Agentic AI Use Cases Across various Indistries

1. Agentic AI Guide Types, Use Cases, & Workflows www.polestarllp.com

2. Stages of Agentic AI From including foundational RPA and GenAI systems into a spectrum of increasingly sophisticated opportunities, the stages go from single agents for small teams/tasks to agent swarms enabling users across teams and tasks. Let’s see how that works.. Basic Single-Purpose Agent (Focused on one task) A These agents operate within predefined parameters ( like a bot) and continuously refining their performance feedback (external and internal) loop. Multi-Capability Agent (Handles varied tasks) A+ Working as highly versatile digital assistants, ensuring contextual continuity, autonomous prioritization, and seamless execution of diverse, dynamic tasks. Department-Level Team (Coordinated specialists) C A Coordination specialists working within structured workflows, ensuring defined roles, seamless handoff protocols, and centralized oversight for efficient multi-agent ecosystems. B Cross-Functional Network (Breaking departmental silos) D C E F Various ‘coordination specialists’ coming together to make an AI ecosystems that can adapt dynamically to enable enterprise- wide intelligence breaking silos. A B Enterprise Agent Swarm(Intelligent , adaptive ecosystem) F J G D H Welcome to A2B2A* era. Now you have a self-organizing AI ecosystem that adapts fluidly to business needs, leveraging distributed intelligence to optimize operations and refine itself. E D B A C *Agent to Business to Agent (A2B2A) Agents interact with businesses and other agents, creating a seamless loop of intelligence and execution. Advanced www.polestarllp.com

3. www.polestarllp.com

4. Agentic AI in Pharma Rare Disease Identification & Sales Enablement Agent This will help improve the QoL of the patients, bring personalized insights about the doctors decreasing TAT for interactions, and more. The example below is that of an orchestrator agent for Rare disease identification and sales enablement managing the entirety of all sub-agents to identify patients and their doctors- to help you not only plan for subsequent activities with your sales team and track the follow-ups. More about Agentic AI in Pharma here P.S. The precursor to even getting started with Agentic AI in pharma is having quality data ( think more about having a unified data) , having integration with the right tools (APIs have come a long way), and managing the internal stakeholders well (Change management FTW) Gartner By 2027, non-technology-related reasons, such as high costs, poor culture integration, lack of proper governance and misaligned processes, will cause 40% of GenAI project failures in life sciences. www.polestarllp.com

5. CPG is saying ‘AI’with Agentic approach Now with CPG companies expected to invest over $2.5 billion in AI and machine learning technologies its natural for them to expect more than just ‘which promotion to run in which store?’ analysis which their traditional AI systems offer currently when the actual question is how do all these pieces fit together to maximize our overall business? An estimated $500 billion to $1 trillion is spent globally on CPG trade promotions annually, but a significant portion yields virtually no results. The reason why you are drowning in the trade spend complexity i.e. the fundamental limitation isn't computational power—it's architectural. Agentic AI provides the change needed with the architectures. And this is whereAgentic AI in CPG in CPG comes into picture. The multi-agent approach works more like your best cross-functional team—with specialists who communicate constantly, see interconnections, and understand how decisions in one area ripple across the entire business. When you look at it, Traditional AI operates like separate specialists who never talk to each other—one handling pricing, another managing promotions, a third overseeing distribution. They each optimize their piece without understanding the whole picture. Agent - Focused Trade Spend Optimization System Data Engineering Agent Data Connector Agent Historical Sales Beat Data Salesman Data Targets Product Distribution Incentive Schemes Prodcut Data Trade Data Retailer Route Trade Promo Externals Harmonizes retailer taxonomies, cleans data, creates unified foundation Maps the relationships across variables for cross dimensional views Strategy Agent Execution Agent Analyst Agent Uplift assessment to optimize trade schemes for Retailers and targets Sales team Integrated Analysis (Cross – dimensional optimization) Trade and Sales Target & incentives Trade Spend Optimization Orchestrator Tracks implementation progress , creates retail-specific plans and works in a Continuous Learning Feedback Loop www.polestarllp.com

6. Agentic AI For Manufacturing Order Management From being confused about where to start their automation journey, to seeing automation as a pillar of IT infrastructure – agents have changed the perspective and industry outlook in a short time. 62% of companies expect ROIs of more than 100% on agentic AI, just like they experienced with Generative AI Here’s a use case for an orchestrator agent for Large Order Management in Manufacturing, which coordinates different sub-agents to streamline inventory, production, and procurement processes. Source: PagerDuty With this agent you can not only track if you have sufficient stock but also look at close warehouses and locations from which the order can be fulfilled. And then further propose the possible value with a change in contract. Large Disruptive Order Alternate Pitch with revised timelines & budgets Orchestrator Agent Expected TAT 30 mins* AI Large Disruptive Order Timeline bot Sufficient for Order Inventory Agent Yes No Nearby Warehouse Levels Transportation Agent AI Gap Check Expected TAT for the entire process is 30minutes – usually this would take days not just hours. Scenario bot Sufficient for Order Production Agent Production Schedule Yes No Material Check AI Overtime Calculation Capacity Calculation Procurement Agent It is possible to create more such agents with ease to reduce decision making TAT and improve operations. www.polestarllp.com

7. Agentic AI In Supply Chain Optimization Agentic AI can fill this gap by analysing thousands of interconnected variables in supplier management across quality, reliability, risk, and cost dimensions – something even expert teams struggle with consistently. According to a Forrester and Ivalua study, only 13%of business leaders have formal supplier management processes in place– which leaves a lot of opportunity for improvement. Agentic Vendor Selection Bot System Inventory Monitoring Agent Vendor Database Agent Inventory levels Threshold data Demand Forecasts Vendor profiles Price data Quality Metrics Product data Historical orders Delivery stats Reliability score Monitors inventory levels and triggers procurement workflow when threshold are reached Maintains comprehensive vendor information for multi-criteria selection RFQ Generator Agent Analysis Agent Recommendation Agent Automatically identifies suitable vendors and raises requests for quotes Evaluates quotes based on price, quality, delivery and vendor reliability Creates actionable reports with optimal vendor selection details Procurment Orchestrator Manages approval workflow , facilitates user verification and executes order placement in a continuous learning feedback loop Our vendor selection agent doesn't simply identify the cheapest vendor; It constructs optimal solutions that balance immediate needs against long-term strategic considerations. Reveals valuable supplier relationships that traditional approaches routinely overlook in complex global supply networks. & more.. www.polestarllp.com

8. About Polestar Analytics At Polestar Analytics, we build data ecosystems that evolve with your business—engineering solid foundations, extracting actionable insights, and deploying intelligent AI solutions that deliver measurable ROI across CPG, Retail, Manufacturing, and Pharmaceutical industries. You should also read Agentic AI for CPG Guide to Agentic AI workflows Agentic AI for RGM Agentic AI for Pharma Understanding Agentic frameworks www.polestarllp.com