Techno Blogging
Enterprise AI is beginning to reshape how organisations buy and build software, with 82% of senior executives expecting the traditional per-seat Software-as-a-Service (SaaS) pricing model to become less relevant over the next five years, according to a new EY survey.
The study, which polled more than 500 U.S. senior executives, found that enterprises are increasingly turning to AI to develop custom applications in-house, reducing their dependence on off-the-shelf software and prompting a reassessment of long-established enterprise software models.
According to the survey, 76% of executives said commercial software packages no longer fully meet their organisations' requirements, while 91% described internally developed AI-built software as critical to their business. Nearly nine in 10 organisations have already deployed or are piloting AI-assisted software development initiatives for internal use.
The shift is being driven by the ability of AI to accelerate application development. Among organisations investing in AI, 94% said AI enables them to build software faster than traditional development methods.
The findings add to growing evidence that generative AI is beginning to alter enterprise software spending patterns, with organisations increasingly favouring customised AI-powered applications over standardised software products.
At the same time, enterprises are becoming more disciplined about AI spending as operational costs rise. The survey found that 82% of organisations investing in AI are concerned about AI token consumption and the associated costs of running large language models. Almost all respondents (98%) said those costs have prompted them to reassess their AI strategies, although only 64% currently monitor AI token usage with defined budget controls.
"'AI saves time' is no longer a sufficient business case when the costs are mounting and difficult to ascertain over the long run," said Dan Diasio, EY Global AI Consulting Leader. "Companies are showing signs of reckoning with setting priorities rather than merely driving adoption."
Despite the growing focus on costs, enterprises are not pulling back from AI. More organisations reported expanding or accelerating AI deployments than reducing them. Thirty-seven percent said rising AI costs had led them to broaden the scope of AI rollouts, compared with 15% that were scaling them back, while 29% said they were speeding up implementation.
The survey also suggests enterprises are becoming more realistic about AI investment levels. While 35% of executives last year expected their organisations to spend $10 million or more on AI by now, only 23% reported reaching that level. Similarly, just 3% said AI accounts for at least half of their organisation's total budget, compared with 18% that had projected doing so a year earlier.
Even so, confidence in AI's business value remains high. Nearly 98% of executives reported positive returns on AI investments, with organisations allocating at least a quarter of their budgets to AI more likely to report significant gains in areas such as cybersecurity and customer satisfaction.
As enterprises build more software internally using AI, governance is emerging as a new priority. Nearly three-quarters of respondents said they face challenges related to cost, talent and trust in AI-generated software, while shadow IT, regulatory compliance and cybersecurity risks were identified as key obstacles. More than 93% agreed that robust governance frameworks will be essential to safely scale AI-driven software development across the enterprise.
The findings indicate that AI is influencing enterprise software strategies in two ways: organisations are becoming more selective about where they spend on AI, while increasingly using the technology to develop applications internally—a trend that could reshape how enterprise software vendors package, price and deliver their products in the years ahead.
The study, which polled more than 500 U.S. senior executives, found that enterprises are increasingly turning to AI to develop custom applications in-house, reducing their dependence on off-the-shelf software and prompting a reassessment of long-established enterprise software models.
According to the survey, 76% of executives said commercial software packages no longer fully meet their organisations' requirements, while 91% described internally developed AI-built software as critical to their business. Nearly nine in 10 organisations have already deployed or are piloting AI-assisted software development initiatives for internal use.
The shift is being driven by the ability of AI to accelerate application development. Among organisations investing in AI, 94% said AI enables them to build software faster than traditional development methods.
The findings add to growing evidence that generative AI is beginning to alter enterprise software spending patterns, with organisations increasingly favouring customised AI-powered applications over standardised software products.
At the same time, enterprises are becoming more disciplined about AI spending as operational costs rise. The survey found that 82% of organisations investing in AI are concerned about AI token consumption and the associated costs of running large language models. Almost all respondents (98%) said those costs have prompted them to reassess their AI strategies, although only 64% currently monitor AI token usage with defined budget controls.
"'AI saves time' is no longer a sufficient business case when the costs are mounting and difficult to ascertain over the long run," said Dan Diasio, EY Global AI Consulting Leader. "Companies are showing signs of reckoning with setting priorities rather than merely driving adoption."
Despite the growing focus on costs, enterprises are not pulling back from AI. More organisations reported expanding or accelerating AI deployments than reducing them. Thirty-seven percent said rising AI costs had led them to broaden the scope of AI rollouts, compared with 15% that were scaling them back, while 29% said they were speeding up implementation.
The survey also suggests enterprises are becoming more realistic about AI investment levels. While 35% of executives last year expected their organisations to spend $10 million or more on AI by now, only 23% reported reaching that level. Similarly, just 3% said AI accounts for at least half of their organisation's total budget, compared with 18% that had projected doing so a year earlier.
Even so, confidence in AI's business value remains high. Nearly 98% of executives reported positive returns on AI investments, with organisations allocating at least a quarter of their budgets to AI more likely to report significant gains in areas such as cybersecurity and customer satisfaction.
As enterprises build more software internally using AI, governance is emerging as a new priority. Nearly three-quarters of respondents said they face challenges related to cost, talent and trust in AI-generated software, while shadow IT, regulatory compliance and cybersecurity risks were identified as key obstacles. More than 93% agreed that robust governance frameworks will be essential to safely scale AI-driven software development across the enterprise.
The findings indicate that AI is influencing enterprise software strategies in two ways: organisations are becoming more selective about where they spend on AI, while increasingly using the technology to develop applications internally—a trend that could reshape how enterprise software vendors package, price and deliver their products in the years ahead.
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