- Enterprise budgets for generative AI projects are expected to nearly triple over the next two years as companies anticipate transformative potential.
- Rapid implementation timelines are testing risk tolerance, with 34% willing to deploy systems even if negative consequences could occur.
- Over 70% see shadow IT usage of unauthorized generative AI tools as a significant threat, even as 57% admit it already occurs.
- Quantifying returns remains a challenge, though early pilots yield promising productivity gains. Better evaluation practices are needed as investment ramps up.
- Finding the right balance between enabling innovation and managing risks poses an unprecedented challenge for typically cautious IT leaders.
Enterprises are moving with breakneck speed to implement generative artificial intelligence systems like ChatGPT, seeing transformative potential in the nascent technology. However, the rapid pace of deployment is testing the risk tolerance of IT departments more accustomed to cautious adoption curves.
According to a new study from Glean and ISG surveying 224 IT executives, budgets for generative AI initiatives are expected to nearly triple over the next two years. By 2025, companies plan to allocate 4.3% of total IT spending to these projects on average, up from just 1.5% today. Firms earning over $5 billion in revenue are even more bullish, with over a quarter budgeting more than 10% on generative AI by 2025.
Full Steam Ahead for Generative AI: Companies Rapidly Deploy Systems While Grappling with Risks
The findings suggest enterprises anticipate substantial rewards from these AI systems. Respondents predict a staggering 7% boost to global GDP over the next decade thanks to generative technology, alongside a 40% increase in individual worker productivity.
However, the breakneck implementation timelines leave open questions around safeguards and governance. Over 70% of those surveyed see unauthorized, shadow deployments of generative AI as a significant business threat. Yet despite this risk, 57% admit such shadow IT systems are already permeating their organizations.
Perhaps most surprisingly, 34% of respondents indicated a willingness to charge ahead with deployments even if negative consequences could occur. Only 8% saw the rapid evolution of generative AI itself as their top concern. This demonstrates an appetite for risk taking that diverges from the typically cautious mindset of enterprise IT managers.
While early pilots have shown promising results, with 46% of respondents citing better-than-expected outcomes, uncertainty still surrounds return on investment. Just 28% could definitively confirm their initiatives had achieved positive ROI so far. Another 31% said they expected positive returns but lacked hard supporting data.
With investment set to surge, developing better evaluation frameworks to quantify benefits may be critical. Most point to higher productivity as the key metric for measuring success, yet few have systematic methods to capture productivity gains.
On balance, enterprises seem ready to embrace generative AI’s disruptive potential, despite lingering questions around security, governance and ROI validation. For IT leaders accustomed to slow technology adoption curves, finding the right equilibrium between enabling innovation and managing risks poses an unprecedented challenge. Yet the vast majority seem willing to rise to the occasion, betting that the rewards will justify the risks.
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