ARMONK, N.Y., Jan. 19, 2026 /PRNewswire/ — A new study from the IBM (NYSE: IBM) Institute for Business Value indicates that nearly 79% of executives anticipate significant contributions to revenue from artificial intelligence (AI) by 2030, a marked increase from 40% today. However, only 24% of survey respondents possess a clear understanding of the potential revenue streams associated with these advancements.
The research highlights a dramatic shift in AI investment priorities, with forecasts suggesting a 150% surge in spending by 2030. Despite this optimism, 68% of executives express concerns about the potential failure of their AI initiatives due to inadequate integration with core business operations. “AI won’t just support businesses, it will define them,” stated Mohamad Ali, Senior Vice President of IBM Consulting. He emphasized that companies that successfully embed AI into their decision-making and operations will possess a decisive competitive edge.
Conducted among 2,000 C-suite executives, the global study reveals that AI is increasingly seen as a crucial catalyst for enterprise growth. Key findings show that while nearly half (47%) of current AI expenditure is aimed at improving efficiency, executives predict that 62% of AI spending will shift towards driving innovation by 2030. Additionally, 64% believe competitive advantages will stem from innovation rather than resource optimization.
The anticipated productivity gains from AI are projected at 42%, with 67% of executives expecting to realize these benefits by the decade’s end. Notably, companies that plan to reinvest these productivity gains into growth initiatives represent a strategic shift towards bolder investments in innovation.
Despite the positive outlook, the study reveals a disconnect between expectations and preparedness. While 57% of respondents identify enhanced AI model sophistication as a competitive advantage, only 28% have a clear understanding of the specific AI models they will require. Furthermore, while 82% predict their AI capabilities will be multi-model by 2030, 72% believe that small language models (SLMs) will outperform large language models (LLMs).
Organizations that effectively scale AI across various workflows and utilize smaller, custom AI models anticipate greater productivity gains—24% more than competitors not following this strategy, alongside a 55% increase in operating margins. However, while 59% of executives foresee quantum-enabled AI transforming their industries by 2030, only 27% foresee actively utilizing quantum computing, indicating a significant opportunity gap for proactive organizations.
The evolving landscape of AI is also set to redefine leadership roles within organizations. By 2030, 25% of enterprise boards are expected to include an AI advisor or co-decision maker. A notable 74% of executives agree that AI will fundamentally alter leadership dynamics, with two-thirds believing it will lead to the emergence of entirely new leadership positions. Concurrently, 67% anticipate that the lifespan of job roles will shorten, with 57% expecting that many currently valued skill sets will become obsolete.
For organizations prioritizing AI, data suggests they are 48% more likely to create new job roles and 46% more likely to restructure their organizations to maximize AI’s value. This finding underscores the necessity for adaptability in a rapidly changing work environment.
The study serves as a roadmap for business leaders aiming to transform their AI-first ambitions into tangible outcomes. As AI increasingly becomes integral to business strategy, organizations will need to focus on aligning their technology investments with overarching operational goals. For more detailed insights, the full study is available at IBM’s website.
The IBM Institute for Business Value, collaborating with Oxford Economics, surveyed executives across 33 geographies and 20 industries to explore strategic priorities and workforce transformations necessary for harnessing AI’s potential. This comprehensive analysis highlights the imperative for organizations to adapt swiftly in order to thrive in an increasingly AI-driven marketplace.
See also
Moonshot AI Valued at $4.8B as Chinese AI Market Grows Amid Geopolitical Shifts
C3.ai’s Lower Valuation Positions It as a Stronger Turnaround Candidate Than BigBear.ai
SAP Tackles AI Skills Gap as ERP Systems Embrace Automation and Analytics
UK Lawmakers Call for AI Stress Tests in Finance to Mitigate Consumer Risks and Instability
Tesla Revives Dojo3 Chip to Pioneer Space-Based AI Compute for Orbital Data Centers
