Written by: Daniel Haurey on 07/11/24

We’ve discussed the importance of key business and technology policies as the backbone for an effective cybersecurity posture. Without detailed documentation to guide technology usage, data management, security processes, and more, many businesses find themselves lacking structure and, in turn, are more susceptible to cyber attacks.

As exploration and adoption of generative AI and other automation tools accelerate, all businesses should invest the time to create a straightforward generative AI policy for using these powerful technologies—from what generative AI use cases are allowed to what AI tools are approved for use in your organization. In particular, your policy should clearly outline generative AI risks and the steps for protecting sensitive or confidential data when using those types of tools.

Let’s start by defining generative AI, epitomized by platforms like ChatGPT, which promises to transform content creation through prompt-based generation. From blog articles to social media posts, this AI-driven technology can churn out content at lightning speed, offering both free and paid versions to cater to diverse needs. The popularity of generative AI stems from its multifaceted benefits, including content creation and optimization, task automation, enhanced creativity and personalization, and research.

Why Your Organization Needs a Generative AI Policy

Nearly everyone agrees that not only is Gen AI a valuable tool, but it also breathes freshness and creativity into a workday. No harm in having a little fun with a productivity tool, right? AI has gained popularity with HR and marketing teams as it enables summaries of long-form content, creates outlines for communications, compares drafts, and provides opportunities for scale. But regardless of what Gen AI is used for, it has its cons: misalignment with brand standards, bias, inaccuracy, privacy limitations, hallucinations, compliance conflict, attribution and copyright issues, and security.

Even those outside of technology look at AI with a skeptical eye: 60% of the public believe AI needs human oversight, 59% think AI needs enhanced security measures, and 58% feel AI needs ethical use guidelines. The public isn’t alone; lawsuits are already queuing up and legislation is pending at both state to federal levels. As a quickly evolving tool that is still in its early stages of use by the general public, Gen AI has yet to solve issues such as data privacy, attribution, and security. That’s why usage is best guided by a simple generative AI policy framework that balances risk mitigation with the value of generative AI. Generative AI best practices should be clearly defined in your policy and then communicated across the organization.

What to Include in Your Generative AI Policy

Policies – regardless of topic and focus – should include several basic elements and corporate guidelines for Gen AI usage are no different. Begin with a clear introduction of the policy’s purpose and scope. For AI, that should include identifying departments or teams that can use Gen AI (e.g., marketing, human resources, executive team) and the types of Gen AI tools covered. Keep in mind that while many people refer to generative AI as “AI,” there are myriad options, from image generation to true business tools built for tasks such as corporate research or analytics. Other key elements of an effective generative AI policy framework are:

Permitted Use: Explain approved uses for generative AI within your organization. Examples: Content creation (marketing materials, social media posts), data analysis (report generation, summarizing large datasets), or brainstorming and idea generation.

Restricted Uses: Clearly explain any generative AI use cases not allowed by your organization. Examples range from generating content that is misleading to improper use of confidential data within the tools.

Data Management: Speaking of data, set guidelines for what organizational data can be used or shared in AI tools. This often is an extension of an existing data access and management policy, particularly if your organization manages customer information. Be certain to emphasize data security and privacy measures, especially if your organization must adhere to regulatory standards.

Oversight and Accountability: Stress the importance of review and the need for human guidance when using generative AI. This should include reviewing and approving all AI-generated outputs before use to avoid missteps with biased or inaccurate outputs. Also, clearly define who on the team is responsible for data management, the tools themselves, and the potential misuse of AI.

Transparency: Legally requiring disclosure of the use of generative AI is already in the works in many states and is encouraged by nearly every AI vendor. Your policy will set expectations as to where and how to disclose the use of AI-generated content and other AI outputs.

Monitoring and Training: Outline procedures for monitoring gen AI use and identifying potential risks or biases. Also, inform your team of any AI training available.  

Review and Revise: Schedule periodic reviews of the policy to ensure it remains current and reflects best practices and laws as those evolve. Work collaboratively with existing policy owners to align your generative AI policy with existing company policies on data security, intellectual property, and ethics.  

Keeping your generative AI policy straightforward will accelerate adherence. One of the challenges of implementing a generative AI policy is the easy access to AI tools by employees – AI solutions rank among the most popular “shadow IT” solutions in use today.

Keep These Generative AI Risks Top of Mind   

The rise of generative AI has revolutionized content creation, research and analysis, and more. But this tech marvel does include hidden risks to brand integrity and customer trust. While some challenges posed by AI usage are easy to remember, do not overlook the role of data security and privacy when you create a generative AI policy and the compliance considerations for AI usage.  Additionally, to create an effective generative AI policy and encourage responsible, ethical AI use, be sure to address issues such as:

Privacy and Compliance Rules: Gen AI tools are cloud-based solutions, and we all know that anything online is hackable. Remember to adhere to your organization’s data usage and management policies and consider that anything you share with an AI tool could be exposed. Even Google learned that lesson the hard way.

Misuse, whether intentional or accidental, can lead to serious consequences. Be sure you read and understand the privacy policy for any AI tools your team is using, and remember that personal data, confidential data, and intellectual property – all of these are susceptible to exposure or misuse if shared with an AI solution. Adding to that need for hyper-sensitivity when it comes to data privacy and approved usage is the role of compliance standards. While many regulatory agencies continue to fight their way through new parameters for handling generative AI tools, being aware that data input into online tools is rarely acceptable by compliance regulations.

Ethical considerations regarding accuracy, bias, transparency, and attribution: Skepticism is your friend as you leverage GenAI in your business, particularly for communications and research. AI hallucinations can tease you with great content … that is entirely fabricated. AI tools can trick you into sharing content with bias baked in – you must review outcomes closely to ensure your communications are culturally aligned with your organization’s beliefs. Acerbating these concerns is the lack of attribution by Gen AI tools and the general lack of adherence to copyright laws—both of which can land your organization in hot water.

Emphasis on the importance of genuine communication: Communications both internally and with customers must reflect the voice, brand, and tone of your organization. Be aware that not only can AI content be easily detected by most users, but it remains challenged by originality and repetition and its use can erode your brand standards and trust levels with clients and prospective customers.

Need additional help?

Check out our generative AI policy template and best practices tip sheet


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