The complete guide to Agentic AI customer service workflows

“The Ticket ID# KZQ-564 has a query for a plan upgrade, so how to tackle this?” asks a team member. You went on to explain the steps and guided your teammate through the actual workflows, so he could assist the customer in addressing the issue. 

This is a familiar scenario for traditional, manual customer service. 

However, this is only good until your support is limited to only a handful of tickets. As you grow, this manual and oral process becomes cumbersome and unsustainable. The real problem is that your team loses context with every handoff, and without real-time data access, your resolution time increases. 

A Forrester study reveals that data silos lead to knowledge workers losing 12 hours per week in productivity, which is a significant concern for customer support. Poor decision-making and error-prone processes become the norm, creating performance bottlenecks. 

Not manual or traditional workflows, but AI agent-powered automated customer service workflows that streamline every customer interaction. By centralizing information for team members, automating routine decisions, and facilitating smart escalations, customer support workflows transform your support operations. 

In this article, you’ll discover the concept of Agentic AI customer support workflows, the pain points of manual workflows, and steps to build a highly efficient framework that works for your support, including its various types.

An AI-powered customer service workflow, or more accurately, AI-agentic workflows, utilizes AI agents to automate a single or multi-turn sequence of steps by interacting with multiple tools, making decisions, and completing tasks with minimal human input. 

Agentic AI customer service workflow automation reduces manual steps, speeds up resolution times, and frees up agents’ time to focus on a broader range of support queries. 

Let’s say a customer support system receives a query for refund issues. Using automated customer service workflows, your customer can instantly get an update via an ongoing Q&A chat without having to go through multiple steps or drop the chat. 

However, when done manually, your support agent either requests references or manually handles steps, such as checking the CRM, obtaining customer data, and retrieving the necessary information to provide to the customer.  Without the standardized and consistent process, your agent can struggle and delay responses.

Your legacy customer support system is not in sync with other tools your business uses. So, your workflows work in silo too, preventing real-time decision making. Here’s how your traditional support workflows are blockers to seamless and effortless support delivery. 

Data silos: The misaligned workflows

When not integrated seamlessly, your customer information is trapped in scattered systems that do not communicate effectively with each other. You have your customer data in one system, purchase history in another, and chat logs spread across multiple collaborative tools. The data silo forces your agents to search for data across each system, resulting in inefficiencies and errors that disrupt customer experiences. 

Handoff troubles: Where customer experiences sink 

With multiple touchpoints working behind the process, from logging records to escalation, the ticket faces a poor handoff, and the context gets lost. Every time the customer connects with a support member, it is a significant ordeal of retelling the story, which has the potential for inefficiencies and errors, such as duplication of repeated actions for the same query. The hidden cost is delayed responses and frustrated customers. 

Governance gaps: support falls apart 

Let’s get back to the data silos: you lack significant data to standardize a process to support your customers. Between new members joining and old members leaving, customer support employs different procedures and varying response templates, resulting in inconsistent and low-quality responses. GDPR, HIPAA, and CCPA compliance risks may ensue. 

These challenges pose a threat to seamless support operations through a series of inefficiencies that impact both operational costs and customer experiences. 

AI-powered customer service workflows are significantly ahead of traditional ones, which utilize AI agents at every step of the touchpoint and accelerate the resolution speed. Here are some significant benefits you can harness using automated workflows for your support. 

• Improved productivity: Automated customer support workflows eliminate unnecessary or miscalculated steps. Streamline customer interactions and automate repetitive tasks to enhance support team productivity and efficiency. 

• Streamlined task management: Automated workflows help you auto-assign tasks, set up reminders, follow-ups, and simplify task delegation to allow customer support managers to streamline tasks and manage strategic responsibilities. 

• Improved SLA: With automated workflows, call routings are done correctly based on expertise. This approach is effective in addressing issues promptly and meeting service level agreements (SLAs). Let’s say you have a ticket regarding laptop delivery; the automated workflow instantly sends this ticket to the inventory team and offers instant help.  

• Unified communications: Customer service workflows, when designed with AI, help integrate all tools, providing a unified view of data. Your agents are familiar with all aspects of tickets and their status, enabling them to offer context-aware answers and avoid unnecessary details. 

• Minimized human errors: Automated workflows easily reduce repetitive steps, which otherwise trigger error-prone activities. Support agents would no longer handle mundane tasks; instead, they would spend time addressing creative needs. 

• Performance improvements: Customer service workflows are a treasure trove for various critical data points. You can fetch them to analyze which queries were easy and which ones were tough, and provide suggestions for performance improvements. 

• Cost reduction: As automation in workflows reduces steps and speeds up the resolution time, each ticket is successfully closed. You can optimize your agents’ time and reduce operational costs. 

These benefits suggest that transitioning to automated workflows for customer service processes is a sensible approach. Initially, you need investment and a better framework to optimize customer support workflows, and you can yield good returns in the long run.

Seamless customer support workflow management with agentic AI requires a strategic approach. It involves careful planning, implementation, reviews, and continuous improvements. Let’s break down each step and share details about the necessary elements to help you build AI agent customer service workflows. 

Start by evaluating your readiness 

For AI agents to work seamlessly and accurately, ensure you have the right environment to support agentic AI workflows. If everything doesn’t work well together, your workflows will break down. 

Key things to assess:

• Well-documented procedures: Ensure that your procedures are well-documented and ready. These documented procedures are essential elements for training your workflows. 

• Data structure: Don’t forget to prepare your data. Clean and store them for your AI agents to pull easily. 

• Technology stack: Verify that your existing tools—CRMs, ERPs, APIs, databases, and knowledge bases — feature seamless integrations to support AI agents.  

• Team awareness: Change management will become smoother if your team understands Agentic AI and their roles in automating workflows. Train them for a smooth transition. 

Before you jump in, take a look at your business procedures and bring people, processes, and technology together. 

Review the best opportunities for agentic customer support workflows 

The same formula applies here as well. AI workflows for customer support are most effective in processes that are repetitive, complex, and require decisive plans across multiple steps. So, review these areas in your customer support operations. 

Map out your customer or internal workflow needs for AI agents:

• Repetitive tasks: Checking statuses, updating records, and resetting passwords are examples of repetitive tasks that can be automated with agentic AI workflows. 

• Time-consuming tasks: Any complex queries that require a significant amount of time to resolve should be considered.

• High-volume interactions: Think of FAQs, onboarding sequences, and support tickets. 

If you find that your support agent takes more than 70% the time resolving ‘subscription upgrade, it is the right use case. Delegate it to the AI agents who can handle them end-to-end. 

Choose an AI agent builder 

Critical features and functionalities are essential for your Agentic AI workflows to support your processes effectively. But not every AI agent builder is built the same way. Go for the one that aligns with your business goals. 

Platform evaluation criteria, for AI agent builders like pagergpt, and others: 

• Team collaboration: Can it allow all team members to connect in real-time for references and knowledge sharing? Look for a feature like a Shared Live Inbox for team collaboration. 

• Seamless integrations: AI workflows for various processes, such as refunds, subscriptions, and ticket creation, require integrations with your tool stack, including CRM systems, email platforms, and more. 

• Scalability: Can your AI agent platform handle volumes as you grow? 

• NLU capabilities: Examine if the AI agent can understand local languages, typos, and the context of a query. 

• Customizability: How easily can you integrate the AI agents into your branding specifications? Check the ease of use of customizations for tonality and branding. 

• Compliance and security: Does the platform have built-in security and compliance standards that meet requirements such as HIPAA and GDPR? 

Also, ask how fast you can achieve the fastest time to market. Or are there effective how-to guide materials for a customer success manager for seamless onboarding?

AI agents are a new addition to your customer support tooling stack and a big AI driver for your business. Check everything carefully. 

Keep humans in the loop 

Human-AI synergy scripts a success story for your agentic AI customer service workflows. Align your team with AI workflow objectives across the board and achieve your goals. 

How to manage AI-human collaboration: 

• AI agent training: Train  your AI agents to work with workflow triggers. 

• Human agent training: AI agents are new, but not the workflows. Train your team to work with AI agents during handoffs. 

• Communication development: For handling nuances and exceptions, human agents play a pivotal role. Train them with adequate customer support scenarios. 

• Feedback loop: Make it easy for your team to share their experience with the agentic AI workflows. You can prepare a weekly survey and collect feedback. 

Test, test, and test 

This is the most crucial step in designing a successful agentic AI customer service workflow. Don’t prepare for all use cases at one go. Try to be strategic and start small. 

How to examine agentic AI workflows:

• Start with small pilots: Take a very small use case. Test your workflows for a limited group of users. 

• Check task execution: Does your AI agent sync well with tools and execute workflows effectively? 

• Try unusual cases: Ask questions related to loyalty programs, billing, shipping, and other relevant topics. 

• Branding alignment: Does your company logo look just right, and do those responses match your brand voice? 

• Monitor metrics: Track success rates, including task completion, response accuracy, and customer satisfaction scores, to identify areas for improvement.

While testing your agentic AI workflows, ensure you address these key areas. If everything goes well, go one by one.

Customer service operations encompass a wide range of user questions. Not only these, but new and unique questions can also arise. Here are a few examples of real-world agentic AI workflows that automate processes from end to end. 

Password reset request flow 

It is a very common customer query that your customer service receives frequently. Let’s say, there’s a query asking, ‘I forgot my Adobe password. How do I reset it?

A traditional chatbot will guide this way: 

• Search across the knowledge base 

• Surface an article 

• Ask the user to read through and find an answer 

• Suggest creating a ticket if no answer is found 

So, it is never quite a seamless experience in the first stage. 

An automated agentic AI workflow will: 

• Search across the company-wide knowledge bases 

• Surface the right link to edit and reset the password 

• Handle a follow-up if the link doesn’t work

• Look for a reference across the previous chat history 

• Provide step-by-step guidance to work through the password reset process

• Update the identity and access management system 

Instead of merely responding and lacking accountability, agentic AI workflows adapt to changing situations, make informed decisions, and complete tasks. 

Subscription billing inquiry handling flow  

“I cancelled my subscription before the new billing cycle could start, but the subscription is renewed and I am billed, and money got debited from my account”. 

A traditional customer support workflow would surface only FAQs and then escalate the query.

With agentic AI workflows, your customers can get answers until they are satisfied. 

The agentic AI workflow might:

• Check across Adobe CMS, Recurly, and Stripe via APIs 

• Check the actions taken 

• Understand what went wrong—is it a platform-related mistake or a user mistake 

• Find subscription was canceled, but confirmation was not made 

• Communicate with the user and brief the mistake 

• Suggest if the user wants to cancel the next recurring billing 

• Logged in to Recurly, canceled the next month's subscription 

• Update the ticket and notify the user 

So, it is an end-to-end process that is executed autonomously by an agentic AI workflow you have set up. 

Product quality issue handling flow

“I received a defective product, and it is not the same as I saw before placing the order ”. 

The traditional workflow might need an invoice ID and product images. If the chatbot cannot sync with ongoing conversations, it will escalate it. 

But when you have your workflows for customer support built with agentic AI, every step is managed autonomously. 

An AI agent workflow will:

• Extract customer ID, product SKU, and issue description 

• Check the CRM database for purchase records, warranty status, and product batch data

• Verify quality databases 

• Generate return labels and initiate refunds via the Stripe API 

• Send a confirmation email and auto-update customers

• Update the knowledge base LLM with new data 

It is not just an automated response, but your AI agent workflow also prepares a stage for unique queries with a knowledge base update. 

Lead capture and ICP creation flow 

Now, let's move on to a different workflow type, lead capture, which can be quite stressful when done manually. 

Your human agent would handle it this way:

• Create a list of prospects using LinkedIn Sales Navigator, Zoominfo, etc 

• Create prospect profiling 

• Craft personalized communication materials 

• Track replies in a spreadsheet 

• Follow up 

Imagine if the person responsible for the engagement is on leave; the entire process would be delayed by a few weeks or months. 

However, an agentic AI workflow operates autonomously and executes tasks without interruption. 

With AI agents, your workflow will:

• Observe visitor behavior 

• Shoot up a pop-up chat window if found visitor’s engagement is found on the pricing page or to spend a long duration on the site 

• Profile high-potential clients based on their intent 

• Follow up with personalized messages (abandonment or demo request)

• Escalate to the human agent when a complex technical question arises

• Follow up to finalize the demo 

• Enable handoffs 

• Update CRMs

Your AI agents do the heavy lifting and allow you to capture a high prospect without missing a beat. 

Customer profile update flow 

Having updated customer profile data helps you complete tasks more efficiently. For example, a customer has a new address. If it is not updated in your CRM, logistical snarls will cause you trouble. 

An old-school method relies on manual data entry, which can be dependent on the availability of the support executive. A lot of uncertainty awaits. 

However, the process is seamless and automated with agentic AI workflows for your customer service. 

An AI agent will:

• Ask what the things are that a customer wants to update 

• Get information, i.e., account details of a new bank, and address 

• Update the CRM system via APIs such as Salesforce, Odoo, etc 

• Send updated information 

• Provide a change summary  

Your support team can stay away from repetitive, boring tasks, while your people love how agentic workflows prevent delays and boost efficiency. 

These are some examples of agentic AI workflows for automating customer support processes. Select any case, such as cart abandonment or gift code issues, for example. You can customize your workflows and feel the freedom.

No longer is there any hurdle to streamlining your processes and building an engaging customer support that listens, makes your customer feel valued, and helps you grow while beating the competition. 

Unlike traditional workflows, AI agent-powered customer support workflows are significantly easier to build, customize, deploy, and manage. So, you are always in sync with your customers and help them resolve their troubles instantly. 

With pagergpt, you have the maximum flexibility and convenience while building your AI workflow. It gives you all that you need to scale fast,

• 100% no-code platform: No tech skill is required, so you get rid of those dev tickets. 

• Plug-and-play model: Get ready-to-use templates, customize your workflows, and get started. 

• LLM accuracy: Keep your customers satisfied with accurate and relevant responses. 

• Quick handoffs: Immediately transfer a call to the right person without losing any context. 

• Unlimited messaging: Build engaging CX with unlimited chat sessions, where your customers are not left hanging in the middle of a query. 

• Flexible pricing: Get the most affordable pricing options. Test and trial with a free plan. 

pagergpt’s AI agent platform makes it easy to transform your customer support culture, which is slow, static, and reactive. With pagergpt, you can,

• Create workflows easily for any industry using industry-ready templates. 

• Provide location-based responses and optimize your workflows.

• Understand user intent and trigger the right workflows for speedier resolutions.

• Utilize visual dashboards to track KPIs and drive continuous improvements in chat responses. 

Notably, pagergpt isn’t just a chatbot. Where your traditional workflows for customer support fail, agentic AI workflows built with pagergpt gain accuracy and speed with built-in autonomy, reasoning, and decision-making. You can manage everything end-to-end and take your support to the next level. To build our first agentic AI workflows, book a demo today. 

What is an agentic AI customer service workflow?

Leveraging LLMs, advanced RAG, and tooling capabilities, a computer software program that uses AI agents to streamline and automate a single or series of queries in a chat and resolve a problem is an agentic AI workflow. AI agents in customer service workflows can reason, make decisions, and execute tasks in dynamic and evolving scenarios. 

How does an agentic AI customer support workflow solve problems found in traditional support?

Agentic AI workflows encompass the inherent ability to handle situations through self-learning and reasoning in multi-turn interactions. With its flexible adaptability, AI can answer outside a predefined set of answer templates, follow fallback, facilitate handoffs, and integrate systems to remove data silos—the missing links in traditional support workflows. 

Will AI agents make support teams obsolete?

Agentic AI workflows can have a significant impact when humans are in the loop. AI agent workflows in customer support automate repetitive tasks. But those nuances, complexities, and unique customer queries still need an emotional touch. Your human support can satisfy this need only. Humans and AI make a perfect blend and complement each other for a frictionless customer support. 

Are agentic AI workflows the same as simple automation?

Typical automation in workflows for customer support only follows if-then“ logic. A customer would be frustrated by an answer that doesn’t solve a problem and also doesn’t facilitate handoffs. Agentic AI workflows understand intent and provide answers based on reasoning. 

Can I build agentic AI workflows without breaking my bank?

AI agent builder, pagergpt, offers a 100% no-code platform. Not only do you save on development expenses, but also on packages. With pagergpt, you can get the most affordable pricing options. Pay nothing to start with AI workflows as you pick the Magic Plan. Contact our sales team.