Reinvent the way your business shows up for customers

For many companies, transforming the customer experience is AI's biggest promise.

Efficiency might justify the investment, but the most ambitious support teams don't just deploy AI to drive efficiency or automate Tier 1 volume. They use it to create improved and entirely new customer experiences; ones that are faster and smarter, that remove friction, anticipate needs, and deliver value in every conversation.

These teams aren't layering AI on top of the old model. They're designing around it, building new models with AI at the core.

This section outlines how to make that transition from reactive service to AI-powered experience design. It's built around five principles that help teams scale trust, consistency, and delight across the customer journey.

First, reimagine the customer experience from first principles

What do customers actually want?

• Fast, accurate, and comprehensive resolutions to their problems.
• A feeling of being heard, respected, and understood, i.e., it feels personal.
• Minimal effort, repetition, or friction.

Those needs haven't changed. What has changed is your ability to meet them – more consistently, more intelligently, and at greater scale.

In the traditional support model, if you had no constraints (infinite time, people, and budget), you might have delivered on those principles by:

• Staffing a global team of highly trained agents to cover every time zone.
• Equipping them with full customer context, real-time data, and flexible systems.
• Investing deeply in onboarding, coaching, and quality assurance.

But you didn't have infinite resources, so you made trade-offs. You might have buried the "Contact Us" button behind help articles, deflected when you could, and triaged the rest. You relied on queues, rules, and SLAs to manage complexity and control cost.

But those constraints are no longer fixed.

Modern AI Agents don't just answer questions immediately. They understand context. They complete tasks. They get better over time. And when you design your systems with that in mind, something powerful happens: support stops being reactive.

So you can stop working around limitations, and start designing around what customers actually want.

How you design your customer experience shifts:

• From reactive to real-time With AI, help is instant. Customers don't wait. They get fast, relevant, context-aware answers and resolutions.

• From high-effort to zero-friction AI makes it possible to eliminate entire categories of customer effort, like dead ends or looping menus, repeating information, or unnecessary steps between question and outcome.

• From queues to journeys The most advanced teams are using AI to guide customers through the journey, nudging them forward, preventing issues before they happen, and delivering help before it's asked for.

• From table stakes to competitive edge With AI, your customers get help faster and with less friction. These great experiences don't just get customers to stay, they encourage them to advocate. Great support becomes a reason to choose you, and stay with you.

Five principles for AI-powered experience design

Each of these principles is engineered to deliver on the first principles of great support: fast, accurate resolutions, empathy, and effortlessness.

1. Treat customer experience like a product

Treating support as a product means designing, building, and managing your support experience with the same rigor and accountability you would apply to your core product.

It's a shift in mindset from seeing support as a reactive function or operational cost to treating it as a customer-facing experience that shapes perception of your brand, drives loyalty, contributes to growth, and accelerates the value customers get from your product.

Just like product teams:

• You define goals (faster onboarding, higher CSAT, lower churn).

• You map flows (AI starts the conversation, human handovers, proactive nudges).

• You instrument the journey (track handoffs, drop-offs, success states).

• You run tests and ship improvements (tone tweaks, fallback paths, training updates).

• You own the outcomes (gather feedback, measure performance, use insights to continuously improve the system).

2. Lead with AI, back with humans

AI isn't replacing the human touch. It's redefining when, where, and how it's most valuable.

In a scaled model, AI becomes the first responder: the default entry point for every conversation (and the end point for most of those conversations too). But it doesn't work in isolation. The experience should be hybrid by design:

• AI handles most conversations, including complex, multi-step queries that once relied on human experience and judgment to solve. It's fast, scalable, and consistent, while delivering personalized, context-aware experiences.

• Humans step in where they add value, either to resolve high-context, high-stakes issues or to improve the system itself. The team's value shifts from reactive resolution to proactive system design and high-value customer interactions.

• Even when humans take over, AI is still involved. AI copilot features like summarization, categorization, and suggested answers make human agents faster and more effective.

• Handoffs between the two are invisible. When a conversation moves from AI to human (or back again), the customer shouldn't notice. Every message should be personalized and contextual. It should feel like part of a single, coherent experience, not a jarring switch.

Every message, whether from AI or a human, should feel like part of one coherent experience. And this should apply across every channel your customers can reach you on – whether that's chat, email, phone, or community platforms like Slack and Discord.

A big mistake teams make when adding AI to the customer experience is tacking it onto something that wasn't designed for it. That's when experiences break: handoffs feel clunky and customers lose trust.

If you want AI to help you deliver a truly seamless experience for your customers, you need to embed it at the core of your system, not tack it on.

Modern AI Agents like Fin achieve consistency by using the same underlying system to process queries from any channel. The knowledge base, reasoning engine, and behavior rules are shared infrastructure, not separate per channel. When you update content or change how Fin responds, that change takes effect immediately across every channel because they're all drawing from the same source, not synced copies.

This unified architecture also enables seamless handoffs when your human team needs to step in. When a conversation moves from the messenger to phone, or from Fin to a human, the full history travels with them automatically, keeping context with the customer, not the channel.

Not only does this help the system perform better, but it helps the customer experience feel better too.

3. Be proactive

Use AI to anticipate customer needs and offer help, guidance, or nudges before they become problems.

It's not about deflection, it's about momentum: identifying drop-offs, surfacing friction, and stepping in at just the right time.

At Intercom, our team is working towards Fin acting as a "digital customer experience agent" for every customer; not only answering support queries but also offering tailored onboarding and proactive help. The aim is for AI to feel integrated into the full lifecycle experience, delivering relevant support without even needing to be asked.

4. Build for trust

Some customers still assume AI won't help them. You're dealing with the legacy of bad chatbots that gave vague answers, clunky menus, and left people in endless loops.

You build trust in AI by showing that it works. At scale, every interaction becomes a test. And every successful resolution is proof.

To build trust at scale:

• Lead with AI Don't hide your AI Agent behind layers of "choose an option" – get the customer to the AI Agent as soon as possible. Show them that this is a different kind of interaction.

• Make handovers seamless If the AI Agent can't resolve an issue, the handoff to your team should feel seamless. Design invisible transitions. Pass context, tone, and conversation history automatically. Empower agents with summaries and suggestions so they can pick up exactly where the AI left off.

• Show customers AI works When customers second-guess a correct AI response, have your team back it up. Build feedback loops that reinforce what's working and fix what's not. Every interaction is a test. When AI consistently delivers the right answers, completes tasks end-to-end, and seamlessly hands over to your team when needed, it will earn their trust.

At Intercom, we surveyed over 1,000 US consumers to see if their sentiment toward AI-first support changed once they saw what an AI Agent was capable of. The change was significant: by simply showing people that modern AI Agents can conversationally engage with customers, perform actions, and seamlessly escalate queries to a human, trust levels jumped by 18 points.

5. Make it feel personal

Your AI Agent represents your brand. The way it speaks, follows policies, and responds matters. With AI Agents, you can use capabilities like tone control, fallback logic, and language preferences to align the experience to your brand's standards.

If you're using Fin, you can use Guidance to control how Fin sounds and behaves using simple, natural language prompts. (If you want to dig deeper into AI Agent guidance, check out these best practices.)

Consistency builds trust, but personality builds connection and loyalty.

A closer look at phone support

Delivering customer experience that feels personal applies across every interaction, but it's especially critical on phone as the channel customers turn to when stakes are highest.

Customers call when something is urgent, emotional, or too complicated to resolve through chat or email because they need to talk to someone who can help them right now.

Despite being the go-to channel when customers need support the most, phone support has historically delivered the most impersonal, frustrating experience. IVR menus force customers through rigid decision trees. Hold times amplify frustration. And even when they get through to an agent, the interaction can feel scripted or transactional.

Modern voice AI, like Fin Voice, is changing this. Its capabilities make the experience feel significantly more natural and personal:

• Conversations follow a natural rhythm: Fin Voice handles interruptions smoothly, knows when to speak and when to listen, and keeps responses naturally conversational.
• It can read emotional cues: When Fin Voice detects frustration, uncertainty, or urgency in someone's voice, it adjusts its tone and approach accordingly. This ability to respond to the caller's emotional state makes the experience feel more personal.
• Help is instant and accessible: Customers get help the moment they call, in their preferred language (28+ languages are supported), without hold times or menu navigation.
• Handoffs are seamless: If a call needs a human to step in, Fin passes it over with complete conversation history and transcripts. Customers don't repeat themselves, and your team has everything they need to continue the conversation.
• Your brand voice stays consistent: You define how Fin Voice sounds, which topics it handles, and when it hands over to your team, so you can maintain the same personal touch and brand standards you've built across other channels.

Great customer experience over the phone challenges a common assumption: that AI makes support feel less personal. When voice AI is designed well, it scales what customers value most about your human team (their empathy and the ability to solve problems) and builds the kind of trust that creates loyalty as customers know that when they call, they'll get the help they need.

What great looks like

In an AI-native customer experience:

• The experience is built with AI at the core, not as an add-on.
• AI is the default first responder across all channels.
• Most queries are resolved instantly, without needing to be handed over to a human.
• Proactive support is embedded into the experience.
• Handoffs between AI and humans are seamless.
• Brand tone is consistent, even at scale.
• Support doesn't just resolve, it retains, activates, and delights.