Data is often heralded as “the new oil” because of its ability to be a competitive advantage. But how can organizations grapple with the deluge of data being generated at breakneck speeds, much less turn it all into a competitive advantage? One solution lies in enabling conversational interactions with structured data. Imagine leveraging AI tools, similar to those that query vast web data stores like ChatGPT, but applying them to your own proprietary databases. 

Consider an insurance firm querying not just generic definitions like “What is a loss ratio?” but diving into specifics with questions like, “How is ‘loss ratio’ defined within our company?” or “What is the loss ratio for policies held for under a year?” This shift from generic to contextually rich, organization-specific data queries is what you need to make possible. 

The Dilemma: Abundant Data, Scarce Insights

Today’s enterprises are drowning in data yet starving for insights. Traditional data management tools often fail to unlock the meaningful stories that data tells.

The promise of AI has been vast, yet until recently, its application has felt more like a superficial exploration than a deep dive. The crux of the issue lies in context. Without it, AI lacks the precision businesses need, operating more on guesswork than informed analysis.

What to Look for in a Structured Data AI Tool 

Whether you’re building it or buying it, look for an AI solution that facilitates secure, conversational exchanges with your organization’s data. It’s akin to having an in-house expert available at any moment, ready to offer deep, actionable insights. Look for solutions that can:

• Conduct AI-powered conversations: Pose natural language questions about your data and receive accurate, understandable answers.
• Provide explainability: You don’t just want answers, you want explanations for them, tracing the logic back to the data source.
• Readily integrate: Ideally your AI tools can integrate with your existing systems, so that you uplevel AI capabilities without disrupting your existing workflows.
• Scale: Whether you’re a small team or a multinational corporation, you want your AI platforms to scale with your team size and organizational needs. 

Why Conversing with Structured Data Is Crucial

The ability to chat with structured data isn’t just an enhancement; it’s a strategic imperative. Generative AI is now reaching the point where it can interpret your specific data, and several organizations in the data sector are advancing the cause of chatting with your structured data. Not only does it enable faster data retrieval, but also brings timeliness to your decision-making. There’s your competitive advantage. 

Moreover, chatting with structured data will democratize data access within your company. That equips everyone, not just the data specialists, with the ability to leverage data insights. Your entire organization’s data literacy improves, virtually overnight.

Also, by automating data discovery, your teams can redirect their focus from mundane data management to more strategic initiatives. This shift not only cuts down on operational inefficiencies, but also empowers your teams to focus on their core work. In other words, they get back to business! 

As generative AI continues to evolve, staying ahead of the curve is essential. Finding a way to chat with your structured data ensures your business is not merely keeping pace but setting the pace for leveraging forthcoming AI advancements.