Automation Anywhere is set to release an advanced AI model later this year, aimed at enabling over 50% of enterprise operations to function autonomously, surpassing the current 40% threshold. Indian enterprises, including Tata Sky, Indian Oil, and Adani Group, are already leveraging AI to optimize operations.
Automation Anywhere is pioneering AI-driven automation, with plans to release the next version of its AI model later this year, enabling over 50% of enterprise operations to function autonomously. CEO Mihir Shukla explained, “Let’s say today with the current model you can do autonomous customer service up to 40%. The next version of this model will take it over 50%.” This marks a major leap in AI-driven automation, especially as businesses continue to incorporate these technologies to optimize their operations.
The company’s open ecosystem approach, offering multiple large language model (LLM) options, is a major differentiator. With metadata covering about 300 million work processes, Automation Anywhere can refine and retrain foundation models to align closely with real-world business needs.
Indian businesses, particularly those with global ambitions, are at the forefront of this AI revolution. Shukla emphasized, “For them to be competitive globally they have to use AI agents in their operation. Because, you know, sometimes AI agents can do what will take a million people to do.” AI agents are transforming operations by handling complex tasks with unparalleled efficiency, far beyond the capacity of human labor. This shift has placed India in a prime position in the AI landscape, driven largely by its robust IT services sector.
According to the Automation Now & Next report, 63% of Indian enterprises plan to invest in AI and machine learning (ML) to automate business processes in the next 12 months, marking an 85% increase in AI investments from the previous year. Furthermore, 33% of enterprises intend to integrate Generative AI to fuel growth and innovation. These findings highlight a shift towards embracing advanced AI technologies as essential for business optimization.
Shukla highlighted that AI adoption in Indian enterprises is not merely about automation, but about transforming operations to handle tasks that were previously unimaginable. He noted that while Global In-house Centres (GICs) are still in early stages of AI adoption, the rapid growth of AI agents capable of performing complex tasks will significantly impact businesses. “GICs are maybe less than about 15% of the market in terms of the possibility of what all can work and be done. So with a fast adoption of AI agents, and especially when I say AI agents, I’m referring to enterprise AI agents that can do complex things, not simple things,” he said.
Indian companies like Tata Sky, Indian Oil, and the Adani Group are already leveraging AI to streamline their operations. Tata Sky has automated its finance, supply chain, and treasury departments, allowing it to close books in less than 24 hours using AI agents. Indian Oil has integrated AI into finance, HR, and inventory management, while the Adani Group has deployed 220 AI-driven solutions across sectors like airports and cement. Bharti Airtel has adopted AI-driven zero-touch automation, reducing errors and enhancing customer service.
The growing affordability of large language models (LLMs) is accelerating AI adoption across various industries. The Automation Now & Next report revealed that 72% of global respondents are planning to invest in AI/ML over the next 12 months, with 78% of enterprises focusing on boosting productivity through automation.
Challenges in Enterprise Automation
1.) Automation Siloes: Automation efforts often remain isolated within individual teams, limiting broader organizational impact.
2.) Identifying Bottlenecks: Pinpointing areas for automation and aligning strategies with business goals can be difficult, compounded by resistance to change.
3.) Data Accuracy: Inconsistent or inaccurate data can hinder automated workflows, requiring strong data integrity and exception protocols.
4.) Automating Non-Standard Tasks: Complex tasks requiring human judgment are challenging to replicate with automation without losing decision-making accuracy.
5.) Scalability: Expanding automation across departments poses scalability issues, requiring systems that can handle increased data and processes without compromising performance.
Automation Anywhere is also engaging with startups and small and medium businesses (SMBs) through its agentic process automation platform, offering an inclusive ecosystem for developers and entrepreneurs. “The fourth is the developers and SMB businesses and startups where they can join our programme, an ecosystem programme where millions of developers and startup ecosystem is part of it,” said Shukla.
By addressing these challenges and leveraging its open ecosystem and vast metadata, Automation Anywhere is positioning itself as a driving force behind the AI-driven transformation of enterprises worldwide. With Indian businesses leading the charge, the future of automation looks set to revolutionize industries and drive innovation, growth, and productivity.
