Building systems that keep humans in the loop
Sravan Vadigepalli is an IEEE senior member and a technology executive at Lowe’s Companies, Inc., where he leads enterprise AI strategy, AI products, and partnerships.
For the first 10 years of my career, I worked in product management and data analytics by myself. I wrote database queries that pulled numbers out of corporate systems, built statistical models to predict what customers would buy, and shipped data pipelines that moved information between business systems.
I built and scaled analytics teams at Best Buy and Target, studying how customers shop and what stores should stock. Today I lead enterprise AI transformation at Lowe’s, the Fortune 100 home improvement retailer.
The goal is not to sell artificial intelligence; it is to use it to deliver useful expertise at the moment a customer needs it. In retail and other customer-facing industries, virtual assistants can help people address everyday questions—such as how to repair a leaky faucet—while guiding them toward relevant products, services, or next steps. As these capabilities become more common, technology roles are changing. The work is no longer limited to building AI systems; it also includes defining how they operate: which decisions they can make autonomously, when they must escalate to a person, and which actions must remain off-limits.
That shift—from building AI systems to governing them—is coming for anyone who is accountable for what such systems produce. Not the casual user typing into a chatbot but the engineers, product managers, analysts, and business operators who sign off on work a machine drafted.
It is the subject of the book I recently coauthored, The Enterprise Brain. I call the change the “governor shift,” from executing tasks yourself to setting the intent, principles, and boundaries within systems that execute them for you.
Business operators might not write code; they will decide which pricing exceptions an agent may approve and which it must escalate.
That is governing.
A 2025 report from MIT Media Lab’s Project NANDA found that, despite an estimated US $30 billion to $40 billion in enterprise generative-AI investment, the vast majority of organizations in its dataset had not yet demonstrated measurable profit-and-loss impact. The report estimated that only about 5 percent of integrated pilots were generating substantial value, underscoring how difficult it remains to move from experimentation to scaled business outcomes.
Researchers named the pattern the GenAI Divide, the term I adopted for the book.
The companies rarely lack technology; they use the same models as the 5 percent that are winners. But they lack people who can direct the systems and stand behind the results.
Here are six guidelines.
When I talk with people about the shift, their resistance is rarely about technical issues. More often it is about identity: If the AI does the doing, what do I do?
I have watched capable people freeze on that question. I’ve also asked myself the question.
Doing was never really the job, though. Judgment was. Doing was just how we expressed it.
AI has not made judgment less valuable. It has made it the scarcest resource in the organization because, for the first time, one person’s judgment, written down well, can guide thousands of decisions each day.
Judgment has a twin we talk less about: taste. Judgment tells you whether an answer is sound. Taste tells you whether the question was worth asking and which of a hundred defensible options to offer the customer. A machine will happily generate all 100 options, but it cannot tell you which is best.
The AI transition rewards instincts many IEEE members already have: systems thinking, precision about requirements, and honesty about failure modes. The tools have changed, but the discipline has not.
Governing is where taste and judgment stop being soft words and become the work itself.
The people who treat it that way, rather than as a step away from engineering, will define the profession in the age of AI.
Sravan Vadigepalli is an IEEE senior member and a technology executive at Lowe’s Cos., where he leads enterprise AI strategy, AI products, and partnerships. He is a coauthor of The Enterprise Brain: Rewiring Your Business for the AI-Native Era.
Source: IEEE Spectrum
