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Home Tech News

AI to Drive Smarter Business Growth Through 2030: IBM

DigitalCIO Bureau by DigitalCIO Bureau
January 23, 2026
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IBM Makes Llama 2 Available Within Its Watsonx AI And Data Platform
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New research from the IBM Institute for Business Value reveals that nearly eight in ten (79%) surveyed executives expect AI will significantly contribute to their revenue by 2030 – up from 40% today – yet, few (24%) have a clear view of where that revenue will come from. Despite this uncertainty, investment is accelerating: respondents predict that AI investment will surge approximately 150% between now and 2030. At the same time, 68% of executives surveyed worry their AI efforts will fail due to lack of integration with core business activities. “AI won’t just support businesses, it will define them,” said Mohamad Ali, Senior Vice President, IBM Consulting. “By 2030, the companies that win will weave AI into every decision and operation. They will own powerful AI assets, move faster than competitors, bring innovations to market quickly, and deliver real, measurable business results using technology and automation.” The global study, based on insights from 2,000 C-suite executives, shows that AI is emerging as a critical driver of enterprise growth through 2030. The findings suggest that future success will come from making bolder strategic bets, even as many surveyed executives face a gap between expectations and outcomes. Key findings include: Executives are looking beyond AI efficiency to drive future gains
  • While nearly half (47%) of AI spend is now focused on efficiency, respondents expect 62% of AI spend will be dedicated to innovation by 2030.
  • 64% of surveyed executives believe that by 2030, competitive advantage will come from innovation rather than resource optimization.
  • 70% of surveyed executives plan to reinvest the value from AI-powered productivity gains into growth initiatives.
  • Respondents expect AI to boost productivity by 42% by 2030, with 67% expecting to capture most AI-enabled productivity gains by then.
Competitive advantage will depend on the right technology bets
  • While most surveyed executives (57%) say their competitive advantage will come from AI model sophistication, only 28% have a clear view of what AI models they’ll need by 2030.
  • 82% of respondents expect their AI capabilities to be multi-model by 2030, and 72% expect small language models (SLMs) to surpass large language models (LLMs).
  • Surveyed organizations scaling AI across multiple workflows, using smaller, custom and foundation AI models, anticipate 24% greater productivity gains and 55% higher operating margins by 2030.
  • While 59% of respondents say quantum-enabled AI will transform their industry by 2030, only 27% expect to be using quantum computing by then — a gap that underscores opportunity for organizations that are prepared to act today.
AI is redefining leadership and the skills that matter most
  • By 2030, executives surveyed expect 25% of enterprise boards will have an AI advisor or co-decision maker, and 74% say AI will redefine leadership roles across the enterprise, with two-thirds believing AI will create entirely new leadership roles.
  • Meanwhile, 67% of respondents say job roles are becoming shorter-lived, 57% expect most current employee skills to be obsolete by 2030, and 67% agree mindset will matter more than skills.
  • In addition, 67% of surveyed executives expect AI to eliminate the resource and skills constraints that hold their organization back today.
  • For AI-first organizations, analysis shows they are 48% more likely to create net-new jobs roles and 46% more likely to redesign their organizational structure to achieve more AI value.
Study Methodology The IBM Institute for Business Value, in cooperation with Oxford Economics, gathered insights from 2,007 senior executives on how they expect their organizations to evolve between 2025 and 2030. The survey was conducted across 33 geographies and 20 industries during the third and fourth quarters of 2025. The survey explored strategic priorities, including AI-first operations, the integration of advanced AI models into products and services, workforce transformation, and readiness for emerging technologies like quantum computing.
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