AI for repetitive customer support questions, grounded self-service, and real-time answer retrieval

AI can answer a customer query in seconds.
But knowing when NOT to answer automatically is equally important.

Recently, I built an AI Customer Support Escalation Workflow in n8n.

The workflow receives a customer inquiry, prepares the data, and lets the AI Support Assistant process the request.

The important part is the decision layer:

→ Normal inquiry → AI responds to the customer → inquiry logged
→ Human support required → escalation acknowledged → support team notified → inquiry logged

The goal wasn’t to automate every conversation.

It was to build a system where AI handles what it can, and humans step in when they should.

That’s where automation becomes more practical — not replacing human support, but routing work intelligently.

#n8n #Automation #AIAutomation #CustomerSupport #WorkflowAutomation #AI #NoCode

AI won't replace support teams, but support teams who use it - will.


I lead support, and I've stopped treating AI as a threat. It's the layer that clears the repetitive work off my team's plate, so they spend their energy where a human matters most.

Here's the stack I run, and where AI does the heavy lifting.

1️⃣ Intercom → where every customer conversation lands.
2️⃣ Claude → drafting replies and untangling the messy, multi-thread tickets.
3️⃣ Jason AI (Reply) → deflecting the repeat questions so my team spends its time on the tickets that need a human.
4️⃣ ChatGPT → fast rewrites when a reply needs a different tone.
5️⃣ Perplexity → quick answers with sources I can check.
6️⃣ Notion → our playbooks and team knowledge in one place.
7️⃣ Airtable → tracking tickets, trends, and how the team is doing.
8️⃣ Trello → the daily task board that keeps everyone on track.
9️⃣ Jira → bugs and escalations that need engineering.
🔟 Slack → where the team actually talks.

Four of these are AI tools, and none of them answer the hard tickets for me. They buy my team the time to handle those well. That's the shift worth making. Let AI carry the repetitive load, and put your people where empathy and judgment change the outcome.

What is your top tool in support? 🤔

We're a customer support team of around 70 agents handling a few thousand conversations every day. Like a lot of companies we've started rolling out AI over the last year. It started with ticket summaries and reply suggestions. Now we're testing AI for handling common requests before they reach an agent. Overall it's been useful so far. AI is great for repetitive questions and speeding up after-call work. The bigger challenge has been deciding where AI should step in and where a human should take over. If it hands off too late the customer is already frustrated. If it hands off too early you're not getting much value from the automation. Most of the reports I've read say AI adoption in customer service is growing fast and companies are using it to support agents more than replace them. That seems to match what we're seeing. Open to different opinions.

I've noticed something changing in customer support lately, and I suspect you might as well.

The chat button that used to connect you with a person now opens a bot. Even my mechanic's phone line has become an AI booking system. The shift has happened quickly. In 2020, only about 5% of support teams were using chatbots. By 2025, that number had climbed to more than 80%.

I understand why. AI scales, it's available 24/7, and it can handle a huge volume of repetitive questions. But when something actually goes wrong, most people still want another person. Not because AI is inherently bad at support, but because when you're frustrated you want to know that someone understands what you're experiencing and cares that your experience hasn't been ideal.

Working in customer support has taught me that some of the most valuable product insights don't come from dashboards or bug reports. They come from conversations.

A customer mentions an odd workaround they've been using for months. Three different people describe the same issue using completely different words. Someone casually says, "It's not a bug, but..." and suddenly you've uncovered the real problem.

AI can absolutely help support teams work more efficiently. But I don't think we should automate away the conversations that teach us the most about the people using our products.

That's something I've been thinking about recently, and I wrote more about it here: https://shorturl.at/MrzzE

Has AI broken customer service? Are the robots causing all of to rage throw our phones out the window? (just me??)

Seriously though, have we gone to far? How many companies have replaced all the humans with AI, only to create an experience so frustrating it actively loses customers?

This morning ASICS helped themselves to £100 from my account with no warning... so, as you would when faced with a ridiculous situation, I called them.

The message on the phone told me 'they had no one available due to exceptional circumstances'... (a quick google tells me this is definitely not exceptional and I'm starting to understand their 2* Trustpilot reviews).

So off I go to their online chat. This is of course an AI agent, and can't help me.

So, on to the next option: 'email us' is what the button says. I head to the contact form. Which has a hilarious 250 character limit. FFS.

It's almost impressive just how many barriers there are to being helpful and creating a good customer experience. Instead I'm down £100, no explanation, no human to speak to, and one customer who 100% won't be buying ASICS again (much to her teenagers disappointment!)

Moral of the LinkedIn story - be more human. We can add agents to take some of the friction away - the "where's my order?" or the "how do I create a return" - but absolutely don't erase the people entirely.

With the General Availability of Service Agent and MCP tools in Microsoft 365 Copilot, service organizations continue to get the benefits of Copilot in customer service, now powered by the rich business context and grounded intelligence of both Dynamics 365 and Microsoft 365. Whether they’re new in career or experienced customer service representatives, your employees get tools from Microsoft to help deliver a better support experience for your customers. With this release, we have added rich, interactive app-in-chat experiences, ensuring that customer service representatives do not need to solely rely on text-based conversational UX. Employees can investigate issues, navigate complex processes, and complete tasks without leaving the conversation. The result is a more connected, action-oriented experience that helps service professionals move from understanding to resolution faster in Dynamics 365 Customer Service and across Microsoft 365 apps.

61 percent of your users will leave for a competitor after exactly one bad experince.

I was biting my tongue today during a hallway conversation so I would not scream this number out loud. A colleague asked why we even need human Customer Support anymore. "Why not just automate everything with AI and close the tickets?"

I love tech people. I really do. But sometimes they think human frustration can be resolved with a version update.

Do not get me wrong, AI is a fantastic sidekick. I use it to answer simple tickets. To summarize past chats, analyze sentiment, and pull up user history. But AI has absolutely zero judgment.

Take a classic edge case. A user buys a time-based package, but real life happens and they cannot use it. The database shows the purchase was delivered successfully. If an AI handles this, it looks at the policy, sees a successful delivery, and politely tells the user to go away.

A human looks at the exact same ticket, realizes we want this person to actually like our brand, bends the rules, and restores the package.

Trap a frustrated user with a bot that makes a mistake, give them no way to reach a real human, and trust is instantly broken. People just want to know there is an actual person behind the system.

Use AI to read the data. Use humans to read the room.

My career has been all over the place honestly. I started in customer support, moved into training the support team, then into learning and development, then implementation, then chose to go back to support because honestly it's where I do my best work, except this time as a team of one at a startup where the job also includes knowledge management and content creation on any given day.

So I've seen this stuff from a lot of angles.

Over the last 18 months my current role has shifted more than it did in the previous five years combined. AI handles a big chunk of what used to fill my day, and the stuff that still comes my way is genuinely different now, messier, more emotionally charged, the situations where someone just needs a real person.

That shift has made me think a lot about how people talk about support experience on resumes, because most of it sounds identical. "Handled customer inquiries." "Resolved tickets." Cool, so did everyone else.

What actually made me hireable across really different roles wasn't any of that. It was the call I talked someone down on. The pattern I noticed before it became a real problem. The moment I went off script because the script would have made things worse. Creating a training program from scratch because no one else had the bandwidth. Sitting in product and engineering meetings as the person who actually knew what customers were saying, and translating that into something the team could act on.

If I was actively job searching right now I'd be writing about those moments specifically, not the volume of tickets I closed.

And honestly, not hiding that you work with AI tools daily is worth mentioning now. A year ago it felt like a weird thing to bring up. Now people who pretend they don't use them just come across as out of touch.

Anyone else who's bounced around roles like this, curious how you're framing that experience right now. Does it feel like an asset or does it still read as unfocused to hiring managers?

A new automation potential report analyzes your customer conversations and identifies requests that can be automated with AI agents. This report provides brand-specific insights and sample ticket data, showing you exactly how an AI agent would respond to customer inquiries.

(Advanced) Agentic AI for advanced email AI agents is now generally available. This enables AI agents to understand emails, answer questions, automate procedures, and escalate when needed, reducing back-and-forth with customers.

Copilot now includes macro content suggestions and trust and safety recommendations. These new recommendation types help you improve agent productivity and account security without spending time going through complex settings.

Generative search in help center now supports a follow-up question for customers using the Web Widget. This enhancement creates a smoother path from self-service search to a conversational experience with an AI agent, reducing repetition and keeping context from the original search.

Hot take: AI doesn't replace great support teams. It reveals them.
I've spent years taking struggling operations and dragging them into something better than I found them. And the biggest unlock in the last few years hasn't been a new hire or a reorg. It's been getting my team out of survival mode so they can actually do the work they're good at.
Here's what that looked like in practice:
We introduced an AI agent to our student support team. Her first month, she handled 25% of all inbound volumn solo. Escalation rate? Around 5%. Meanwhile, our old chat platform was managing 200 conversations a month.


She did nearly 4,000 without missing a single kids baseball game. Guess who got to go to those? The team.
Did people panic? Yes, but I reminded my CS team that the invention of the calculator didn't eliminate the need for mathematician, did it? Let's be MASTERS of this.
What I told them was this: the team members who learn to work alongside AI, who master the tools instead of fearing them, who let the AI catch the routine stuff while they focus on the complex, emotional, high-stakes moments, those people become indispensable.
And here's the thing nobody talks about enough: when AI absorbs the backlog, humans stop drowning. My team went from perpetually behind to actually present for the students who needed them most. The work got better. The humans got better.
One of our highest-rated agents in feedback? Was the AI. Students praised her by name, not knowing she wasn't human. Not because we were hiding something, but because she was genuinely helpful.
That's the bar. That's what good AI deployment looks like.
AI in support isn't a threat. It's a force multiplier, but only if you deploy it with intention, build trust with your team through the transition, and stay honest about what you know and what you don't.
The leaders who figure that out are going to build teams that can do more than they ever could before.
That's the unlock.