Artificial Intelligence – Article Series- Article 1
For nearly five decades of my professional career, I have watched technology evolve from mainframe computers to personal computers, enterprise software, the Internet, mobile computing, cloud computing, and digital transformation.
Businesses have leveraged each successive wave of technology to improve productivity, reduce costs, and gain a competitive advantage. Global IT services companies—including one of my former employers, Tata Consultancy Services—helped organizations implement these technologies at scale and, in doing so, created one of the world’s largest technology services industries.
Artificial Intelligence represents the next stage of that evolution. Yet it differs from previous waves in one important respect: for the first time, sophisticated digital capability is available directly to the end user. Large language models (LLMs) have shifted part of the innovation balance from technology providers to individuals, professionals, businesses, universities, and governments.
Today, users can interact directly with models such as ChatGPT, Gemini, Claude, DeepSeek, and others using plain everyday language. These systems are rapidly becoming research assistants, writing partners, analytical collaborators, planning tools, coding assistants, and decision-support companions.
This change has disrupted both users and technology providers. IT services companies are redesigning their business models, while governments, educational institutions, and businesses are trying to understand how to integrate AI into everyday work.
Senior decision-makers are consequently confronted with a new set of questions:
- Which AI model is appropriate for our needs?
• Is ChatGPT simply another software application?
• How can AI help us solve better problems?
• How can it improve the quality of our thinking?
• How can it support better institutional decision-making?
• How can it improve the quality, speed, and scale of knowledge work?
These are not primarily technology questions. They are questions about leadership, management, and institutional transformation.
They require policymakers, administrators, researchers, educators, entrepreneurs, managers, and professionals to rethink how knowledge is created, analyzed, communicated, and applied.
Over the coming months, I will explore these themes through a series of articles examining AI from the perspectives of governance, public administration, knowledge work, entrepreneurship, education, business, and institutional transformation.
My objective is not to discuss AI as technology. It explores how AI can help governments, businesses, universities, and individuals think more effectively, work more productively, make better decisions, and ultimately create greater value for society.