Indian companies lag in AI adoption: Salesforce’s Arundhati Bhattacharya
The President and CEO of Salesforce South Asia says Indian firms should take the leap of faith from proofs of concept to production
Last Updated: Nov 26, 2025, 16:27 IST4 min
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US-headquartered CRM company Salesforce’s bet on AI-first platform development has been a key strategy shift in the past few years. The company, which has a significant presence in India with over 13,500 employees across multiple cities, has seen the implementation of AI agents grow internally, apart from developing solutions for key sectors in India.
India is Salesforce’s second largest market, and the Salesforce India entity reported revenue of Rs 13,385 crore for the financial year ending March 2025, a 47 percent increase year-on-year. Some of Salesforce’s major customers in India include Tata Motors, Tata Power, Dr Reddy’s, Razorpay, among others. On the global level, Salesforce has a guidance of $41.3 billion on the lower end of revenue for the financial year 2026.
With focus on growing its customer base in the Agentic AI space with its suite of Agentforce 360, Salesforce is running multiple Proofs of Concept (PoC) with Indian enterprises and companies, though uptake for production has been slow.
“We might be late to the market, but we will not let a product to be released into the market unless and until it addresses the question of trust and the data remains with whosoever it belongs to,” said Arundhati Bhattacharya, president and CEO at Salesforce South Asia, at an event in Delhi recently.
In an interview with Forbes India, Bhattacharya said Indian enterprises have been cautious in largescale adoption of AI compared to the US and others. She added that, as the quality of data to train the Agentic AI PoCs improves, so will customer satisfaction and speed to get to production and rollout.
Excerpts from the interview:
Q. Salesforce is perceived to be slow in capitalising on the recent AI surge. Can you tell us how Agentforce launched in 2024 has been implemented by your customers?
I think what we do really well is to implement Agentforce in the workflow. For instance, if you automate the workflow, the routine tasks can be automatically triggered by the digital agents, which is where we excel. We have the CRM data in multiple organisations and it empowers how you deal with the particular customer and use AI agents intelligently to improve the interactions over time. This is where we add value, because we have always been creating experiences. We are in the engagement layer rather than the transaction layer. And the engagement layer is where you see how people are reacting to the technology.
Q. How does the rate of AI adoption among Indian enterprises compare to their US or Western counterparts? What explains the trend?
There is better acceptance of AI in the West. We (in India) are generally hesitant to take large steps and would like to start with smaller deployment. Also, we try to see how we can optimise costs all the way, and, so, you find people who are trying to do it by themselves. The problem today is that technology is evolving at a pace at which trying to keep track of the updates is actually tough.
So while, initially, you can make something but to keep improving is not so easy. To that extent, I feel the Indian industries are willing to experiment and build some of the solutions themselves. On whether we are on par with Western nation companies to quickly adopt this, I would say we are still following the average routine of being a little behind the others. However, people at large have taken to AI on an individual basis, and the digitally enabled population is using AI in every way possible. With enterprises, we still see some hesitancy.
Also Read: Inside Arundhati Bhattacharya's Playbook for Salesforce India
Q. Can you tell us more about the nature of companies in India whom you are piloting with?
Most of our customers in India are Indian conglomerates and not MNCs. The MNCs are trying out agentic AI at their headquarters rather than India. While most of them are at PoC stage, we would like to see more of them going into production stage.
Some of the common sectors where we can offer agentic AI are BFSI, support centres, autos, contact centres, and improve the customer satisfaction.
Q. What are the key challenges faced by Indian enterprises at large to move from PoC to production stage when it comes to AI deployment?
There are two kinds of challenges we hear about. One is regarding the data itself—how well organised is the data and how quickly they have managed to do so. Second is the automation of workflows. There are process changes which have to be made for adoption. Of the main challenges these are the two important ones.
Another area where we see people need to take a leap of faith is when you run a PoC or pilot, they are working on very restricted data. The restricted data does not obviously return the level of responses that you would like to have or use. That is where we need to encourage our customers to try to use better data for satisfactory results.
Q. How has Salesforce internally implemented AI across its functions?
We want to be customer zero on our own software and want to show that being an agentic enterprise enables us to spend more time with customers and diverting talent from sitting at a console to creating real relationships with customers.
We are using AI in many areas—for training, answering our questions, summarising emails and drafting responses, creating sales plans, IT support and to write basic code. We are using AI to look at sawdust—little opportunities that fall off because we do not have the opportunity to follow up.
Our support helpline help.salesforce.com, which was earlier manned entirely by engineers, is now manned by agents. At this point of time, around two percent of the cases still get referred to manual agents. We have around 77 percent first call resolution at the support helpline. So we are implementing AI in a big way.
First Published: Nov 26, 2025, 16:45
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