Agentic AI: From Hype to Last-Mile Adoption 

The next wave of enterprise AI is not just about systems that respond — it’s about those that can reason, act, and adapt. Welcome to the age of Agentic AI, where intelligent agents carry out complex workflows, collaborate with humans, and continually learn to improve business outcomes. 

1. Agentic AI — A Fast-Growing Frontier and Industry Momentum 

Agentic AI represents a leap from static automation to autonomous decision intelligence. 

The market is already showing tremendous momentum — projected to reach USD 93 billion by 2032 (CAGR ~45%). This growth is powered by enterprises embedding agentic systems into everyday workflows — from customer support and supply chain to marketing and demand planning. 

Simply put, Agentic AI is becoming the operating system for enterprise intelligence. 2025 has also seen a surge in ecosystem activity. For instance, Accenture and HCLTech–Google Cloud unveiled frameworks to assist enterprises in scaling multi-agent systems. These partnerships signal a clear shift — Agentic AI has moved beyond the innovation labs and into boardroom strategies. 

2. Position on the Hype Cycle 

Agentic AI is currently at the peak of interest on the hype curve. There’s excitement, experimentation, and a flurry of pilot programs — but few large-scale, production-grade deployments yet. 

Enterprises now face the crucial test: moving from “can we build it?” to “can we scale it safely, measure it, and sustain value?” 

3. Enterprise Outlook: Curious but Cautious 

Fortune 500 companies are eager to embrace Agentic AI — but they’re also pragmatic. 
Governance, reliability, and explainability remain top concerns. The opportunity is undeniable, but success depends on disciplined implementation, clear KPIs, and scalable architectures. 

4. From ROI to RO(A)I 

Traditional Return on Investment (ROI) metrics fall short for agentic systems. 
We need to look at Return on (Agentic) Intelligence (RO(A)I). 

This involves measuring various aspects such as tasks that are autonomously executed or accelerated, human hours saved and effectively redeployed, and the reduction in decision-cycle time. Additionally, it encompasses continuous learning and ongoing improvement. 

5. The Tredence Approach: From Pilot to Production 

At Tredence, we see Agentic AI as a key enabler of Last-Mile Adoption — turning insights into measurable impact. 

Our approach combines deep industry understanding with innovation driven by Tredence Studio, our in-house innovation arm. This integration ensures that every solution is contextual, relevant, and ready for adoption.

We adopt a pilot-to-production approach that goes beyond mere proof-of-concept. Our goal is to build intelligent systems capable of learning, adapting, and delivering sustained business outcomes.

We also prioritise clarity on measurement, defining success upfront by tracking metrics such as productivity, efficiency, cost reduction, and business value. This ensures that every agentic initiative drives real results, not just activity.

Ultimately, Agentic AI is a vehicle for achieving business impact. The true objective is to enhance customer satisfaction, improve on-shelf availability, optimise return on ad spend, refine promotions, and attain various other business goals. 

By enabling insights faster, at scale, and at lower cost, Agentic AI helps organisations convert intelligence into action — driving the next frontier of enterprise value creation. 

Introducing MilkyWay: Multi-Agentic Decision Intelligence 

Our latest innovation, MilkyWay, advances this vision further. MilkyWay is Tredence’s multi-agent workflow and decision intelligence system, designed to coordinate multiple agents across data, analytics, and insights workflows. It aims to increase analyst productivity fivefold and deliver up to 50% cost savings — helping enterprises transition from manual analysis to autonomous decision-making at scale. 

In essence, MilkyWay exemplifies how Agentic AI can unlock exponential gains in efficiency and agility. 

At Tredence, we’re helping enterprises move from insights to action, from pilots to production, and from ROI to RO(A)I — ensuring Agentic AI becomes a sustainable driver of transformation, not just another wave of hype.  

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