Agentic AI is no longer a distant frontier; it’s already reshaping how industries operate. In just the past two years, investment in agentic AI has surged, prompting Cloudera to survey IT leaders across 14 countries to understand how global enterprises are embracing this next wave of intelligent automation. You can read my initial overview of the survey here.

While we discovered several nuanced use cases, one near-universal finding emerged: The time to invest is now. In fact, 83% of organizations believe it’s important to invest in agents to maintain a competitive edge within their industry.

As a Chief Data and Analytics Officer, I see agentic AI as more than just another wave of automation. It’s a shift toward more intelligent autonomous systems that can augment human decision-making in complex, high-stakes environments.

Here’s how leading industries are starting to leverage that shift today:

Manufacturing: Optimizing supply chains and safety

From protecting workers to improving product quality, agentic AI is transforming how manufacturers solve their most pressing challenges.

Take the production line — a source of many costly delays and mistakes. AI agents are monitoring production lines to catch defects early on or intelligently reroute supply chain logistics when disruptions occur — significantly improving efficiency. Nearly half (49%) of manufacturing organizations are exploring supply chain optimization through AI agents, and 47% are leveraging them for quality control. In this way, agentic AI has the potential to fuel Industry 4.0 objectives, directly impacting enterprises’ bottom lines.

AI agents are also transforming safety practices in manufacturing by helping prevent accidents before they happen. Traditionally, health and safety inspections rely on manual, on-site assessments by contractors, which can be slow, inconsistent, and reactive. Agentic AI shifts this paradigm. By analyzing sensor data, incident reports, and environmental variables in real time, AI agents can detect early warning signs of equipment failure, hazardous conditions, or non-compliance.

Forty percent of manufacturers are exploring predictive maintenance agents to identify these early signals. This allows organizations to intervene proactively, prevent injuries, avoid catastrophic incidents, and in some cases, save lives. In high-risk environments like factories and plants, every minute matters, and agents enable faster, smarter decisions that protect frontline workers.

Healthcare: Elevating care with agents

In healthcare settings, AI agents have immense potential to drive better patient outcomes – especially when it comes to streamlining time-consuming tasks such as appointment scheduling (51%), diagnostic assistance (50%), and medical records processing (47%).

AI agents are helping medical professionals focus on what matters most: delivering better care. By relieving clinicians of time-consuming administrative tasks, such as surfacing relevant EMR data, processing insurance information, or helping a human more quickly analyze imaging results, agents free up valuable time and cognitive load. They also enhance the clinical workflow by summarizing patient histories, identifying patterns in diagnostics, and even providing evidence-based treatment recommendations.

This way, AI agents go far beyond simple automation. They serve as intelligent partners in making faster, more informed, and potentially life-saving decisions.

Far from simple automation, these agents act as intelligent partners in care delivery. A diagnostic agent trained on thousands of X-rays, for example, could detect early signs of pneumonia or lung cancer that might escape the human eye, alerting radiologists to review specific areas more closely. With AI agents enhancing both speed and accuracy, healthcare teams are better equipped to make life-saving decisions, faster.

Retail and ecommerce: Personalization at scale

In retail and e-commerce, agentic AI is unlocking new levels of personalization and operational agility. Retailers are already seeing measurable gains in customer satisfaction and sales by using AI agents to deliver more individualized experiences.

Retail and e-commerce organizations that took part in Cloudera’s survey plan to use AI agents for customer support (50%), price optimization (49%), and demand forecasting (48%).

On the front end, AI agents analyze things like browsing behavior, purchase history, and external trends to recommend products, adjust promotions, and respond instantly to customer needs. These interactions not only drive sales but also build loyalty through personalization at scale.

On the back end, agents are helping retailers anticipate demand, optimize inventory, and allocate resources more effectively. The common goal: smarter decisions made faster, with fewer manual inputs.

 The common thread: A future-ready data foundation

While the applications of agentic AI vary by industry, one factor unites them all: these systems are only as powerful as the data that fuels them. For agentic AI to succeed, enterprises need secure, unified, and real-time access to diverse data sets. They must ensure their infrastructure can support high-volume, high-velocity workloads. And just as important, they must embed governance, transparency, and accountability into every AI deployment.

Whether a healthcare provider hopes to streamline life-saving care, or a retailer seeks to entice loyal customers, enterprises can implement these systems and pull ahead in this early chapter of agentic AI.

About the Author:

Shayde Christian is Chief Data and Analytics Officer at Cloudera. Christian guides data-driven cultural change for Cloudera to generate maximum value from data. He enables Cloudera customers to get the absolute best from their Cloudera products such that they can generate high-value use cases for competitive advantage. Previously a principal consultant, Shayde formulated data strategy for Fortune 500 clients and designed, constructed, or turned around failing enterprise information management organizations. Shayde enjoys laughter and is often the cause of it.