How to Unearth Agentic AI Use Cases with a Consulting Approach
Agentic AI is making waves – not just in tech circles, but also in boardrooms. These systems go beyond responding to commands; they set goals, make decisions, adapt in real time, and act with purpose. For businesses, the big question is no longer “What is AI?” but “Where & how can we use it effectively?”
That’s where a consulting-led discovery process becomes essential – aligned with broader vision, reimagining processes, and backed by trust & explainability. With the right approach, businesses can move from generic AI hype to identifying use cases where agentic AI delivers measurable value.
What Exactly is Agentic AI?
Agentic AI refers to systems that act like autonomous agents. They’re capable of independently pursuing goals, learning from their environment, and making complex decisions, without waiting for human prompts every step of the way.
Think of systems that automatically adjust supply plans, personalize customer outreach on the fly, or monitor contracts for compliance. These are digital actors capable of driving real outcomes.
A Practical Consulting Framework for Discovering Agentic AI Use Cases
The process of discovering where agentic AI fits begins with a structured approach. Here's a breakdown of a consulting-style framework that guides businesses through this journey:
| Stage | Goal | Activities | Deliverables | Sample KPIs |
|---|---|---|---|---|
| 1. Discovery & Alignment | Uncover strategic pain points and opportunities | Stakeholder interviews, process mapping, strategic deep-dives | Priority areas mapped to business goals | # of high-friction or bottleneck workflows identified |
| 2. Capability Mapping | Assess how agentic AI could solve those problems | AI capability scans, system audits, data & infra readiness assessments | Use-case-to-capability fit analysis | Data maturity score, feasibility ratings |
| 3. Ideation Workshops | Co-create agentic AI concepts with humans in the right part of the loop | Cross-functional brainstorming, design thinking sessions | Top 3–5 use case concepts considering feasibility vs business value | Engagement level, number of viable use cases |
| 4. Value & Risk Assessment | Evaluate ROI and risk mitigation plan for (ethical, operational risks, etc.) | Business case modeling, compliance checks, and ethical scenario planning | ROI forecast, risk register | Projected ROI, risk severity index |
| 5. Pilot & Iterate | Test use cases in the real world | Build Minimum Viable Agents (MVA), gather feedback, and refine agentic behavior with rigorous testing | Working prototype and rollout | Pilot success rate, time-to-feedback cycle |
| 6. Scale and Govern | Ensure successful adoption & governance | Develop a roadmap along with governance frameworks for monitoring and ensuring regulatory compliance. Invest in org-wide adoption | Scaling roadmap, change management plan, and governance framework | User satisfaction, error rate reduction, cost, or time savings. |
Sample Agentic AI Use Cases and Their Business Impact
Here are some real, cross-industry use case types that show where agentic AI can deliver serious value, alongside the KPIs that matter most:
- Dynamic Supply Chain Planning
- What it does: AI agents forecast demand, adjust procurement orders, and reroute logistics based on disruptions.
- Why it matters:
- 20–30% fewer stockouts
- 10–15% reduction in logistics costs
- Faster response to market shifts
- Customer Service Automation
- What it does: Autonomous agents handle inquiries end-to-end and escalate only when necessary.
- Why it matters:
- Up to 50% faster issue resolution
- 60% of queries resolved without human help
- Better customer satisfaction
- Marketing Campaign Optimization
- What it does: Agents allocate budget, tweak messaging, and optimize targeting in real time.
- Why it matters:
- 20–25% improvement in ad ROI
- Reduced manual campaign management by half
- Higher engagement and conversion rates
- Contract & Policy Monitoring
- What it does: AI scans legal documents, flags anomalies, and monitors real-time compliance.
- Why it matters:
- 50% faster audit cycles
- Reduced legal workload
- Proactive issue detection
- Financial Reconciliation
- What it does: Agents match records across systems, identify mismatches, and generate audit logs.
- Why it matters:
- 70% automation of reconciliation tasks
- Faster month-end close
- Fewer human errors
- Intelligent Staffing & Scheduling
- What it does: AI assigns shifts or projects based on availability, performance, and demand.
- Why it matters:
- Better resource utilization
- Shorter scheduling cycles
- Happier and more productive teams
Final Thoughts
Agentic AI isn’t just another tech buzzword; it’s a shift in how work gets done. However, finding the right fit requires more than just technical expertise. It requires a thoughtful, business-first approach that starts with listening, mapping opportunities, and measuring what matters.
A consulting mindset can make the difference between deploying another tool and building a game-changing capability. With the proper discovery process, agentic AI can go from an abstract idea to a tangible business advantage.
Are you ready for an organizational transformation? Talk to our experts in Data & AI Consulting.
Using our proprietary AI Scale @ Speed Framework, we help build the foundation for a comprehensive Data, AI, and Automation Strategy. We assess the alignment of AI vision with business goals, develop business cases, and identify use cases, including prioritization. Our experts ensure underlying data readiness by creating the required capabilities to enable lasting organizational change. Leveraging our AI Tech Stack Evaluation Framework, we help accelerate AI implementation and a net positive impact thereafter. Throughout our data and AI work, our experts ensure the embedding of fairness, transparency, and accountability.
