Why Modern Enterprises Are Turning to Conversational & Agentic AI for Insights

As data grows more complex and decision timelines shrink, traditional analytics tools are hitting their limits. Businesses need more than dashboards—they need intelligent systems that understand, respond, and even act.

Enter conversational AI and agentic AI—two rapidly maturing technologies reshaping how organizations unlock insights and power decision intelligence across the enterprise.

In this blog, we explore how these technologies are being used today, what platforms are leading the way, and how organizations can harness them to create business value.

Business analytics has long revolved around static dashboards and scheduled reports. These tools helped answer “what happened” and “how it happened,” but they rely heavily on IT teams, offer limited interactivity, and don’t scale well to real-time business needs.

Today, decision-makers need more agility. They want to ask questions using natural language, get answers instantly, and take immediate action—all without technical complexity.

Conversational AI enables users to interact with analytics systems through natural language, asking questions like:

“What were our top 5 products by revenue last month?”

“Why did customer churn increase in Q2?”

Rather than navigating filters or building queries, users get real-time insights—visually or textually—within seconds.

Benefits of conversational AI in analytics include:

• Easier data access for non-technical users
• Faster decision-making through real-time Q&A
• Greater adoption of analytics across functions

This direct access to insights lays the foundation for stronger decision intelligence across the organization.

While conversational AI improves insight discovery, Agentic AI goes a step further by performing autonomous tasks. An agentic system doesn’t just respond—it acts.

For example, an agentic analytics system can:

• Detect anomalies and send proactive alerts
• Chain tasks like data pulling, summarization, and reporting
• Execute pre-defined actions like updating dashboards or notifying teams

According to Gartner, over 60% of enterprise AI deployments by 2025 will include agentic architectures, signalling a shift from predictive to proactive intelligence.

Many analytics and data platform vendors are embedding conversational and agentic capabilities into their ecosystems. One of the most advanced and integrated offerings comes from Microsoft, which provides a full-stack approach:

1. Power BI Copilot

Offers natural language querying and report generation directly within Power BI. Business users can generate visuals, ask questions, and summarize data without needing technical expertise. The recently introduced Standalone Copilot also allows querying across reports, models, and Fabric agents independently.

2. Microsoft Fabric Data Agents

Designed for interacting with data stored in Fabric Lakehouse or Warehouse tables. These agents specialize in supporting descriptive analytics and prompt-based exploration using a conversational interface.

3. Copilot Studio

A low-code platform that enables business users to create their own conversational AI agents. It connects to structured and unstructured data sources like SharePoint, SQL, Salesforce, and cloud databases, and can be embedded in enterprise tools like Teams or M365.

4. Azure AI Foundry

Supports more sophisticated, agentic AI architectures at scale. This platform enables multi-agent orchestration, integration with custom LLMs, and enterprise-grade performance. It’s best suited for organizations looking to build advanced automation workflows with custom logic.

5. Azure AI Services

For highly customized applications, developers can use Azure’s AI services to build agentic systems from scratch. These services offer maximum flexibility in model selection, orchestration, and deployment—ideal for enterprise-grade custom solutions.

Together, these platforms provide multiple paths to embed conversational AI and agentic AI across enterprise analytics workflows, from quick insights to full automation.

At Infocepts, we’ve implemented conversational and agentic AI solutions across industries to drive real outcomes:

1. HR Analytics Bot: Enabled a global auto manufacturer to conduct workforce planning through natural language interaction.
2. Sales Assistant Bot: Provided mobile-based real-time product insights to field teams at a global media conglomerate.
3. Customer Feedback Agent: Helped a polymer company analyze survey sentiment using conversational AI.
4. Insight Generator: Allowed business users at an agritech company to ask natural language questions and receive SQL-generated insights instantly.
5. FinGenie: A finance chatbot that empowers business teams to explore sales trends and performance metrics autonomously.

Each solution leverages either conversational or agentic AI—or both—to make analytics more accessible and decision-making more intelligent.

For organizations needing custom, enterprise-grade solutions, Infocepts offers a modular Agentic AI framework that integrates with:

• Any data source—cloud, on-prem, or semantic models
• Any foundational or enterprise LLM (Azure, OpenAI, AWS, etc.)
• Orchestration tools like Semantic Kernel and LangChain

Our framework supports:

• Multi-agent collaboration
• Context-aware dialogue
• Autonomous task execution
• Scalable, secure architecture

It’s built to handle the analytics workloads that modern enterprises demand.

The convergence of conversational AI, agentic AI, and modern analytics platforms is redefining how businesses think, act, and compete.

By embedding intelligence into every layer—from insight to action—organizations can make faster, smarter decisions, reduce dependence on IT, and unlock new levels of agility.

But success requires more than great tools. It takes strategic vision, technical know-how, and real-world experience—something we’ve honed across hundreds of enterprise engagements.

Download our expert guide: “Reimagining Decision Intelligence with Conversational & Agentic AI”. Inside, you’ll discover:

• A breakdown of conversational and agentic AI
• Microsoft’s platform offerings and how to evaluate them
• A comparison of co-pilots vs custom agents
• Infocepts’ architecture and real-world case studies

Download the Guide Now and learn how to move from insights to intelligent action—with AI that truly works for your business.