What Generative AI Actually Enables for Business Leaders

There's been a lot of hype around generative AI. Chances are, you've tried at least one AI tool (ChatGPT), but many enterprise leaders still struggle to see its tangible value.

Here are three practical use cases to spark some ideas:

1. AI as a Smarter OCR

OCR (Optical Character Recognition) has been around for decades, but it's often unreliable—especially with tabular data. Vision-language models change that. By combining AI with code, you can extract tabular data from images and PDFs in seconds.

🔹 Example: In Vietnam, financial reports often include screenshots of balance sheets in PDF form. Instead of spending hours manually transcribing data into Excel, AI can recognize the financial statements and convert them instantly—so analysts can focus on valuation.

2. AI as an Intelligent Information Translator

In supply chains, information constantly moves upstream and downstream. Consider a procurement team placing purchase orders: suppliers must translate those POs into production schedules and logistics.

AI can automate this process using past data—transforming upstream inputs into downstream outputs in the right formats. No more manual copy-pasting from emails to Excel!

3. AI as a Research Analyst

Research is a core part of many industries. Whether you're a marketing agency analyzing prospects or an investment firm studying markets, manual Googling is tedious. AI agents can automate this process, gathering insights efficiently.

While tools like DeepResearch exist, many organizations need custom AI research assistants tailored to proprietary data and workflows. If research is crucial to your business, building your own AI agent might be the solution.

💡 How can AI fit into your business? If you need guidance, feel free to reach out- I’m happy to chat! 😄