Shyam Uthaman

Shyam Uthaman is a data, analytics and AI leader and the author of The Data-Driven Executive, AI to ROI for Business Leaders, and The Lost Map to Your Career. His experience spans billion-dollar enterprises and global teams across the United States, Europe and Asia. He writes about building capable teams, turning AI into measurable business results, and the judgment required to make technology useful. He has published practical technical and leadership writing since 2011.

AI Operating Model: How Teams and Decision Rights Scale

An AI operating model determines who selects AI opportunities, who owns the business outcome, who builds reusable capabilities, who accepts risk, and who keeps the product working after the pilot ends. Without those decisions, organizations can have an AI strategy, modern platforms and talented teams while still struggling to move useful ideas into production. I

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AI Maturity Assessment: Where to Start at Every Level

An AI maturity assessment should tell leaders what the organization can do reliably today, what is holding it back, and which action deserves funding next. It should not produce a flattering score that places the company in a fashionable category while teams continue running disconnected pilots with unclear business value. I have seen maturity assessments

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Data Governance Best Practices: What Actually Makes Governance Work

Data governance best practices should help a company settle important data decisions, prevent recurring failures and prove that agreed controls are working. If governance mainly produces meetings, glossaries and ownership spreadsheets, it may look mature while the same business problems continue underneath it. I have seen this gap across ERP programs, data warehouses, analytics platforms,

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Data Governance Framework: How to Build Ownership and Decision Rights

DATA GOVERNANCE FRAMEWORK FOR BUSINESS LEADERS A data governance framework earns its place when it helps the organization make a decision. If it produces a large glossary, a committee calendar and hundreds of assigned data elements but cannot resolve which revenue number belongs in an executive meeting, the framework is busy rather than effective. I

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AI Governance Framework: Eight Practical Controls for Business Leaders

AI GOVERNANCE FRAMEWORK FOR BUSINESS LEADERS An AI governance framework becomes real when an output can change a payment, a contract decision, an inventory order or an executive metric. Before that point, governance can look like policy work happening somewhere outside the project. After that point, it becomes part of whether the system is safe

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Databricks Genie Tutorial: Build Your First AI/BI Agent

BEGINNER DATABRICKS TUTORIAL Databricks Genie gives business users a familiar chat interface for asking questions about company data. Instead of starting with SQL, they can ask a question such as “What were gross sales last quarter?” and receive a written answer, result table, chart, and the SQL used to calculate it. If you have used

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Databricks Genie Tutorial: How Business Context Improved Accuracy From 0% to 93%

PRACTICAL AI EXPERIMENT This Databricks Genie tutorial tests a simple question that matters far more than whether an AI tool can write SQL: does the agent understand what the business means? I gave the same Genie Agent the same six tables and fourteen benchmark questions twice. The data stayed fixed. The questions stayed fixed. The

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AI Inventory Management: I Tested ChatGPT on Reorder and Overstock Decisions

PRACTICAL AI EXPERIMENT Inventory reports have a habit of looking simple until you actually have to decide what deserves attention. A product can be below its reorder point and still be fine because stock is already arriving. Another can look healthy today while a long supplier lead time means it will run out before replacement

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