This is an excerpt from our “Securing GenAI” guide, which you can access here
Generative AI (GenAI) promises colossal productivity gains, but its adoption is being held back by data privacy and security concerns.
In our new guide, you’ll get access to practical advice for overcoming these challenges. Download your copy to learn about:
- Performing application and use case audits
- Defining AI usage policies
- Training end users
- Selecting vendors
- Monitoring for process deviations
Data Privacy Concerns Hold Back GenAI Adoption
Enterprises recognize the necessity of embracing GenAI technologies to stay competitive and reap productivity rewards, understanding that the right use cases can lead to significant gains. Yet, while adoption is expected to increase over the coming years, it’s currently stuttering. A recent survey from MIT found that, despite widespread interest and experimentation with GenAI, only 9% of respondents said they had adopted the technology widely.
In the same MIT survey, 77% of the respondents cited regulation, compliance, and data privacy as key barriers to the rapid employment of generative AI. Gartner's research tells a similar story, with “uneasiness over data security, privacy, or compliance” listed as the top barrier to adopting GenAI.
Employees are piling data into these tools, and security teams have no idea what data is sensitive. Any leak of intellectual property can prove costly, yet existing tools are not built to detect sensitive data shared within vast flows of unstructured text.
Overcoming Shadow AI Challenges
Faced with such challenges, the knee-jerk reaction from many enterprises has been to block GenAI tools. We’ve already seen this play out with the likes of Samsung, Amazon, and the New York Times reportedly blocking access to GenAI tools entirely.
Even if you wanted to block these tools, it’s becoming harder to do so in reality.
First, most SaaS tools now have some form of GenAI baked in, which makes it very tricky to outright ban GenAI. Second, the appeal of these tools is so strong that employees are bypassing restrictions to use them. This leads to an unintended consequence where users resort to personal devices and networks, moving away from secure corporate systems. This has led to an extension of pre-existing Shadow IT challenges.
Practical Advice for Security Teams
We’ve been careful to ensure that this guide is as actionable to use as possible. To this end, we’ve already published an AI Usage Policy Generator to help to get start on creating your AI program.
Within the guide, each section will have practical tips that you can implement straight away. For example, when discussing the impact of GenAI on your supply chain, we’re providing a list of recommended questions to ask suppliers.
Download Your Copy
If you grappling with securely rolling out GenAI use in your organization, we’d encourage you to check out the Best Practice Guide for yourself: https://www.harmonic.security/resources/secure-genai-adoption-a-ciso-guide-to-overcoming-data-privacy-challenges.
If you have any questions or you’d like to learn more about Harmonic, don’t hesitate to get in touch with the team by visiting https://www.harmonic.security/get-demo.
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