CEOs Double Down on AI While Navigating Enterprise Hurdles

CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study.

The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale.

IBM

Image Source: IBM

According to the findings, 68% of surveyed CEOs identify integrated enterprise-wide data architecture as critical for cross-functional collaboration, and 72% view their organization's proprietary data as key to unlocking the value of generative AI. However, the research indicates organizations may be struggling to cultivate an effective data environment: half (50%) of respondents acknowledge that the pace of recent investments has left their organization with disconnected, piecemeal technology.

In the foreword of the study, IBM Vice Chairman Gary Cohn writes, "As AI adoption accelerates creating greater efficiency, and productivity gains, the ultimate pay-off will only come to CEOs with the courage to embrace risk as opportunity. Meaning, focusing on what you can control, especially when there is so much you can't. When the business environment is uncertain, using AI and your enterprise data to identify where you have leverage is a competitive advantage. At this point, leaders who aren't leveraging AI and their own data to move forward are making a conscious business decision not to compete."

"CEOs are balancing the pressures of short-term ROI and investing in long-term innovation when it comes to adopting AI," said Mohamad Ali, Senior Vice President and Head of IBM Consulting. "But we know that organizations that keep innovating, especially during periods of uncertainty, will emerge stronger and be better positioned to capitalize on new opportunities."

Other key findings include:

CEOs face competing pressures of short-term ROI and long-term innovation

  • Surveyed CEOs report that only 25% of AI initiatives have delivered expected ROI over the last few years, and only 16% have scaled enterprise wide. 
    To accelerate progress, two-thirds (65%) of CEO respondents say their organization is leaning into AI use cases based on ROI, with 68% reporting that their organization has clear metrics to measure innovation ROI effectively.
  • Just over half (52%) of CEO respondents say their organization is realizing value from generative AI investments beyond cost reduction.
  • 64% of CEOs surveyed acknowledge that the risk of falling behind drives investment in some technologies before they have a clear understanding of the value they bring to the organization, but only 37% say it's better to be "fast and wrong" than "right and slow" when it comes to technology adoption.
  • 59% of surveyed CEOs admit their organization struggles to balance funding for existing operations and investment in innovation when unexpected change occurs, as 67% say more budget flexibility is needed to capitalize on digital opportunities that drive long-term growth and innovation.
  • By 2027, 85% of surveyed CEOs expect their investments in scaled AI efficiency and cost savings to have returned a positive ROI, while 77% expect to see a positive return from their investments in scaled AI growth and expansion.

CEOs see strategic leadership and specialized talent as essential to unlocking AI value, amid expertise and skills gaps

  • 69% of CEO respondents say their organization's success is directly tied to maintaining a broad group of leaders with a deep understanding of strategy and the authority to make critical decisions.
  • 67% of CEOs surveyed say that differentiation depends on having the right expertise in the right positions with the right incentives.
  • CEOs cite lack of collaboration across organizational silos, aversion to risk and disruption, and lack of expertise and knowledge as top barriers to innovation in their organization.
  • Surveyed CEOs say roughly one-third (31%) of the workforce will require retraining and/or reskilling over the next three years, while 65% say their organization will use automation to address skill gaps.
  • 54% of CEO respondents say they are hiring for roles related to AI that did not exist a year ago.

Methodology: The IBM Institute for Business Value, in cooperation with Oxford Economics, surveyed 2,000 CEOs from 33 countries and 24 industries between February and April 2025.

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CEOs Double Down on AI While Navigating Enterprise Hurdles

CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study.

The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale.

IBM

Image Source: IBM

According to the findings, 68% of surveyed CEOs identify integrated enterprise-wide data architecture as critical for cross-functional collaboration, and 72% view their organization's proprietary data as key to unlocking the value of generative AI. However, the research indicates organizations may be struggling to cultivate an effective data environment: half (50%) of respondents acknowledge that the pace of recent investments has left their organization with disconnected, piecemeal technology.

In the foreword of the study, IBM Vice Chairman Gary Cohn writes, "As AI adoption accelerates creating greater efficiency, and productivity gains, the ultimate pay-off will only come to CEOs with the courage to embrace risk as opportunity. Meaning, focusing on what you can control, especially when there is so much you can't. When the business environment is uncertain, using AI and your enterprise data to identify where you have leverage is a competitive advantage. At this point, leaders who aren't leveraging AI and their own data to move forward are making a conscious business decision not to compete."

"CEOs are balancing the pressures of short-term ROI and investing in long-term innovation when it comes to adopting AI," said Mohamad Ali, Senior Vice President and Head of IBM Consulting. "But we know that organizations that keep innovating, especially during periods of uncertainty, will emerge stronger and be better positioned to capitalize on new opportunities."

Other key findings include:

CEOs face competing pressures of short-term ROI and long-term innovation

  • Surveyed CEOs report that only 25% of AI initiatives have delivered expected ROI over the last few years, and only 16% have scaled enterprise wide. 
    To accelerate progress, two-thirds (65%) of CEO respondents say their organization is leaning into AI use cases based on ROI, with 68% reporting that their organization has clear metrics to measure innovation ROI effectively.
  • Just over half (52%) of CEO respondents say their organization is realizing value from generative AI investments beyond cost reduction.
  • 64% of CEOs surveyed acknowledge that the risk of falling behind drives investment in some technologies before they have a clear understanding of the value they bring to the organization, but only 37% say it's better to be "fast and wrong" than "right and slow" when it comes to technology adoption.
  • 59% of surveyed CEOs admit their organization struggles to balance funding for existing operations and investment in innovation when unexpected change occurs, as 67% say more budget flexibility is needed to capitalize on digital opportunities that drive long-term growth and innovation.
  • By 2027, 85% of surveyed CEOs expect their investments in scaled AI efficiency and cost savings to have returned a positive ROI, while 77% expect to see a positive return from their investments in scaled AI growth and expansion.

CEOs see strategic leadership and specialized talent as essential to unlocking AI value, amid expertise and skills gaps

  • 69% of CEO respondents say their organization's success is directly tied to maintaining a broad group of leaders with a deep understanding of strategy and the authority to make critical decisions.
  • 67% of CEOs surveyed say that differentiation depends on having the right expertise in the right positions with the right incentives.
  • CEOs cite lack of collaboration across organizational silos, aversion to risk and disruption, and lack of expertise and knowledge as top barriers to innovation in their organization.
  • Surveyed CEOs say roughly one-third (31%) of the workforce will require retraining and/or reskilling over the next three years, while 65% say their organization will use automation to address skill gaps.
  • 54% of CEO respondents say they are hiring for roles related to AI that did not exist a year ago.

Methodology: The IBM Institute for Business Value, in cooperation with Oxford Economics, surveyed 2,000 CEOs from 33 countries and 24 industries between February and April 2025.

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Signs It May Be Time to Reassess Your IT Infrastructure Strategy

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Enterprise Edge AI Reaches Inflection Point

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

AI Is Hitting Operational Limits

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

Alert Fatigue Is No Longer a Morale Problem, It's a Reliability Risk and a System Failure

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

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Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

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