Too many tickets, not enough time. It’s the same challenge that’s been plaguing support teams every day for as long as anyone has been working on tickets. As ticket volumes continue to rise and customer expectations grow along side it, traditional methods are struggling to keep up.
AI-powered workflow automation is changing that. Instead of relying on rigid “if-then” rules, AI can analyze context, learn from past interactions, and adapt in real time—helping teams resolve tickets faster, reduce manual work, and improve efficiency.
According to Zendesk, 65% of CX leaders now see AI as a strategic necessity, proof that automation in conjunction with artificial intelligence is the way of the future. Platforms like eesel AI integrate seamlessly with Zendesk, cutting response times by up to 50% through AI-driven automation without the high cost of native AI solutions.
In this guide, we’ll explore five real-world examples of how AI is transforming Zendesk workflow automation, helping support teams work smarter, not harder.
What is AI workflow automation in Zendesk?
AI workflow automation in Zendesk transforms traditional support processes by combining artificial intelligence with automated workflows to create more intelligent, adaptive systems. Unlike standard automations that follow rigid “if-then” rules, AI-powered workflows can understand context, learn from patterns, and make smart decisions about handling different scenarios.
To understand how AI workflow automation works in practice, let’s examine its core technical components:
- Natural language processing capabilities that analyze ticket content to determine customer intent and extract key information for faster resolution
- Advanced machine learning algorithms that continuously improve routing accuracy and response suggestions by learning from your team’s past ticket handling patterns
- Seamless integration framework that connects with existing Zendesk macros and business rules while maintaining workflow consistency
- Intelligent API orchestration that automatically pulls relevant customer data and context from connected systems
This intelligent workflow system delivers multiple benefits. First off it automatically categorizes and routes tickets based on content and urgency meaning more critical tickets get seen and dealt with first. It also generates contextually relevant responses by leveraging your knowledge base, ensuring that information always accurate. The workflow helps to identify opportunities for workflow optimization, making any changes in process easier to spot and update. Another benefit is that it provides agents with smart suggestions helping to draft replies faster. Lastly, it helps scale support operations without proportionally increasing headcount, allowing for more efficient budget management. Solutions like eesel AI enhance these capabilities further by providing both automated ticket handling and AI-powered assistance for your support team.
AI workflow automation: 5 real-world examples
AI is transforming how support teams leverage workflow automation, delivering measurable improvements in efficiency and customer satisfaction. Let’s explore five powerful examples that showcase how AI enhances support operations.
1. Order and product information retrieval
Use case: e-commerce
E-commerce businesses handle thousands of customer inquiries daily, ranging from order tracking to returns. Without AI automation, support teams can become overwhelmed, leading to slower response times and frustrated customers.
A great example of this is Helthjem, a food delivery service that automated its order status updates to reduce customer inquiries. By doing so, the company significantly improved response times and customer satisfaction, resulting in a 25% increase in average order value (AOV).
AI automation helps by pulling real-time order details from platforms like Shopify and WooCommerce, ensuring that customers receive accurate updates without the need for manual intervention. It also streamlines the organization of inquiries, allowing teams to resolve issues faster and more efficiently. By reducing the burden of repetitive tasks, support teams can focus on more complex issues, ultimately enhancing the overall customer experience.
2. Patient scheduling, billing, and data
Use case: healthcare
Managing patient scheduling, billing, and medical record updates is a significant challenge for healthcare providers. Delays in these areas can lead to missed appointments, administrative bottlenecks, and inefficiencies that impact both staff and patient care.
A prime example of automation improving healthcare workflows is how AI-driven scheduling tools have transformed patient appointment management. Hospitals and clinics that integrate automated scheduling systems have reduced no-show rates by up to 38% by sending timely reminders and optimizing time slots. This ensures that patients receive care without unnecessary delays while reducing the burden on administrative staff.
Beyond scheduling, AI automation also plays a crucial role in medical documentation and billing. Manual data entry in electronic health records (EHRs) is time-consuming and prone to errors. Automating these tasks to intelligent AI, ensures accurate and up-to-date patient records, reducing the likelihood of misfiled information or delayed treatments. Additionally, automated billing solutions help prevent coding errors and streamline claims processing, leading to faster reimbursements and fewer claim denials.
3. Account security, faster transactions and fraud detection
Use case: banking and finance
Banks and financial institutions handle vast amounts of transactions daily, making fraud detection and risk management critical concerns. Traditional methods often struggle to keep up with the speed and complexity of modern financial threats, leading to delays, errors, and potential security breaches.
A real-world example of AI automation improving financial workflows is shown by banks leveraging AI systems to monitor transactions in real-time. According to IBM data, mature AI adopters in finance experience a 43% reduction in uncollectible balances and a 33% faster cycle time for the monthly close. By automating fraud detection and compliance monitoring, banks can quickly flag suspicious activity and prevent financial losses.
AI automation helps by instantly analyzing transaction patterns, identifying anomalies, and triggering alerts for potential fraud. It also streamlines compliance reporting, ensuring that financial institutions meet regulatory requirements without the burden of manual data processing.
4. Managing guest inquiries and bookings
Use case: travel and hospitality
Managing bookings, guest inquiries, and pricing manually slows down travel businesses. Many hotels now use automation to streamline operations and improve service quality.
Marriott International personalizes guest experiences by automating room preferences and service requests. Hilton Worldwide uses automated pricing to adjust rates based on demand, maximizing revenue. With 50% of hoteliers relying on automation to cut costs, it’s clear that efficiency is a priority.
5. Improving support while reducing wait times
Use case: telecommunications
Telecom providers are under increasing pressure to improve customer experience, streamline operations, and maintain reliable networks. With over 5 billion customers worldwide, telecom companies are turning to AI-powered automation to keep pace with demand. According to NVIDIA’s 2024 report, 90% of telecom companies are now using AI in some capacity, with 48% piloting AI solutions and 41% actively deploying them.
One of the biggest applications of AI in telecom is customer support automation. Companies like NVIDIA are helping telecom providers implement generative AI-powered virtual assistants that resolve common customer issues instantly. This reduces wait times and improves engagement, with 57% of telecom providers using generative AI to enhance support interactions.
Network reliability is another key focus. Telecom companies are using AI-driven predictive maintenance to anticipate potential issues before network failures happen, reducing downtime and preventing costly disruptions. By analyzing massive datasets in real time, AI ensures smooth service delivery and optimizes network performance.
Why eesel AI is a better alternative to Zendesk AI
eesel AI seamlessly integrates with Zendesk, enhancing workflow automation without the high cost of Zendesk’s native AI solutions. Unlike traditional automation, it uses natural language processing to analyze tickets, machine learning to refine responses, and intelligent API orchestration to pull relevant customer data. This enables faster ticket resolution, smarter routing, and improved support efficiency, reducing response times by up to 50%. By combining advanced AI with easy integration, eesel AI offers a powerful, cost-effective alternative to Zendesk’s built-in AI tools, that allows businesses of all sizes to scale without running into any monetary issues.
Choose a smarter AI for your workflow automation
Ultimately, AI workflow automation is no longer a luxury but a necessity for modern support teams facing increasing ticket volumes and rising customer expectations. With AI-driven solutions, businesses can streamline operations, improve response times, and reduce manual workloads without compromising quality. While Zendesk offers AI capabilities, third-party solutions like eesel AI provide a more cost-effective, flexible alternative, delivering advanced automation at a fraction of the price. By adopting AI-powered automation, support teams can focus on meaningful interactions, drive efficiency, and scale without the overhead of traditional support models.
Try eesel AI for free—no payment details required. Sign up for a free trial or book a demo to see AI-powered automation in action. Have questions? Reach out at hi@eesel.app.
