AI's Role In Automating Routine Customer Tasks

What does "𝘼𝙜𝙚𝙣𝙩𝙞𝙘 𝘼𝙄" really look like in the enterprise today? 🤯 Spoiler alert: It’s not synthetic AI employees taking over entire departments (yet). Instead, it’s smart, focused workflows designed to handle specific tasks efficiently and accurately. Here’s a real-world example from one of our retail clients: they’ve automated the process of helping customers who’ve lost their return labels. 𝗧𝗵𝗲 𝗼𝗹𝗱 𝗽𝗿𝗼𝗰𝗲𝘀𝘀: 1️⃣ A customer emails support saying they can’t find their return label. 2️⃣ A customer service agent reads the email in Zendesk, identifies the issue, and checks the CRM for details. 3️⃣ Most of the time, the problem isn’t the label—it’s something simple like a typo in the zip code or missing phone number. 4️⃣ The employee fixes the issue, selects the correct email template, drafts a response in the right tone, and sends it to the customer. 5️⃣ Finally, they resolve the ticket in Zendesk. It’s repetitive, manual, and time-consuming - requiring judgment calls and multiple tools. 💡 𝗡𝗼𝘄, 𝘁𝗵𝗶𝘀 𝗲𝗻𝘁𝗶𝗿𝗲 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗶𝘀 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱: 1️⃣ Detect the Issue Automatically When a customer emails support, AI scans the ticket to see if it’s about a missing return label. If the model is unsure, it’s routed to a human for validation. 2️⃣ Check Eligibility Instantly The agent pulls order details from Salesforce—validates if: • The return window is still open (within 30 days) • Customer info (like phone number or postal code) is correct 3️⃣ Fixes Common Errors AI corrects simple mistakes in Salesforce and then sends it to the another agent specialized in customer comms. 4️⃣ Generate a Personalized Response A text-generation agent drafts a tailored email in the brand’s voice, ensuring it’s clear, helpful, and compliant. 5️⃣ Update Systems & Close the Loop The AI agent updates the customer info in Salesforce, the email is sent via Zendesk, and the ticket is marked as resolved. This is “𝘼𝙜𝙚𝙣𝙩𝙞𝙘 𝘼𝙄” in action: Logic (e.g., classifying what the email was about / checking if an order was delivered within 30 days) + text generation agents (like an email generator trained in the brand’s voice, tone, and compliance rules) + seamless integrations with enterprise systems (e.g., Zendesk, Salesforce) working together to solve a problem from start to finish. What's exciting is once enterprises build one workflow like this, they can quickly replicate and scale—reusing components and tackling more complex processes. And this is just the beginning. As these workflows grow, they lay the foundation for 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝗴𝗲𝗻𝘁𝘀 which are systems capable of coordinating across workflows to tackle enterprise-wide challenges. 🚀 The majority of 2025 will still be dominated by these highly targeted workflows. But every workflow built today is compounding toward something much bigger.

I have been working with AI in customer support for a while now. And lately, one thing is becoming clear. This space is getting crowded. Every vendor claims their AI is the magic wand. Just plug it in, and your support problems disappear. But the reality is different. AI isn’t magic. It’s a strategy. It has to be planned, adapted, and rolled out based on: 🔹 Your goals 🔹 Your current challenges 🔹 And your team’s capacity Most support leaders we speak with aren’t confused about the tech. They are confused about where to use it. That’s the real challenge. So we created a simple matrix to help teams make better AI decisions. It’s built on just two questions: 1. What’s the risk if AI gets this wrong 2. How complex is the task When you map support work using this lens, things get clearer: - Use AI fully for low risk, repetitive tasks like tagging, triaging, or summarising. - Use AI as a helper for pattern based tasks like routing, recommending actions, or drafting replies. - Keep humans in control for high risk, complex issues like escalations, complaints, or anything tied to revenue.   And here’s the other mindset shift: Don’t think of support AI as one giant bot. Think of it as a system of specialised agents: 🔹 Analyzers – Understand queries, profiles, logs 🔹 Orchestrators – Manage workflows, routing 🔹 Reasoners – Diagnose problems 🔹 Recommenders – Suggest next steps 🔹 Responders – Write or send replies Each agent plays a specific role, just like your support team does. Done right, AI doesn’t replace humans. It supports them, speeds them up, and helps them focus where it matters most. This approach is also being recognised by the front-runners in the space. At a recent ServiceNow event I attended, many speakers echoed the same thought: AI is not one size fits all. It must be tailored to each organisation’s structure, systems, and bandwidth.   Let’s stop using AI for the sake of it. Let’s start using it where it actually makes a difference.   If you are building or evaluating AI for support and want to walk through the matrix, Feel free to drop me a message.  Always happy to exchange notes.

Last month our team of 5 did the work of 50 people. While taking every weekend off. The secret? We replaced the most expensive job with code: Let me show you exactly how this works. Three features transformed our support from "answers questions" to "handles entire workflows": 1. Guidance: When someone requests a feature, our AI: - Thanks them properly - Logs feedback automatically - Directs to feedback portal - Updates them on progress - Maintains perfect brand voice 2. Processes: Take a refund requests. Our AI: - Checks account status - Verifies eligibility - Processes through Stripe - Sends confirmation - Logs everything instantly 3. Actions: This is the real power. AI can: - Pull CRM data - Process payments - Update records - Trigger notifications - Make API calls Real workflow example: Customer: "Can I get a refund?" AI: - Verifies account instantly - Checks eligibility - If eligible: processes immediately - If not: explains why + alternatives - Everything logged in seconds What used to take 30 minutes Now happens automatically. Start with feature requests. It's simple but shows the power. Then you'll want to automate everything. Because your support team should solve problems. Not copy-paste responses at 3AM. What would you automate first? Interested in seeing how Helply can do this for you? Shoot me a DM