H1B, Indian Talent & AI Revolution: Superteams.ai's Soum Paul on Next Wave of Workflows

(Full interview on Industry Wired).

TL;DR: Soum Paul, Founder & CTO of Superteams.ai, shares how AI-augmented teams are transforming enterprises, which industries are adopting AI fastest, the impact of H1B regulations on India's tech talent, and balancing efficiency with ethical AI adoption. Read the original interview here.

Superteams.ai focuses on training early-career talent and creating AI-augmented teams. How does your bespoke training approach prepare candidates for real-world enterprise challenges from day one? How do you ensure that these AI-augmented workflows drive both productivity and innovation for clients across industries?

Over the last three years, we've realized that AI talent falls into two broad camps: those who focus on training models, and those who can build systems using pre-trained models. The reality is that over 99% of enterprise use-cases don't require model training. What companies really need are engineers who can design and deploy AI workflows, agents, and assistants using pre-trained models, smart search engines, and advanced agentic workflows.

Our approach is simple: we collaborate with enterprises to identify their core challenges and assemble AI teams that solve these problems hands-on. After an incubation period that lasts a few months, companies can choose to absorb these engineers into their organization or continue working with us as a flexible AI team provider.

This hands-on, problem-driven training prepares engineers for the real-world AI challenges enterprises face, while enabling companies to explore AI ROI without the upfront cost of building and training an in-house team.

Which industries are adopting AI-augmented teams fastest, and which ones are lagging? What's driving the difference?

The fastest adopters are businesses where AI directly drives growth, revenue, or cost efficiency. This includes companies building AI-native B2C or B2B products, as well as organizations looking to gain a competitive edge by being first to market with an AI solution.

Typically, these are B2C companies focused on enhancing customer experience or B2B firms burdened with manual workflows that AI can streamline. That's why some of the most prominent AI use-cases include customer support, recommendation systems, chatbots and virtual assistants in B2C companies, and agentic workflows in B2B that improve productivity, like speech-to-text, invoice parsing, contract management, report generation, data extraction and so on.

In all the above scenarios, AI directly impacts topline or bottomline, or happens to be central to their product strategy.

With the recent H1B regulation slowing down US visa approvals, how do you see the global AI talent landscape shifting, and what opportunities does this create for Indian tech hubs?

There are two major reasons why the recent $100K H1B price-tag will impact the industry. First, it makes hiring talented engineers from India and relocating them to the US prohibitively expensive. Second, it introduces uncertainty for both businesses and individuals, prompting a strategic rethink in how global talent is hired and engaged.

The reality is that India produces the largest pool of engineering talent in the world. This shift creates a unique opportunity for Indian technologists to build for the world—and for India—without leaving home. As Kunal Bahl recently shared, his H1B rejection led him to create ventures in India and eventually back Indian entrepreneurs through his fund. We will likely see many more stories like this in the coming years.

Most importantly, GCCs, startups, and enterprises now have a rich, readily available talent pool to tap into, which will further accelerate India's technology ecosystem in the long run.

With rapid AI adoption, how do companies balance efficiency gains with ethical considerations and workforce impact?

AI is a ground-breaking technology, and the best way for businesses and leaders to grasp its potential is by adopting an R&D-first mindset. It's important to recognize that AI goes far beyond chatbots or generative image tools. Real enterprise use-cases emerge from OCR and document parsing, ASR and speech-to-text, advanced retrieval-augmented generation systems, vision AI, and more.

From what we've seen so far, AI consistently drives efficiency, enhances user experience, improves safety, helps detect anomalies, and reduces manual effort in repetitive workflows. The resulting efficiency gains and revenue growth alone make a compelling case for adoption.

Beyond that, AI is opening entirely new avenues—through innovative product lines, novel automation approaches, and smarter decision-making—which in turn is creating a strong demand for skilled AI engineers. In this sense, AI is not just a tool for productivity; it is also a job creator and a catalyst for new opportunities.

(Full interview on Industry Wired.)