AI is a horizontal technology with transformative potential not seen since the rise of the smartphone. Now, its latest evolution, agentic AI, has sparked an adoption race.
What makes agentic AI different is its ability to manage and execute end-to-end processes through cycles of reasoning and action, not just answer questions or follow fixed rules. In doing so, AI agents move beyond being tools and become true team members, marking a new era of enterprise productivity, efficiency, and growth.
But are organizations moving so quickly that they’re committing to agentic AI before identifying the right use cases?
Research shows that by 2025, 60% of enterprise AI rollouts will embed agentic architectures. Yet by 2027, more than 40% of those projects are expected to be cancelled. Enthusiasm alone isn’t enough; business leaders must pinpoint where agentic AI can create real, measurable impact.
Download this e-book to discover proven and practical applications of agentic AI across retail, manufacturing, BFSI, and insurance, designed to spark ideas and help you identify where the technology can deliver the greatest value in your organization.
A snapshot of agentic AI use cases across industries
Discover how Agentic AI helps businesses across retail, manufacturing, wealth management, and insurance tackle deeply entrenched challenges that can’t be solved through incremental productivity gains alone.
In retail, agents hold the key to superior customer experience
Traditional e-commerce works when shoppers know exactly what they want. Today, customers expect guidance, personalization, and seamless journeys. Agentic commerce makes this possible by reimagining retail from discovery to checkout.
- Autonomous shopping journeys: Shop on behalf of customers by browsing catalogs, applying promotions, and completing purchases.
- Dynamic personalization: Adapt recommendations and interfaces in real time based on shopper behavior.
- Smarter merchandising: Enrich catalogs with structured data, optimize layouts, and bundle offers dynamically.
- 24/7 customer support: Deliver human-like interactions, reduce call abandonment, and improve churn prediction.
In manufacturing and supply chains, agents ensure resilience
A great customer experience starts long before a product reaches the shelf—or the cart. Intelligent agents orchestrate, optimize, and communicate across the value chain, ensuring agility from production to delivery.
- Production orchestration: Optimize runs, adapt to demand shifts, prevent breakdowns, and ensure quality through computer vision.
- Smarter warehouses: Use live signals and simulation to streamline slotting, picking, and replenishment.
- Real-time logistics: Reroute shipments around disruptions, reduce waste, and minimize unnecessary trips.
- Demand sensing & forecasting: Blend IoT, macroeconomic data, and sentiment to refine procurement, pricing, and inventory strategies.
In wealth and asset management, agents deliver customized, compliant investments
Wealth and asset management firms juggle massive data, complex regulations, and rising client expectations that outpace traditional automation. Agentic AI enables real-time, adaptive decision-making across the financial lifecycle.
- Personalized financial advice: Robo-advisors rebalance portfolios and match suitability in real time, both client-centric and regulator-approved.
- Allocator decision support: Reduce $15–25M in annual drag by automating rebalancing, hedging, swing pricing, and compliance.
- Structured product issuance: Design, simulate, and risk-manage payoffs with real-time hedging and capital optimization.
- Regulatory compliance: Leverage bitemporal databases to reproduce exact historical data instantly, reducing penalties and delays.
- Client lifecycle management: Enhance onboarding, support, and engagement with conversational AI assistants and sentiment-driven insights.
In insurance, agents automate decisions from quote to claim
Insurance remains weighed down by manual workflows, fragmented data, and slow claims cycles. Embedding agents across the value chain accelerates decisions, cuts errors, and improves customer satisfaction.
- Faster underwriting: Scan contracts, flag risks through online searches, and suggest exclusions, streamlining reviews, reducing errors, and improving accuracy
- Claims automation: Automate broker communications, easing underwriter workload and speeding responses to keep claims and submissions moving smoothly.
- Risk management: Identify upcoming renewals and accumulation risks early to adapt policy documents and prevent costly exposure.
- Portfolio reporting: Deliver up-to-the-minute portfolio insights, automating reports, tracking goals, and surfacing performance data.
Your agentic AI questions, answered
