Workflow automation in 2025: Everything you need to know in one comprehensive guide
The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.
That was Bill Gates, from his 1996 book, The Road Ahead … published nearly 30 years ago.
The world — and automation — has changed a touch over the past three decades. Most recently, AI has introduced a new paradigm in how businesses think about automation.
Yet Gates’ words still ring true, arguably now more than ever.
Let’s revise that quote to one more applicable for 2025:
The first rule of any technology used in a business is that AI-powered automation applied to an efficient operation will magnify the efficiency. The second is that AI-powered automation applied to an inefficient operation will significantly magnify the inefficiency.
This article will go “all in” on workflow automation — everything you need to know, for now (technology moves quickly!). From defining it to sharing how it works in the real world, to best practices and benefits. We’ll explore how workflow automation addresses repeatable tasks that are performed across business processes.
Ready? Let’s start with a clear definition.
Workflow automation, defined
According to this Fall 2024 Gartner, Inc. blog post, in 2026, 30% of enterprises will automate more than half of their network activities, an increase from under 10% in mid-2023
Automation is essential! But what is workflow automation?
Workflow automation is the technology-enabled automation of activities or tasks that make up a business process, where human input is reduced by defining business rules and having technology automatically route items through the steps of a workflow. It is a way to automate tasks within a business process, focusing on streamlining repetitive, manual processes to increase efficiency, reduce errors, and free up human resources for more valuable work. Unlike robotic process automation (RPA), which typically automates a single task, workflow automation is designed to automate multiple interconnected routine tasks or simple tasks across a process.
TL;DR: Workflow automation transforms manual tasks into digital processes that adapt to conditions and optimize efficiency.
Workflow automation works as part of a broader process automation strategy, automating tasks across various steps to improve operational efficiency. Organizations use workflow automation tools—software solutions that enable them to automate workflows and integrate with other business systems.
Remember that Gartner stat above? In 2026, 30% of enterprises will automate more than half of their network activities.
We predict that stat to increase as we get closer to 2026. Why? The explosion of AI (more on AI in a bit).
Definition? ✅ Importance? ✅
To streamline your business processes, use workflow automation.
How does it actually work? Let’s review the mechanics of workflow automation.
How workflow automation software works: from trigger to action
Every automated workflow follows a fairly straightforward pattern that includes the following:
- Triggers: The events that start a workflow (think: ticket submission or capturing incoming data through a form)
- Rule(s): The “if-then” logic that determines how the workflow behaves
- Conditions: Specific criteria that must be met before actions occur
- Actions: The tasks that happen automatically (like assigning tickets, sending notifications, or updating records). Workflow automation tools handle tasks such as these automatically, reducing manual effort and errors.
To better visualize this process, here’s an example of a password reset service request.
Imagine a service request traveling through your Managed Service Provider (MSP) like a package with its own smart routing system. The typical journey may follow these six steps:
1. Trigger Activation: A user submits a password reset request.
2. Rule Application: The system checks user permissions and request type.
3. Condition Evaluation: Determines what type of user this is —standard or priority.
4. Action Execution: Routes to the appropriate support help, sends confirmation message (email, Slack, etc.), and creates a timeline entry.
5. Cross-Tool Movement (if applicable): Updates both the ticketing system and the customer portal simultaneously.
6. Department Handoff: Escalates to the appropriate team if permission changes are required.
Note: The above 6 steps have all occurred using AI … without human intervention.
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Other workflow automation examples include:
- Client onboarding, where workflow automation tools capture and consolidate incoming data from new clients and route it to the right team.
- Processing incoming data from web forms or partner portals, ensuring secure sharing and reducing errors.
- Automating invoice approvals, lead follow-up, and social media monitoring.
These examples show how workflow automation tools can handle tasks across different business processes.
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Xurrent example: Our AI-Powered Automation Builder empowers users to describe automations in plain English. Tell Xurrent’s AI how you want the automation to work … like “send an email to the manager when a high-priority ticket is unassigned for more than 30 minutes”… and the platform builds it automatically. With Xurrent, you can automate workflows and quickly create new workflows using customizable templates and low-code options.
This conversational approach saves 5-30 minutes per automation compared to traditional manual configuration.
Not too shabby.
But that’s just one of the many benefits. Here are a few more.
The many benefits of workflow automation for repetitive tasks
Workflow automation streamlines repetitive tasks, boosts productivity, and reduces human error. The net result: organizations free employees for creative work while ensuring consistency and compliance across operations. By automating low value tasks and reducing manual work, companies are improving efficiency and enabling staff to focus on higher-impact activities.
Here are a few specific benefits.
Increased efficiency: cut manual task time in half
When repetitive tasks like ticket routing, password resets, and system monitoring are automated, techs spend significantly less time on administrative work. This means you can handle more tickets without increasing headcount. Automating low value tasks and manual work directly contributes to improving efficiency across the organization.
Fewer errors: standardized processes = fewer mistakes
Human errors in IT service delivery can be costly. Automated workflows ensure consistent handling of each request by following predefined rules and validation steps. Critical information is never missed, configurations are applied correctly every time, and documentation becomes comprehensive and accurate.
Better collaboration: shared visibility and task ownership
Automation creates a central, single source of truth across departments. Everyone sees the same status updates, knows precisely where a request stands, and understands who owns the next action. This transparency eliminates the “I didn’t see it” scenario, building trust through consistent communication. Project managers benefit from streamlined workflows, as automation helps them assign tasks, track progress, and ensure projects stay on schedule.
Scalability: run the same process across 10 or 10,000 users
As your MSP grows, manually managing increased ticket volume becomes unsustainable. Automated workflows handle growth without proportional staffing increases. The same processes work for SMBs and enterprise organizations. Scale the business without significantly increasing operational costs.
Improved decision-making: more time spent analyzing, not collecting
When data collection and reporting become automated, your team can focus on analyzing trends and making strategic decisions. Instead of building reports, they can use that time to identify recurring issues, spot potential service improvements, and develop proactive maintenance strategies.
Workflow automation empowers knowledge workers and business users by freeing them from repetitive, manual work. This allows them to focus on problem solving, creativity, and higher-level decision-making, leading to greater productivity and job satisfaction.
For example, workflow automation can help social media managers create content, schedule posts, and track engagement, or optimize marketing campaigns by automating campaign launches and performance analysis.
Sounds good, right?
But not all workflow automation capabilities are the same.
The 5 levels of workflow automation
The various “levels of maturity” of workflow automation capabilities are similar to the “evolution of a coffee drinker.”
Level 1: “What’s this bitter stuff?”
Level 2: “I need caffeine to function.”
Level 3: “Actually, I prefer medium roast.”
Level 4: “Let me tell you about this single-origin Ethiopian…”
Level 5: “I roast my own beans.”
The 5 levels of workflow automation are not all that different — each one gets a bit more sophisticated
Level 1: Manual workflows with triggered automation
Level 2: Rule-based automation
Level 3: Orchestrated multi-step automation
Level 4: Adaptive automation with intelligence
Level 5: Autonomous workflows
Let’s break each one down:
Level 1: Manual workflows with triggered automation are limited to specific tasks within a largely manual process. Characterized by task-based automation and human-initiated actions, it has no orchestration across steps. Robotic process automation (RPA) is often used at this level to automate a single task, such as data entry or calculations, while workflow automation can handle more complex workflows that involve multiple steps.
Example: A website form submission sends an email notification. A human handles the remainder of the process.
Level 2: Rule-based automation is when processes are automated based on predefined rules and conditions. Characterized by IF/THEN logic and limited decision branching, it still requires human oversight to handle exceptions.
Example: A “high priority” ticket is automatically escalated to Tier 2.
Level 3: Orchestrated multi-step automation is when multiple tasks and systems are connected sequentially to form an end-to-end automated workflow. Characterized by cross-functional coordination and workflow visualization tools, this level of automation requires fewer human handoffs. At this stage, business process automation and business process management frameworks often integrate workflow automation and RPA to optimize organizational processes and improve efficiency.
Example: A new employee onboarding triggers the creation of accounts in multiple systems, sends welcome emails, and assigns tasks.
Level 4: Adaptive automation with intelligence leverages AI/ML to adapt workflows based on data patterns and past outcomes. Characterized by predictive decision-making and learning from outcomes, this automation has dynamic workflows that adjust over time. AI models and natural language processing enable these systems to understand unstructured data, make context-based decisions, and interact more naturally with users.
Example: System routes tickets to the most effective agent based on historical resolution times and expertise.
Level 5: Autonomous workflows are fully automated, self-optimizing workflows operating with minimal human intervention. Characterized by closed-loop automation and real-time data-driven decisions, these automations continuously improve via feedback loops. Advanced AI models and natural language capabilities further enhance the ability to handle complex workflows autonomously.
Example: An incident management system detects anomalies, creates a ticket, runs diagnostics, triggers resolution scripts, and updates stakeholders automatically.
The most sophisticated workflow automation systems integrate with various applications and data sources, powering seamless information and data flow across departments and tools while maintaining audit trails and meeting compliance requirements. Citizen developers now play a key role in building, managing, and optimizing these automated workflows, making automation more accessible across organizations.
And last, but certainly not least, it’s time to talk about AI. After all, what would a blog post be in 2025 without those two letters?
Integration capabilities and collaboration in workflow automation
One of the most powerful features of modern workflow automation software is its ability to seamlessly integrate with a wide range of business tools and systems. Whether you’re connecting your CRM, ERP, HRIS, or other essential platforms, integration capabilities are the backbone of implementing workflow automation that truly transforms business operations.
By linking multiple workflows across departments, businesses can automate complex processes that once required hours of manual labor. For example, when a new client is onboarded, automated workflows can assign tasks to the right person in sales, trigger data entry in finance, and update records in HR—all without manual intervention. This not only streamlines workflows but also ensures that information flows accurately and instantly between systems, reducing the risk of errors and delays.
Integration capabilities also foster better collaboration. When workflow automation software connects different teams and tools, everyone has access to the same up-to-date information, making it easier to coordinate efforts and keep projects moving forward. Assigning tasks, tracking progress, and sharing updates become effortless, allowing teams to focus on strategic work rather than chasing down information or handling repetitive manual tasks.
Ultimately, by automating workflows and integrating with other tools, businesses can boost productivity, reduce errors, and deliver a smoother, more satisfying experience for both employees and customers. The result? Happier teams, more efficient business processes, and higher customer satisfaction—all driven by the right automation software.
Data collection and analysis for smarter automation
Data is the fuel that powers smarter workflow automation. Automated workflows are not just about moving tasks from point A to point B—they’re about collecting valuable data at every step of the process. By gathering information from customer interactions, service requests, and internal workflows, businesses gain a comprehensive view of their operations.
This data collection enables organizations to identify inefficiencies, redundant tasks, and repeatable processes that are ripe for automation. For instance, if data analysis reveals that a particular service request is handled manually dozens of times a week, it’s a clear candidate for automation. By automating these low-value, time-consuming tasks, businesses can free up resources for more strategic work that drives growth.
Real-time insights from data analysis also empower businesses to make informed, agile decisions. Instead of relying on guesswork, teams can use concrete data to refine their automation processes, boost efficiency, and respond quickly to changing business needs. Whether it’s optimizing internal workflows or enhancing customer satisfaction, data-driven automation ensures that every workflow is continuously improving.
In short, by leveraging data collection and analysis, businesses can create automated workflows that are not only efficient but also intelligent—constantly learning, adapting, and delivering better results.
AI and workflow automation: The icing on the cake
Before automation, marketing was like driving without a map — relying on intuition alone, often getting lost.
Then automation arrived. Google/Apple Maps provides clear, optimized directions with basic traffic updates.
Weave in AI, and the entire experience is elevated. You are now a passenger in a self-driving car, one that drives for you while optimizing the route based on real-time traffic, weather patterns, and your schedule. The vehicle anticipates obstacles before they appear, suggests better destinations based on your preferences, and continuously improves with each journey.
This progression shows how automation created efficiency, but AI delivers intelligence — transforming marketing from a guided process into an adaptive system that optimizes performance while freeing your team to focus on strategy and creativity. AI-powered automation can now handle tasks that were previously too complex or unstructured, thanks to advanced AI models and natural language processing. This enables automating tasks across complex workflows, including routine tasks and low value tasks, which frees employees to focus on higher-level, strategic work.
Said another way, the most “sophisticated” workflow automation uses intelligent decision-making capabilities — via AI and ML (machine learning) — to address complex scenarios, exceptions, and atypical cases. As a result, AI automation is augmenting job roles by allowing human workers to focus on creativity and problem-solving, rather than being replaced.
AI is the icing and the cherry on top of an already fabulous cake.
Modern workflow automation platforms (see Xurrent) offer no-code/low-code interfaces to easily build, design, and modify these workflows. With the help of AI, workflow automation systems can adapt to changing conditions, learn from patterns, and continuously optimize processes.
AI has (forever, likely) changed workflow automation by transforming it from a rule-based system for handling repetitive tasks into an intelligent framework capable of learning, adapting, and making decisions.
AI executes predefined tasks to create intelligent, adaptive systems that can learn and improve over time. Traditional workflow automation follows rigid, rule-based processes that work well for simple, repetitive tasks but lack flexibility for more complex, modern service management challenges.
AI workflow automation is:
✓Adaptive. ✓Scalable. ✓Able to handle complex processes.
All with minimal (or no) human intervention.
AI-embedded workflow automation vs. traditional workflow automation means that service management platforms now can:
Make intelligent decisions: AI enhances automation by using historical data to recommend optimizations and trigger approvals, enabling systems to make data-driven decisions without constant human intervention. This allows workflows to dynamically adapt to changing conditions … in real-time.
Leverage unstructured data: While traditional automation struggles with unstructured inputs like emails, images, and voice data, AI-powered systems can natively understand and process these varied formats, greatly expanding automation possibilities.
Take advantage of predictive analytics: AI applies predictive analytics to workflow management, allowing businesses to anticipate future outcomes based on historical data. This capability enables forecasting demand, optimizing resource allocation, and identifying potential bottlenecks in workflows before they occur.
The business impact of AI-enhanced workflow automation is substantial.
From that same Gartner report (above), 44% of respondents indicate that “GenAI will automate repetitive and manual tasks in I&O [Infrastructure & Operations] workflows, increasing efficiency and reducing human effort.”
However, a critical prerequisite remains: processes must be appropriately documented and structured first to fully leverage AI’s potential.
Up next: How to kickstart (or improve) your workflow automation programs.
5 best practices for ramping up your workflow automation
With any new (or improved) process, coming out too hot out of the gate could be disastrous. Instead, we recommend starting small—common use cases like client onboarding are ideal for initial workflow automation efforts. Business users and citizen developers can leverage workflow automation tools to build and manage new workflows efficiently. Follow these 5 best practices to ensure success.
Best practice #1: Start small: Pick one process
Beginning with a single, manageable process allows you to demonstrate value quickly without overwhelming your team. Pick one workflow automation — say onboarding or SLA approvals — and master it before moving on to the rest of the organization.
Apply ITIL frameworks to categorize processes and identify tasks with high potential for automation, prioritizing based on business impact and SLA alignment. We suggest password resets, ticket routing, or standard service requests as your starting point.
Best practice #2: Map first, then automate
Before automating any process, thoroughly document and analyze its current state. What's working? What's not? Where are the bottlenecks? What can be automated?
Strategic planning keeps automation efforts aligned with the overall company and/or IT department objectives. Be sure to set clear goals, assess available resources, and identify the processes that will benefit most from automation.
If possible, create visual process maps that uncover possible redundancies. In other words, be sure you are automating an optimized workflow, not a broken one.
Best practice #3: Include stakeholders
Don't automate in a vacuum! Involve both technical teams and end-users in the automation planning process. Foster collaboration and encourage feedback to continuously refine and improve automation strategies.
Technicians can identify what tasks consume their time, while users can highlight pain points in service delivery.
Best practice #4: Monitor. Measure. Iterate. Improve
Successful automation is an ongoing process, not a one-and-done deal. Creating a uniform process simplifies operations and instills a sense of predictability in ITSM operations. Create dashboards to track key metrics like resolution time, ticket volume, and automation success rate, then use this data to continuously improve each automated workflow.
Best practice #5: Keep humans in the loop
Not every aspect of a workflow should be fully automated. ITSM automation tools can handle many tasks, allowing IT staff to concentrate on more challenging problems and essential plans. But be sure to leave more complex decision-making to experts.
Design workflows with decision points where human judgment adds value, particularly for exceptions, possible outliers, and high-impact changes.
The future is now.
Measuring success: How to track efficiency and ROI in workflow automation
Implementing workflow automation is just the beginning—measuring its impact is what ensures lasting success. To truly understand how automation is transforming your business operations, it’s essential to track key performance indicators (KPIs) that reflect efficiency, productivity, and quality.
Metrics like process cycle time, throughput, and defect rate provide a clear picture of how automated workflows are performing. By monitoring these KPIs, businesses can pinpoint bottlenecks, reduce errors, and identify opportunities for further optimization. Collaboration tools play a crucial role here, offering real-time visibility into workflow performance and making it easy for teams to track progress and share insights.
Calculating ROI is another vital step. By comparing the costs of manual processes with the savings and increased efficiency delivered by automation, businesses can quantify the financial benefits of their investment. Improved productivity, faster turnaround times, and higher customer satisfaction all contribute to a compelling ROI.
Regularly measuring the success of workflow automation ensures that your processes remain aligned with strategic business goals. It also creates a culture of continuous improvement, where every workflow is refined to deliver maximum value. In today’s fast-paced business environment, tracking efficiency and ROI isn’t just good practice—it’s essential for staying ahead.
The future of work is ... automation — workflow automation
Bill Gates' words about automation remain as relevant in 2025 as in 1996, with one critical update: AI has dramatically amplified both the potential and the stakes. Workflow automation has evolved from simple rule-based systems to intelligent frameworks that can learn, adapt, and make decisions autonomously ... thanks to AI.
By strategically implementing workflow automation, starting with well-documented processes, organizations will create the foundation for top-notch efficiency. When repetitive tasks are automatically handled (sans human intervention), your team gains valuable time for strategic work that truly requires human expertise. The numbers tell a compelling story — reduced errors, faster resolution times, improved client satisfaction, and healthier profit margins.
Xurrent's Workflow Automation Platform — complete with our AI-Powered Automation Builder — represents the cutting edge of this evolution, allowing you to describe workflows in plain English and have them built automatically. This conversational approach saves 5-30 minutes per automation (at 100 automations per year, that is an 8.4-50 hour time savings!) and democratizes the creation process, removing technical barriers previously limiting automation to specialists.
Workflow automation isn't optional for growing organizations. In today's business environment, where clients demand more for less, automation is the difference between thriving and merely surviving.
The companies that master workflow automation will be on the leading edge of efficiency, reliability, and client satisfaction, while those who delay will struggle to catch up in an increasingly automated world.
Which side of the equation do you stand on?
FAQs
1. What is workflow automation?
Workflow automation is the technology-enabled automation of activities or tasks that comprise a business process, where human input is reduced by defining business rules and having technology automatically route items through the workflow's steps. It focuses on streamlining repetitive, manual processes to increase efficiency, decrease errors, and free up human resources for more valuable work. Unlike robotic process automation (RPA), which typically automates a single task, workflow automation is designed to automate multiple interconnected routine tasks across a process.
2. How does workflow automation software work?
Every automated workflow follows a straightforward pattern that includes triggers (events that start a workflow like ticket submission), rules (the "if-then" logic that determines how the workflow behaves), conditions (specific criteria that must be met before actions occur), and actions (the tasks that happen automatically like assigning tickets, sending notifications, or updating records). The system routes requests through appropriate steps based on predefined logic, often without human intervention.
3. What are the main benefits of workflow automation?
The key benefits include increased efficiency (cutting manual task time in half), fewer errors through standardized processes, better collaboration via shared visibility and task ownership, scalability (running the same process across 10 or 10,000 users), and improved decision-making by freeing up time for analysis rather than data collection. Organizations can handle more work without increasing headcount while ensuring consistency and compliance across operations.
4. What are the 5 levels of workflow automation?
The five levels are: Level 1 (Manual workflows with triggered automation - limited to specific tasks within largely manual processes), Level 2 (Rule-based automation using IF/THEN logic with human oversight), Level 3 (Orchestrated multi-step automation connecting multiple tasks and systems sequentially), Level 4 (Adaptive automation with intelligence leveraging AI/ML to adapt workflows based on data patterns), and Level 5 (Autonomous workflows that are fully automated and self-optimizing with minimal human intervention).
5. How does AI enhance workflow automation?
AI transforms workflow automation from rule-based systems into intelligent frameworks that can learn, adapt, and make decisions. AI-enhanced automation can make intelligent decisions by leveraging historical data, utilizing unstructured data such as emails and images, and utilizing predictive analytics to anticipate future outcomes. This creates adaptive, scalable systems that can handle complex processes with minimal human intervention, thereby moving beyond rigid, predefined rules.
6. What are the best practices for implementing workflow automation?
The five best practices are: Start small by picking one manageable process to demonstrate value quickly, map first then automate by thoroughly documenting and analyzing current processes before automation, include stakeholders from both technical teams and end-users in planning, monitor and measure results to continuously iterate and improve, and keep humans in the loop for complex decision-making and exceptions while automating routine tasks.
7. What's the difference between workflow automation and robotic process automation (RPA)?
RPA typically automates a single task, while workflow automation is designed to automate multiple interconnected routine tasks across a process. Workflow automation is part of a broader process automation strategy, automating tasks across various steps to improve operational efficiency. In contrast, RPA focuses on specific, isolated tasks within a larger manual workflow.
8. How do you measure the success of workflow automation?
Success is measured through key performance indicators (KPIs) like process cycle time, throughput, defect rate, resolution time, ticket volume, and automation success rate. ROI is calculated by comparing the costs of manual processes with the savings and increased efficiency delivered by automation. Regular monitoring through dashboards helps track these metrics and identify opportunities for further optimization and continuous improvement.
9. What role do integration capabilities play in workflow automation?
Integration capabilities allow workflow automation software to seamlessly connect with a wide range of business tools and systems like CRM, ERP, and HRIS platforms. This enables complex processes across departments to be automated, ensuring information flows accurately between systems while reducing errors and delays. Integration fosters better collaboration by providing teams with access to the same up-to-date information, making coordination effortless.
10. How does data collection and analysis improve workflow automation?
Data collection at every step of automated workflows enables organizations to identify inefficiencies, redundant tasks, and processes ripe for automation. Real-time insights from data analysis empower businesses to make informed decisions, refine automation processes, and respond quickly to changing needs. This creates intelligent automated workflows that continuously learn, adapt, and deliver better results based on concrete data rather than guesswork.