As artificial intelligence becomes more deeply integrated into your business operations, its ethical use is a legal, reputational, and moral necessity. Unethical AI usage can expose you to significant risks, including legal consequences and loss of consumer trust.
Companies deploying AI tools that discriminate or invade privacy are increasingly being held accountable. Regulatory landscapes are evolving rapidly, with legislation like Colorado’s AI Act and New York City’s Local Law 144 mandating transparency, bias audits, and consumer protections for high-risk AI systems [1].
Beyond the courtroom, the court of public opinion is equally unforgiving. Consumers are becoming more aware of how their data is used and how decisions about them are made. A single breach of trust can lead to viral backlash and a sharp decline in customer engagement.
That’s why you need specific guidelines and preparation to ensure your use of AI is ethical and responsible.
Responsible AI for customers
So, why is AI transparency important?
AI systems are used by customers on a daily basis. Therefore, transparency into how these AI tools work is important, especially since the brand reputation might depend on their accurate responses.
Here’s a checklist you should follow when examining your AI in terms of customer usage:
Evaluate how the business should stay transparent
Type up privacy policies and terms of use for your AI. Also, if you’re using third-party conversational AI platforms, you need to read the policies as well as the terms and conditions thoroughly to ensure your customers are well informed.
Make sure your policies are easy to find and the AI system provides the necessary information, as well as links to the available resources.
Inform users when they’re interacting with AI and what it can do for them
This is not just a nice-to-have. It’s a legal requirement in the European Union and Utah (US) for companies to tell people when they’re interacting with an AI system rather than a human. [2]
So, if you’re using AI agents or any other AI communication system, add a disclaimer at the beginning of the chat stating that the user is chatting with artificial intelligence. This can be as simple as “Hi, I’m Silver, your AI helper. How can I help you today?”
Explain how your AI works to users who request it
Write a quick list of the actions that your AI can perform and set up a chat trigger that will send that message to users who ask for it. If you have more information available on your website’s FAQs or AI knowledge base, include a link to that page for further references.
Communicate incidents and errors
If your AI system makes a mistake, make sure you spot it and own up to it. Let the user know what happened and how you’re fixing it. Right the wrongs straight away to avoid frustration and ensure a good user experience. When people see that you react quickly and efficiently, they’ll want to continue doing business with you.
Ethical AI in a customer service team
Human representatives are extremely important to customer support. They provide empathy and monitor AI’s performance as well as jump in for complex inquiries.
And businesses should be human about AI. This means changing your agents’ positions when AI takes over their repetitive tasks. Instead of letting go of people, use them for higher-impact tasks and roles. For example, at Tidio, we changed our customer service specialists’ roles to AI content managers, sales development specialists, QA specialists, and product trainers.
Human oversight
Studies show that over 30% of customer service agents are expected to automate processes with the use of AI by 2026 [3]. Therefore, human agents are still the cornerstone of customer service, but their tasks and responsibilities are changing rapidly.
Determine AI’s limitations
Make sure you know what your AI is capable of doing and where its limitations lie. Try to minimize the limitations by providing additional information and training your AI thoroughly. And for tasks that are out of reach for AI, provide a handover to human representatives.
Provide a smooth handover experience
This involves the AI offering the option to connect the user to a human representative. It also provides the human agent with all the information exchanged during the chat. This will ensure that the representative knows about the user’s issue and all the details provided to avoid the customer repeating themselves.
Implement alerts based on keywords or behaviors
Specific keywords like “Talk to a human” or actions like clicking the “Book a demo” button can trigger a live chat conversation with a human representative. These alerts have a clear intent of speaking to an agent, so it’s best to connect the customer to the right person to ensure they’re satisfied with their experience.
Develop documentation about human oversight and intervention
Set clear expectations for your human agents by outlining their role in AI-assisted conversations. Create a document that states the level of oversight of AI conversations, when the representative should intervene, and how they should step in. These should be straightforward instructions for people to follow.
Training
For AI to deliver accurate outcomes, it must be trained on high-quality, representative data that reflects the diversity and complexity of real customer interactions. Poorly trained AI can lead to biased responses or failed automations that frustrate users and damage trust.
Equally important is training human agents to understand how AI tools function and how to intervene when needed. When agents are well-versed in using AI-powered systems, they can collaborate more effectively with the technology. This dual investment in chatbot training and human enablement ensures your business maintains a high standard of service and accountability.
Train employees on the system
When you decide on the platform you want to use, ensure your employees get a full onboarding to know how to use the system to its full potential. Dedicate a specific time for training and get everyone from the team on the same page.
Provide clear and relevant training data for the AI system
Your artificial intelligence system will be as good as you train it to be. These tools need data to perform well. So, if you provide your AI with a lot of details, it will work well for you. But if you only give it basic information, its functionality will be very limited. Make sure the system you use is easy to train and provides you with suggestions for further improvements.
Ensure the AI does not hallucinate
The AI should stick to the information you provide it with instead of pulling the answers to customer questions from somewhere on the internet. So, it’s important to ensure the system avoids inaccurate responses and routes users to a human agent when it can’t confidently answer.
At present, about 90% of conversations are handled by Lyro, and in the vast majority of cases the responses have been perfect. My biggest fear of AI hallucination seems to have been unfounded, as even intentionally attempting to get Lyro to provide false information has been unsuccessful.
Monitoring
Ongoing AI monitoring ensures both ethical performance and regulatory compliance. Unlike static systems, AI models can evolve in unpredictable ways over time, especially when exposed to new data or dynamic user interactions. Monitoring helps to detect issues early and allows the team to adjust algorithms or implement human overrides when necessary.
Regularly review and update AI’s training materials and knowledge base
If your AI has outdated information, it will provide inaccurate responses to customer questions. So, you should keep all of your documentation up to date. This includes your FAQs, knowledge base, your AI’s training material, and internal resources.
Determine KPIs
If you don’t have any goals to achieve, how can you know if you’re any closer to achieving them? The same goes for your AI customer service system. You need to determine the KPIs you’ll use to assess the AI’s performance and catch any needed improvements.
Track metrics and AI’s impact
When you know the metrics you want to track, you should set up a system that tracks the results. Some platforms, like Tidio, provide an analytics page where you can clearly see your AI’s performance throughout time. Make audits regular. You can do weekly checks for smaller improvements and monthly deep dives for bigger changes.
Headcount
There’s no denying that AI is seen as a means to limit CS team headcount. But its implementation should be done with the intention to maintain the team while changing the job description of current team members. Less so to trim the team.
Don’t replace humans with AI—make sure they work side by side
Assess the strengths of each of your agents and find the position that best matches their skillset. And if they’re willing to, train them and expand on that skillset to help them grow into the new position.
AI responsibilities as a business
As AI becomes integral to business operations, companies have a growing responsibility to implement robust AI governance frameworks that prioritize ethics, transparency, and data protection. By embedding these principles into your AI strategy, your company reduces the risk of compliance breaches and public backlash, as well as fostering a culture of trust with your customers.
AI governance
As AI takes on more responsibilities, it also gains the power to influence customer experiences and outcomes. Effective AI governance establishes clear accountability for how these systems are designed and monitored to deliver compliant AI-driven customer support.
Stay on top of the legal matters
Governments, as well as big brands like Google, are stepping up and creating regulations for AI. For example, Google’s Agent2Agent Protocol [4] and EU AI Act [5]. So, as an AI developer or user, you must stay compliant.
Create policies
Draft policies that you will follow when it comes to AI usage. These are the documents you will refer back to whenever anyone is unsure of a specific rule, so make these clear and complete.
Knowledge repository
Create a place where everyone using your AI system will input their experiences, challenges, and how they handled the issues. This is also where you’d put any guides and step-by-step instructions for the setup and usage of the AI.
Get board members informed
Make sure the board members know about AI and the newest technology. Provide training and get them on board with the system you’re implementing.
Schedule regular meetings with leadership
To align the team and the leadership, you should arrange regular check-ins. This will allow you to discuss any issues and further developments of the AI customer service tools.
Determine the people in charge
Assign specific team members to manage the AI’s knowledge base, monitor performance metrics, and review suggested content. While it should be a team effort, one person should serve as your point of contact for this information.
Perform internal audits
Undergo internal audits of your AI system. This is where you can check the compliance of your software, the usage, and the safety of your data. And if your platform needs an update, you’ll definitely catch it during the audit.
Ethics
Ethical AI requires clear policies on how algorithms are built and evaluated for fairness and bias. You should also delegate who is accountable for the outcomes and monitoring of the system.
Determine the business ethics and legal requirements for AI
Discuss with the leadership team how you should use AI in order fairly and ethically. This includes the protection of human rights, minimizing biases, as well as limiting the risks associated with AI. This is important, especially now that UNESCO is working on AI ethics governance[6] and the American Psychological Association is studying human vs AI bias [7].
Code of conduct for the use and development of AI
You probably have a code of conduct in your company. Now it’s time to draft the AI code of conduct. This should include defining AI principles, determining usage guidelines, providing training, and creating reporting systems.
Establish a data ethics committee
These are the people who will be on top of making responsible decisions when it comes to AI. They need to be able to stand up and say that something is not ethically right, even though it might be legal. So, choose your committee wisely and listen to their advice.
Data governance
Businesses must safeguard the data that powers AI customer service systems. This will ensure that information is collected lawfully, stored securely, and used in a manner that respects user privacy.
Document data origins
Do you know where each piece of data comes from? Knowing where your data comes from helps you track it more effectively and ensures it’s transferred securely across your systems. For example, Microsoft has now created a new tool designed for AI data governance[8], which adds to the importance of putting this practice in your workflows.
On top of that, you should use software that makes all of your integrations safe. For example, at Tidio, we make sure that integrating Tidio with your other platforms is secure [9] so you don’t have to worry about it later down the line.
Limit the input of personal data
Only use data that’s necessary for training the AI. Don’t input personal information into the AI; it doesn’t need it. This will help you keep people safe and prevent the AI from sharing their details with others.
Ensure safeguards on the data
At Tidio, we made sure that your data is safe by storing credentials as hashed values, encrypting data via HTTPS while it’s being transferred and at rest, as well as handling personal data according to the GDPR and CCPA laws.
We also implemented TLS protocol encryption for our servers which safeguards your team’s and your customers’ data. And if you want control, then you can restrict access to certain areas of the system with roles and permissions [11].
Key takeaways
As AI becomes more embedded in customer service operations, responsible usage is a must. To ensure your AI supports and enhances customer experience instead of undermining it, keep these principles in mind:
- Transparency builds trust
- Ethical AI is compliant AI
- Humans and AI should work side by side
- Strong governance ensures accountability
- Ongoing training and monitoring are critical
- Data ethics can’t be overlooked
Responsible AI customer service is not just about avoiding risk. It’s about creating better, more human-centered experiences. By embedding ethical principles into your AI strategy today, you build a foundation of trust, compliance, and sustainable innovation for tomorrow.
Use a secure and compliant AI customer service system
Resources
- Using AI in Customer Service and Telemarketing: Top-7 Legal Tips
- Drawing-up a General-Purpose AI Code of Practice
- Gartner Says 20% of Inbound Customer Service Contact Volume Will Come From Machine Customers by 2026
- Announcing the Agent2Agent Protocol (A2A)
- The EU Artificial Intelligence Act
- Global AI Ethics and Governance Observatory
- Addressing equity and ethics in artificial intelligence
- Introducing modern data governance for the era of AI
- SECURITY AT TIDIO
- Privacy Policy
- Tidio Trust Center
