Generative AI tools have changed the game for businesses in every industry. AI advancements streamline day-to-day operations by automating time-consuming and error-prone tasks, supporting rapid and informed decision-making, and more.
However, as much as this revolutionary technology is a source of positive change, businesses are quickly discovering that it also comes with some downsides. In short, AI is advancing faster than data security protocols, putting companies at risk for compliance challenges, data breaches, and other costly issues.
Machine Learning and Security Risks
AI tools use large language models (LLMs) that learn from publicly available information, a major reason for the massive gap between a company’s willingness to adopt AI tools and risk preparedness. If a company’s information is accessible anywhere online, generative AI tools can learn from it. When they do, they can use it against the source for nefarious purposes.
Most organizations have security protocols to prevent sharing sensitive data with public LLMs, including prohibitions on using unsanctioned tools. However, in many organizations, employees use these tools without authorization, effectively uploading information to public models, leaving the organization vulnerable to cyber threats.
Compounding the problem is a lack of employee training on how to use AI technology to its greatest advantage and how to do so securely. Experts note that cybersecurity policies and practices often tank the user experience, forcing workers to implement workarounds so they can use the tools that make their jobs easier. Unfortunately, these “solutions” can inadvertently create security risks, however effective they may be.
Catching Up to AI Advancements
Ironically, many companies report that despite AI adoption risks, the technology is a critical component of efforts to improve their overall security posture and response, particularly regarding overall efficiency. AI-based security tools can more quickly identify and thwart threats, freeing up humans for more in-depth work. At the same time, AI tools can learn from the very threats and incidents they detect, putting them a step ahead of security protocols.
However, considering the rapid proliferation of risks, security teams must make their policies and standards more user-friendly. Finding a balanced approach that addresses network security and user-friendliness is the core challenge that security teams cannot afford to put on the back burner.
Some of the ways that businesses are creating stronger security barriers without sacrificing user experience include:
- Requiring the use of zero-trust environments or VPNs to secure sensitive information
- Implementing multi-factor authentication requirements
- Developing formal strategies to manage AI security risks
- More in-depth employee training
- Limiting application permissions and restricting applications to those from approved sources
- Embed privacy into tool development, including anonymizing data
AI advancements promise many benefits for companies to grow and thrive in a competitive landscape. They can also spell an organization’s downfall if not properly managed. Taking steps to remain ahead of the security risks will allow your business to effectively and safely tap into the potential of AI and give you peace of mind.
