Is Reporting Dead? The Rise of Agentic AI

Businesses have obsessed over reporting for years. We’ve built dashboards, cranked out endless reports, and convinced ourselves that if we just had better data, we’d make better decisions. But here’s the uncomfortable truth: reporting isn’t action. Most reports don’t drive change—they just tell us what we already know or suspect. Is reporting dead?

At NRF ’25 this year, we saw a demo of Quorso, a software service being used by one of our Fortune 500 retail clients. Instead of overwhelming store leaders with reports, it generates specific objectives based on peer store data. These aren’t just insights—they’re clear, actionable steps tied to outcomes. That’s the shift we’re starting to see: reporting isn’t just about tracking performance anymore—it’s about influencing it.

Take a simple example: a retailer notices portable fire pits are underperforming in some stores. The traditional response? Generate a report, compare numbers, pass it to store managers—and hope they figure out what to do next. With a more action-driven approach, the system identifies what’s working in similar stores and suggests specific actions—moving the display, bundling with accessories, or running a weekend promo. Store leaders get real-time, data-backed recommendations, not just numbers.

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The Problem: Data Without Direction

We’ve all done it. We generate reports thinking they’ll magically fix problems. We pull together dashboards, highlight the issues, and hope people will do something with the data. But too often, reporting is just shaming without a strategy. 

Here’s how it usually plays out:

1. Identify a problem. (“We need more pipeline!”) 
2. Run a report to confirm the problem. (“Yep, pipeline is low.”) 
3. Create another report to dig deeper. (“Looks like activity levels are down.”) 
4. Hold a meeting to discuss the reports. (“Pipeline is weak, we need more activity!”) 
5. Wait another quarter to see if anything changes.

Meanwhile, nothing happens. More data doesn’t fix the problem—testing actions and measuring results does.

What Needs to Change?

From Static Thinking to Data-Driven Action.

Mindsets need to change. It’s not just about having better tools—it’s about rethinking how we use data. Before we build the report or push for a new dashboard, we need to think about how the data will change behavior.  

From Reporting to Experimentation. 

What if instead of obsessing over reporting the problem, we put more energy into testing potential solutions? Data is great at showing us what happened, but it doesn’t tell us what will work next. That takes experimentation, iteration, and learning.

From Analysis to Ownership.

Too often, reporting lives at the leadership level. What happens when the people closest to the work—sales teams, store managers, product owners—have access to data that drives action instead of just oversight? What if they didn’t just see the numbers but had the ability to adjust and test in real-time? 

From Lagging Indicators to Leading Action.

Most reporting tells us what happened after the fact—quarterly performance, monthly sales, weekly utilization. What happens when businesses start using AI, automation, and real-time insights to identify and act on opportunities before they show up in a report? 

So, What’s Next? Agentic AI   

This isn’t just about automation. We’ve had automated reports and scheduled workflows for decades.  Agentic AI is different. Traditional automation follows predefined rules—a script, a cron job, or a scheduled task that runs at a set time or when triggered by a simple event. Agentic AI adapts, learns, and executes dynamically. It can:  

• Understand context. Instead of blindly following predefined steps, it considers changing conditions, business priorities, and past outcomes before acting. 
• Make autonomous adjustments. It doesn’t just flag problems—it proposes solutions and refines them based on what works. 
• Operate in real-time. It doesn’t wait for a report to be reviewed in a meeting—it detects issues and responds before they become problems. 

For years, businesses have relied on AI to surface insights—analyzing trends, generating reports, and making recommendations. But that’s not enough anymore. The next evolution is Agentic AI—AI that doesn’t just inform decisions but actively works to solve problems in real time.

Unlike traditional AI, which waits for human input, Agentic AI takes autonomous, context-aware actions. It doesn’t just highlight a problem—it adapts, tests, and refines solutions dynamically. 

• From reporting to execution. Agentic AI doesn’t just present a dashboard; it suggests the next best actions and tracks results. 
• From static workflows to adaptive systems. Instead of waiting for a scheduled report, Agentic AI monitors trends in real time and adjusts as conditions change. 
• From human-led decisions to AI-augmented strategies. Agentic AI identifies patterns, proposes solutions, and refines them based on what works—all while keeping humans in control of the bigger picture. 

Agentic AI transcends traditional reporting by autonomously identifying challenges and executing adaptive solutions in real time. It empowers businesses to shift from analysis to action, driving continuous improvement and measurable impact.  

So, what do you think—is traditional reporting a relic of the past? Is Agentic AI the next big thing?