From Concept to Impact: Agentic AI Use Cases That Prove the Power of Intelligent Automation

Today's AI landscape is rapidly shifting: from traditional AI that analyzes data and follow rules with human guidance to dynamic, independent agentic AI. These agentic systems can set goals, sketch out plans, and coordinate multi-step actions across tools — adjusting as new information comes in.

92% of leaders expecting that agentic AI will deliver measurable ROI within two years, as Agentic AI eases the burden of repetitive work and reduces workflow noise, giving teams more time for actual strategy.

The core capabilities enabling these transformative Agentic AI use cases are:

• Reasoning and planning: Breaks large objectives down into a strategic, multi-step sequence for execution.
• Execution and monitoring: Activates and uses external software tools while actively checking task output against the goal.
• Adapting to changing conditions: Uses memory and feedback to self-correct and instantly revise the plan when a task fails or conditions change.
• Integration across systems: Efficiently coordinates work and data across all disconnected enterprise platforms.

In this guide, we explore the specific, real-world scenarios where agentic AI is tackling complex problems and driving unparalleled efficiency across your business.

Why agentic AI matters for the enterprise  

Enterprises are feeling the strain of legacy automation. Over time, teams have layered tools, bots, and workflows to offload repetitive tasks — but these setups often evolve into a complex mix of systems that still require significant human oversight.  The result? Fragmented data, slow resolution times, and service backlogs that drain productivity.

Agentic AI changes that dynamic. It brings autonomy and reasoning into the automation layer, giving enterprises a way to orchestrate entire workflows—not just single tasks. 

Instead of following static rules or scripts, agentic AI interprets goals, determines the best path, and takes action across systems like ERP, HRIS, ITSM, CRMs, to achieve measurable outcomes.

This matters because enterprise work today doesn’t happen in one place. 

• IT manages incidents and access.
• HR supports onboarding and benefits.
• Finance processes invoices and expenses.
  

Each function depends on a chain of connected systems—and when those systems don’t communicate, employees waste hours chasing updates and approvals.

Compounding the problem is the fact that the cost pressure is growing: Gartner reports that enterprise SaaS costs are rising 10–20% or more at renewal, far outpacing IT budget growth.

Agentic AI acts as the connective tissue across these silos. It integrates data, evaluates intent, and executes actions end-to-end, ensuring continuity from request to resolution. For leaders, that means less time coordinating teams and more time driving strategy. For employees, it means fast, contextual support when they need it.

The shift is clear: from fragmented automation to unified intelligence, Agentic AI transforms how enterprises scale service, reduce manual effort, and deliver faster, more seamless experiences across every department.

Agentic AI in IT

IT has always been the proving ground for enterprise automation — but even the most advanced systems struggle to keep up with today’s pace of change. Manual ticket management, access provisioning, and system monitoring still take time that could be spent on innovation.

Agentic AI helps IT become a more proactive function. Instead of waiting for tickets or incidents,  these autonomous systems can monitor complex environments, anticipate potential issues before they cause downtime, and independently execute corrective actions across infrastructure and services. They integrate with existing infrastructure across IT and your entire tech stack — including ServiceNow, Jira, and Microsoft 365 — to manage problems autonomously while maintaining visibility.

Top IT use cases:

• Proactive incident resolution: AI agents identify access or configuration issues, resolve them automatically when possible, and escalate when exceptions arise.
• Automated provisioning: Agentic systems grant or revoke access securely, enforcing policies and role-based permissions across all connected enterprise applications (HR systems, cloud services, directories) without manual effort.
• Self-service support: Employees receive instant support via conversational interfaces where the AI agent doesn't just respond, but can diagnose the technical issue based on the conversation and then autonomously execute the necessary fixes (like resetting credentials or clearing cache) to resolve routine issues instantly, significantly reducing ticket volume and resolution time.
  

This isn’t just faster IT — it’s smarter IT too. Agentic AI works with reasoning layers that work across workflows, not just tickets, helping teams prevent disruptions, uphold compliance, and focus on strategic initiatives.

Power Design deploys agentic assistants  

As Power Design grew, its IT team faced rising ticket volumes and a flood of repetitive requests, from password resets to device troubleshooting. Employees often waited longer than they wanted for help with routine issues, and IT needed a way to scale support without adding headcount.

Power Design implemented an AI assistant named HelpBot to deliver self-service support through chat. Powered by agentic AI, HelpBot interprets employee requests in natural language, identifies intent, and acts across multiple systems to resolve issues autonomously. It can reset credentials, support device monitoring use cases, and escalate complex cases when necessary.

The impact? Since launching HelpBot, Power Design has automated more than 1,000 hours of repetitive IT work, freeing technical staff to focus on higher-impact projects. Employees now resolve many issues in minutes rather than waiting in queue, improving productivity across the organization.

HelpBot’s ability to reason through requests, integrate with systems, and take secure, autonomous action has helped shift IT from a reactive service desk toward a more proactive, data-driven partner to the business.

Agentic AI in HR  

HR teams are under constant pressure to support employees quickly while managing complex, repetitive workflows like onboarding, benefits updates, and policy requests. Manual case management slows response times and drains capacity that should go toward employee engagement and retention.

Agentic AI enables HR to automate these repetitive, policy-driven processes end to end. It plans and executes tasks across systems such as HRIS, payroll, and collaboration tools—handling employee requests, routing approvals, and updating records autonomously.

The impact: With agentic AI, HR teams streamline onboarding, improve accuracy in benefits administration, and deliver faster, more personalized employee support. Requests that once required manual review now resolve in minutes. This frees HR professionals to focus on strategic initiatives like workforce planning and culture development.

Across the enterprise, agentic AI helps HR balance high-touch service with operational efficiency — creating a better experience for both employees and HR teams.

Top HR use cases

Agentic AI is reshaping the HR experience by automating everyday requests, orchestrating multi-step workflows, and giving employees instant, reliable answers. These are the HR use cases where agentic AI delivers the greatest impact:

1. Autonomous employee self-service

Agentic AI can provide instant answers to common questions about benefits, onboarding, PTO, payroll, and HR policies., freeing HR teams to focus on people, not processes.

For example, an employee may ask, “How do I update my tax withholding?” Leading agentic AI solutions can retrieve the right policy, surface the relevant form, and walk them through next steps — all in seconds.

2. Automated onboarding and employee transitions

Agentic AI can plan and execute multi-step workflows across HRIS, IT, Finance, and Facilities systems. For example, it can guide a new hire through paperwork, benefits enrollment, equipment setup, and mandatory training — while triggering access provisioning behind the scenes.

The result? Fewer manual handoffs, smoother transitions, and a consistent onboarding experience.

3. Policy interpretation and case resolution

Agentic AI can interpret policy language and provide clear, contextual guidance based on role, location, and eligibility rules. For example, an employee may ask whether they qualify for a specific leave type. A well-implemented agentic AI solution can check policy criteria, apply the employee’s data, and give a personalized answer.

This can reduce escalations, improve consistency, and minimize errors in policy communication.

Ciena accelerates HR service delivery with agentic AI  

Ciena’s HR team faced a familiar challenge: delivering consistent, high-quality support to a global workforce spread across time zones and systems. Employees needed help with everything from benefits questions to onboarding and access requests—but a steady stream of routine tickets slowed response times and stretched HR and IT resources thin.

To solve this, Ciena implemented an agentic AI system to automate HR and IT service delivery and create a unified support experience. The AI integrates with existing HR and IT platforms to interpret employee requests, understand intent, and take secure, autonomous actions such as updating records, routing approvals, or resolving common issues directly in chat.

Since deploying the solution, Ciena has automated more than 100 workflows across IT and HR, cutting approval times from days to minutes. Employees get faster, more reliable help, while HR teams spend less time on repetitive requests and more time improving the employee experience.

By introducing agentic AI, Ciena built an intelligent, connected support model that scales globally without adding complexity—turning everyday HR operations into a more seamless, employee-first experience.

Agentic AI in finance

Finance teams are under constant pressure to deliver accuracy, speed, and compliance, all while managing growing workloads across expense reporting, invoice processing, and payroll. Manual reviews and approvals slow everything down, creating bottlenecks that delay close cycles and frustrate employees.

Agentic AI helps finance operate smarter and faster. By reasoning over data and acting autonomously across ERP, payroll, and expense systems, it can generate reports, flag anomalies, and reconcile records faster. The result is an automation layer that doesn’t just move data between systems — it ensures every step follows policy, reducing errors and manual oversight.

Theresults show meaningful value: expense reports are processed faster, approvals are routed automatically, and compliance checks happen as part of every transaction. Finance teams gain clear audit trails and confidence that data is accurate and up to date, while employees experience faster reimbursements and fewer delays.

Agentic AI frees finance leaders to focus on forecasting and strategy instead of paperwork — turning operational efficiency into measurable business impact.

Top finance use cases

Leading agentic AI solutions can help finance teams streamline high-volume, rules-driven processes while improving accuracy and speeding up decision-making. These are the use cases where the impact shows up immediately.

1. Autonomous invoice processing

Agentic AI can automate the flow of invoice data across ERP and procurement systems, reducing the manual effort usually required to reconcile details across vendors, line items, or cost centers. The AI extracts key fields, checks for completeness, and routes each invoice to the appropriate approver. As a result, AP teams spend less time correcting errors and more time focusing on higher-value analysis.

2. Automated expense report generation

Agentic AI can also simplify expense reporting by reading receipts, applying policy rules, and compiling complete submissions for employees. Instead of manually attaching documentation or correcting categorization issues, employees can forward their receipts and let the AI assemble the report end to end. Finance teams receive cleaner, more consistent submissions, reducing back-and-forth review cycles.

3. Real-time financial inquiry resolution

Agentic AI can give business partners instant clarity into budgets, spend, accruals, or policy requirements by pulling live data from ERP and finance systems. Managers can ask a question and receive accurate, contextual responses without filing a ticket or waiting for a colleague to respond. This reduces inquiry volume for finance and helps teams across the organization make faster, better-informed decisions.

A global financial services company automates customer experience with agentic AI  

A leading financial services company wanted to simplify how employees and customers received support. Repetitive, manual requests — like password resets, expense inquiries, and account updates — slowed down service teams and led to longer resolution times.

By implementing an agentic AI system, the company introduced a self-service experience that operates across IT, finance, and customer service workflows. The AI connects to key enterprise systems, interprets intent, and takes secure action to fulfill requests, whether that means resetting access credentials, initiating reimbursements, or updating records automatically.

Today, employees and customers alike receive faster, more consistent support. Routine requests that once required manual review are now handled autonomously through chat, while exceptions are routed to the right specialist with full context. The result is higher satisfaction, lower ticket volume, and teams that can focus on more strategic work.

Agentic AI has become a foundation for service excellence — helping the organization deliver faster outcomes, improve accuracy, and scale support globally without sacrificing compliance or control.

Agentic AI in security  

Security teams face a near-impossible task: monitoring endless alerts, triaging threats, and enforcing policies across an expanding digital footprint. Manual review slows response times, while static automation can’t adapt fast enough to evolving risks.

Agentic AI helps security teams move from reactive to adaptive defense. It continuously evaluates system data, identifies anomalies, and executes to contain or mitigate threats — such as isolating affected systems or triggering compliance workflows — based on established policies and permissions.

Top security use cases

Leading agentic AI solutions can augment security teams by analyzing vast amounts of behavioral, network, and system data in real time, helping teams respond faster without increasing manual workload. Below are security use cases where agentic AI delivers meaningful impact:

1. Autonomous anomaly detection

Agentic AI can continuously analyze user behavior, system activity, and network patterns to identify anomalies the moment they emerge. Rather than waiting for manual review or rule-based thresholds, security teams see unusual activity earlier and can investigate faster — reducing time to detection and limiting exposure.

2. Intelligent alerting and triage

Security teams often face overwhelming alert volumes, many of which are false positives. Agentic AI can correlate signals across security information and event management (SIEM), security orchestration, automation, and response (SOAR), identity and access management (IAM), and cloud tools to enrich and prioritize alerts. Analysts receive fewer noisy notifications and gain immediate clarity into which incidents require action, improving response efficiency.

3. Adaptive policy enforcement

Traditional policy enforcement applies static rules, even when user context changes. Agentic AI can evaluate conditions — such as risk scores, device posture, access behavior, or data sensitivity — and apply the right controls in real time. This reduces unnecessary friction for legitimate work while strengthening protections where risk is higher.

4. Cross-tool workflow orchestration

When a threat emerges, responders often have to jump between systems to isolate devices, reset credentials, revoke tokens, or block suspicious IPs. Agentic AI can coordinate these steps across endpoint detection and response (EDR), IAM, SOAR, and cloud platforms, executing actions within established permissions and policies. Security teams spend less time on repetitive manual tasks and more time on strategic investigation.

Darktrace leverages agentic AI-style techniques to detect and respond to emerging threats  

Darktrace, a leader in cybersecurity, leverages AI to monitor enterprise network traffic and detect potential attacks before they spread. Its AI agents reason over network patterns in real time, identifying anomalies that traditional tools might miss. When irregular activity is detected, the system autonomously determines the appropriate response, such as isolating compromised segments or notifying incident response teams.

This agentic approach has enabled Darktrace customers to cut response times and strengthen defenses without increasing headcount. The AI’s continuous learning and context awareness allow security teams to focus on strategic risk management instead of manual monitoring.

By reasoning over security signals and coordinating actions across monitoring, identity, and incident-response systems, agentic AI builds a faster, more reliable defense posture.

Agentic AI in customer service  

Customer service is one of the most visible areas where agentic AI delivers impact. Support teams juggle thousands of requests daily, many of them repetitive and time-sensitive. Traditional tools can triage messages, but they can’t reliably act across multiple systems to resolve them.

Agentic AI changes that dynamic. It connects customer service platforms, knowledge bases, and ticketing systems to reason over context and take the next step — whether that’s retrieving account details, escalating priority issues, or automating refunds.

As an example, one global financial services company deployed an agentic AI assistant to streamline internal support and improve the customer experience. Employees and service representatives now get instant, contextual help through an intuitive chat interface. The AI handles common tasks like password resets and data lookups autonomously, while routing complex issues to specialists with full case context.

This combination of reasoning, planning across systems, and action shortens resolution times and reduces ticket volume—helping customer support teams focus on building stronger relationships, not managing repetitive tasks.

Top customer service use cases

Below are some of the most impactful ways agentic AI can support customer service teams.

1. Autonomous support request triage

Agentic AI can classify, prioritize, and route incoming requests the moment they arrive — interpreting intent, identifying urgency, and applying customer context. Instead of manually sorting queues or redirecting misrouted issues, support teams start with organized, high-quality cases. Customers reach the right workflow or specialist sooner, improving first-contact resolution rates.

2. Customer context aggregation

Support teams often waste valuable time piecing together information from CRM systems, ticket history, product logs, and previous conversations. Agentic AI can consolidate that data into a single, contextualized view before the agent even opens the case. With full context at their fingertips, agents resolve issues faster and deliver a more personalized experience.

3. Automated issue resolution

Many high-volume support requests — such as account resets, subscription changes, order-status questions, or basic troubleshooting — can be resolved automatically through agentic AI. By handling these routine tasks end to end, AI reduces ticket volume and frees human agents to focus on complex or high-value cases where human judgment matters most.

4. Proactive customer outreach

Agentic AI can analyze patterns that signal product friction, negative sentiment, or potential churn. When the system detects a trend, it can trigger timely outreach or surface recommended actions for the support team. This helps CS and CX teams intervene early, strengthen customer relationships, and prevent issues from escalating.

Choosing and scaling the right use case

Leading organizations succeed with agentic AI by starting small and focusing on the workflows where automation will have the biggest impact. Rather than trying to transform everything at once, they target high-volume, rules-based tasks, validate early results, and then expand to more complex, cross-department workflows. This approach reduces risk, builds internal confidence, and ensures the technology scales responsibly.

1. Identify high-impact, rules-based processes

The best starting point is a workflow that is repetitive, structured, and happens frequently across teams. These are often cross-system processes that require employees to jump between tools or follow multi-step checklists — password resets, account changes, approvals, case routing, and routine data lookups.

By mapping where employees spend disproportionate time on predictable tasks, leaders can quickly spot the opportunities where agentic AI can reduce manual effort without disrupting daily operations.

2. Evaluate autonomy potential

Not every process is equally suited for agentic AI. Teams should assess whether the steps involved can be guided by clear logic, policies, and decision criteria. If the workflow depends heavily on subjective human judgment, it may not be an ideal first candidate.

Establishing guardrails — such as allowed actions, escalation thresholds, and required verification points — helps ensure the AI operates safely within well-defined boundaries. This builds trust while still enabling meaningful automation.

3. Assess data and system integration readiness

Agentic AI performs best when relevant systems of record are accessible, data is reasonably clean, and key workflows have available APIs or integration points.

Teams should examine whether the information the AI needs — such as customer profiles, HR records, policies, ticket histories, financial data, or identity attributes — is complete and consistent across systems. If data is siloed or outdated, some cleanup or consolidation may be needed before automation begins.

4. Start small, then scale across departments

A focused first workflow allows teams to measure impact, refine guardrails, and build operational muscle before expanding further. Once initial success is proven — reduced handling time, lower ticket volume, faster cycle time, or improved satisfaction — organizations can extend automation to adjacent processes.

Over time, teams can evolve toward multi-step, multi-system automations and eventually multi-agent orchestration that spans HR, IT, finance, customer service, and more.

5. Governance, risk, and change management

Scaling agentic AI responsibly requires thoughtful governance. Teams should establish human-in-the-loop review for sensitive actions, maintain transparent audit trails, and version policies that define what the AI can and cannot do.

Equally important is preparing employees for the shift: communicating the goals, providing training, and ensuring clear guidance on when to rely on AI versus when to escalate. Strong governance and transparent controls help organizations adopt automation with confidence.

Turn agentic AI potential into reality with Moveworks

 Agentic AI has the power to connect every part of the enterprise, reasoning across systems, orchestrating actions, and maintaining compliance at scale. Moveworks makes that potential real.

The Moveworks platform unifies the core capabilities of agentic AI — reasoning, orchestration, and secure action — across IT, HR, Finance, Security, and Customer Service. 

Moveworks connects to all your systems with an intuitive, AI-native experience that meets employees where they work, and in over 100 languages.

• Search and action in one intuitive workspace
• Powered by a superior Reasoning Engine
• Easy to add and build AI agents for any use case
• AI Agent Marketplace with pre-built templates

Get started and speed up time-to-deploy with a curated library of 1000+ AI agents to uplevel all your business applications with ready-to-use, production-proof AI agents that are customizable and free to install.

Moveworks turns every employee into an agentic AI power user — giving enterprises an AI platform that makes work flow.

With Moveworks, enterprises gain a single, agentic automation layer that unifies people, data, and systems—turning the promise of agentic AI into measurable business impact.

Learn more: Discover how Moveworks helps enterprises operationalize agentic AI.