Best Practices for Responsible AI Use Among Businesses

The use of AI tools by businesses has seen a huge uptick in the recent past. AI has permeated different departments of organizations in areas ranging from customer service to data analysis and beyond, and investments in AI are only rising. While some companies utilize commercially available AI tools, others invest in developing proprietary AI solutions tailored to their specific needs, despite the higher costs required for in-house AI solution development. ChatGPT – a large language model which amassed a user base of 1 million withing just a week of its launch – is being enthusiastically adopted by many businesses looking to increase productivity. As per Forbes, 90 percent of business leaders say that knowing how to use AI tools like ChatGPT is a key skill. Gartner forecasts that almost 30 percent of large organizations’ outbound marketing messages will be created by AI, a big jump from just 2 percent in 2022. However, AI tools, while becoming more embedded within everyday business processes, come with their own set of challenges. Without proper guidelines and training, their use can lead to issues like misinformation, biased outputs, and compromised corporate integrity. Many companies have imposed a ban on use of AI tools by due to these very concerns. However, missing out on ChatGPT also means missing out on the extraordinary benefits it offers. A better way forward is to lay down clear rules when it comes to AI use by teams so that the tool is used responsibly, doesn’t churn out inaccurate data, and is fully compliant with all regulations.  Doing this is not just a checkbox compliant requirement, it is highly essential for ensuring consumer trust and organizational integrity. Let’s look at some of the safety measures companies are taking when it comes to effective AI tools usage.

Best Practices for Responsible AI Use Among Businesses

# 1 Establish Clear Purpose and Scope of Use of AI Tools

Before the AI tool is deployed, business leaders must clearly explain the purpose of implementing AI in a particular department as it is crucial that employees have a clear understanding of both the purpose and the scope of the AI tools they will be using. Companies need to articulate why these tools have been introduced and what they aim to achieve with them. For example, in a customer service department, the primary objective might be to reduce response times and free up human agents for more complex queries. Clear communication helps align the use of AI with the company’s strategic goals. Also, employees should be made aware of what AI tools are capable of within their specific roles. This includes detailed guidelines on when and how to use these tools. For instance, marketing teams might use AI for data analysis and customer insights, but should understand the boundaries regarding customer data privacy and ethical advertising practices.

Also, it is important to ensure that while training the AI tool, confidential company information remains secure. Companies cannot afford to compromise sensitive data while training the AI model, which is why businesses should consider using techniques like data masking and anonymization, use synthetic data, follow differential privacy, train on sampled data, and so on. They must also ensure that the AI is trained in a highly secure environment with private servers, encrypted data storage and transfers, and strict access controls. In these environments, only authorized personnel should be allowed access to the AI and the data used to train it, and all access should be logged and monitored.

#2 Clearly Define Use Cases and Mandate Human Intervention for Anything Complex

Companies should define specific use cases where AI tools can be applied. This helps in setting clear expectations for employees on when and how to use these tools. For example, in customer service, AI tools like chatbots and virtual assistants are increasingly being used to handle routine inquiries such as checking account balances, updating personal information, scheduling appointments, or tracking order statuses. However, when more complex, nuanced queries come in, ones that need to be handled with empathy, judgment, and deep problem-solving skills, human support is critical. For example in the healthcare industry, AI tools can be deployed for patient interaction as in the case of scheduling appointments. But when it comes to, diagnosing conditions, prescribing treatments, or handling emergencies, human support is indispensable. AI-generated advice must be vetted by medical professionals before being relayed. This ensures that no inaccurate response is passed on to the patient. In the area of marketing too, while AI is commonly used to analyze consumer behavior, automate email campaigns, and personalize advertisements, the creation of complex marketing strategies, understanding brand nuances, and decision-making on sensitive advertising campaigns are areas where seasoned marketers are indispensable.

#3 Ensure Secure Data Handling and Privacy

With regulations such as GDPR and CCPA in place, companies are particularly cautious about how AI tools handle data. It is imperative for businesses to establish and adhere to robust data handling protocols. AI tools, especially those involved in AI-driven chats, collect vast amounts of data during interactions. To ensure compliance existing regulations, companies must:

• Obtain Consent: Before collecting data, explicit consent must be obtained from the user. This consent should be informed, meaning the user is aware of what data is being collected and for what purpose.
• Minimize Data Collection: Collect only data that is necessary for the specific purpose stated. This principle of data minimization helps reduce the risk of privacy breaches.
• Secure Storage: Use encryption and other security measures to protect data from unauthorized access.
• Follow Jurisdictional Laws: Be aware of requirements concerning data localization, which might restrict the transfer of personal data across borders, depending on jurisdictional laws.
• Use Data for Stated Purpose Only: Use the data only for the purpose for which it was collected and for which the user has given consent.
• Limit Access Controls: Limit access to the data to only those employees who need it to perform their job functions, and ensure they are trained on responsible data use. AI-driven chat tools are particularly sensitive because they interact directly with users and collect a wide range of data. Here’s how data privacy can be maintained in these interactions.
• Initial Disclosure: At the beginning of an interaction, disclose that an AI tool is being used. This informs users about the nature of the data processing and maintains transparency.
• Data Collection Practices: Clearly explain what data the chat tool collects during the interaction, how it will be used, and how long it will be stored.
• User Rights: Inform users of their rights under GDPR and CCPA, including the right to access their data, request corrections, or demand deletion of their data.

By implementing robust guidelines for data collection, storage, usage, and sharing, businesses can not only comply with legal standards like GDPR and CCPA but also build trust with their users.

#4 Impart Training and Awareness

Proper training can help employees understand how AI tools work, their capabilities as well as limitations, and ways to use them to get the maximum benefits. These sessions should cover not only interactive demonstrations on how to use the tools but also when to use them, especially focusing on tasks they are meant to automate. Companies should invest in ongoing training programs to keep employees up to speed on the latest AI capabilities, guidelines to follow, and responsible usage. For example, in the retail sector, AI is used extensively for customer interaction and personalization of shopping experiences. Retail companies are training their marketing teams to ensure that AI-generated product recommendations or promotions adhere to advertising standards and do not mislead customers.

Companies must also encourage employees to provide feedback on AI tools’ performance and use it to continuously improve the tool. A support system needs to be established where team members can report issues or uncertainties regarding AI usage. In the event where AI is misused, companies must establish clear consequences for breaches of policy and enforce these are enforced consistently to maintain discipline and trust in AI usage. Also, should an AI mishap occur, companies should have a robust incident response plan that should outline steps for immediate action upon detecting an issue, including who to notify, how to contain the issue, and strategies for mitigation. Businesses should conduct a thorough root cause analysis (RCA) to understand why the AI failed.  This analysis should involve AI developers, data scientists, operational teams, and any other relevant stakeholders. The goal should be to identify the specific breakdowns in data handling, algorithmic design, or operational processes that led to the failure. Based on the findings from the RCA, companies must develop and implement a plan for corrective actions to fix the immediate issues. Preventive actions are also crucial to ensure similar incidents do not recur. This might include revising AI models, updating data sets, enhancing quality control processes, or improving training data to remove biases.

#5 Ensure Ethical AI Use

Employees using AI irresponsibly put an entire organization at risk. Employers should have mandatory training on ethical AI use that mirrors the organizational policy. This includes training employees on the importance of non-biased outputs. Companies need to develop a clear ethical AI framework that includes principles such as fairness, accountability, transparency, and respect for user privacy. The framework should guide all AI initiatives and be aligned with the company’s core values and the legal requirements of the jurisdictions in which the company operates.

Another issue to consider is that of copyright infringement and culpability when it comes to AI-generated content. Suppose a brand notices that its trademarked logos, images, and other content look very similar to that of another brand, and it wants to take legal action, can brand two be charged if that content was generated not by a person but by AI? Who would have to take the blame for trademark infringement if the content creator was not human but a machine? Can brand two even claim it as their branded content, given there was no human involvement in the creation of the content? There is some legal ambivalence in this, matter, especially when it comes to whom to fix the blame on, and legislation is still developing. Meanwhile, there are tools like AI-powered trademark searching (AI systems that can detect minute resemblances and variations among the trademarks, making it feasible to quickly identify possible disputes), real-time brand monitoring systems (that can detect variety of online venues, such as social media networks, e-commerce websites, and digital marketplaces) etc. that can help to detect unlawful usage and brands can use these while developing their own content to prevent potential copyright issues.  

#6 Mitigate Inaccuracies With Regular Monitoring

Regular monitoring of AI interactions with customers and internal processes should become a standard practice. This helps companies identify any deviations from expected behaviours and correct them before they impact the business negatively. For example, in finance regular audits are conducted to ensure AI tools do not produce biased or inaccurate outputs, which could lead to regulatory penalties. Regularly monitoring of AI interactions ensures compliance with existing policies and also helps to gauge the effectiveness of AI tools. Companies need to set up audit trails to track AI outputs, especially in cases where AI actions affect customer interactions significantly.

Closing Thoughts

As AI continues to evolve and integrate into various business processes, the need for clear rules and training on its use becomes more critical. Companies that proactively address these needs by setting strict guidelines and investing in employee training can leverage AI effectively without compromising on accuracy or integrity. This not only protects the company but also ensures that innovations in AI are used responsibly and beneficially.