How to use task mining to understand current state, find AI use cases, create an agent blueprint, and ground your AI agent.

Generative AI is everywhere in the headlines, but most companies still struggle with one basic question: where should we actually apply it?

The truth is, GenAI pilots often fail because they aren’t connected to the reality of how employees work day to day. That’s where task mining comes in. By capturing user-level activity—clicks, lookups, copy/paste actions, and time spent across systems—task mining reveals the hidden opportunities for automation and provides the foundation to ground AI agents in real operational data.

In this article, we’ll explore the top use cases for task mining and GenAI across Customer Service, Finance, and IT, and show how organizations are turning repetitive steps into measurable ROI.

👉 If you haven’t already, start with our guide on how to identify generative AI use cases.

Why Task Mining Matters for GenAI

Most AI pilots fail because they start with technology instead of business reality. Leaders often underestimate the amount of manual, repetitive work still buried in everyday processes.

Task mining fixes this by:

• Capturing real work as it happens (not how managers think it happens).
• Surfacing high-frequency, repetitive steps like copy/paste or system lookups.
• Quantifying time and cost impact so leaders can prioritize the right use cases.

These insights become the blueprint for generative AI: which tasks to automate, which workflows to enhance with copilots, and how to ground agents in the actual data employees use every day.

Use Cases in Customer Service

Customer service agents spend countless hours switching between systems, looking up customer details, and retyping similar responses. Task mining often reveals:

• Copy/paste of account data between CRM and ticketing tools.
• Lookups in knowledge bases for common issues.
• Manual “after-call” notes and wrap-up steps.

How GenAI helps:

• Drafts customer responses instantly, cutting handling times by 20–50%.
• Summarizes calls and updates tickets automatically.
• Provides real-time copilots that surface knowledge as the agent speaks.

Example: A support center used task mining to map the 5–6 clicks agents repeated on every Wi-Fi troubleshooting call. By training a GenAI co-pilot on this workflow, resolution times dropped and agents spent less time on manual system navigation.

Use Cases in Finance

Finance and accounting teams are some of the heaviest users of repetitive tasks. Task mining consistently highlights:

• Manual invoice entry and reconciliation.
• Spreadsheet consolidation for reporting.
• Compliance checks and audit prep.

How GenAI helps:

• Automates invoice processing, reducing costs by 20–60%.
• Generates financial commentary and reconciliations automatically.
• Streamlines close processes so teams can close books faster, with fewer errors.

Example: A finance department discovered through task mining that analysts spent nearly a third of their time consolidating spreadsheets. Automating that step with GenAI cut days off the monthly reporting cycle.

Use Cases in IT

IT help desks and service management teams face endless repetitive requests: password resets, account provisioning, basic troubleshooting. Task mining exposes:

• Repeated sequences for routine ticket resolutions.
• “How-to” requests that account for a large share of Level 1 tickets.
• Manual triage of alerts and incidents.

How GenAI helps:

• Virtual agents now handle many of these tickets, cutting resolution times dramatically.
• GenAI can generate troubleshooting guides and even take actions directly (e.g., resetting accounts).
• IT teams save hours by automating 24/7 monitoring and response.

Example: One IT team used task mining to document password reset workflows. By deploying an AI agent trained on these steps, they eliminated thousands of low-value tickets per month, freeing engineers for more strategic work.

The ROI: From Busywork to Business Impact

When task mining and GenAI are combined, organizations consistently see:

• Time savings: Cutting process cycle times.
• Cost reductions: Invoice processing, ticket handling, and reporting made faster and cheaper.
• Adoption success: Employees embrace automation when it removes the most tedious parts of their jobs.

The key is that GenAI agents aren’t “guessing” at what to do—they’re grounded in the reality of your operational data, as captured through task mining.

ClearWork: From Task Mining to Agent Blueprinting

At ClearWork, we call this Agent Process Intelligence. We:

1. Automatically map processes and capture task-level activity.
2. Identify the most valuable GenAI use cases.
3. Generate blueprints that ground AI agents in how your work actually happens.

This ensures AI isn’t just bolted onto your workflows—it’s embedded into them, with the right guardrails.

👉 Learn more on our ClearWork Agent Process Intelligence page.

Final Thoughts

Generative AI is at its most powerful when it’s applied to the work that consumes the most time but delivers the least value—copy/paste, lookups, form fills, data entry. Task mining reveals exactly where those opportunities lie and provides the evidence to prioritize the right use cases.

Business leaders who start with process visibility, not just technology hype, will be the ones who move from failed pilots to real transformation.

FAQ: Using Task Mining to Ground GenAI and Build Effective Agent Blueprints

1. What is task mining in simple terms?

Task mining captures user activity—like clicks, lookups, form fills, and copy/paste actions—to reveal how work is actually done. Instead of relying on assumptions, it provides a data-driven view of real workflows, including bottlenecks and repetitive steps.

2. How does task mining connect to Generative AI?

Generative AI performs best when grounded in operational reality. Task mining supplies that reality by showing how employees truly work. This data becomes the blueprint for AI agents, ensuring they automate or enhance the right workflows instead of guessing.

3. What types of tasks are best suited for GenAI automation?

High-frequency, repetitive, and rule-based activities are ideal. Examples include:

• Customer service responses and after-call notes
• Invoice entry, reconciliation, and financial reporting
• IT helpdesk requests like password resets or account provisioning

4. What ROI can companies expect from combining task mining and GenAI?

Organizations often achieve:

• 20–50% faster cycle times in service and support
• 20–60% cost savings in areas like finance and operations
• Higher adoption rates, since automation eliminates tedious work employees want to offload

5. How does ClearWork help organizations with task mining and AI adoption?

ClearWork automates process mapping and task capture, highlights the most valuable GenAI use cases, and generates blueprints that ground AI agents in real workflows. This ensures AI isn’t bolted on but embedded into daily operations with measurable results.