Technology companies are investing megabucks on generating AI pilots to build competitive moats and futureproof revenue streams, but all of these capital outlays may not necessarily translate into scalable businesses, multiple industry experts and founders told ET.
Globally, a large number of organisations are pursuing 20 or fewer GenAI experiments, and of this 10-30% are expected to scale into production, Deloitte said in a recent report. The pace of transformation at most companies is in line with the pace of organizational change, but it often trails the rate at which technology is changing, said the report.
Somshubhro Pal Choudhury, partner, Bharat Innovation Fund, told ET that while GenAI startups are seeing successful pilots, transition to full deployment is a much slower process.
“Enterprises adopt new technologies cautiously as they prioritise solutions that have clear and predictable outcomes,” Pal Choudhry said.
Customer caution about potential pitfalls of GenAI in the industry wide ecosystem and lack of clarity around where they need to be deployed are reasons for the circumspect adoption. With the macroeconomic uncertainty, companies are also evaluating their discretionary spends, which includes AI pilots.
'Not material'
Shobhit Jain, managing director and head, enterprise technology and services, Avendus Capital, said that for large cap companies, the work on GenAI does not go beyond 3-4%.
“What we are hearing from our clients is that while there is work happening, materially they are not even crossing 5-10% of the revenue,” Jain said.
Companies are spending in areas such as GenAI-powered data and analytics, cloud and testing and quality assurance, Jain said.
However, while there is a lot of experimentation going on, a fraction of these pilots would get into production.
Venk Krishnan, founder, NuWare, an enterprise software company, said that as of now, there is more experimentation than actual value generation.
“We are doing a lot of PoCs with the clients across retail, BFSI and healthcare space. What we are seeing from our portfolio companies is that hardly 5-10% of the PoCs are translating into actual business,” Krishnan said. “The biggest problem is that there is not much clarity on where to use AI in the enterprise pipeline.”
Priority is another hurdle for AI adoption. For large enterprises, their existing business remains key and more often than not, they are not willing to pull out key resources to focus on the GenAI use cases, particularly when the return on investment is unclear.
Avendus Capital’s Jain said that while many are talking about GenAI projects, these are also coming as commentary to queries by research analysts. “But none of the IT companies are correlating their demand and growth narratives to GenAI work,” he pointed out.
“Because of recession and other external factors, there is fear that PoCs and investments (in GenAI) may not happen,” Jain said. However, he added that so far, they have not seen their large or mid-cap companies highlight any change and continue to invest in merger and acquisitions. “We have yet to hear anything different,” he said.
#Operation Sindoor
Live Updates| From Sindoor to showdown? Track Indo-Pak conflict as it unfolds
India hits Lahore's Air Defence Radars in proportionate response
Pakistan tried to hit military targets in these 15 Indian cities, New Delhi thwarts strikes
Somshubhro Pal Choudhury, partner, Bharat Innovation Fund, told ET that while GenAI startups are seeing successful pilots, transition to full deployment is a much slower process.
“Enterprises adopt new technologies cautiously as they prioritise solutions that have clear and predictable outcomes,” Pal Choudhry said.
Customer caution about potential pitfalls of GenAI in the industry wide ecosystem and lack of clarity around where they need to be deployed are reasons for the circumspect adoption. With the macroeconomic uncertainty, companies are also evaluating their discretionary spends, which includes AI pilots.
'Not material'
Shobhit Jain, managing director and head, enterprise technology and services, Avendus Capital, said that for large cap companies, the work on GenAI does not go beyond 3-4%.
“What we are hearing from our clients is that while there is work happening, materially they are not even crossing 5-10% of the revenue,” Jain said.
Companies are spending in areas such as GenAI-powered data and analytics, cloud and testing and quality assurance, Jain said.
However, while there is a lot of experimentation going on, a fraction of these pilots would get into production.
Venk Krishnan, founder, NuWare, an enterprise software company, said that as of now, there is more experimentation than actual value generation.
“We are doing a lot of PoCs with the clients across retail, BFSI and healthcare space. What we are seeing from our portfolio companies is that hardly 5-10% of the PoCs are translating into actual business,” Krishnan said. “The biggest problem is that there is not much clarity on where to use AI in the enterprise pipeline.”
Priority is another hurdle for AI adoption. For large enterprises, their existing business remains key and more often than not, they are not willing to pull out key resources to focus on the GenAI use cases, particularly when the return on investment is unclear.
Avendus Capital’s Jain said that while many are talking about GenAI projects, these are also coming as commentary to queries by research analysts. “But none of the IT companies are correlating their demand and growth narratives to GenAI work,” he pointed out.
“Because of recession and other external factors, there is fear that PoCs and investments (in GenAI) may not happen,” Jain said. However, he added that so far, they have not seen their large or mid-cap companies highlight any change and continue to invest in merger and acquisitions. “We have yet to hear anything different,” he said.
