Almost every tech company and startup today claims to be AI-powered

…Especially business intelligence (BI) tools. But are these tools leveraging agentic AI to the technology’s fullest extent? Or do these platforms simply feature traditional dashboards with a few minor AI features, like chatbots? With so much noise in the tech world today, evaluating AI BI tools for enterprise use is becoming more challenging. 

With the rise of agentic AI, writing SQL (Structured Query Language) and performing manual analysis is becoming less of a barrier to both technical and non-technical users across enterprises. Agentic AI platforms like Oraion don’t just answer questions. Our agentic AI platform uses your data to reason, surface insights, make predictions, and offer suggestions on next steps. 

If you’re working in data analytics or IT, selecting BI tools that make full use of agentic AI ensures that your team can get the actionable insights they need – and fast. Here’s what you can do to make sure you’re choosing the right solution for your enterprise. 

What are AI-Powered BI tools? Artificial Intelligence Use in Business Intelligence 

AI-powered BI tools use artificial intelligence to help businesses collect, process, and analyze data. While traditional BI includes dashboards, data warehouses, and reports based on historical data, AI-powered BI allows organizations to automate data analysis, predict future trends, provide deeper insights, and ask questions using natural language. 

Here are some examples of how AI can help enhance business intelligence tools:

• Understand context and intent: Agentic AI pulls data from across different systems to better understand the context around your natural language queries. 
  
  

• Reason across your scattered data sources: AI tools can pull from your CRM, traditional BI tools like Looker, Slack, and other platforms to connect dots you might otherwise miss.
  
  

• Provide actionable insights: BI tools that use agentic AI can alert you from where you work, like in Slack or via email when the platform detects anomalies, trends, or opportunities to drive revenue. 
  
  

• Recommend actions: While traditional BI looks to the past, AI-powered BI can forecast the future and offer tips on actions you can take now.
  
  

• Learn and adapt: AI-powered BI tools learn from your actions, inputs, and data, so you’re constantly improving. 

While some traditional BI tools offer limited AI features (e.g., ChatBots), Agentic AI takes your business intelligence to a deeper and more tailored level. 

Core Criteria for Enterprise-Grade AI BI

Implementing and deploying any BI tool requires buy-in from both the business and IT teams. While business users will be looking for features that optimize and enhance their strategy, IT will have specific requirements to ensure compliance and enterprise-grade security. 

Here are the non-negotiables:

Industry 

Be sure to check that the BI solution you’re evaluating is a good fit for your specific industry. 

Security and Compliance

For companies working in – or selling into – highly regulated industries like healthcare, finance, and government, your BI platform must meet best-in-class security standards. Look for:

• SOC 2 Type II certification: Ensures controls around security, availability, processing integrity, confidentiality, and privacy
  
  

• HIPAA compliance: Critical for healthcare organizations handling protected health information, or PHI. 
  
  

• Role-based access controls (RBAC): Granular permissions to ensure users only see data relevant to their role, improving access management 
  
  

• Data encryption: Both at rest and in transit
  
  

• Audit trails: Complete logging of data access and changes for compliance reporting

Oraion is both HIPAA and SOC 2 certified, meeting the compliance requirements that enterprise IT teams demand.

Data Management, Governance and Oversight 

Because agentic AI draws from multiple data sources, understanding how your data is being used is key for building trust with stakeholders, as well as ensuring compliance. 

• End-to-end data lineage: Track data from source systems through transformations to final reports
  
  

• Version control: Maintain history of changes to data models, metrics, and reports
  
  

• Data quality monitoring: Automated checks for completeness, accuracy, and consistency
  
  

• Certified metrics: Centralized definitions of business metrics to eliminate conflicting numbers across teams

Without robust governance, even the most sophisticated AI will produce insights that teams don't trust. Worse, misusing data can lead to regulatory fines, customer churn, skeptical investors, and lengthy lawsuits. 

Scalability and Integration

Your BI platform needs to scale with your organization and integrate seamlessly with your existing tech stack. As you begin evaluating tools for your organization, ask yourself these questions to ensure the solution is the right fit.

• Do you need cloud, on-premise, or hybrid deployment?
  
  

• Can the BI tool handle my organization’s datasets while maintaining performance?
  
  

• Does the platform connect to your data warehouses (Snowflake, Databricks, BigQuery), databases, SaaS applications, and Excel files?
  
  

• Is there API access to enable custom integrations and workflows?
  
  

• Will this BI tool integrate with collaboration tools like Slack, Microsoft Teams, and email?

Actionability and Automation

Traditional BI tools offer reports, visualizations, and graphics, which display information but don’t drive action. Agentic AI enables BI tools to analyze data in order to automate repetitive workflows or suggest future actions, leading to automated insights, intelligent alerting, automated reporting, workflow automation, and prescriptive recommendations. 

Automated reporting alone can save analysts hours per week, freeing them to focus on strategic analysis instead of manual report generation.

Natural Language Understanding

Before AI, analyzing and managing relational data bases required writing SQL. Now, natural language querying allows users to ask questions in their native language. The best AI-powered BI tools take this a step further and use context to understand not only your language but your intent. 

Agentic AI enables your team to write natural language queries that accomplish the following:

• Handles ambiguity: Interprets "sales" correctly based on context clues, whether the user means the team itself, revenue, units sold, or pipeline value
  
  

• Maintains conversation context: Remembers what you asked three queries ago and builds on it, like Claude, ChatGPT, Perplexity, and Gemini 
  
  

• Better answer follow-up questions: "Why did that happen?" "Show me the same thing for last year"
  
  

• Learns your business’s unique terminology: Adapts to your company's specific language, acronyms, and metrics, including naming conventions 

User Experience for Technical and Non-Technical Users

Enterprise BI needs to serve everyone from C-suite executives to data analysts:

• Customizable interfaces: Allow non-technical users to design their own views.
  
  

• SQL notebooks: Give analysts the power to write custom queries when they need to go deeper.
  
  

• Interactive filtering and drill-downs: Let users explore data dynamically with complex filters and highly tailored insights.
  
  

• Data visualizations on-demand: Get charts, graphs, maps, and tables created for you one the fly.

Oraion's built-in SQL notebook demonstrates this balance perfectly. It gives data analysts the power they need without replacing them with automation. Instead, it amplifies their capabilities, handling routine queries while they focus on complex analysis and strategic insights.

Customization and Personalization

Enterprise buyers have a wide range of needs and priorities. When choosing an BI tools, consider the following:

• Ease of building custom dashboards: Can teams like operations, finance, and sales build dashboards with KPIs and metrics without data analysts? 
  
  

• Personalize for roles: Can the solution be personalized per role?
  
  

• Enable white-labeling: Does the solution allow you to showcase your company's branding?
  
  

• Adapt to organizational structure: Is the BI solution a good fit for your company's hierarchy, business units, and reporting lines?

When users see only what's relevant to them, adoption skyrockets and decision-making accelerates.

Outcomes First, Not Features 

When evaluating BI platforms, especially solutions that use AI features matter less than outcomes. Don’t chase after shiny AI features. The right platform should deliver:

• Instant insights: Users get answers in seconds without putting in a ticket for the data analytics team. Questions that used to take days now take moments.
  
  

• Reduced analyst dependency: Routine questions are handled automatically, analyst reports are generated in seconds. This allows non-analysts to become more autonomous, and allows analysts to deliver quicker results to decision-makers. 
  
  

• Smarter decisions, faster: When insights are automated and recommendations are proactive, decision-makers act on opportunities your competitors are likely missing.
  
  

• Automated reporting: Finance, operations, sales, and other teams get their recurring reports automatically, eliminating hundreds of hours of low-impact manual work
  
  

• Measurable ROI: Track the platform's impact through time savings, faster decision cycles, improved forecast accuracy, and increased adoption across the organization.

Making the Right Choice for BI Tools 

As mentioned earlier, many businesses approach BI evaluation by comparing feature lists. But features don't drive business value. Ask yourself these questions to make an informed decision:

• Does this platform actively make our people smarter, or does it just give them more dashboards to check and additional busy work?
  
  

• Will this BI tool reduce the time from question to decision, or add complexity to our analytics workflow?
  
  

• Can this AI-powered business intelligence solution scale with our growth and adapt to our changing needs?
  
  

• Does IT trust the new solution, and will the business actually use it?
  
  

• Does it meet enterprise-grade security and compliance requirements for our industry?

Oraion is the BI Tool for Enterprise AI 

As a part of the next generation of AI-powered BI tools, Oraion was built from the ground up to meet enterprise requirements:

• Security and Compliance: HIPAA and SOC 2 certified, with comprehensive data encryption, role-based access controls, and complete audit trails for regulated industries.
  
  

• Integration: Seamlessly integrates with Slack, Microsoft Teams, major data warehouses, and your existing data infrastructure.
  
  

• Analyst Empowerment: The built-in SQL notebook gives data analysts complete flexibility to write custom queries while AI handles routine requests. Oraion doesn't replace analysts. On the contrary, our agentic AI platform multiplies their impact.
  
  

• Automated Intelligence: Oraion goes beyond dashboards to deliver instant insights, automated reporting (a critical capability for finance teams), and prescriptive recommendations. Users get answers in seconds instead of days.
  
  

• Customization: Fully customizable so teams only see metrics and insights relevant to their role. No information overload. Just what matters.

Ready to see how Oraion meets every enterprise requirement for AI-powered BI tools... and goes further?

Traditional BI tools tell you what's already happened. Oraion shows teams across the enterprises what's happening, what will happen, and what steps to take next. With enterprise-grade security, seamless integrations, automated insights, and tools that empower both analysts and business users, Oraion delivers the outcomes that matter: faster decisions, smarter actions, and measurable business impact. Read about Oraion’s use cases and features.  

Schedule a demo to see how Oraion transforms business intelligence from reactive reporting to proactive decision intelligence.

FAQ

What are some of the benefits of using agentic AI in business intelligence?

• Automated insights: Proactively surface anomalies, trends, and opportunities

• Intelligent alerting: Smart notifications based on thresholds, patterns, and business context

• Automated reporting: Schedule and distribute reports without manual intervention—a game-changer for finance teams drowning in recurring report requests

• Workflow automation: Trigger actions in other systems based on data conditions

• Prescriptive recommendations: Go beyond "here's what happened" to "here's what you should do"