Blog / January 24, 2025

The Ultimate Guide to Agentic Workflows: What they are, key components, benefits, and examples

Ashmita Shrivastava, Content Marketing Manager

agentic workflows guide

What if the repetitive processes that slow your team down could run on autopilot? 

Imagine tasks like resetting passwords, approving time-off requests, or answering routine questions happening instantly and accurately — freeing up your team to focus on more strategic work.

That’s exactly what agentic workflows can do for you.

Agentic workflows represent a major leap forward in automation. By combining artificial intelligence (AI) with automation, these workflows are designed to handle not just simple tasks but complex, multi-step processes with precision. 

This isn’t just hype. Gartner has named agentic AI one of the top technology trends for 2025. By 2028, 33% of enterprise software will use agentic AI, and at least 15% of day-to-day work decisions will be made autonomously. 

For you, this means less time on mundane tasks and more time focusing on innovation and growth.

Let's learn more about agentic workflows: how they work, their benefits, and real-world examples that show how they can transform your business operations.

What are agentic workflows?

Agentic AI workflow is a series of tasks performed seamlessly and automatically, without the need for human assistance. These workflows use intelligent AI systems to automate and optimize sequences of tasks. 

While agentic AI serves as the engine, an agentic workflow is the structured series of actions this AI drives to achieve specific outcomes. 

Think of it as automation on steroids. While automations can handle simple repetitive tasks, agentic workflows take things a step further, by interpreting and streamlining complex and large-scale processes. 

Once an agentic workflow is set up, your team no longer has to manually fill the gaps that traditional automation may leave behind (or not be able to address at all). 

These workflows can have a huge impact on operations — so much so that experts predict that 50% of businesses using generative AI will implement agentic AI pilots by 2027. 

Investors also clearly recognize the potential, with over $2 billion poured into agentic AI startups in the past two years.

So, what does this mean for you? Agentic workflows let you: 

  • Automate more
  • Optimize faster
  • Improve processes
  • Reduce manual errors
  • Scale smarter

Let’s dive deeper into how they work and the difference they can make for your business. 

Basics of agentic AI workflows

An agentic AI workflow is a well-oiled machine that runs on its own. Imagine a series of tasks performed seamlessly and automatically without employee assistance. These workflows rely on AI systems capable of making decisions and learning along the way.

At the heart of agentic workflows is agentic AI, a technology driving the next evolution of enterprise AI. Unlike traditional AI, which requires constant human supervision, agentic AI enables systems to operate autonomously. This means it can pursue complex goals that atraditional AI couldn’t handle on its own. 

How do agentic workflows work?

Agentic workflows rely on a few key technologies to carry out intricate tasks:

Machine learning (ML) algorithms

These allow AI models to learn from data over time, adapting and optimizing processes. So the workflow can improve continually without human help. Algorithms analyze information, make predictions, and ultimately help streamline operations.

Natural language processing (NLP) 

This helps the AI understand and respond to human language inputs. Whether it’s managing customer inquiries or generating detailed reports, NLP allows workflows to handle complex, conversational tasks.

Robotic process automation (RPA) 

RPM works in tandem with agentic AI to handle repetitive, rule-based tasks. Together, these technologies create a reliable framework for automating even the most complex workflows with minimal effort on your part.

Consider a real-world scenario: an AI-driven customer support system can use an agentic workflow to autonomously handle common questions. 

It’s 2025, and AI is now handling about 95% of customer interactions. AI gathers data, understands queries through NLP, and uses continuous, deep learning to provide helpful, accurate answers. 

The result? Your team no longer has to manually handle repetitive inquiries. 

Studies show that AI-driven workflows like this can reduce average customer handle time by 27%, saving time and keeping your customers happy! 

Now, let’s bring it closer to home. You could also use agentic HR workflow automations for your onboarding process — from training schedules to paperwork — ensuring everything is completed quickly and accurately. 

These workflows ensure that tasks are completed quickly and accurately, helping get your new hires up and running faster and with less friction. 

Key components of agentic workflows

To understand how agentic workflows operate, let’s break them down into their core components:

AI agents

While traditional AI agents are designed based on existing models and training data, agentic AI agents are built to evolve and adapt over time. 

Agentic agents are often more flexible and capable of learning in environments where traditional AI might struggle without constant human guidance or training.

Large language models (LLMs)

AI agents use the power of machine learning and large language models (LLMs) to make decisions and perform tasks autonomously. 

One key feature of AI agents is their ability to use reasoning and perception. This means they can analyze data and understand situations — much like humans. 

So agents can make informed decisions and take action based on them. They manage tasks, assess progress, and adjust plans as needed. 

Agentic workflow patterns

Agentic workflow patterns are the foundation of how AI agents achieve goals, make decisions, and adapt over time. They focus on flexibility and continuous improvement, using four key elements: planning, tools, reflection, and multi-agent collaboration. 

Let’s break these down so you can see how they work for you. 

Planning

Planning means mapping out workflows, anticipating challenges, and preparing strategies for deployment. 

By decomposing tasks into smaller, manageable parts, such as automating password resets or PTO approvals, planning ensures precise execution of organizational processes. This step enables the AI to handle each task efficiently and prepare for potential complications.

Tool use

Tools play a critical role in agentic workflows by aiding in automation and task execution. Consider a scenario where you submit an IT issue like a software installation request. 

With appropriate tools, the workflow instantly verifies access permissions, triggers the installation process, and updates the system logs—all without human intervention. 

These tools, including AI agents and workflow orchestration platforms, continuously optimize business processes based on real-time environmental feedback.

Reflection

Reflection is where you assess completed tasks, evaluate outcomes, and refine methods for future tasks. 

For instance, say a workflow manages customer service inquiries. Reflection might reveal that response times are great but certain complex queries still require manual input. 

Using this insight, you could tweak the workflow to escalate those queries faster or add additional AI capabilities to handle them.

Ongoing evaluation helps in understanding what worked well and what needs improvement, enabling adaptation to changing needs and enhancing decision-making patterns.

Multi-agent collaboration

Multi-agent collaboration combines different perspectives and capabilities to solve complex problems, thus improving operational efficiency and supporting content generation and generative AI technologies.

Studies find that multi-agent collaboration can boost AI performance up to 10.5% across multiple language model benchmarks. 

Further, Amazon finds that multi-agent collaboration shows marked improvements compared to single-agent systems for handling complex, multi-step tasks.

By leveraging multiple agents working together, agentic workflows can tackle more sophisticated challenges and optimize performance.

Common types of agentic workflows

Agentic AI workflows are changing the way tasks are completed, allowing for flexibility, innovation, and better problem-solving. Let’s explore some common types and how they can impact your workplace.

  • Personal productivity workflows 

Examples include goal-setting systems. Only 16% of employees say their company is effective at setting and communicating goals. 

By automating this process, you can bridge the gap and enhance productivity.

  • Creative problem-solving workflows

Examples include design thinking processes where you empathize, define, ideate, prototype, and test to innovate solutions, and agile iterations where continuous development cycles help optimize creative and technical tasks.

  • Collaborative decision-making workflows

Examples include workflow automation in teams. Tools like Slack or Asana integrations can help assign and track tasks in shared projects. These tools now integrate AI into their workflows which acts like another teammate. 

  • Automated agent workflows

Examples include AI-driven chatbots that respond to customer inquiries with context-aware recommendations, and robotic process automation (RPA) which automates repetitive, rules-based tasks, such as invoice processing or data entry.

Benefits of agentic workflows

Agentic workflows offer advantages across every aspect of your business. They improve productivity, drive autonomous systems and decisions, support continuous improvement, and reduce operational costs.

Here are the seven key advantages of adopting agentic workflows:

1. Increased efficiency and productivity

AI-driven workflows break tasks into manageable pieces, enabling you to complete work faster. Repetitive, multli-step tasks are handled seamlessly, freeing your team to focus on high-priority initiatives that drive impact.

According to McKinsey, AI could deliver an extra $200 billion to $340 billion annually through productivity improvements.

Productivity soars when humans and machine-driven processes work together.

2. Autonomous decision-making

Agentic workflows enable real-time, AI-driven decisions, saving manufacturers 10-15% in operating expenses, up to $30 million annually. 

Here’s why: 

  • Agentic workflows can adapt without human intervention, so decisions are made quickly. 
  • Workflows also help your systems analyze data and respond in real time. 
  • Ongoing self-evaluation encourages an environment that’s always improving.
  • Workflows naturally evolve, leading to better use of resources.

3. Constant improvement

With machine learning at their core, agentic workflows support your business’s continuous development. Machine learning helps your systems identify areas for improvement, analyze performance data, learn from results, and adjust processes for better future results.

How this works:

  • Feedback loops: AI agents collect feedback on performance and outcomes after each task execution, using this data to refine their models and improve execution in the future. 
  • Learning from interactions: As user interactions increase, AI agents progressively improve their understanding and task execution capabilities.
  • Self-reflection: AI systems use data-driven methods like reinforcement learning to fine-tune their performance, which involves analyzing and learning from data to improve outputs.

4. Better user experience

Agentic workflows create smoother, faster interactions for customers and employees. They do this by dynamically responding to customer inquiries in real-time, learning from each interaction to continuously refine and personalize the user experience. 

With agentic AI that learns and adapts over time, customers benefit from more relevant, accurate, and helpful responses. 

This boosts satisfaction, which is terrific for lowering churn and retaining more customers long term. Stellar user experiences also add to your bottom line: retaining a current customer is 5–25 times less expensive than acquiring a new one.  

5. Scalable automation

Agentic workflows allow you to easily scale as your needs grow. 

As your operations grow and become more complex, agentic platforms can dynamically incorporate new technologies. This lets you automatically adjust workflows based on performance data and operational requirements, keeping up with changing environments without additional manual oversight. 

For example, whether you’re serving ten clients or ten thousand, workflows ensure consistent service delivery with minimal extra effort.

6. Reduced costs

Agentic workflows help you better allocate resources, reduce waste, improve operational efficiency, and can generate cost savings as much as 20–30%. Automation reduces the costs associated with manual labor and errors, since you’re automating repetitive tasks. 

You’re lowering the number of mistakes made since your employees don’t have to do these tasks anymore. 

And here’s something to keep in mind: reduced expenses obviously contribute to a healthier bottom line, but you also free up capital for other investments that drive growth.

Limitations of agentic workflows

Like any technology, agentic workflows have their limitations. Here’s what to watch out for:

  • Reliance on high-quality data: If the input data is flawed or biased, your workflow can produce unexpected or inaccurate results. You should ensure data accuracy to prevent these issues.
  • Complex integration with existing systems: Implementing agentic workflows often needs a huge amount of time, expertise, and financial resources. You'll need skilled team members to ensure smooth integration and operation.
  • Limited reasoning: While these systems handle many tasks autonomously, they may struggle with tasks requiring nuanced decision-making. This is where human intervention becomes necessary for reliability and accuracy.
  • Handling unstructured or sensitive data: Agentic workflows excel with structured data, but unstructured data — which lacks a clear format — can be problematic and need extra processing. 

Sensitive data must be handled cautiously. The automated nature of agentic workflows needs stringent security measures to protect any sensitive information.

  • Compatibility issues with traditional AI: While agentic workflows give you advanced features, ensuring smooth communication with existing AI is crucial for a seamless operation.

AI agentic workflows: Use cases and examples

While there are many applications for agentic workflows in business operations, let’s discuss four time-saving, impactful use cases where you can start benefiting from right away: password resets, time-off approvals, customer service, and cybersecurity. 

 

1. Password resets

Password resets make up around 40% of all IT service desk calls. AI-powered systems can manage and automate these password resets so your employees don’t have to wait for assistance. 

When someone forgets their password, AI helps by verifying their identity through multi-step processes, allowing them to regain access quickly. Agentic workflows can save time and reduce costs by automating this task — requests are handled quickly around the clock, offering a smooth user experience.

 

2. Time-off approvals

Approving time-off requests is a time-consuming task for HR departments, especially during peak vacation seasons. Automation can ensure requests are processed smoothly and without delays. 

AI agentic workflows can simplify this by analyzing employee schedules, department needs, and workload impacts before granting approvals. An AI system using reasoning to check against schedules, remaining leave balances, and workload impact, so that its decisions are well-informed.

HR departments can also focus on more strategic tasks when they no longer have to handle time-off requests. Employees enjoy faster responses, making the process more fluid and predictable. 

3. Customer service

AI enhances customer service by providing instant adaptive responses to common inquiries and automating repetitive tasks. For example, in customer service automation, these systems can handle routine questions autonomously, escalating more complex issues to human agents with relevant context.  This can help to speed up resolution times, improve customer satisfaction, and free up human agents to handle more complicated issues. 

And don’t forget that AI systems can continuously learn from interactions, so their responses improve over time. You can also integrate them with your CRM so they provide personalized experiences through predictive analytics. Your customers enjoy consistent, high-quality interactions and you improve your brand reputation and customer loyalty.

4. Cybersecurity

AI also plays a role in cybersecurity through dynamic threat detection and response capabilities. Instead of relying on fixed rules, these systems analyze patterns, detect anomalies, and adapt to new threats in real time.

This proactive approach not only mitigates risks faster but also evolves to handle sophisticated cyber-attacks. In this way, it can provide robust, ever-improving defense mechanisms for your organization.

AI's monitoring systems are capable of acting swiftly during incidents, reducing response times and damage. These systems continually adjust to new threats, giving you improved protection for your organization's sensitive data.

Streamline your workflows with Moveworks agentic AI 

Agentic workflows aren’t just about saving time — they’re about transforming how your organization operates. 

Tools like Moveworks AI Assistant make it easy to implement and scale these intelligent workflows across your organization, ensuring efficiency and adaptability. 

With Moveworks AI Assistant, you can:

  • Automate routine tasks across IT, HR, and other departments, from password resets to PTO approvals, without needing to switch between multiple apps. 
  • Complete tasks end-to-end seamlessly, handling everything from routine requests to complex onboarding processes without switching between apps. 
  • Developers can customize workflows in minutes with Moveworks Creator Studio, ensuring they fit your team’s needs perfectly and scale with your organization.

These tools not only accelerate your workflows but also adapt to your unique business environment. This means you can focus on strategic initiatives – instead of getting bogged down by repetitive tasks.

 

Find out how easy it is to supercharge your most used enterprise systems with an AI agent roadmap! Just check a few boxes and get your own customized AI agent roadmap.

 

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