The Rise of Generative AI in the Retail Sector

The retail sector is at the forefront of adopting generative artificial intelligence, with recent reports indicating a trend among many companies to leverage this technology to enhance their operations. However, this rush towards AI also brings significant security challenges that require attention.

The Spread of AI in Retail

A recent report from cybersecurity firm Netskope reveals that 95% of retail companies now use generative AI applications, a significant increase from 73% the previous year. This reflects the rapid pace at which retailers are embracing modern technology to avoid falling behind.

Nevertheless, this swift adoption of AI comes with considerable security risks. Integrating these tools into business operations creates new surfaces for cyber attacks and the potential exposure of sensitive data.

Shift Towards Approved AI Tools

According to the report, the sector is witnessing a shift from random usage to a more organized approach led by companies. The use of personal AI accounts by employees has decreased from 74% to 36% since the start of the year, while the use of company-approved tools has doubled from 21% to 52%.

This shift reflects a growing awareness among companies of the risks associated with “shadow AI” and a desire to maintain control over the situation.

The Most Popular Tools in Retail

In the battle for dominance on the retail desktop, ChatGPT remains the most prominent, used by 81% of companies. However, its dominance is not absolute, as tools like Google Gemini and Microsoft Copilot have gained significant popularity.

ChatGPT recently experienced its first decline in popularity, while the use of Microsoft 365 Copilot has increased thanks to its deep integration with daily productivity tools.

Security Risks of AI

Beneath the widespread adoption of AI lies growing security nightmares. The ability to process information, which makes these tools useful, also represents their greatest vulnerabilities.

Reports indicate that company source code is the most common type of exposed data, accounting for 47% of policy violations. This is followed by structured data, such as confidential customer and business information, at 39%.

Conclusion

Security leaders in the retail sector must take decisive actions to control the use of AI within their organizations. Haphazard adoption can quickly lead to data breach scandals. Therefore, it is crucial to enhance full visibility of web traffic, block high-risk applications, and enforce strict data protection policies.