Reports have indicated that 65% of companies don’t have adequate policies in place to govern the use of generative AI, whilst 40% of HR professionals say their companies lack AI policies.
There is a clear need for companies to foster adequate AI policies, without which, businesses risk their data privacy and intellectual property, which ultimately can lead to loss of consumer trust, reduced revenue, and potential collapse.
But what are the key policies to consider for businesses, and what could these look like?
What Could Good AI Usage Policies Look Like?
1. Data privacy guidelines
AI tools often rely on vast amounts of data in order to work, and by nature, this tends to include a lot of sensitive information. Therefore, it is key to ensure that employees avoid inputting personal or patented information into these tools. If sensitive information is inputted, this could be retrieved, leading to data hacks and leaks, which can damage business proceedings and reputation.
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Enforcing a well structured AI data privacy policy can help businesses reduce the risk of such incidents. It is crucial to ensure that this is well tailored in alignment with the company’s core values and principles, setting clear expectations, in order to reduce uncertainty around the tool. As we see more and more regulatory analysis of AI, every business should aim to get these policies right to decrease risks of data hacks, and protect customers and preserve their trust.
It’s also important to note that most AI tools have features which allow users to disable data storage. Employees should make use of these features to prevent company data from being used for AI model training. Compliance with legal and regulatory standards like GDPR is imperative.
2. Ethical guidelines & avoiding biases
Guiding the ethical use of AI is crucial in the rapidly evolving landscape of AI. Businesses should look to include a comprehensive code of ethics regarding AI usage, and best practices for the unbiased and responsible use of AI tools. There can be harmful consequences if your company utilises data in AI that is biased or inaccurate. In summary, your ethical guidelines should focus on factors such as; inclusivity and explainability, mitigating bias, transparency, positivity in use, and compliance with data privacy rights.
3. Training for employees
Surprisingly, only 48% of employees say they have received any type of AI training. All businesses who leverage AI should ensure employees are sufficiently trained in the tools. This does not only ensure they get the most out of the tool, but also that they comply with all other company guidelines regarding AI, such as data privacy regulations.
Training should include specifics tailored to your business sector and company needs. This is key to ensure AI is used in the best way for your organisation. For instance, the way AI is utilised in healthcare would be different to how it is used in the retail sector.
Some key considerations and factors to cover for employee training include but are not limited to:
- Building a foundation of understanding among employees around the basics of AI, such as machine learning and ethical considerations.
- Training on specific AI tools used in the job and how these will be leveraged, this could be in sales, marketing, or operations for instance.
- Ensure employees know the best and most secure ways to use the tools.
- Incorporate hands-on training and real world scenarios, to build employee confidence.
- Continued development, stay up to date on AI advancements as a company, and construct new training as needed.
- Foster a positive environment, where employees can express questions, ideas, or concerns about the tools.
4. Risk management
As with many technological tools in business, there are risks associated with AI usage, which is why it is vital to conduct risk assessment and risk management processes regularly, in order to use the tools in the safest and most effective way.
Good risk management entails continued monitoring of tools and systems to identify any outliers at the earliest time. Data risks should be mitigated by analysing data regularly and complying with privacy and security measures, to avoid data loss and unauthorised access to company data. AI tools should also be trained on unbiased, and accurate data, in order to maintain integrity and mitigate bias risks.
AI models may also be at risk of cybersecurity breaches, which could lead to the loss of key consumer and business data. To mitigate this risk, businesses should implement security practices such as regular software updates, strong authentication methods, isolation of sensitive data, and ensuring proper training for staff on responsible AI usage and potential threats.
Ethical risks should also be considered, and as discussed above, adequate ethical guidelines should be in place to mitigate risk, in order to avoid violations of privacy and bias.
Regular risk assessments are imperative for effective and secure AI usage in business.
5. AI Governance
As AI becomes increasingly integrated into the daily business workload, the potential negative impacts have become more widely known. Sufficient AI governance acts to mitigate this, by building trust, efficiency, and responsible AI use. Companies should look to establish committees that oversee AI use and policies, to ensure ethical standards are complied with. Effective governance policies ultimately help safeguard your business and its consumers.
Organisations should understand the societal implications of AI, as well as the technological impact. It is essential to thoroughly examine training data to avoid implementing biases into AI algorithms. Clarity and openness in how AI algorithms operate and make decisions must be consistently maintained, so that your business can explain the reasoning behind AI-driven outcomes.
Companies should set and adhere to high standards in AI use, and manage the significant changes AI can pose, holding accountability for its influence.
Christoph began programming computers as a young teen, and since then has built his career in technology and AI. He has founded AIPRM on principles such as empowering creativity and productivity, and AIPRM works to enable users to get more out of platforms like ChatGPT with engineered prompts, providing individuals and businesses with the resources they need to do more in less time.
