commerce giant employs an AI-powered system that blocks or flags potentially malicious activity on its platform in real-time.
Beyond these two broad examples, there are countless ways companies of all sizes have successfully incorporated some element of AI in cybersecurity strategies already. Most cloud-based services use some form of machine learning to detect threats. As this type of AI tech improves, so will the results in these use cases.
AI Cybersecurity Challenges
While the integration of AI in cybersecurity offers tremendous benefits, there are challenges. I talk a lot about the need for transparency and ethics, because any given AI’s efficiency comes down to its design and its users.
Just like regulations were put in place for both the banks and the borrowers when it came to lending policies, I expect regulations to be created for both the AI developers and the general public in relation to how we use it.
The AI on its own won’t cause an issue (at this time). It’s the hackers using it maliciously who will try to cause an issue. The need for oversight and ethical considerations are being addressed at state levels as of today (updated 8/23/24) and the hope is we see some legislation coming soon.
I’ll continue to add to this article as the cybersecurity element of the AI revolution evolves. Subscribe to my YouTube channel for weekly videos on all things tech at youtube.com/@racheltalkstech!
Questions? Get in touch: rachel@bellestrategies.com or book a Complimentary Consultation.
With nearly two decades in the industry, Belle Strategies Owner Rachel Creveling is a seasoned business consultant who crafts comprehensive frameworks that integrate operations, marketing, sales and HR to position her clients for optimal success. She excels at incorporating trending tech ethically and studied Strategies for Accountable AI at Wharton.