Artificial intelligence could revolutionize the customer experience (CX) — but only if humans remain involved. The synergistic potential of this collaboration could enhance customer satisfaction at rates never before seen. How should business leaders go about implementation?
How Human and AI Collaboration Enable Synergistic CX
AI has quickly become a leading CX technology. According to a McKinsey & Company report, approximately 72% of businesses are utilizing it in at least one business function as of 2024. Information technology, sales and marketing support are among the leading use cases.
AI and humans are synergistic — they compensate for each others’ gaps. A model can recall past conversations, hyper-personalize responses and hold hundreds of conversations simultaneously. Consumers don’t have to wait until business hours or spend time on hold.
On the other hand, humans can recognize context, think critically and respond in an emotionally intelligent way. What they lack in speed, recall and accuracy, AI makes up for with data-driven insights and lifelike interactions.
Ultimately, their collaboration improves CX. Considering 94% of consumers are more likely to continue buying from a brand after a positive customer experience, this synergy translates to real-world business benefits.
Potential Applications for AI in CX
A chatbot is one of the most clear-cut CX applications for AI. It can handle routine inquiries like frequently asked questions, appointment scheduling or password reset requests. This speed and convenience may be why about 67% of consumers prefer chatbots.
Human agents can use chatbots internally for invoice generation, record retrieval or request summarization. This way, they can spend more time on value-adding tasks or building customer relationships.
Another potential internal application for AI in CX is pattern recognition. A model can alert decision-makers to an unusually high complaint volume, enabling customer support agents to better prepare for conversations.
With AI-powered predictive analytics, staff can anticipate consumers’ needs and preferences. They can use this knowledge to tweak their scripts, making interaction seem more seamless and personal.
AI-driven semantic analysis — leveraging natural language processing to extract emotions from text — facilitates an in-depth understanding of customers on an individual level. A model that recognizes a person’s mood can better meet their needs.
Best Practices for Merging AI Insights and Human Expertise
According to the Chamber of Commerce, businesses using AI are more likely to experience performance improvements and increase profit. However, integration doesn’t guarantee success. Firms must follow best practices.
1. Train AI on Business-Specific CX
Generic training datasets will generate nonspecific insights and vague responses, creating unnecessary friction. Decision-makers should train their model on business-specific information and real-world customer interactions to make coordination seamless.
2. Have Multiple Humans in the Loop
Striking a balance between AI and humans is crucial — overreliance on technology may result in longer hold times and higher frustration rates as customers queue for advanced help. Having multiple agents in the loop reduces response times, driving customer satisfaction.
3. Build Trust by Fostering Transparency
Although 23% of people are unsure whether they could differentiate human and AI-generated text, companies shouldn’t leverage AI without informing them. Telling users their data will be processed by an algorithm to improve CX can build trust and foster loyalty.
Decision-makers should consider allowing consumers to opt-in to training data collection. This option shows them the brand values their privacy and security. Considering how trendy AI is, it may even act as a selling point.
4. Integrate AI Into CX Incrementally
Getting used to running decisions by an algorithm or writing practical prompts takes time. Businesses should incrementally implement their collaborative programs to ease staff into the change. This way, they can identify process improvements and resolve issues early on.
Capitalizing on the Synergy of AI and Humans
Business leaders must carefully proceed with integration to ensure their team is receptive to the AI tools. Agent buy-in is crucial to the long-term success of their program. While the upfront investment may be high, they will see long-term cost savings.
