Are Your Employees Using AI Tools Safely?
Balancing AI innovation and security is crucial for businesses.
Navigating the adoption of AI tools requires balancing innovation and security. Learn how to manage risks and benefits effectively in this dynamic landscape., says Dylan Border of Hyland.
Earlier this year, employees at Samsung uploaded sensitive code to ChatGPT. Leaders became concerned the generative AI tool would reference the company’s intellectual property when generating responses to questions posed by external users. Samsung swiftly banned employees from using ChatGPT and other publicly available generative AI tools on company devices. Several other companies, including Apple and JPMorgan Chase, quickly followed suit.
However, blanket generative AI bans may only sometimes be in the business’s best interest. Leaders are right to be cautious, and the risks of inadvertently exposing company and customer data are real. However, falling behind the AI adoption and knowledge curve is also risky in an environment where achieving speed and efficiency is essential.
Some enterprises, like Amazon, have redirected employees away from publicly available AI tools and toward internal offerings, ensuring sensitive information stays within the company’s domain. Unfortunately, most organizations don’t have this option and instead need to develop a playbook for maintaining security while adopting innovative third-party technologies like generative AI.
Whether your company is wary of AI, embracing it wholeheartedly, or somewhere in between, it’s critical to strike the right balance between security and experimentation. Doing so requires constant collaboration and communication between IT and stakeholders throughout your organization to determine how to move forward with AI to maximize benefits while minimizing risks.
Where Is Your AI Journey Headed?
AI capabilities are evolving every day, and the pace of change and development can feel overwhelming. Against this backdrop, it’s useful for company leaders to come together and determine your organization’s AI stance — both with generative AI and with AI-powered applications designed to make operations easier and more efficient. Consider questions like:
- Do we want to be an early adopter, or are we content to see how the industry evolves? What are our goals for using AI tools in our operations?
- What types of AI tools are most relevant to our work? What efficiencies and benefits will they introduce? Are there any downsides? How will our customers be impacted?
- Who should be involved in evaluating AI tools? What types of training, guidance, and communication do we need to provide to users throughout the organization?
Defining clear goals for AI adoption enables you to position your organization strategically for the future while making informed decisions about integrating AI into your operations.
See More: Leveraging AI to Embed Actionable Decision Intelligence
How to Manage Risk While Embedding AI Tools Throughout Your Organization
Conversations about generative AI tools like ChatGPT, Bing, and Bard dominate headlines and company Slack channels. But other AI-powered SaaS tools, from HR applicant tracking systems to marketing analytics platforms, should elicit a similar internal discussion before you give them the green light and begin incorporating them into your operations. It’s essential to approach the possibility of adopting any new AI-enabled tool — generative or not — from a risk-management perspective.
When any team in your organization considers implementing a tool with AI capabilities, it is important to weigh the business benefits against data accuracy and privacy concerns.
1. What is the business case for using an AI-powered solution?
Start by outlining the specific business outcomes and benefits the tool can deliver. By identifying key objectives and aligning them with the potential impact of AI, you can clearly articulate the value proposition of trialing an AI solution. These conversations should involve input from IT team members, who can speak to technical considerations and security requirements, and end users and stakeholders the AI tools will directly impact. Their input and insights are invaluable for understanding specific needs, user experience requirements, and potential risks.
2. How is the AI model built and trained?
AI learns from humans, and humans are flawed. Without rigorous controls, biases and inaccuracies can arise. For example, if an AI model is trained primarily on data from a specific demographic, it may need help to provide fair and accurate predictions for individuals from other demographics. A third-party AI provider should be prepared to demonstrate the measures in place to address bias and ensure the fairness and accuracy of the model.
Similarly, AI models are built on algorithms and statistical techniques, and their accuracy and reliability must be rigorously evaluated. Confirming the model’s performance through testing, validation, and comparison against ground truth data is essential. But like human decision-making, AI isn’t perfect. Your organization will need to establish its risk tolerance for different vulnerabilities in the model and identify the circumstances and use cases where you are comfortable incorporating AI.
3. How will your company and customer data be stored and used?
All companies should know how AI tools access and store sensitive information. That’s doubly true for those dealing with high volumes of personal customer data, such as health and financial records. It is crucial to remain cognizant of the inherent risks associated with AI since unintentional data breaches or mishandling can occur through accidental exports as your company’s data becomes integrated into the model’s training dataset. The most secure AI tools keep your data contained in a local environment. (For businesses hesitant to use ChatGPT, a new business version is in the works to give companies more control over how their data is used.)
See More: How To Integrate AI With HR for Better Decision-Making
AI Is Here to Stay. What Role Will It Play in Your Organization?
AI has the power to transform business operations across industries, but we’re still in the early days. It’s important to begin testing, trialing, and evaluating AI capabilities in a controlled manner so users throughout your organization can begin engaging with this technology without exposing the business to unnecessary risk.
By navigating the complex landscape of AI from a risk management perspective, you can unlock the full potential of AI while safeguarding data privacy, mitigating exposure, and achieving your strategic objectives in an increasingly AI-driven world.
Can strategic integration of AI help improve efficiency and security? Share your thoughts with us on Facebook, X, and LinkedIn. We’d love to hear from you!
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