For the last three months, I've been building Business Hero, an AI lead automation agent on WhatsApp. A few days back, we launched a demo video on social media platforms and, as expected, received numerous enquiries. Among them, one question from a well-meaning friend caught my attention. He asked: "In India, where labor is cheap, why would somebody opt for AI? Wouldn't it be more expensive than hiring humans to do the same work?"
This is an interesting question. However, it represents a simplistic view of the employer-employee relationship. Let me explain why.
The challenges of human-driven sales
Let me explain this from the context of Business Hero as the insights are fresh in the memory. In our product, we're automating incoming lead enquiries from various social media and marketplace channels. With mass internet adoption, it's become easier for potential customers to fill forms, send messages, or express interest with a single button. This creates a large volume of enquiries at the top of the funnel. Determining which leads to focus on—those likely to convert into sales—requires significant intelligence.
Typically, businesses face several challenges when using people for this task:
Repetitive Communication: Regardless of conversion potential, you must invest the same effort across all channels, explaining your products and services in detail without getting tired. It's essentially repeating the same information continuously.
Timing Mismatches: Enquiries often peak at specific times—nighttime for some businesses, weekends for others, or during festivals. If your support or sales team isn't available at these crucial moments, leads go cold. Failing to respond within a few hours of expressed interest means potentially missing opportunities.
Workforce Limitations: Since this is primarily a filtering mechanism to move leads from the top to the bottom of the funnel, businesses are reluctant to hire highly qualified people at significant expense. Consequently, those who take these jobs often view them as temporary positions, leading to high attrition rates and increased training costs.
Beyond simple cost comparison
Equating AI's cost solely to people's salaries is overly simplistic. When pitching AI to businesses, we should emphasize efficiency improvements and greater control over processes. Until now, only tech companies had the ability to implement robust project management, track tasks, and maintain organized workflows through tools like Jira. AI extends these capabilities to non-tech industries with minimal manual intervention.
AI's value in different contexts
In many cases, AI can be particularly valuable in tier 2 and tier 3 cities where skilled professionals may be scarce. Specialists like doctors, computer engineers, or teachers often migrate to larger cities for better opportunities, leaving smaller towns with unmet needs. AI can help bridge this gap.
I've also seen examples in India where businesses employ AI to monitor existing salespeople rather than replace them. Automated phone calls or WhatsApp messages can check why CRM entries haven't been completed or leads haven't been followed up. This creates a form of AI middle management that optimizes efficiency.
Changing labor dynamics in India
A recent episode of a Tamil show 'Neeya Naana' debated why Tamil Nadu MSMEs are hiring workers from northern India for labor jobs. One interesting point was that Tamil society has improved educationally because basic survival needs are partially covered by the government or previous generations. The younger generation is encouraged to study, with the Tamil Nadu government allocating substantial budgets for education.
This has produced a generation unwilling to do blue-collar work, preferring white-collar jobs instead. While many "paper engineers" may need reskilling, they won't return to the menial jobs their parents did. It's not just about the type of work but also about dignity and respect. Some modern jobs, like delivery work for Swiggy, Zomato, or Zepto, have achieved a level of dignity that traditional blue-collar jobs like carpentry or construction work lack.

This creates a mismatch: factories struggle to find workers while white-collar positions see intense competition despite fewer openings.

The need for automation in India
The same person who enquired about my product mentioned about a lady working for 8,000 rupees monthly for ten years trained on a software without a yearly raise, I pointed out that finding her replacement will be difficult once she retires. Moreover, her children will likely never accept the same job at that pay rate.
This is precisely why automation in India will become necessary—not because we lack people, but because we need to improve efficiency across the board. We see this disparity when comparing B2B enquiry responses from Indian platforms like IndiaMart to those from China, with the former being significantly slower.
For Indian business owners competing globally, especially against countries like China, automation offers a way to increase efficiency and excel in their work. To conclude Indian businesses will not deploy AI to reduce cost but to improve efficiency. While this may be a controversial perspective, I believe it's an important conversation to have.
Cost is still a concerne even for AI adoption.
The want to limit the cost to one time factor or minimize the billing of software products.
Increasingly the new age gen businesss people use the same AI tools to suggest freelancers to build small softwares and then they continue to just pay API bills.
Great insights! With conversational voice AI, there also comes the language-dialect factor. Many a times human agents can't understand users dialects even when users can understand their urban hindi-hinglish. Voice AI agents can code-switch across all dialects.