Workflow sync crucial to get maximum AI returns: Automation Anywhere

Automation Anywhere says enterprises must move beyond siloed AI deployments and orchestrate workflows across functions to improve returns on investment and business outcomes

Enterprises are moving beyond deploying artificial intelligence (AI) in isolated workflows and are instead focusing on orchestrating work across business functions to generate meaningful returns on their AI investments, according to agentic process automation (APA) firm Automation Anywhere.

 

“Customers have bought AI, in the last one-and-half years, the way they bought SaaS (Software as a Service) in silos from one copilot in this department to one agent there. And they realise that's not how work is happening. It cannot happen in silos,” the company’s cofounder and chief operating officer Ankur Kothari told Business Standard.

 

Most customers, in a rush to demonstrate being AI-native, deployed agents in some workflows, while using copilot in another, only to realise that it is not giving them the desired results apart from incurring costs and minimum returns on investment.

 

“So, understanding the value of orchestration, that work happens across systems is critical. It's not about showing something cool; some chat bots here and there and showing it to people. You have to truly change your business model and it is about orchestrating work,” he added.

 

The company, backed by Goldman Sachs and SoftBank Vision Fund, said the focus is more on end to end automation instead of automating certain mission critical processes as enterprises seek more return on investment from their AI endeavour.

 

Enterprise adoption of AI has lagged compared to general usage globally due to a host of reasons, which include scattered data, orchestration problems, change management issues, reskilling and even token-maxxing, which has led to overblown AI budgets in a short span of time with minimum returns.

 

Meta CEO Mark Zuckerberg recently admitted AI agents had not progressed as quickly as he expected, even as the company laid off thousands of people in its push to improve efficiency, productivity and reduce cost. Meta is projected to spend as much as $145 billion on AI infrastructure this year, a significant portion of Big Tech's more than $700 billion outlay on the technology.

 

Automation Anywhere’s platform, Kothari said, can auto resolve 80 per cent of the IT service management tickets, which can bring down cost by 50 per cent. That is why the conversation has veered towards tangible outcomes from a board perspective. And for that contextual data, or enterprise specific data becomes critical rather than general data.

 

“A year ago, there were a lot of discussions about chat bots and small use cases here and there. If you spend one entire year using AI and you have 10 good use cases to show and yet it did not impact your P&L, it is a long time where there are companies who have moved faster,” he added.

 

Automation Anywhere, whose customers include KPMG, Cargil and Petrobras, also said usage of its agentic platform has been doubling sequentially and many enterprises are now looking to create an autonomous enterprise, especially in areas such as finops, networkops, security, finance, HR and customer support.

 

“The thought process is how do I make few departments autonomous where 40-60 per cent processes are automated. That is a big mindset shift. For the first time, so many customers are looking to change the way businesses operate. So, suddenly from an IT conversation this is now a boardroom conversation, which changes the dynamics of our business,” said Kothari. 

Tech Talk

 

• Automation Anywhere is backed by Goldman Sachs and SoftBank Vision Fund
• Its platform can auto resolve 80% of the IT service management tickets, which can bring down cost by 50%
• Its customers include KPMG, Cargil and Petrobras
• The company said usage of its agentic platform has been doubling sequentially
• The focus is more on end-toend automation instead of automating certain mission critical processes as enterprises seek more return on investment from their AI endeavour