2024: The year of AI at Work

marking the beginning of a new era of AI experimentation. According to Microsoft’s Work Trend Index Annual Report, the use of generative AI has nearly doubled in the last six months, with 75% of global knowledge workers now utilizing it. Employees, overwhelmed by the pace and volume of work, are increasingly bringing their own AI tools to the workplace.

This phenomenon, known as “shadow AI,” introduces new risks and challenges for IT teams and organizations. In this blog, we’ll explore the significant impact of shadow AI and how companies can mitigate these risks.

1. Security vulnerabilities

Unauthorized AI tools can lead to data breaches, exposing sensitive information such as customer, employee, and company data to cyberattacks. Without proper vetting, these AI systems may lack robust cybersecurity measures, making them vulnerable to exploitation.

2. Compliance issues

Shadow AI can create significant compliance challenges. Organizations must adhere to strict data protection and privacy regulations, and unapproved AI applications make it difficult to ensure compliance. This is especially concerning as regulatory scrutiny of AI solutions increases.

3. Data integrity

The uncontrolled use of AI tools can compromise data integrity. Multiple, uncoordinated AI systems can lead to inconsistent data handling practices, affecting data accuracy and complicating data governance. Employees inputting sensitive information into unsanctioned AI tools further jeopardizes data hygiene.

1. Establish clear acceptable use policies

Develop and enforce clear AI usage policies for employees. Define acceptable and unacceptable uses of generative AI in business operations, specify approved AI tools, and outline the process for vetting new AI solutions.

2. Educate employees on the risks

Make AI education a priority, specifically highlighting the risks of shadow AI. Training programs should emphasize the security, compliance, and data integrity issues associated with unauthorized AI tools, reducing the likelihood of shadow IT practices.

3. Create an open and transparent AI Culture

Foster a transparent AI culture by encouraging open communication between employees and the IT department. This helps ensure that security teams are aware of the tools employees are using. A culture of openness around AI use allows IT leaders to better manage and support AI tools within the security and compliance framework.

4. Prioritize AI standardization

Develop an enterprise AI strategy that prioritizes tool standardization. Ensure all employees use the same tools under the same guidelines by vetting and investing in secure technology for every team. Promote a culture of AI openness and responsible use of generative AI tools.

As shadow AI continues to grow within companies globally, IT and security teams must act to mitigate the associated risks. By defining clear acceptable use policies, educating employees, fostering a transparent AI culture, and prioritizing AI standardization, organizations can address the challenges posed by shadow AI.

Understanding the risks and implementing these strategies will help companies manage shadow AI effectively, ensuring a secure and compliant AI adoption journey.