Today, AI usage is common practice in the workplace, and with benefits such as increased productivity and cost efficiencies, it is easy to see why.
Despite AI’s many benefits, the prevalence of AI tools at employees’ fingertips is triggering a rise in shadow AI – the unapproved or unauthorised use of AI tools and technologies within an organisation, typically without the knowledge or oversight of the IT or data governance teams.
The risks of shadow AI are extensive and daunting, with data security and privacy breaches, legal and ethical issues and reputational damage all at stake.
In this article, we will dive into these risks and discuss how companies, small and large, can mitigate against the risks caused by the rise of AI. By addressing these risks proactively, organisations can harness the benefits of AI without falling prey to the dangers of shadow AI.
The Unseen Threat: Employees Using AI Tools Without Oversight
When employees use unsanctioned AI tools, they may unknowingly expose their company to security and compliance risks. For example, an employee may use an AI-driven application to handle sensitive customer data, but if that tool isn’t adequately secured or regulated, there’s a chance that the data could be compromised. Furthermore, unapproved tools may not align with industry-specific compliance requirements, putting the business at risk of violating regulations like GDPR.
These issues are compounded by the fact that many employees are unaware of the potential risks associated with using AI tools. While they may be excited about the possibilities AI offers, they often lack the knowledge needed to evaluate the security and compliance implications of the tools they choose. Without oversight and regulation, businesses are left in the dark about the tools being used within their organisation, making it difficult to identify vulnerabilities or risks.
Why AI Policies Are No Longer Optional for Businesses
In the face of these risks, businesses must implement clear AI policies that define acceptable usage while providing guidelines for safe and secure AI practices. Without such policies in place, companies risk falling into a reactive approach, dealing with breaches and compliance failures after they’ve already occurred. The best defence against the challenges of AI adoption is a proactive one, this entails establishing clear guidelines and strategies before problems arise.
An AI policy should cover several key aspects, for example:
- Acceptable Use: Companies should define which AI tools are approved for use within the organization and outline how employees can request new tools. This ensures that only secure and compliant tools are used, minimising the risk of unauthorised access to sensitive data.
- Data Privacy and Security: AI tools often process vast amounts of data, especially personal and sensitive information. So it is vital for businesses to have strict data privacy and security measures in place. Policies should define how data is handled, stored, and processed by AI tools, ensuring compliance with data protection laws.
- Compliance with Regulations: Different industries are subject to varying regulations regarding data privacy and AI usage. An AI policy should align with industry-specific compliance requirements to ensure that the company avoids costly fines and legal consequences.
- Monitoring and Auditing: Regular monitoring of AI tool usage is essential to identify potential risks before they escalate. A policy should include guidelines for auditing AI usage and ensuring that tools are being used appropriately and in compliance with company standards.
- Employee Training and Awareness: As AI technology evolves, employees must be continuously trained on how to use AI tools responsibly and securely. Policies should emphasise ongoing education to ensure that workers understand the risks associated with AI.
The Resource Gap: Many Businesses Are Unprepared for AI Governance
Despite the clear need for AI governance, many businesses still lack the expertise and resources required to effectively manage AI risks. In addition to resourcing issues, the rapidly evolving nature of AI technology makes it difficult for organisations to stay ahead of potential threats, and many businesses are overwhelmed by the complexities of AI governance.
For smaller companies, the challenge is worsened by a lack of in-house expertise. AI governance requires specialised knowledge in areas such as data privacy, cybersecurity, and regulatory compliance, – fields that may not be represented on the company’s existing team. Additionally, the rapid pace of AI development means that what works today may not be sufficient tomorrow, requiring businesses to constantly update their policies and practices creating a continuous cycle.
Large organisations also face challenges in managing AI governance. With sprawling teams and multiple departments, it can be difficult to maintain consistency across the organisation. In these environments, AI tools may be used informally for various uses, making it harder to implement universal policies and ensure compliance across all areas of the business.
Ultimately, businesses of all sizes need to recognise that AI governance is a critical area that demands attention and investment. While it may be tempting to put off addressing these challenges, the cost of ignoring AI governance outweighs the investment needed to implement proper safeguards.
AI Governance is Essential for a Secure Future
As AI continues to reshape the working world, businesses must take essential steps to manage the risks associated with its usage. As discussed, the unregulated use of AI tools by employees can expose organisations to significant security and compliance vulnerabilities. To safeguard against these risks, companies need to be proactive in implementing clear AI policies, and ensure ongoing monitoring and training.
