AI Customer Service done right: automation to empower humans

Executive summary: what you will learn

This whitepaper explores why AI Customer Service has become essential and how businesses can adopt it ethically and effectively.

Customer service is undergoing one of the most significant transformations in decades, driven by rapid advancements in generative AI. As customer expectations continue to rise (demanding speed, precision, and 24/7 availability) traditional support structures can no longer keep pace. Generative AI is now positioned as a core capability for future-ready organizations, not a nice-to-have technology.

Data shows that poor customer experiences come at a steep cost: more than half of consumers reduce or stop spending with a brand after just one negative interaction. Meanwhile, 98% of customers report frustration with traditional IVR systems. Businesses that ignore AI risk falling behind competitors that are already leveraging it to deliver faster, smarter, and more consistent service.

AI’s role is not to replace human agents, but to elevate them. By automating high-volume, repetitive inquiries such as order tracking, appointment scheduling, and account questions, AI frees human teams to focus on high-value conversations that require empathy, critical thinking, or complex problem-solving. This hybrid “AI-assisted” model enhances both customer satisfaction and agent well-being.

The whitepaper outlines the eight key ways AI is reshaping the service landscape, from proactive support and hyper-personalization to multilingual capabilities and omnichannel continuity. It also answers a central question: Will AI replace humans in customer service? The conclusion is clear: AI empowers, not replaces. Organizations that combine human expertise with AI automation will outperform those that rely solely on either.

Introduction

Let’s face it – AI for contact center is here to stay and to improve day by day. It’s bound to be included in any business and even personal processes, with customer service at the forefront of this change.

Being scared or trying to run away won’t help your customer service performances. The best course of action is to understand how AI works and how to ethically implement it.

The reasons for this are many, starting from the fact that while customers are increasingly asking for round-the-clock presence, most businesses don’t have the capacity to have live customer service agents working 24/7. That would be costly – to say the least – and would take an unimaginable toll on agents’ lives.

When we turn to data, we see how Gartner predicts gen AI to be used by 50% of the workforce of Fortune 100 companies by the end 2025. A McKinsey report had 40% of respondents say they plan to invest in gen AI due to its fast progression in features.

Looking at customers, 98% of them find traditional IVRs frustrating and 66% try to bypass them completely.

Data clearly shows refusing AI customer service will undeniably leave your company behind while competitors flourish. But looking at the other side of the coin – adopting it and leaving it to handle all sides of customer service can do the exact same thing.

It’s the perfect mix of human and virtual that will keep your business up to speed and performing well, and in this whitepaper you’ll discover exactly what you need to do to achieve it.

We’ll start with how AI call center software is changing customer service, answering the pressing question of will it replace humans?, and wrap up with real world use cases.

AI Customer Service Business Trends

Gone are the days of calling during business hours and waiting thirty minutes on the phone only to be transferred to four wrong operators before getting an answer. Or worse – never getting to an operator because of long queues.

Customer today want speed and precision and not as a nice-have. A global study by Qualtrics XM Institute found that after a negative interaction, consumers reduce or stop spending with the brand more than half the time (51%). In certain sectors (parcel delivery, fast food) the figure rises to 60%+.

Having a gold tier product can’t save you from bad customer service. Today, customers would rather turn to a mediocre product with 24/7 self-service customer service available to them.

AI Customer Service is playing a big role in this redefinition of priorities. While customer expectations rise, agents can’t give them what they want if they’re forced to answer repetitive questions and tend to hundreds of calls a day. The concentration and empathy of human agents should be spared for what really matters.

In a nutshell, if AI for contact center can answer those tedious questions about opening times and shipping statuses for them, then maybe they can focus on retaining the customer that lost their package altogether and is threatening a lawsuit.

But what can AI Customer Service concretely do for you with the level it’s at right now?

Here are the key ways AI is reshaping the landscape:

1. From reactive to proactive

AI call center software can identify patterns and predict issues before they arise. For example, it can alert customers about potential service disruptions, anticipate billing questions, or guide them through product onboarding without waiting for a support ticket.

2. Next-level multitasking

AI assistants can handle thousands of conversations simultaneously, providing consistent, accurate information around the clock. This reduces wait times dramatically while freeing human agents to focus on complex, relationship-driven interactions.

3. Granular personalization

AI can analyze purchase history, previous conversations, sentiment, and preferences to tailor its responses. Customers feel understood without requiring agents to manually sift through data.

4. Support agents while they support customers

AI does not just serve customers; it also serves agents. Intelligent tools can summarize tickets, suggest responses, surface relevant knowledge-base content, and automate after-call work, significantly reducing cognitive load and burnout.

5. Abolish business hours and wait times

AI Customer Service can run 24/7/365, answering questions and resolving simple requests even when human teams are offline. This means no “we’re currently closed” dead ends, and far fewer queues piling up overnight or over the weekend. Customers get instant support whenever they need it, and agents return to a cleaner, more manageable backlog.

6. Break language barriers

AI for contact center usually supports multilingual models can automatically detect a customer’s language and respond accordingly. This allows businesses to offer consistent, high-quality support across regions without hiring full teams of native speakers for every market. Customers can explain problems in their own words and still receive accurate, relevant help.

7. Turn every interaction into insight

Every chat, email, or call handled by AI Customer Service becomes structured data. AI can automatically tag issues, detect emerging problems, measure sentiment, and highlight friction points in real time. Instead of guessing what customers struggle with, businesses get a continuous feedback loop that informs product, UX, pricing, and even marketing decisions.

8. Create truly omnichannel experiences

AI can unify customer data and context across channels: chat, email, voice, social, and in-app. A conversation started on a website chatbot can be picked up by a human agent on the phone without customers repeating themselves. This continuity is one of the biggest differentiators of mature AI Customer Service: the channel changes, but the experience feels seamless and coherent.

Related content

• Microsoft Teams Contact Center: 5 Reasons Why It Needs AI
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• AI Virtual Receptionist: the cost of not investing in it

Will AI replace humans in customer service?

Did machines replace humans during the industrial revolutions?

The short answer: No. AI won’t replace humans, but humans who use AI will replace those who don’t.

AI agents excel at handling repetitive, transactional, and high-volume tasks. It’s ideal for resetting passwords, checking order statuses, processing refunds, and answering common questions. But when it comes to complex problem-solving, high-stakes situations, emotional conversations, or relationship-oriented support, human agents remain essential.

What AI will do is reshape roles:

• Agents will spend less time on rote tasks and more time on strategic or high-value interactions.
• Support teams will evolve toward hybrid “AI-assisted” work models.
• Soft skills (empathy, negotiation, critical thinking) will become even more important.

Rather than replacing humans, AI elevates them, giving agents the tools they need to work faster, smarter, and more meaningfully.

This circles back to what we said in the beginning of this document. Running away from AI isn’t the answer. The answer is ethically implement it and make it a ‘new colleague’.

Use cases from the world

According to data sourced from our Salesforce platform, in 2025, 52% of potential Imagicle customers expressed interest in adopting AI for their customer service. Here are some of the success stories that followed:

In retail

A large apparel retailer struggled every year with a massive spike in customer inquiries during the holiday season. Questions about order status, returns, and size availability overwhelmed the support team, leading to long wait times and a sharp dip in CSAT. Hiring seasonal agents helped only marginally and created onboarding and training overhead.

To break this cycle, the retailer implemented an AI omnichannel assistant by Imagicle across web chat, social messaging, and voice. The AI instantly handled high-volume, low-complexity requests, provided real-time order tracking, generated return labels, and recommended alternatives for out-of-stock items. Human agents focused on complex or sensitive cases. Support ticket volume dropped significantly, holiday queues disappeared, and CSAT reached record levels. AI agents turned a recurring operational crisis into a scalable, predictable experience.

In Healthcare 

A regional healthcare provider was facing growing pressure on its contact center as patients demanded faster access to appointments, referral updates, and prescription renewals. Front-desk staff were overwhelmed, which translated into long phone queues and inconsistent experiences from one clinic to another.

The provider turned to Imagicle to deploy an AI-driven patient access assistant embedded in its website and patient portal. The AI scheduled appointments, checked insurance eligibility, routed patients to the right care setting, and processed routine prescription renewal requests, all within strict privacy and compliance requirements. Call volume dropped, staff recovered time to focus on in-person patients, and patients reported shorter wait times and clearer guidance. In this scenario, AI agents freed clinical and administrative teams to do what only humans can: deliver empathetic, high-quality care.

In Financial Services 

A fast-growing credit union wanted to offer highly personalized service while keeping operational costs under control. Members frequently reached out with questions about loan eligibility, card disputes, fraud alerts, and account issues. Human agents were knowledgeable but overwhelmed, and the organization struggled to maintain its “high-touch” brand promise as membership grew.

To support both growth and member experience, the credit union introduced an AI-assisted banking concierge by Imagicle. The AI authenticated members, answered everyday questions in natural language, guided users through tasks like applying for a loan or disputing a charge, and surfaced personalized insights based on spending patterns. Routine interactions were resolved instantly; complex financial conversations were seamlessly escalated to specialists with full context passed along. AI Customer Service allowed the credit union to scale personal, relationship-driven service instead of diluting it.

How to Implement AI in Customer Service

Just like any other pivotal and big change, implementing AI for contact center needs structure, strategy, and commitment. ‘Buying an AI agent’ isn’t nearly enough.

1. Define objectives and constraints

Ask yourself: What exactly do I want to improve about my service? Maybe it’s handle times, wait times, support hours, deflection… Only you know. Don’t start with ‘a bit of everything’, clarify your goals and, most importantly, your non-negotiables. What do compliance regulations require of your company? Do you want your tone of voice to fit a certain standard? Which calls should always go to humans?

2. Identify use cases worth automating first

Data-driven decisions are going to be your best companions. Leave your gut aside and analyze your contact center data on a span of time of 3-6 months. Group by channel (calls, chats, emails) and intent, such as FAQs (hours, shipping, basic troubleshooting), account questions, status checks, etc. The ones high the volume and low in complexity are your starting point – you can then work your way up as you tweak the AI to your needs.

3. Prepare your knowledge and workflows

In and of itself, AI doesn’t know anything but what you teach it. Clean and centralize the content AI will rely on: FAQs, policies, product sheets, help articles. Make sure your AI colleagues always have access to the newest information, and make sure there’s only one reliable source for each piece. Avoid having multiple KB pieces for common inquiries such as refunds, returns, appointment booking, or password resets. The clearer the rules, the more efficient deflection will be. Last but not least, decide which actions the AI can perform autonomously (e.g., track order, reschedule appointment) vs. where it only suggests steps.

4. Design the human–AI handoff

Your agents should be involved in the AI implementation project from day 1. See how they feel about escalation rules, what they feel safe delegating to the AI, and where they feel the need to always be involved. Some examples can be: “escalate if sentiment is negative,” “escalate for billing disputes,” “escalate if more than 2 failed attempts”. Remember that the people on the field will always have clearer insights than C-level on how to handle customers. Secondly, ensure you set up the AI to give agents full context when they receive an escalation. This includes conversation history, AI summary, customer details, and attempted resolutions.

5. Pick your channels

Whether you’re currently running a voice-only call center or a full contact center, be mindful of the channels you want to pilot the AI on. Don’t implement everywhere, pick 1–2 channels and 3–5 intents to automate first. Launch in a controlled way (limited geography, customer segment, or time window if needed) and decide the KPIs that matter to you. Is it CSAT? Response time? Escalation rate? 

6. Iterate based on real data

Now your AI is up and running – and you need to know how it’s performing, how your customers are feeling, and how your agents are collaborating with it. In other words, it’s time to review transcripts where AI failed or escalated prematurely; adjust prompts, knowledge, and workflows.

Make sure you’re aligned and content with your pilot projects before expanding to new intents. At any stage of your AI implementation, you should always regularly audit for bias, hallucinations, and compliance issues; and update policies accordingly.

7. Scale across channels and regions

Once everything is smooth and how you like it, it’s time to go bigger. You can extend channels with the same backbone, even go multi-lingual (with native reviewers to validate the AI’s tone and accuracy), and cover more use cases. What’s important is to keep one central governance model (owners, review cadence, approval process) to avoid fragmented experiences and keep customer and employee experience high.

Want to dip your toes in AI for your customer service?

Here at Imagicle, we’re here to help you. Let’s start with a conversation – you’ll tell us how you’d like to improve your customer service and we’ll propose a tailored AI solution for you. You’ll even get to try it for 30 days, free of charge and commitment.

Contact us whenever it suits you best.

Conclusions

AI is no longer an optional enhancement for your customer service: it is a foundational capability for organizations that want to stay competitive in a world of rising expectations and constant availability. But the companies that will thrive aren’t the ones that seek to replace human agents; they’re the ones that empower them.

By intentionally blending human empathy with AI-driven efficiency, businesses unlock faster resolution times, richer insights, and a more resilient support structure. As the examples across retail, healthcare, and financial services show, AI transforms customer service when it is implemented ethically, transparently, and with a clear sense of purpose.

The path forward is not about choosing between humans or AI: it’s about orchestrating both to deliver experiences that are smarter, more personal, and more human than ever before.

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About Imagicle

Imagicle develops a complete unified portal for AI, UC, digital and collaboration services, designed to enhance team and customer experiences. Its solutions make on-prem, hosted, or cloud calling platforms better places through enhanced security, flexibility, and simplicity. Founded in 2010 and part of the Zucchetti Group, Imagicle has grown into a global presence with over 130 professionals across seven offices in Italy, France, the United States, and the Middle East, working everyday to make customers happy.

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Any question?

1. What is AI customer service and how does it differ from traditional support?

AI customer service uses artificial intelligence – such as chatbots, virtual assistants, and automated workflows – to handle customer interactions. Unlike traditional support, which relies solely on human agents, AI can respond instantly, automate repetitive tasks, and operate 24/7.

2. What are the key business trends driving AI adoption in customer service today?

Companies are adopting AI due to rising customer expectations for instant responses, the need to reduce operational costs, workforce shortages, and the increasing availability of reliable conversational AI technologies. AI also enables omnichannel experiences that customers now expect across chat, voice, and digital channels.

3. Will AI replace human agents in customer service?

No, AI enhances human work rather than replacing it. AI handles repetitive and low-value tasks, allowing human agents to focus on complex, emotional, or specialized cases. The most effective customer service strategies use a hybrid model combining AI efficiency with human empathy.

4. What are the main use cases where AI can make a meaningful impact?

AI excels at automating FAQs, triaging requests, routing tickets, assisting agents during live interactions, analyzing sentiment, and providing self-service options to customers. It can also generate summaries, fill forms automatically, and support voice interactions with conversational IVRs.

5. How should organizations begin implementing AI for customer service?

Implementing AI in customer service requires a structured, data-driven, and iterative approach: define clear goals and constraints, identify high-volume low-complexity use cases, prepare unified knowledge and workflows, design an effective human-AI handoff, pilot on a limited set of channels and intents, refine based on real data, and then scale responsibly across regions and channels with strong governance.

6. Which channels should I start with when deploying AI in customer service?

Most organizations begin with chat because it’s easy to implement and delivers quick ROI. Once stable, AI can expand to voice channels, email automation, and backend support processes. A phased, omni-channel strategy ensures consistent customer experiences.

7. How do you ensure a smooth handover between AI and human agents?

Effective handover requires clear triggers (such as customer frustration, complex requests, or regulatory queries)and seamless transfer of conversation history to agents. This ensures that customers never have to repeat themselves and that agents can continue with full context.

8. What role does knowledge management play in AI-powered customer service?

Knowledge management is the “brain” of the AI. High-quality, well-structured content ensures accurate responses and reduces hallucinations. Without an updated knowledge base, even the best AI models will deliver inconsistent results.

9. How can AI help with multilingual support?

AI can translate and generate messages in multiple languages in real time, helping support teams communicate consistently with customers around the world. It enhances accessibility, speeds up response times, and ensures linguistic accuracy, while human agents can still review or step in for nuanced or sensitive interactions.

10. What metrics and KPIs should companies monitor?

Key metrics include resolution rate, first-response time, customer satisfaction (CSAT), containment rate, agent productivity, and cost per interaction – but they vary for every business need and use case.

11. What ethical or governance considerations should be addressed?

Organizations must ensure transparency, data privacy compliance, and responsible use of customer information. Governance frameworks should define what AI is allowed to answer, when it must escalate, and how quality is continuously checked.

12. How can companies scale AI customer service beyond the pilot phase?

Scaling requires strong integration with existing tools, continuous improvement of the knowledge base, systematic measurement of performance, and training employees to collaborate effectively with AI. Once early wins are validated, companies can expand workflows, channels, and automation depth.