AI agentic workflows: The smarter AI that’s transforming CX

Imagine your customer service team as a symphony orchestra—each musician has a specific instrument and part they need to play with precision. Without a trained conductor, your orchestra is out of tune and offbeat. However, a well-trained, masterful conductor helps them keep perfect time and anticipates how they can work together and continue to grow.

Your masterful conductor is your AI agentic workflows for customer experience (CX), and they transform traditional workflows into flexible and responsive elements of CX. With these intelligent systems, businesses can orchestrate efficient and cohesive customer service processes that create harmonious, resonant experiences that stay with customers long after an interaction.

To transform your CX symphony, let’s explore how AI agentic workflows for CX are changing the tempo of customer service in our guide.

More in this guide:

• Agentic workflows vs. traditional workflows
• Key components of AI agentic workflows
• What are the benefits of agentic AI for CX?
• Characteristics of AI agentic workflows
• Examples of AI agentic workflows for CX
• 5 steps for implementing AI agentic workflows
• Challenges of AI agentic workflows for customer experience
• Frequently asked questions
• Seamlessly connect AI agentic workflows for CX with Zendesk

Agentic workflows vs. traditional workflows

While traditional workflow automation software streamlines many customer service processes, it often follows rigid, pre-determined paths with little flexibility to adapt to unique customer needs. Agentic workflows powered by artificial intelligence (AI) represent a fundamental shift in customer experience automation.

Rather than simply following pre-programmed rules and decision trees, AI agents—the next generation of AI-powered bots—can make decisions, learn from interactions, and autonomously solve problems. Much like a conductor who doesn’t just keep time but actively interprets the music, these bots use AI agentic workflows to reach complex goals and dynamically execute tasks.

The additional differences between agentic workflows vs. traditional workflows are significant and include:

• Decision-making capabilities: Traditional workflows execute fixed actions, while agentic workflows can choose optimal paths.
• Adaptability: Traditional systems struggle with exceptions, while AI agents adjust their approach based on customer context and history.
• Learning capacity: Static workflows require manual updates, while agentic systems continuously improve through interaction data.
• Proactive vs. reactive: Traditional automation responds to triggers, but AI agents can anticipate issues and initiate preventative actions.
• Personalization depth: Rule-based systems offer limited personalization options, while agentic workflows can craft truly individualized experiences.

With AI agentic workflows for customer experience, businesses don’t rely on simple CX automation (CXA)—they enable an intelligent, responsive, evolving system that delivers consistent experiences across touchpoints.

Key components of AI agentic workflows

To create truly orchestrated customer experiences and help AI improve CX, AI agentic workflows rely on three components that work harmoniously to deliver exceptional service.

Large language models

Large language models (LLMs) power modern agentic workflows and serve as sophisticated systems interpreting customer communication. LLMs use powerful neural networks to process and generate human language, allowing them to understand intent, recognize emotional undertones, and craft natural, personal responses.

Using LLMs, AI agentic workflows can interpret slang, typos, lingo, and ambiguous requests without requiring customers to adapt their language to a system’s program. Plus, continual training on diverse datasets allows AI models to understand industry-specific terminology and nuanced service contexts, making them feel intuitive rather than mechanical.

Generative AI networks

While large language models understand and respond to text, generative AI enables workflows to create and generate content on demand. Generative AI networks (GAINs) can:

• Automatically develop personalized recommendations.

• Create custom guides.

• Develop visual demonstrations.

• Write dynamic scripts based on specific customer situations.

Rather than depending on pre-written responses or decision trees, generative AI ensures customers receive information tailored to their needs, technical understanding, and brand history. As customer needs evolve, these generative capabilities enable workflows to produce novel solutions rather than being limited to pre-defined options.

AI agents

At the center of effective AI agentic workflows for CX are the intelligent digital agents that make decisions and take action. AI agents are more than chatbots—they connect to backend systems and can resolve complex customer queries. For example, Zendesk AI agents are trained on billions of customer interactions and conversation data, meaning they’re equipped to understand and solve sophisticated customer issues.

Unlike simple customer service chatbots, these sophisticated agents can:

• Understand complex requisitions.

• Maintain context across interactions.

• Execute multi-step processes autonomously.

• Interpret nuance and customer intent or sentiment.

• Prioritize issues based on urgency and business impact.

• Seamlessly escalate tickets to human agents when necessary.

The most effective AI agents learn continuously from each interaction, gradually expanding their capabilities and evolving AI in customer service.

What are the benefits of agentic AI for CX?

AI in the workplace transforms experience delivery by bringing intelligence and autonomy to every customer touchpoint. Below, we explore the benefits and impact of AI agentic workflows for CX.

• Autonomously resolved issues: By handling complete customer journeys from inquiry to solution without human intervention, AI agents increase first-contact resolution rates while freeing human agents for more complex, empathetic tasks.
• Increased efficiency and productivity: Agentic workflows improve agent productivity and efficiency by scaling to meet demand spikes, working continuously, and handling routine tasks.
• Enhanced customer service training: AI workflows accelerate onboarding and enable consistent service quality by capturing successful resolution patterns and identifying areas for improvement or targeted coaching.
• Advanced decision-making: AI can simultaneously analyze millions of variables and eliminate data silos, helping teams make more informed decisions about routing, prioritization, and resolution.
• Refined and personalized marketing: Genuine needs revealed during service interactions allow teams to identify upsell and cross-sell opportunities and offer contextually relevant recommendations that feel helpful rather than intrusive.
• Improved cost savings: Dynamic workflows that improve average handle time, minimize escalations, and increase self-service reduce the per-interaction cost of customer service.
• 24/7 support: Customers receive immediate, high-quality assistance at any hour, meeting modern customer expectations for instant service regardless of time zone or business hours.
• Reduced human error: AI boosts agent intelligence, improves procedural reliability, maintains consistency, ensures compliance, and enhances service quality, even during high-volume periods.

Additionally, according to the Zendesk CX Trends Report 2025, 68 percent of customers agree that human-centric AI agents—those exhibiting human-like traits, including personalization—matter, improving retention and customer loyalty.

Characteristics of AI agentic workflows

AI agentic workflows have distinct characteristics that separate them from traditionally automated workflows. These defining features include:

• Autonomy: AI agentic workflows operate independently, making judgment calls and taking action without human oversight.
• Decision-making models: Sophisticated decision frameworks allow AI agentic workflows to evaluate multiple factors and select responses based on immediate context and long-term objectives.
• Human management: AI is transforming human agents, allowing them to become AI managers while intelligent AI agentic workflows efficiently resolve or escalate tickets when necessary.
• Integrations: Well-managed workflows can integrate with current tech stacks, pulling information from and pushing updates to CRMs, order management systems, knowledge bases, and other platforms.

When these characteristics work in harmony, AI agentic workflows for CX transcend simple automation to become strategic assets that continuously refine customer interactions.

Examples of AI agentic workflows for CX

Consider these real-world examples that demonstrate the benefits of intelligent automation to illustrate the potential of AI agentic workflow for CX across different industries.

Customer service AI agentic workflow use case

Papier, an online stationery retailer, uses Zendesk AI agents to offer 24/7 support to customers, allowing the brand to expand its​​ business from the U.K. to the U.S. The brand used AI agents to identify common problems and build in-depth conversation flows for customer inquiries.

Suzanne Duffy, Papier’s head of customer service, says it best: “Even if the AI Agent isn’t resolving queries, it frees up agent time to work on the more complex issues. It will collect order IDs, ask for a picture upload if something is faulty, and it’ll do all of that legwork upfront.”

AI multi-agent workflow use case

After experiencing explosive growth, Unity, a development platform for 3D projects, needed to improve its CX system to address high ticket volumes. By creating multiple collaborative AI agentic workflows for ticket deflection, self-service, and more, Unity saved more than $1.3 million in service costs.

Finance AI agentic workflow use case

AI integrations are the name of the game when it comes to the partnership between Zendesk and Siemens Financial Services, a finance company. According to Steve Franklin, head of global customer services at Siemens, “Ultimately, we want to get to the point where we have a holistic global digital customer journey. With Zendesk as the foundation and the various apps and integrations such as AI sitting on top of that, we are getting closer and closer to achieving that.”

With AI agentic workflows, Siemens offers proactive customer service, 24/7 financial support, and autonomous responses to inquiries. Global productivity has also increased, and CSAT has reached 86 percent.

Marketing AI agentic workflow use case

With Zendesk, Honeylove, a direct-to-consumer fashion brand, markets to consumers through dynamic SMS messages. Honeylove can meet its customers where they are, provide 24/7 support, and prioritize a customer-centric strategy without sacrificing marketing quality.

Trevor Humphrey, Honeylove’s VP of customer experience, says that Zendesk has allowed them to align CX and marketing: “A customer expects the brand to know who they are, what they’ve done, and how to communicate in a genuine way … There was a whole missing piece of data around the customer support experience that we didn’t have on the marketing side. Now those two sides of the business are aligned.”

Human resources AI agentic workflow use case

LATAM Airlines is the leading airline in Latin America, serving 62 million passengers in 22 countries. After experiencing major success using Zendesk to improve customer service, the company pursued AI-powered employee service.

“We saw how our customer service team was working with Zendesk to become more efficient and improve the customer experience,” Monica Obando, senior HR manager at LATAM Airlines, said, “And we decided to bring that magic to our internal employee operations.”

With Zendesk, LATAM Airlines services more than 30,000 employees. Despite this extensive team, the company’s AI agents boast an 80 percent accuracy rate, massively improving people’s experiences, internal customer service, and organizational success.

5 steps for implementing AI agentic workflows

Transforming your CX with AI agentic workflows requires thoughtful planning and execution—just like introducing a new conductor to an established orchestra. Follow these steps to a successful and seamless workflow implementation:

1. Assess readiness

Before implementing AI agentic workflows, you need to assess the readiness of your company by evaluating your:

• Existing technology

• Data quality and data silos

• Team capabilities

• Customer touchpoints

Organizations with centralized customer data, standardized processes, clear performance metrics, and an open organizational culture tend to transition to agentic workflows more smoothly and are prepared for the change management required.

Identify automation opportunities

Map your customer journey to pinpoint high-impact opportunities where AI agentic workflows for CX can deliver the greatest value. These tend to be processes that are:

• Repetitive

• High-volume

• Defined by patterns

• Consuming significant agent time

Prioritize workflows and intelligent automation that directly impact key metrics like first contact resolution or customer satisfaction (CSAT) scores. Businesses must also document current performance metrics for these processes to establish baselines for measuring AI effectiveness.

3. Select your AI agent

Choose an AI-powered chatbot that aligns with your specific business needs, technical environment, and customer expectations.

Before investing in an AI agent, consider:

• Security and compliance

• Reporting and analytics

• Language processing capabilities

• Industry knowledge or adaptability

• Integration options

• Scalability

• Customization

Additionally, look beyond technical specifications to examine the vendor’s customer support track record, their approach to continuous improvement, and their roadmap for future capabilities. The right AI agent will serve as a foundation you can build upon, gradually expanding its abilities and responsibilities over time.

Train your team

If you plan to integrate AI in the workplace through AI agentic workflows for CX, you must prepare your team for their evolving roles. Offering training that focuses on technical platform operations and specialized skill development, including:

• Handling complex emotional situations

• Exercising judgment on exception cases

• Identifying when to intervene in automated processes

Create clear guidelines for the human-AI collaboration, defining handoff protocols and escalation paths. Allow agents to define workflows and leverage their expertise to foster buy-in and excitement.

5. Test each AI agentic workflow

Before full deployment, test each workflow in controlled environments with progressively increasing complexity. These tests should cover:

• Expected patterns

• Unassuming variations

• Exceptions

• Edge cases

Monitor each workflow’s technical performance and quality indicators by tracking metrics like accuracy, tone appropriateness, and brand adherence. Further, implement a feedback loop where agents can flag issues, suggest improvements during the testing phase, and prioritize a phased rollout to allow your team to refine the system while minimizing risk.

Challenges of AI agentic workflows for customer experience

While AI agentic workflows for CX offer tremendous potential, organizations must navigate some hurdles to realize their full benefits. However, businesses can mitigate these challenges with the right solution, like Zendesk.

• Bias: AI systems can unintentionally amplify biases in their training data, potentially leading to inconsistent service quality across demographics. With Zendesk, you can implement rigorous testing protocols and AI transparency initiatives to refine algorithms.
• Implementation: Integrating agentic workflows with existing legacy systems can be complex. However, the Zendesk Marketplace offers more than 1,700 integration options to simplify this process.
• Scalability: As expectations and needs evolve, workflows must grow without sacrificing performance or requiring complete redesigns. Zendesk is designed to scale with your business, allocating resources to continual improvements and optimizations.
• Security: AI agentic workflows operate with extensive access to sensitive customer data and critical business systems, creating potential vulnerabilities if not properly secured. With Zendesk, businesses have access to advanced privacy and customer data protection protocols.

Despite these challenges, the benefits of well-implemented AI agentic workflows with Zendesk substantially outweigh the obstacles.

Frequently asked questions

Papier

How an AI agent paved the way for Papier’s US expansion

“Even if the AI Agent isn't resolving queries, it frees up agent time to work on the more complex issues. It will collect order IDs, ask for a picture upload if something is faulty, and it’ll do all of that legwork upfront.”

Suzanne Duffy

Head of Customer Service

Read customer story

Seamlessly connect AI agentic workflows for CX with Zendesk

Just as a world-class orchestra requires brilliant musicians and an exceptional conductor, your CX strategy needs intelligent AI orchestration and powerful software to reach its full potential. By integrating AI agentic workflows with customer service software from Zendesk, you’re giving your CX symphony a conductor that ensures symphonic harmony and adapts to real-time customer expectations. Because the future of customer experience isn’t just automated—it’s intelligently orchestrated.