“Do more with less” is more than just the mantra of the day—it’s a business necessity. For many customer service leaders, the answer to this challenge comes in the form of AI adoption.
The full power of AI-enabled customer service extends far beyond deploying chatbots; it’s fundamentally transforming how customer service operates as a whole. Thanks to AI handling routine tasks, CS teams are becoming more efficient and strategic, providing more personalized, seamless, and responsive customer support.
But this transformation is not an overnight, plug-and-play solution; companies are progressing along a spectrum of AI customer service maturity. At the most mature level of AI adoption, more than 95% of service interactions can be resolved through digital touchpoints (e.g., live chat, email, social media, self-service chatbots, etc.), enabling businesses to reduce handle times by 30% and improve customer satisfaction by 20%.
We’ll explore how AI can fill in the gaps left behind by traditional customer service offerings, delve into specific use cases for AI in customer service, and discuss how Bird helps companies reach a new level of maturity in the future of AI-enabled customer service.
Here’s what AI can do for CS efficiency
Here’s the thing: You only have one chance to get the customer experience right. According to PwC, 32% of all customers will stop doing business with a brand after just one bad experience. And customer expectations are rising: The same study found that nearly 80% of American consumers see speed, convenience, knowledgeable help, and friendly service as critical components of customer service. In addition, 73% of all customers say that customer experience significantly influences their purchasing decisions.
As customer expectations rise, so do the costs associated with meeting them, pushing more than 80% of organizations to increase their investments in AI for customer service, with 37% of leaders citing cost reduction as a top priority.
Yet, at the same time, customer service teams are grappling with resource constraints as customer inquiry volume steadily increases and agents struggle to keep pace. From McKinsey, 57% of customer care leaders expect call volumes to keep rising over the next two years, adding even more pressure on already overburdened teams. A surprising trend drives this surge in call volumes: live phone conversations remain a highly preferred medium for customer support inquiries among consumers of all ages — yes, even Gen Z. This trend underscores the evergreen significance of human, personalized interaction in customer service.
Faced with resource constraints and higher call volumes while trying to lower costs, the solution is clear: improve your customer satisfaction scores by rolling out AI-powered customer service.
AI can help improve overall agent handling times by 30%. One bank highlighted by McKinsey, reduced its cost-to-serve by more than 20% by deploying AI self-service channels.
One key way to do this is managing all your customer interactions from a single, unified platform that routes inquiries through AI first before directing them to the right people. By maximizing deflection rates—where AI resolves issues without needing to escalate them to a human—this approach reduces the strain on your human agents, allowing them to focus on more complex, value-adding tasks.
However, it’s important to understand that AI’s role in customer service goes beyond simply rolling out a chatbot. The real value of AI lies in its ability to augment human CS agents, providing them with the real-time data and customer insights necessary to deliver exceptional customer experiences. With the right implementation, AI can scale operations, improve efficiency, and ultimately drive higher levels of customer satisfaction through more personalized, enhanced interactions.
Putting AI-enabled customer service into practice
When a query does reach a human agent, AI can make that agent as efficient as possible. Here are some features and use cases for your customer service agents to leverage AI.
Knowledge base
A knowledge base is a centralized repository of information, such as FAQs, troubleshooting guides, and other essential resources that customer service teams rely on to answer customer inquiries. A well-curated knowledge base is the backbone of any effective AI-driven customer service strategy. By integrating AI with your knowledge base, you empower your agents with the most accurate and up-to-date information at their fingertips. They can quickly retrieve and double-check relevant information, consequently resolving queries faster.
Use Case: A customer contacts support with a question about a newly launched product feature. The agent is unfamiliar with the latest update, but the AI quickly accesses the knowledge base and pulls up detailed documentation on the feature, including FAQs, troubleshooting steps, and usage tips. The agent can then confidently guide the customer through the process without escalating the issue or putting the customer on hold.
Suggested replies
AI-driven suggested replies can significantly speed up customer interactions by providing agents with contextually appropriate responses based on past interactions. Suggested replies improve response times and ensure consistency in customer information and brand voice.
Use Case: A customer initiates a live chat to ask about the company’s return policy for a product purchased on sale. The AI analyzes the query and suggests a reply with a specific return policy for sale items, slightly different from the standard return policy. The agent can then quickly review and send the suggested reply.
AI assistant
An AI assistant can be a powerful partner for your customer service agents by providing real-time support during interactions. It can pull up relevant information or suggest replies, reducing the cognitive load on your agents and allowing for faster handle times.
Bird’s AI assistant equips CS teams with comprehensive analytics that allow you to track the number of conversations resolved autonomously by AI and those transferred to human agents. These insights help you continuously refine your AI customer service strategy and optimize human agent workloads.
Use Case: Imagine a customer service agent dealing with a billing issue involving multiple transactions over several months. The AI assistant monitors the conversation, suggesting the most relevant transactions and pulling up historical billing records. It even suggests responses based on past resolutions of similar issues. This allows the agent to resolve the query faster and with greater accuracy.
Chatbots
Chatbots are often the first digital touchpoint for customers and can handle a wide range of inquiries autonomously. Bird enhances this capability by implementing strict guardrails to prevent misinformation, giving you more precise control over the information your bots provide.
Use Case: A customer uses a chatbot to inquire about the status of an international shipment. The chatbot pulls real-time tracking data and provides an update if available. However, if the tracking information is unclear or delayed, the chatbot has instructions to escalate the query to a human agent before providing any speculative information so that the customer always receives the most accurate response.
Intention recognition
Understanding the customer’s intent is crucial for providing relevant, personalized support. Through sentiment analysis and intention recognition, AI analyzes customer inputs to determine the underlying need or request, allowing for a more targeted and effective response.
Use Case: A customer sends a vague message like, “I’m having trouble with my account,” which could mean several things. The AI identifies the most likely intentions—such as password reset, account lockout, or billing issues—based on past interactions and the customer’s account history. It then prompts the agent with the most relevant next steps, reducing back-and-forth and getting to the heart of the issue faster.
AI summaries
AI can automatically generate summaries of conversations, saving time for agents who would otherwise need to manually recap customer notes. AI summaries and transcripts can also help maintain continuity in customer interactions across different channels or agents.
Use Case: After a lengthy troubleshooting session over the phone, the AI generates a concise summary of the call, highlighting the key issues discussed, solutions attempted, and any follow-up actions needed. This summary is then added to the customer’s profile. If the customer calls or engages through another channel, the next agent can pick up right where the previous conversation left off without requiring the customer to repeat themselves.
Omnichannel AI-enabled support
Modern customer service teams stretch across multiple channels and platforms. It’s only fitting that AI support should be omnichannel, too.
Use Case: A customer initiates a conversation via Facebook about a technical issue. The AI bot responds initially, but the customer switches to email for further assistance as the conversation becomes more detailed. The AI seamlessly continues the conversation via email, with full context from the social media interaction, helping the customer experience a smooth and consistent journey across channels.
Integration with your systems, apps, and web
AI systems are most effective when integrated with your existing infrastructure, including CRM systems, apps, and web platforms. This connectivity enables AI to pull relevant data from multiple sources to comprehensively and accurately respond to customer inquiries.
Use Case: A customer begins a chat session on your website inquiring about the status of their recent order. The AI instantly connects with your order management system, retrieves the latest shipping status, and informs the customer without needing to involve a human agent.
Seamless escalation to human agents
Bird’s AI system categorizes and tags all messages handled by AI bots, making it easier for human agents to take over when necessary. When a conversation becomes too complex for AI, that action can smoothly transition to a human agent with full context.
Use Case: A customer starts a conversation with a chatbot about a billing dispute. The AI handles the initial queries, but as the issue becomes more complicated, the AI tags the conversation as requiring human intervention. When a human agent takes over, they have access to the entire chat history, categorized by the AI, allowing them to address the issue without needing the customer to repeat themselves.
Easy training capabilities
AI systems must evolve and learn to stay effective. Bird provides tools to fine-tune your AI bots over time so that they continue to deliver high-quality service. Bird’s unique mind map functionality allows you to see all AI's responses, where they originated in the knowledge base, and how they were used across conversations.
Use Case: Over time, you notice that customers frequently ask about a specific product feature that isn’t well covered in the knowledge base. Using Bird’s mind map functionality, you track how the AI has been handling these inquiries and identify gaps in the information provided. You then update the knowledge base with more detailed guidance to handle future AI-enabled interactions more effectively.
Voice bot
Despite the rise of digital channels like chat and email, a majority of customers still prefer the immediacy and personal touch of a phone call when dealing with complex issues or urgent inquiries. To be exact, 71% of Gen Z, 81% of Millenials, 86% of Gen X, and a staggering 94% of baby boomers are more likely to reach out to customer support via phone. This is where AI-powered voice bots can come into play to alleviate high call volume and help engage customers in complex conversations.
Bird’s voice bot integrates deeply with your existing knowledge base, allowing it to conduct natural, informed customer conversations. It can handle various inquiries autonomously, resolving many issues on the spot. But when a customer’s problem requires a more nuanced approach, the voice bot doesn’t just pass the call off—it provides a detailed transcript and summary of the conversation to the human agent, giving them all the context they need to resolve the issue efficiently.
Use Case: A customer calls in with a billing discrepancy that involves multiple accounts and transactions over several months. The voice bot starts the conversation by verifying the customer’s identity and gathering details about the issue. As the customer explains the problem, the bot pulls relevant data from the knowledge base and attempts to resolve the issue. When it becomes clear that the situation requires human intervention, the bot seamlessly transfers the call to an agent, providing them with a complete transcript of the conversation, including any troubleshooting steps already attempted. The agent can then pick up right where the bot left off, armed with all the information needed to resolve the issue quickly and to the customer’s satisfaction.
Good for your agents, great for your customers
With AI-powered tools like Bird’s Service Cloud, your customer service team can be “always on,” providing continuous support across all your channels, from chat and email to phone and social media. No matter where or when a customer reaches out, someone (or some bot) will be there to deliver consistent, quality support.
AI goes beyond efficiency; it brings personalization to every interaction. In a world where 71% of consumers expect tailored experiences and 76% are frustrated when they don’t get them, Bird’s intelligent automation taps into customer data to deliver responses that resonate, building stronger relationships and driving customer satisfaction.
What’s good for your customers is even better for your agents. By automating routine tasks and delivering real-time insights, Bird’s AI allows your team to focus on complex issues, working more efficiently and with greater satisfaction.
With Bird Service Cloud, you’re not just improving customer service—you’re making the customer experience smarter for your customers and agents. Contact us today to discover how.