By Heather Shoemaker, CEO of Language I/O

2022 marked a watershed moment when ChatGPT showed us AI's transformative potential. Since then, AI has become woven into our daily workflows - from using Gemini to streamline calendar management to leveraging Jasper for content creation.

While organizations are unlocking remarkable efficiencies through AI adoption, recent incidents at major companies like Ticketmaster, Uber and 23andMe have exposed a critical vulnerability: our data security. As teams rush to integrate these powerful tools, they're potentially feeding sensitive information into AI models without fully considering the implications. Google researchers even demonstrated how large language models can inadvertently reveal personal information, highlighting why business leaders must now take a more measured approach to AI implementation - one that balances innovation with robust security measures.

As AI becomes even more integrated into seemingly every corner of business and life, it will be necessary to pay increased attention to the potential risks and vulnerabilities associated with GenAI. This necessity will spur a data security renaissance. Organizations will prioritize robust data security and governance to mitigate risks, build trust and prepare for future regulations. These measures will ultimately help gain a competitive advantage in the evolving AI landscape.

GenAI best practices for 2025 and beyond

While AI technology is advancing quickly, regulations and legal frameworks are struggling to keep pace, creating a situation where AI usage is largely unregulated. In the absence of comprehensive government regulations, the responsibility of ensuring the security and proper use of these tools falls on the businesses that are leveraging them.

According to a recent Deloitte report, data privacy is at the top of tech professionals' ethical worries when it comes to implementing GenAI - in fact, 72% ranked data privacy as one of their top three most pressing ethical concerns with 2 out of 5 ranking it first. This is a dramatic uptick from 2023's 1 in 4.

Another recent report revealed that 1 in 4 employees see no issue with feeding confidential customer information into online AI tools like ChatGPT or Google Translate.

While comprehensive AI regulations may not exist yet, they are likely to be developed in the future. Organizations that proactively implement strong security measures will be better positioned to comply with future regulations when they do emerge. Organizations can safeguard data while reaping these tools' benefits by establishing robust data governance policies to mitigate the risks associated with GenAI. This includes practices like:

• Carefully vetting AI platforms and tools
• Implementing strict data access controls
• Regularly auditing AI systems for security vulnerabilities
• Ensuring transparency in how AI systems use and process data
  

Another best practice is to use platforms that commit to zero data retention, meaning the AI service provider doesn't store any of the data processed by its tools, which can significantly reduce the likelihood of data breaches or misuse.

Galvanizing customer trust

By prioritizing data security and being transparent about GenAI usage, organizations can build and maintain trust with their customers. This is increasingly important as consumers become more aware of and concerned about data privacy issues, especially since 7 in 10 Americans say they have "little to no trust in companies to make responsible decisions about how they use AI in their products." If an organization is upfront and honest about its GenAI policies and procedures, it is already going to stand out from the crowd.

Additionally, organizations that take a thoughtful, security-first approach to AI adoption will have a competitive advantage over those that implement AI tools without adequate safeguards. This edge could translate to better customer retention, reduced risk of costly data breaches and a stronger reputation in the market. By prioritizing security in AI implementation now, organizations can set themselves up for long-term success. This investment involves not just adopting AI for its immediate benefits, but also considering the big picture, such as the broader implications and potential risks associated with these technologies.

It's time to look at data security as it relates to GenAI usage in a new light - one with a renewed vigor around safety and transparency. As AI continues to proliferate, the need for a more mature, security-focused approach to AI adoption will be a top priority moving forward. Organizations must shift from viewing it as a buzzy "next big thing" that needs to be adopted as quickly as possible to seeing it as a powerful technology that requires careful implementation strategies and comprehensive security measures to be leveraged successfully. By doing so, organizations can reap the benefits of AI while minimizing risks and ultimately building a foundation for sustainable, responsible AI use.

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ABOUT THE AUTHOR

Heather is the CEO of Language I/O, an AI-powered translation platform that provides real-time language translations in over 150 languages. With integrations with Salesforce, ServiceNow, ZenDesk and Oracle, Language I/O's tech can be up and running for companies in less than a day. Language I/O also has best-in-class security that encrypts data in transit and retains zero data.

Prior to co-founding Language I/O, Heather was well-known for globalizing code for Fortune 500s. She was also the senior director of Product Management and Globalization for eCollege, which was acquired by Pearson Education during her tenure. While at Pearson/eCollege, Heather and her team built a next-generation, online college education platform, which was launched globally.

Heather holds a Master of Science from the University of Colorado at Boulder College of Engineering as well as a Bachelor of Arts in Latin American Studies from the University of Washington in Seattle. She has lived in various parts of the United States and Mexico and speaks English and Spanish.