As Voltaire once said, "With great power comes great responsibility." In today's world, this wisdom can be adapted to say, "With every great innovation comes even greater responsibility." Generative AI has the potential to revolutionize how we work, plan, and redefine what's possible. Yet, with this transformative power comes significant risks that we must proactively address.

Customer service is field rife with manual processes. However, customer calls are turning increasingly complex with a talent shortage, as covered by a McKinsey report. Hence it is ripe for AI-driven innovation with huge potential for impact. This article explores five critical risks associated with AI in customer support. It also offers practical strategies to mitigate them effectively.

Risk 1: The Empathy Gap

Can AI-powered chatbots replace human empathy in customer support?

How many times have you had a conversation that went something like this:

You: Hi, I received a damaged product and need to return it.

Chatbot: Thank you for your request. Do you want to track your order or cancel it?

You: No, I want to return it!

Chatbot: I'm sorry, I didn't catch that. Please choose from the following options: 1) Track my order, 2) Cancel my order, 3) Speak to a human agent.

A frustrated you: I want to speak to a human agent.

Chatbot: I'm here to help! Please describe your issue in detail.

Interactions like these make people preemptively frustrated and annoyed when they encounter a chatbot. This is a common example of a legacy chatbot and the keyword-based experience it provides. As AI becomes more sophisticated, one might wonder if it can truly replicate the human touch in customer interactions.

Historically, AI excelled at processing information and providing quick responses. However, it often falls short when responding to emotional situations that fall outside of its hard-coded pattern. The issue then becomes that if AI fails to provide sufficient empathy in sensitive or emotionally charged customer interactions, it could potentially lead to customer dissatisfaction, damaged relationships, and negative brand associations.

Mitigation strategies:

• Choose a Gen AI customer service chat that does not rely on keywords or patterns for its responses but rather mimics your best agents. Ema auto-generates ticket categories based on previous transcripts and mirrors the tone, style, and brand voice when responding to customers.
• Analyze past transcripts to identify questions or queries that require human involvement. In Ema, you can add specific topics that you would like Ema to pass on to a human agent.
• Train AI consistently to improve response quality and emotional response. Training Ema is easy and part of the onboarding process. You can rate and compare Ema's responses with your agents' responses and provide feedback that Ema can use to keep improving.

Risk 2: Data Security Vulnerabilities

What are the data security risks of AI customer service platforms?

To provide effective customer service, AI platforms need to handle a lot of customer data, including sensitive personal information. This makes data security one of the biggest concerns for companies using AI in customer support.

Explanations for questions like data safety, safeguard and compliance have become table stakes.

It's important to ensure that AI systems only collect data that's necessary and legal, store it securely, and keep customers informed about how their information is being used. Customers should also have control over their own data, with clear safeguards in place to ensure it’s only used for the right reasons.

Mitigation strategies:

• Implement robust encryption protocols for data in transit and at rest:
  • Ema's Security Measure: All data is encrypted in transit and on disk using strong 256-bit encryption, ensuring that sensitive information is secure during both transfer and storage.
• Regularly update and patch AI systems to address newly discovered vulnerabilities:
  • Ema's Security Measure: Ema employs secure development practices, conducts regular training, and integrates continuous monitoring and observability to ensure that all systems are up-to-date and any vulnerabilities are promptly addressed.
• Conduct frequent security audits and penetration testing for the platform:
  • Ema's Security Measure: Ema performs regular PEN, SaST, and DaST testing, alongside continuous monitoring and third-party risk management. These practices ensure that the system’s defenses are regularly evaluated and strengthened.
• Ensure compliance with data protection regulations like GDPR and CCPA:
  • Ema's Security Measure: Ema is compliant with leading standards such as GDPR, HIPAA, SOC2, ISO 27001, NIST AI RMF, NIST CSF, and more, ensuring comprehensive adherence to global data protection regulations.

Risk 3: Misinterpretation of Customer Queries

How often do AI customer service solutions misinterpret customer queries?

AI in customer service is far from a solution that can be ‘set and forgotten’. While AI, particularly with the advanced insights it can uncover, brings intelligence to customer service workflows, it doesn't make them error-proof. While NLP has made significant progress, AI still struggles with nuances, context, and ambiguity in human language.

Mitigation strategies:

• Continuously train AI models on diverse datasets to improve language understanding. Instead of having to train manually, Ema autonomously improves so that each interaction is better and is an extension of your brand.
• Implement context-aware AI that considers previous interactions and customer history. Ema consistently evaluates interactions, chats, and new information to minimize any misinterpretation that can happen.
• Integrate human oversight for complex or high-stakes interactions.

Risk 4: Over-reliance on AI

Are businesses becoming overly dependent on artificial intelligence for customer service?

Generative AI seems to be finding its way into every function of every industry. This inevitably leads to the question of what the role of AI is and whether businesses are leaning too heavily on artificial intelligence. As AI continues to evolve, there's a growing concern that companies might sideline the development of human skills in favor of automation. In the race to innovate, are we risking the loss of the personal touch that sets exceptional customer service apart?

Mitigation strategies:

• Understand the role that AI can play in your customer support. Whether it is helping agents, improving your internal knowledge base, or deflecting queries with a chatbot, have clear guidelines on what human agents are responsible for. Create clear escalation paths from AI to human agents for complex issues.
• With generative AI tools being able to handle so much of customer service, it frees up human agents to focus on relationship building and handling ad-hoc issues that come up.
• Foster a culture of continuous learning and adaptation in the customer service team. Train the team consistently to combat the fear of new tools and processes. Show how much time is saved and how much better the experience can be internally and externally.

Risk 5: Managing Customer Frustrations

How do you handle customer frustrations with the limitations of AI chatbots?

What happens when AI chatbots miss the mark? When AI chatbots fall short, customer frustration can quickly escalate. If a chatbot struggles to understand or resolve an issue, experiences a hallucination, and there's no clear path to human assistance, the experience can turn negative very quickly. Frequency occurrences of this can lead to loss of business and customer loyalty.

Mitigation strategies:

• Be mindful to select GenAI tools for customer support that focus on minimizing hallucinations. Ema tackles this with the patented EmaFusion™ Model technology. It is a fusion of experts model that ensures the most accurate results while minimizing any possible hallucinations.
• Implement easy-to-use escape hatches for customers to reach human agents. When setting up Ema's AI Employee for customer service on Ema’s Agentic AI platform, you can select exactly when Ema should pass the ticket to a human agent.
• Ensure no context is lost when a ticket is transferred from chatbot to a human agent. Ema ensures the agent has full context of the chat and therefore doesn't have to start from scratch (which usually leads to more frustration).

Benefits of AI in Customer Support

While it's crucial to be aware and consistently address these risks, it's equally as important to remember the significant benefits AI brings to customer support:

• 24/7 availability, ensuring customers can get help anytime
• Consistent responses, reducing variability in customer service quality
• Rapid resolution of queries, freeing up human agents for relationship-building
• Scalability to handle large volumes of customer interactions simultaneously

By implementing generative AI tools thoughtfully and addressing these risks proactively, organizations can utilize the power of AI to transform their customer support operations. The key lies in striking the right balance between AI efficiency and human touch, ensuring that technology enhances rather than replaces the human elements of customer service.

Ema has been designed to boost productivity tenfold across customer support and deliver value in days. Leading enterprises like Envoy, Truelayer and Moneyview are using Ema’s customer support solution to supercharge their customer support operations.

Ema is compliant with SOC 2, ISO 27001, HIPAA, NIST and GDPR. Thus making Ema the most performance and trusted Agentic AI platform to revolutionize your customer support.

Ready to elevate your customer service? Hire Ema today.