Summary

A multinational retailer receives triple its usual online orders overnight. A lot needs to be done to keep up—pivot warehouse schedules, re-route shipping plans, keep customers informed in real-time, reconfigure the backend systems, and much more. Traditional systems freeze under pressure. Operations stall. Customer satisfaction plunges. If only the retailer had an infinite, perfectly synchronized workforce moving at supersonic speed. This once-mythical advantage is creeping closer to reality and Agentic AI will soon make it possible.

The Original AI Trajectory

Early AI efforts were rule-based, built to follow a set of strict if-then statements. They handled routine tasks but required meticulous programming. Next came cognitive systems, which learned from historical data and made predictions—helpful, but still limited in their ability to operate independently.

Now we are approaching a phase where AI “agents” can autonomously orchestrate actions based on highlevel objectives. It’s the difference between a tool waiting for input and a teammate taking initiative. These agents detect problems, hunt down needed resources (like relevant APIs or data repositories), and solve challenges as they occur.

The shift is transformative: from passively taking orders to proactively making decisions.

  1. Adaptive Execution

    Agents flex in real-time, analyzing current conditions and resources. They don’t just follow a plan; they course-correct if new data suggests a better path.

  2. Reduced Human Bottlenecks

    Instead of requiring sign-offs or waiting for instructions, agents self-navigate. This frees up human talent to focus on strategy, design, and innovation.

  3. Cross-System Collaboration

    Agentic AI doesn’t exist in a vacuum. It taps into CRM platforms, ERP modules, and external data sources, orchestrating end-to-end workflows that once required tedious manual intervention.

  4. Operating at Scale

    With the right foundation, thousands of agents can function across an enterprise, each specialized for tasks like fraud detection, supply chain updates, or IT maintenance.

An Evolution, not a Silver Bullet

Agentic AI remains an evolving concept, shaped by continuous breakthroughs that expand its practical potential across industries. As organizations move beyond pilot programs, they can expect AI-driven agents to collaborate more seamlessly—managing entire processes together and passing context fluidly—while adopting increasingly nuanced planning techniques that draw on both short-term data and historical knowledge. Over time, these autonomous solutions will refine their understanding of immediate tasks and overarching goals, making them more adaptive and capable of forging real-time connections across multiple systems.

In tandem with these technical strides, outcome-based pricing is poised to gain traction, where enterprises pay for AI services only when they realize measurable efficiency or performance gains. Taken together, these developments point to a future in which Agentic AI transcends isolated experimentation and transforms the very fabric of how businesses operate, innovate, and compete.

Building an Agentic Enterprise

In 2025, atleast 25% of enterprises using GenAI are set to experiment with Agentic AI. If history is any indication, organizations often overspend on AI tools, hoping for breakthroughs that never materialize. Why? Because these projects are siloed or duplicative, with overlapping budgets and limited visibility into overall ROI.

How do we solve this?

Agentic AI thrives when built on a unified platform. This platform handles data governance, system interoperability, and usage metrics. Instead of each department rolling out its own agent with separate tools, a shared platform means consistent standards, better cost control, and a single source of truth for tracking performance. While “platform-centric” might sound buzzy, it’s the practical antidote to uncoordinated AI sprawl.

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Waiting for the dust to settle?

Contrary to headlines touting AI as a magic fix, Agentic AI is a natural extension of the evolution we have seen over decades. Yes, it’s more advanced and capable, but it’s not a sudden meteor impacting your business. It is simply the next logical step in enterprise technology, shaped by user needs for speed, flexibility, and resilience.

Hype often outstrips reality. Many organizations experiment with AI pilots, only to realize they lack the infrastructure or budgets for large-scale deployment. Genuine ROI emerges only after iterative deployments and real-world testing. The novelty is that now, with Agentic AI, those deployments can learn, adapt, and pivot far faster than before.

Done right, Agentic AI can make organizations truly agile, proactive, and ready to adapt in real-time. And without a doubt, the journey requires cultural shifts, governance structures, and a willingness to experiment. Now is the window of opportunity.

Disclaimer Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the respective institutions or funding agencies.