Here's a sobering statistic: nearly 80% of companies have deployed generative AI in some form, yet roughly the same percentage report no material impact on earnings.

An MIT Media Lab Project released in August 2025 made the claim 95% of businesses aren’t seeing any returns on Gen AI investments. This bias against generative AI has made some organizations cautious about investing in AI tools overall. Most AI tools stop at generating outputs. Agentic AI, on the other hand, understands context, takes action, and is leaving hallucinations and legacy tools far, far behind.

In a recent report about unlocking the potential of Agentic AI, McKinsey calls this challenge the gen AI paradox. The larger problem: businesses are trying to bolt new technology onto legacy systems that were never designed for the speed and complexity of today's fast-moving business environment. But writing off the potential for Agentic AI to reshape business intelligence would be like dismissing the future of the internet when Amazon, now the leader in cloud computing, was near bankruptcy as the DotCom bubble was bursting. 

If you're running operations, data, or finance at a mid-size or enterprise company, you've probably felt this tension firsthand. Your BI stack (e.g., Tableau, Power BI, Looker) gives you visibility into what happened last week or last quarter. But by the time you see the data, analyze it, and decide what to do, the moment has passed. You're constantly playing catch-up, and your team is stuck waiting on analysts to answer questions that should have answers in seconds, not days.

The gap between what legacy BI delivers and what your business actually needs is widening. Oraion’s agentic AI solution closes that gap. 

Understanding the History of Business Intelligence Tools

BI tools became popular in the 1970s and 1980s, when on-premise data warehouses became crucial to make business decisions. Tools like IBM's Cognos, SAP Business Objects, Microsoft's SQL Server Reporting Services, Oracle's OBIEE, and MicroStrategy enabled IT teams and data scientists to analyze and manage enterprise-scale data. For teams like sales, marketing, operations, and finance, getting the necessary insights was practically impossible. 

The cloud era ushered in more user-friendly tools like Tableau, Power BI, and Looker, with modernized interfaces that made data more accessible across organizations. 

But problems still persisted. Static dashboards, analysts bottlenecks, and lagging insights meant that teams across the organizations lacked the insights they needed to make informed decisions. Traditional BI tools still showed what already happened, not what was about to happen. 

While enterprises and other established organizations continue to optimize legacy BI systems, a new crop of Agentic AI solutions are hitting the scene from both startups like Oraion and major tech companies like Salesforce (Agentforce). Agentic AI promises to change how we use data to make business decisions. According to a report by IBM, 86% of executives believe that by 2027, AI agents will make process automation and workflow reinvention more effective.

What are AI Agents?

So what are AI agents exactly? Buzzwords aside, AI Agents are software systems that perceive context, reason, and execute multi-step tasks. Agents take into account the user’s goal and constraints to make dynamic decisions, adapt quickly, and evolve based on interactions and feedback across multiple systems.  

Advantages of Agentic AI over Traditional BI Tools

• From fixed outcomes to predictive insights: Traditional BI tools follow fixed workflows and rules. Agents make contextually forecasted insights based on your organization’s unique history and position, linking in context from multiple sources. 
  
  

• From static to adaptive: Legacy BI tools have limited functionality. Agents use data from your organization's disparate system to learn, improve, and adjust their behavior over time. Agents don’t rely on memory or fall subject to hallucinations, instead they retrieve data from its original source to ensure accurate answers every time.
  
  

• From code-first to evaluation-first: Traditional software metrics don't predict agent success. What matters is outcomes, not perfect implementation.

Beyond "What Happened": The Four Levels of Agentic AI Analytics

Legacy BI gets stuck at helping businesses understand what happened, or Description Analytics. To stay competitive in today’s market, businesses also need Diagnostic, Predictive, and Prescriptive Analytics, which are enabled by Agentic AI platforms like Oraion.  

• Descriptive analytics tell us, "What happened?" This is helpful to understand historical performance and trends, but doesn’t help businesses understand what’s happening in real time. 
  
  

• Diagnostic analytics help us understand, "Why did it happen?" It digs into root causes using drill-downs, correlation analysis, and data mining. With the additional context offered through Agnetic AI, businesses can better understand the various factors influencing their outcomes.
  
  

• Predictive analytics answers questions like "What is likely to happen?" Using historical data and AI, predict analytics forecasts changes in customer demand, sales performance, or potential risks before they materialize, with the help of real-time data. 
  
  

• Prescriptive analytics helps us decide, "What should we do about it?" Agents can make recommendations to help you achieve specific goals based on real-time data. The results? You reduce risks, optimize operations, and automate complex and mundane tasks, freeing your team to focus on the more interesting aspects of running and scaling your business. 

If organizations are going to see the real value of investments in Agentic AI, they need to embrace the value offered by diagnostic, predictive, and prescriptive analytics. And Legacy BI won’t get you there. 

Getting Started with Oraion: Agentic AI Built for Business Intelligence

Most organizations today rely on two separate layers to get insights:

• A data warehouse or lake (like Snowflake, Databricks, BigQuery, or Redshift)
  
  

• A BI tool (like Power BI, Tableau, or Looker) on top to visualize data.

That dual-stack setup is costly, slow to implement, and dependent on analysts to deliver insights. Oraion removes that divide.

Oraion is the full stack — your data engine and your intelligence layer in one platform. It ingests, organizes, and analyzes data natively, removing the need for multiple tools and integrations.

For companies already deeply invested in Snowflake or Databricks, Oraion works alongside them, too. It connects directly at the data layer to unify context, automate insights, and deliver answers instantly.

Whether you are consolidating your stack or complementing it, Oraion turns complex data ecosystems into one powerful, context-aware intelligence platform.

Let’s dive in deeper. 

Context-Rich Insights in Natural Language

Data scientists, as well as members on the Ops and Finance teams can query large datasets and generate powerful insights in easy-to-understand visualizations and actionable language in plain English – in seconds. No SQL or middlemen required. 

By democratizing access data across the organization, non-technical users such as your Sales Ops Manager can pull real-time data and act on opportunities without waiting for data scientists to put together a dashboard. 

From Reactive to Proactive Intelligence

While BI tool shows what happened, Oraion tells you why it's happening and what to do next.

We move beyond descriptive analytics into diagnostic, predictive, and prescriptive territory. Our platform helps you understand the various factors impacting your business, allowing you to better forecast and make real-time decisions. This means you’re staying ahead of the curb. 

Speed and Simplicity at Scale

Setting up Orion takes minutes, while implementing legacy BI tools often takes weeks or even months. Our agentic AI platform cleans and prepares your data, eliminating the tedious manual work that eats up analyst time. 

Key benefits of Oraion’s Agentic AI platform 

• Eliminate delays: Real-time insights mean you can act on opportunities as they emerge, not after they've passed.
  
  

• Remove manual tasks: Automated data prep and analysis free your team to focus on strategic work.
  
  

• Scale seamlessly: As your business grows, Oraion scales with you without requiring massive investments in data storage.
  
  

• Personalize at scale: Different teams such as Financial, Operations, Data Analytics, and Sales  get the insights they need, in the format they need, without custom development.
  
  

• Build adaptability and resilience: When everyone across the organization  has access to actionable, real-time intelligence, your operations become more adaptive and resilient to change.

Agentic AI isn’t just about optimizing your existing BI tools. It’s about reinventing your processes entirely to run your business more efficiently and strategically. 

Integrating Agentic AI with Your Tech Stack

We understand that startups, scale-ups, and major enterprises alike put significant time and resources into building their tech stacks. That’s why Oraion integrates with your existing systems, supporting open standards like the Model Context Protocol and Agent2Agent. These buzzwords, which are becoming more popular among the hyperscalers, basically mean that our Agentic AI solution builds a layer of intelligence on top of your current tech stack without ripping and replacing everything. 

Making the Move to Agentic AI 

With Oraion, making the transition from legacy BI to Agentic AI is straightforward. You can keep using your existing tech stack and legacy BI tools leverage. Within days Oraion will allow you to start produces game-changing insights that would be impossible without Agentic AI. 

Ready to leave legacy BI in the past? 

Are you for a world where you can get answers immediately? Where you can see what happened, what’s happening, and what’s going to happen?

See what Oraion can do in minutes.  Real insights. Real-time. For real people across your organization. No lengthy implementation. No analyst bottlenecks. No more falling behind while you wait for outdated insights. 

The move from legacy BI to agentic AI starts now. Schedule your demo today. 

FAQ

What are the key challenges or problems with legacy BI tools?

Challenge 1: You're looking at what already happened

Legacy BI excels at descriptive analytics that tell you what happened, such as last quarter’s revenue or last month’s conversion rates, or where inventory levels were after Black Friday. By the time data science teams configure and share the dashboards, the data is already outdated. 

While past trends can help businesses identify patterns and cycles, measure performance, understand customer behavior, and optimize operations, real-time insights allow you to respond to what’s happening in real-time to sudden social, economic, and political changes affecting your business. 

Challenge 2: Analyst bottlenecks slow down time to insights.

Today, sales, operations, finance, marketing, and other teams are still submitting tickets to the data team for visualizations on clunky dashboards. 

Data scientists, who often need to leverage specialized skills like writing SQL queries to access data and generate reports, mean non-technical employees are stuck waiting. The process of preparing and cleaning data – often line by line – means key business functions don’t get the insights they need in time. In fact, poor data quality cost large organizations $12.9 million annually, according to Gartner. 

Challenge 3: Integration complex and tech debt leads to data silos and poor governance

Your business’s data is scattered across email, Slack, CRM, ERM, support tickets, databases, spreadsheets, and across other SaaS tools in the cloud. 

Traditional BI tools often fail to stitch data from these different sources together. Integration is expensive, and tech debt rises quickly. Without a singular source of truth, teams across the organization struggle to align. 

Is Agentic AI just another trend? Why should we invest in an Agentic AI solution now?

The shift to agentic AI represents the next frontier in business intelligence. Companies that embrace agentic AI are moving fast, iterating, and seeing results. 

Legacy players like Microsoft with Power BI and Salesforce with Tableau offer sophisticated tools that will remain sticky for some time to come. Agentic AI platforms like Oraion offer businesses agility so you don’t need to wait weeks to get the answers you need, even if the legacy BI tools offer compelling data and visualizations. 

Major tech companies like Microsoft, Salesforce, AWS, Google, and ServiceNow are investing heavily in Agentic AI. Investors are pouring money into Agentic AI startups. On the other side of the AI boom, business intelligence will be radically transformed. Early adopters will be rewarded for making the change.