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New global research from the IBM Institute for Business Value reveals that nearly eight in ten (79%) surveyed executives anticipate AI will significantly contribute to revenue by 2030 - nearly double the current 40% - yet only 24% have a clear understanding of the specific sources of that revenue growth. Despite this uncertainty, AI investment is projected to surge approximately 150% between now and 2030, while 68% of executives express concern that their AI initiatives could fail due to insufficient integration with core business activities.
Quick Intel
The IBM Institute for Business Value study, based on insights from 2,007 C-suite executives across 33 geographies and 20 industries, highlights AI's transition from efficiency tool to core driver of enterprise growth and competitive differentiation through 2030. While expectations are high, a significant gap persists between ambition and execution, particularly around strategic clarity, model selection, and integration.
Shift Toward Innovation and Competitive Differentiation "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."
Executives are increasingly prioritizing innovation over efficiency. While 47% of current AI spending focuses on efficiency, respondents expect 62% to target innovation by 2030. Competitive advantage is expected to stem from innovation (64%) rather than resource optimization, with 70% planning to reinvest AI-driven productivity gains into growth initiatives. Productivity is projected to rise 42% by 2030, with most gains captured by that time.
Strategic Technology Bets and Model Evolution Model sophistication is seen as a key advantage (57%), yet only 28% have clarity on future model needs. Multi-model environments are anticipated by 82%, and 72% expect small language models to outperform large ones. Organizations scaling AI across workflows using smaller, custom, and foundation models project 24% greater productivity and 55% higher operating margins by 2030.
Quantum-enabled AI is viewed as transformative by 59%, though only 27% expect to adopt quantum computing by 2030—highlighting a readiness gap and opportunity for early movers.
Redefining Leadership and Workforce AI is expected to reshape leadership, with 74% anticipating redefined roles and 25% foreseeing AI advisors or co-decision makers on enterprise boards by 2030. Two-thirds believe AI will create entirely new leadership positions. Job roles are becoming shorter-lived (67%), most current skills may become obsolete by 2030 (57%), and mindset is expected to outweigh skills (67%). AI-first organizations are 48% more likely to create net-new roles and 46% more likely to redesign structures for greater value.
Roadmap for AI-First Success The study outlines a clear path: make bolder strategic bets on AI integration, invest in governance and multi-model capabilities, prepare for quantum advancements, and prioritize workforce mindset shifts. Organizations that act decisively on these fronts are positioned to capture disproportionate value from AI by 2030.
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