A few months ago, a marketing executive in Mumbai asked ChatGPT to help shortlist agencies for a campaign.
A doctor used an AI assistant to simplify a dense research paper before a patient consultation. A founder in Bengaluru used Claude to draft a board memo. Somewhere else, a college student asked an AI tool whether she should accept a job offer.
These are small moments. Together, they point to something much bigger.
For decades, technology changed what people did. Email changed communication. Smartphones changed access. Social media changed attention. Artificial intelligence is different.
It is changing how people think.
That is why AI Appreciation Day, observed globally on July 16, feels oddly timed. The industry continues to celebrate larger models, bigger investments and faster chips. Yet the more consequential story is unfolding quietly, in offices and homes, where millions of people are beginning to outsource parts of their judgment to machines.
The question is no longer whether AI will replace humans. It is whether humans will become comfortable letting AI shape their decisions.
India is emerging as one of the world's biggest laboratories for this experiment.
The Second Life of Sanskrit #
10 Jul 2026 - Vol 05 | Issue 28
Being classical has become cool
Read Now The Second Life of Sanskrit According to Deloitte's latest State of AI report, Indian enterprises are among the fastest adopters of AI globally, outpacing many developed markets in deploying AI across business functions. Meanwhile, workplace studies suggest Indian employees use AI tools more frequently than workers in most major economies.
That should not be surprising. India has always embraced technologies that improve access and affordability. UPI democratised payments. Cheap mobile data transformed internet adoption. AI, too, is following a familiar pattern: rapid adoption first, deeper questions later.
Those questions are finally beginning to catch up.
"AI Appreciation Day feels like the right moment to be honest about something the industry has been slow to say out loud: the models have delivered. The governance hasn't," says Nilesh Bhojani, Chief Product and Technology Officer at Seclore.
His comment captures the state of enterprise AI in 2026.
Businesses know AI works. What they do not yet know is how to govern it.
Employees are feeding contracts into AI tools. Teams are using copilots to write code. Customer service functions are deploying AI agents. The technology has entered workplaces faster than policies designed to regulate it.
Boards are asking new questions. What data leaves the company? Can an AI recommendation be audited? Who is accountable if an AI system gets it wrong?
These are not technical questions. They are management questions.
And increasingly, they are questions about judgment.
"AI is not replacing human judgment; it is fundamentally changing how that judgment is formed," says Swagat Sarangi, Co-founder of Smytten and PulseAI Research.
It is an important distinction.
For most of modern business history, companies have relied on historical data. They looked backward to move forward. AI promises something more ambitious: the ability to identify patterns before humans can. Consumers are already using AI to compare products, summarize reviews and make purchase decisions. Businesses are using it to identify trends, forecast demand and anticipate changing preferences.
"The companies that win will not simply have more data, but better intelligence," Sarangi says.
There is a temptation to dismiss statements like these as the usual language of the technology industry. But consumer behaviour suggests otherwise.
Search is changing. Younger users are increasingly treating AI assistants as a starting point rather than a destination. Instead of typing "best running shoes under ₹5,000" into a search engine, they ask an AI what to buy and why.
That subtle shift matters.
For nearly two decades, businesses optimized themselves for Google. The next decade may require them to optimize for AI. Healthcare offers another glimpse into this future.
"Healthcare is a domain where speed can never come at the cost of accuracy," says Nilesh Aggarwal, CEO of IJCP and Founder of Medtalks. "The real challenge is ensuring AI is trained on credible, evidence-based sources and that every output is guided by clinical oversight and ethical responsibility."
Healthcare exposes both the promise and the limitations of AI.
A chatbot hallucinating a restaurant recommendation is an inconvenience. A chatbot hallucinating a medical dosage is a crisis.
The closer AI gets to consequential decisions, the more valuable human judgment becomes.
That may explain why the conversation around jobs has evolved. Three years ago, AI debates were dominated by fears of mass unemployment. Today, most organisations speak instead of augmentation.
At Prozo, Founder and CEO Dr Ashvini Jakhar says AI has dramatically compressed timelines across functions.
"The world is rapidly moving towards a clear divide: people and organisations will either be users of AI or creators of AI," he says.
History suggests technological revolutions rarely eliminate work altogether. They redistribute value.
The calculator did not eliminate mathematicians. Excel did not eliminate accountants. The internet did not eliminate journalists.
AI is unlikely to eliminate knowledge workers. It will, however, reward different skills.
The premium of the future may not lie in possessing information. AI has made information abundant. The premium may lie in asking better questions, exercising better judgment and knowing when not to trust the machine.
This is already visible in workplaces.
Employees are spending less time gathering information and more time validating it. Managers are increasingly acting as editors of AI-generated outputs. Software developers are reviewing code written by machines.
Human work is moving up the value chain.
Yet there is another reality that receives far less attention.
Enterprise AI is, at its core, an infrastructure story.
"Its true value depends not just on the intelligence of the models, but on the infrastructure, governance and engineering that support them," says Sumed Marwaha, Managing Director of AHEAD India.
Most companies, it turns out, are not nearly as ready as their AI strategies suggest.
Their data remains fragmented. Their workflows remain inefficient. Their governance frameworks remain incomplete.
"Enterprise AI is only as effective as the operational context behind it," says Kaushik Mitra, Vice President and Head of India GTM at Celonis.
His company's research found that 90% of business leaders believe process improvement depends on accurate, contextual data. It is a reminder that AI's greatest obstacle is often not the technology itself, but the organisation attempting to deploy it.
This may ultimately become the defining business story of the decade.
For years, executives insisted that data was the new oil. AI is forcing a correction. Data, by itself, is not enough. Context matters. Judgment matters. Trust matters. The winners of the AI era will not necessarily be the companies with the biggest models or the largest budgets.
They will be the ones that answer a deceptively simple question: Can we trust the decisions our machines are helping us make?
For centuries, humans built machines to reduce physical effort. AI is the first machine designed to reduce cognitive effort. That is why this moment feels different.
We are no longer outsourcing what we do.
We are beginning to outsource how we think.
And whether that makes us more intelligent—or merely more efficient—may be the question that defines the next decade.