Table of contents
Highlights
- Agentic automation combines large language models, reasoning engines, and generative AI to enable software agents to perceive, reason, and act autonomously across complex, multi-step enterprise workflows without constant human intervention.
- Unlike RPA and intelligent automation, which rely on predefined rules and structured inputs, agentic automation is designed to adapt in real time to dynamic conditions, making it a capable option for enterprises managing high-volume, judgment-heavy processes across departments.
- The business case is clear: enterprises that deploy agentic automation see measurable gains in efficiency, accuracy, decision-making speed, and employee experience.
- Getting started with agentic automation doesn't require a full-scale transformation. Enterprises that see the fastest results begin by identifying high-volume, repetitive workflows in IT or HR, where the potential for measurable impact tends to be most immediate.
- Moveworks brings agentic automation to life across IT and HR through a purpose-built platform that combines a proprietary Reasoning Engine with out-of-the-box enterprise integrations, helping customers like Broadcom autonomously resolve 88% of support issues without human intervention.
It's Monday morning. An employee can't access a critical system to complete their work, so they submit an IT ticket. On Wednesday, that ticket is still sitting in a queue: unassigned, unresolved, and quietly costing your business.
But often, the bottleneck is the automation layer itself. Most rule-based automation tools do exactly what they're told and nothing else. As soon as a request requires any degree of judgment, traditional automation stalls.
Agentic automation is built to address this gap. In fact, 79% of senior execs say their companies actively use AI agents, and 66% say agentic AI is already delivering measurable productivity value.
Here, we'll break down the benefits agentic automation is positioned to deliver across real-world enterprise use cases, plus a roadmap to deployment.
What is agentic automation?
Agentic automation is the application of agentic AI to automate workflows. Taking this approach can enable systems that perceive context, plan a path forward, and execute autonomously to achieve goals.
Unlike traditional automation that follows a specific script, agentic systems are designed to adapt in real time to handle complex, multi-step tasks across systems, with little to no manual human intervention.
How agentic automation works
Agentic automation combines three core AI technologies:
- Large language models (LLMs) interpret and generate human language, making it possible to understand employee requests in natural, conversational terms.
- Large action models (LAMs) determine what actions to take and execute them across enterprise systems.
- Generative AI produces outputs, including written text, decisions, or instructions, in response to real-world conditions.
When used together, these technologies create a continuous loop of perceive → reason → act. Here's how this works:
- An employee requests software access.
- The system reads the request and its context.
- AI determines what approvals and systems should be involved.
- The request gets routed to the right team or system automatically.
- Access provisions and approval workflows get triggered without manual intervention.
An orchestrator ties all of these elements together, acting as a coordination layer that selects and sequences actions toward a goal, rather than executing a single predefined workflow.
Agentic automation vs. other types of automation
There are various forms of traditional and AI-powered automation enterprises can use. Below are three of the most common types and how they differ.
Robotic Process Automation (RPA) | Intelligent Automation | Agentic Automation | |
How it works | Follows predefined rules to execute repetitive, structured tasks | Combines RPA with AI and machine learning to enable smarter decision-making | Perceives context, reasons through complexity, and acts autonomously across systems |
Best suited for | High-volume, rule-based tasks with little variation (data entry or invoice processing) | Semi-structured workflows that benefit from pattern recognition and basic judgment | Dynamic, multi-step workflows that require real-time adaptation and cross-system action |
Key limitation | Breaks down when rules change or exceptions arise | Still relies on human oversight for complex or unpredictable scenarios | Requires thoughtful governance and integration to deploy at enterprise scale |
Each approach has its place, and the right choice depends on your business needs and the complexity of your workflows.
Traditional automation tools like RPA can still be effective for high-volume, predictable tasks, and intelligent automation may add meaningful functionality on top of that.
But when business operations require systems that can adapt in real time, orchestrate across multiple platforms, and handle requests that don't fit a predefined rule, agentic automation is a capable option.
Key characteristics of agentic AI
There are six key characteristics that set agentic AI apart from other automation approaches:
- Autonomy: Agentic AI systems are built to operate independently, executing complex tasks, making decisions, and adapting to changing conditions as they go.
- Goal-oriented behavior: These systems focus on specific objectives and break them into sub-goals, optimizing each step to reach the desired outcome.
- Reasoning and problem-solving: Rather than following a fixed script, agentic AI can analyze complex problems, plan a course of action, and adjust its approach when conditions change.
- Adaptive learning: Through machine learning, agentic systems can improve over time, refining responses based on past interactions and new data.
- Decision-making capability: Agentic AI is designed to weigh trade-offs, assess risk, and make informed choices based on available information.
- Proactive behavior: Instead of waiting for instructions, agentic AI is capable of anticipating needs, initiating workflows, and taking action before problems escalate.
Benefits of agentic automation for the enterprise
The business case for agentic automation goes well beyond efficiency. Enterprises that deploy it effectively often see faster decision-making, greater scalability, and increased productivity.
Built-in governance can help orgs deploy agentic automation more confidently because actions can be logged, permissioned, and auditable. The goal is to allow teams to move more quickly, without losing visibility or control over what's happening across their systems.
Increased efficiency
Agentic automation can help enterprise teams avoid the grind of repetitive, low-value work. With orchestrated workflows, IT teams often spend fewer hours resolving tier-1 tickets and more time on higher-priority infrastructure work.
The impact of this shift can be significant. Broadcom, a global infrastructure technology company with roughly 15,000 employees worldwide, now resolves 88% of support issues autonomously thanks to its agentic AI solution. That's up from just 10% at launch, with employees now receiving support in seconds instead of days.
Improved decision-making
Enterprise teams make hundreds of routing and triage decisions every day, and most of them follow the same logic. Agentic automation can use these repeatable patterns to execute real-time decision points faster and more accurately than when handled manually.
Think of a complicated employee request that might touch several departments at once. Instead of relying on a predefined rule or waiting for someone from IT or HR to review the request, an agentic system is capable of acting immediately.
Agentic AI can thoroughly read the request, interpret intent, and route it to the right team automatically. Accelerating workflows in this way can help reduce delays, avoid costly bottlenecks, and keep teams productive.
Strengthened scalability
Scaling traditional automation typically means rebuilding workflows from scratch. Every new department, system, or use case requires custom configuration as major changes are introduced.
With agentic automation, it's typically a much simpler process. Since agentic AI systems can reason from context rather than following a prebuilt script, they can scale across teams and systems with significantly less implementation lift.
AkzoNobel, a global coatings company operating across 150 countries with nearly 35,000 employees, put this to the test. After deploying their own agentic AI solution, 72% of the workforce adopted the platform. This enabled the enterprise to access AI-powered support across 100+ languages without rebuilding workflows for each market.
Improved accuracy
Too many manual workflows is a common cause of increased errors. A simple data-entry error in an HR system can trigger failed provisioning, delayed onboarding, or a compliance gap that surfaces weeks or months later.
Agentic automation can help reduce this risk by cross-referencing data across sources in real time. Instead of waiting for an employee to spot the issue, the system can flag anomalies and may even resolve them outright. The result for many orgs is cleaner data, fewer downstream failures, and workflows that hold up under audit.
Better employee experience
When agentic automation works well, the experience is seamless. Requests resolve quickly, the right information surfaces in the tools employees already use, and support finds people instead of the other way around.
Moveworks is designed to deliver this experience through a conversational AI interface that meets employees where they already work. Albemarle, a global chemical company and the world's largest lithium manufacturer, deployed it to resolve 80% of support tickets without any IT back-and-forth.
Agentic automation use cases: What it looks like in the enterprise
Agentic automation is an enterprise capability that can transform how work gets done across the entire business.
Here's what this can look like across three of the highest-impact use cases.
Self-service support desk
Agentic automation can help turn a basic self-service support desk into an actionable experience that employees genuinely want to use.
Equinix, the world's largest interconnection and colocation platform, deployed an agentic AI assistant that lives inside Microsoft Teams, known as E-Bot.
When an employee submits a request in Teams, E-Bot reads through and synthesizes the information. Based on its findings, the AI assistant either resolves the request directly or routes it to the right expert.
All of this happens within 30 seconds, without a queue, a follow-up email, or a wait.
E-Bot now routes 82% of Equinix tickets with 96% routing accuracy, cutting average ticket lifespan by nearly a third, without upping headcount.
IT security
IT security teams are expected to monitor threats continuously and respond instantly, all while managing a constantly evolving surface area of systems, applications, and compliance requirements.
Agentic automation can help carry much of this burden. Platforms like Moveworks are designed to operate within role-based access controls and maintain full audit trails.
For security leaders evaluating agentic AI, these governance controls are often the main difference between an automation platform they can trust and one they can't deploy.
Leidos, a Fortune 500 technology company supporting national security operations with 47,000 employees worldwide, deployed Moveworks in its own enterprise. They were able to cut their MTTR from hours to minutes, deflecting 3,000+ IT issues monthly, while still meeting strict federal compliance standards.
Talent acquisition and onboarding
The first week at a new job often sets the tone for the employer-employee relationship. But when new hires spend day one waiting for system access, chasing down benefits enrollment, or submitting tickets just to get basic tools provisioned, first impressions take a hit.
With the help of an agentic automation solution, new talent can experience a much more seamless onboarding journey. One leading enterprise software company deployed Moveworks to help with these challenges and saw immediate results.
Account access and application provisioning now happen automatically for new hires, without requiring additional HR team members. The Moveworks platform enables the org to resolve over 30% of employee issues instantly, allowing new hires to get what they need without waiting.
Get started with agentic automation
Deploying agentic automation is about starting in the right place and building from there.
The right place is typically where ROI is potentially fastest and easiest to measure. High-volume IT and HR workflows make the strongest first case, including:
- Password resets
- Access requests
- Onboarding tasks
These are frequent, well-defined, and easy to benchmark, which makes them ideal for proving value and justifying expansion.
From there, a few practical steps can help keep the rollout on track:
- Identify high-volume, repetitive workflows where resolution patterns are predictable.
- Connect systems and integrations first, since the number of native connectors available will often determine how fast new workflows go live.
- Set baseline KPIs like ticket deflection rate, MTTR, and automation rate before deployment.
- Build enterprise readiness into your rollout plan from the start.
- Establish role-based access controls that govern what actions each agent can take.
- Plan out permissioned, scoped integrations that limit each agent's reach to its intended systems.
- Create audit trails and logging for full compliance review.
Setting all of this in motion is important, but equally critical is making sure you have the right agentic solution in place.
Moveworks is an agentic AI platform built to deliver the governance, control, and visibility enterprises need to deploy agentic automation confidently.
It includes a built-in runtime layer with compliant guardrails that help turn an LLM from "chat" into safe action. Instead of trusting natural-language instructions that models can work around, Moveworks' security harness is designed to enforce consent, policy checks, and runtime constraints at every step.
Paired with audit logs, promotion workflows, and regression gates, the platform supports reliable, compliant agents, even as prompts, tools, and AI models change over time.
Powering orchestrated automation is Moveworks’ proprietary Reasoning Engine that plans and executes multi-step workflows. Hundreds of out-of-the-box integrations connect Moveworks to existing systems from day one to deliver immediate value, while the low-code Agent Studio enables teams to expand workflows over time by building custom agents without a heavy development lift.
Ready to put agentic automation to work for your enterprise? Explore Moveworks today.
Frequently Asked Questions
Agentic AI refers to the underlying technology — artificial intelligence systems capable of autonomous reasoning, decision-making, and goal-directed behavior. Agentic automation is the application of that technology to business processes and workflows. Think of agentic AI as the engine and agentic automation as the vehicle — the former describes what the technology can do, the latter describes how enterprises put it to work.
This depends heavily on the platform. Legacy automation tools often require significant IT resources to configure, maintain, and scale. But modern agentic platforms like Moveworks are designed for rapid deployment with out-of-the-box integrations that connect to existing enterprise systems without heavy customization. Enterprises should evaluate vendors not just on capability but on time-to-value and the ongoing technical lift required to keep the platform performing.
This is one of the most important questions enterprise leaders should ask before deploying any agentic AI-driven solution. Effective governance requires role-based access controls that limit the actions an agent can take, audit trails that log decisions and actions for compliance review, and human-in-the-loop escalation paths for requests that fall outside defined parameters. Enterprises should prioritize platforms that treat governance as a core architectural feature rather than as an add-on.
Yes, and cross-system orchestration is a touted advantage over point solutions. A single agentic workflow can span multiple systems simultaneously, pulling data from an HRIS, updating a ticketing system, provisioning access in an IAM tool, and notifying an employee via a messaging platform like Slack or Teams, all within a single automated sequence. The key evaluation criterion is how many native integrations a platform offers and how much custom development is required to connect new systems.
A single AI agent handles a defined task or workflow independently, while a multi-agent system coordinates multiple specialized agents working in parallel or in sequence to complete more complex, end-to-end processes. Multi-agent architectures are particularly well-suited to enterprise environments where different agents can specialize in specific domains, one handling IT requests, another managing HR workflows, while an orchestration layer coordinates their efforts toward a shared business outcome.
