
The Role of AI in Customer Experience
AI Call Agents at your service
Remember when chatbots first appeared? They were clunky, frustrating, and often left customers more irritated than assisted. Fast forward to today, and AI chatbots have seamlessly integrated into our online shopping experience, becoming so integrated that we barely notice them. They’ve evolved from rudimentary decision trees to sophisticated conversation partners capable of handling complex customer questions. Now, we’re witnessing an even bigger revolution in voice-based customer support.
After years of promising developments in natural language processing and speech recognition, AI calling agents have finally reached a level that makes them practically indistinguishable from human agents.
While traditional call centers struggle with long wait times and inconsistent service quality, AI calling agents provide a solution that transforms how online retailers interact with their customers.
Unlike their early chatbot predecessors, these AI agents can understand context, process natural speech patterns, and even detect emotional undertones in customer voices, making them capable of handling truly complex customer interactions.
Benefits of AI-Powered Automation
- Personalization
- Increased efficiency
- Enhanced support availability
AI’s Effect: Transofming Customer Experience with Automation (CXA)
At its core, CXA uses artificial intelligence to automate customer touchpoints & streamline processes while maintaining—and more importantly, improving—the quality of service. For e-commerce businesses, this means being able to handle customer inquiries 24/7 without the limitations of human staffing.
Online marketplaces can now deploy AI agents and drop customer support call wait times to zero, with customers receiving immediate responses to their calls.
Always on Call
Unlike human agents who need breaks, sick days, and holidays, AI calling agents operate around the clock. This 24/7 availability means customers from different time zones can get support or faster resolutions whenever they need it. The consistency in service quality also eliminates the variability that comes with the human mood swings or fatigue – it’s like having the best day, every day.
No Call Left Behind
During peak shopping seasons like Black Friday or Christmas, e-commerce businesses traditionally struggle with support volume. AI calling agents can handle multiple conversations simultaneously, automatically scaling up or down based on demand.
Savings at Your Service
According to Deloitte, companies outsourcing customer service to countries with lower labor costs can achieve savings ranging from 40% to 60%. The issue is, however, the quality of the service.
Implementing AI calling agents can help bridge this gap by maintaining cost efficiency while ensuring consistent, high-quality interactions and real-time data integration. Furthermore, AI technology at scale can even be cheaper than the workforce in these low-cost labor markets.
Impact on Customer Satisfaction
Contrary to initial concerns about customer resistance to AI, data shows that customers often prefer AI interactions for certain types of support.
According to Zendesk, nearly 8 in 10 consumers say AI bots are helpful for simple issues. Customers appreciate the immediate responses and no waiting times.

Source: Zendesk Benchmark Data
The reliability and precision of information offered establish trust, as AI agents consistently provide high-quality responses to similar queries. Language barriers also become obsolete, as AI systems effortlessly transition between various languages to cater to a global customer base.
Perhaps most importantly, customers feel comfortable asking simple or repetitive questions, knowing they won’t face judgment or impatience from an AI agent.
Practical Applications of AI in CRM
- Generative AI in service interactions
- Smart ticket routing
- Real-time agent assistance
The Human-AI Collaboration
An important aspect of AI calling systems is their ability to seamlessly hand off complex cases to human agents. The AI doesn’t just transfer the call; it provides the human agent with a conversation summary and relevant customer history.
This hybrid approach offers a unique combination of advantages and disadvantages. While AI systems efficiently manage the high volume of routine inquiries that would typically overwhelm human agents, customer service representatives can dedicate their time to solving more complex challenges.
This benefits customers on both ends of the spectrum: those with straightforward questions receive instant assistance without waiting in a queue, while clients facing complicated issues get the focused human attention they need, backed by AI-gathered context and insights.
🧐Let’s imagine a real-life scenario:
A customer calls about a delayed order at 3 AM. The AI call agent doesn’t just provide a generic response; it:
- Accesses real-time order tracking
- Explains the delay’s specific reason
- Offers personalized compensation options
- Communicates in the customer’s preferred language
What benefits do these modern AI call agents offer to us, e-commerce owners? Better sleep scores and mornings where we check dashboard metrics instead of missed calls and angry emails, and the ability to turn daily firefighting into strategic oversight.

Source: Deloitte Global Outsourcing Sourvey 2022 (% respondents)
Elevating Customer Satisfaction through AI
- Streamlining workflows
- Proactive problem resolution
The Call of the Future
Today’s AI systems are not only automating tasks and streamlining processes, but they are also developing emotional intelligence. This allows them to recognize and respond appropriately to customer sentiment, adjusting their tone and approach based on subtle conversational cues.
By analyzing customer behavior and previous interactions, these systems can now predict potential issues before they arise. They can even proactively reach out to customers with solutions. Each customer interaction is personalized, considering individual preferences, past experiences, and communication patterns.
AI agents are progressing beyond reactive support to proactive problem resolution. They can identify and address potential issues before customers even need to make a call. Imagine your call agent advising clients on the best delivery schedule or real-time checking their order status during a call. This approach not only prevents problems but also builds customer trust and loyalty.
Challenges of Implementing AI
- Data privacy and security concerns
- Integration with existing systems
- Change management and training
When implementing an AI solution of your choice into your company, especially if it’s more corporate than a startup, several challenges tend to arise.
A very common one is data security. Knowing where you are sending your data and how it’s being processed is important for getting the go-ahead when implementing it into a corporation or a more bureaucratic environment. A simple way to get these answers is to request compliance documents from your AI service provider. If they can’t provide them, avoid working with that provider.
Do keep in mind that the ones you should be looking for vary based on your use case.
For example, when handling medical data, look for HIPAA compliance. AI vendors commonly use various providers, or sub-processors, so the compliance documents may contain the names of these entities as well, while their compliance and security standards are applied throughout the whole workflow and usage of the AI service or product.
A properly integrated AI workflow makes a night-and-day difference, and some AI vendors may not deliver the seamless experience and efficiency boost you expect—in fact, a sloppy and barely functioning AI integration usually causes more hassle than it solves.
Every vendor and AI tool will promise full integration; however, the reality is often quite different.
Generic solutions require extensive customization, lack user-friendly support, and can even misinterpret data and disrupt your workflows. Make sure to conduct thorough research and consider more than just attractive promises. The more generic the solution is, the cheaper it is, so if your goal is to find the lowest-priced vendor, you may be unpleasantly surprised by their utter lack of value in the long run.
Best Practices for AI Implementation
- Setting clear objectives
- Continuous monitoring and evaluation
- Engaging stakeholders
How to Get Started with AI Calling Agents
The journey begins with an analysis of your current support operations. This means diving into your existing call patterns and observing parameters such as peak hours, common customer inquiries, and pain points in your current processMany businesses find it beneficial to initiate a pilot program, which enables them to experiment with a simplified version before transitioning to a more complex solution.n.
The next phase involves training your AI system with company-specific knowledge. This isn’t about feeding information into a database – it’s about teaching the AI to understand your brand voice, product details, and unique customer interaction patterns. AI systems can be configured to access your existing data sources and CMS, ensuring they have the most up-to-date information at their disposal.
Integration with your existing systems ensures that the AI calling system works seamlessly with your current CRM, order management,nt and customer service platforms. This integration typically takes a few days, with technical teams handling the setup process and configuring appropriate call flows.
Establishing clear escalation protocols means implementing triggers for when to transfer calls to human agents, which allows complex issues to receive appropriate attention. These protocols are refined over time based on performance data and customer feedback.
The beauty of this approach lies in its flexibility. Starting with a streamlined version allows businesses to familiarize themselves with the technology while maintaining the option to quickly switch to more sophisticated solutions as their needs evolve.

Source: McKinsey & Company
The Future of AI in Customer Experience
Emerging trends and predictions
AI is Reinventing Customer Support
We all recall the times when reaching out to customer support meant your day is about to get ruined. Long waiting times and limited availability were the defining characteristics of the industry.
A McKinsey Global Institute report’s numbers have revealed a compelling story in 2017. Companies reported they had lost nearly $62 billion annually due to poor customer service.
More critically, 68% of customers now expect personalized interactions that feel human, immediate, and relevant. Traditional support models are fundamentally flawed. Limited hours, language barriers, and inconsistent service are simply becoming unacceptable.
According to a more recent McKinsey survey from March 2024: “The availability of powerful generative AI (gen AI) tools, especially large language models (LLMs) that can parse and respond to unstructured text or speech, has opened new possibilities for technology in customer care.
More than 80 percent of respondents are already investing in gen AI or expect to do so in the coming months, with leaders highlighting a wide range of potential applications.”
Conclusion: Customer Interactions are Changing Forever
We’re witnessing a major shift in business communication due to the advancement of AI-powered systems. AI call agents are breaking down barriers of time, language, and complexity, creating a more connected, responsive, and satisfying shopping experience.
It means by far more than a technological upgrade—they represent a fundamental reimagining of customer engagement. By combining advanced technologies with human-centric design, these systems create more efficient and satisfying customer experiences.
Those who fail to innovate risk losing their competitive edge and missing out on opportunities. With a team of experts on board, the setup process becomes a smooth journey.

Source: Depositphotos