New research from the IBM Institute for Business Value highlights a growing disconnect between executive optimism around artificial intelligence and the clarity needed to convert that optimism into sustained revenue growth.
The global study, based on insights from 2,000 C-suite executives, finds that 79 percent of surveyed leaders expect AI to significantly contribute to their organization’s revenue by 2030, compared with just 40 percent today. However, only 24 percent say they have a clear understanding of where that future AI-driven revenue will come from.
The findings point to a decisive shift toward what IBM describes as the “Enterprise 2030” era, where AI is no longer a supporting technology but a defining force shaping business models, leadership, and competitive advantage.
AI investment accelerates, integration concerns persist
Despite uncertainty around monetization, executive confidence in AI investment is rising sharply. Respondents predict AI investment will increase by around 150 percent between now and 2030. At the same time, 68 percent of executives worry their AI initiatives could fail due to weak integration with core business activities, underlining a critical execution challenge.
Mohamad Ali, Senior Vice President at IBM Consulting, said by 2030, leading companies will embed AI into every decision and process, enabling them to move faster, innovate more effectively, and deliver measurable business outcomes through automation and advanced technologies.
Shift from efficiency to innovation-led growth
The IBM study shows that enterprises are already moving beyond using AI purely for operational efficiency. While 47 percent of current AI spending is focused on efficiency gains, executives expect 62 percent of AI investment to be directed toward innovation by 2030.
About 64 percent of respondents believe competitive advantage in the next decade will come primarily from innovation rather than resource optimization. In addition, 70 percent plan to reinvest productivity gains generated by AI into growth initiatives. Executives expect AI to improve productivity by 42 percent by 2030, with 67 percent anticipating that most AI-enabled productivity gains will be realized by then.
Technology choices will shape competitive advantage
While 57 percent of surveyed executives believe their competitive edge will depend on AI model sophistication, only 28 percent have a clear view of the AI models they will need by 2030. The research indicates a strong shift toward diversified AI architectures, with 82 percent expecting their AI capabilities to be multi-model and 72 percent predicting that small language models will outperform large language models in enterprise use cases.
Organizations that are already scaling AI across multiple workflows, using a mix of smaller, custom, and foundation models, anticipate 24 percent higher productivity gains and 55 percent higher operating margins by 2030.
The study also highlights emerging technologies such as quantum-enabled AI. While 59 percent of executives believe quantum-enabled AI will transform their industry by 2030, only 27 percent expect to be using quantum computing by then. This gap signals a potential advantage for organizations that begin preparing earlier.
AI reshapes leadership and workforce dynamics
AI is also expected to have a profound impact on leadership and skills. By 2030, executives predict that 25 percent of enterprise boards will include an AI advisor or co-decision maker. Around 74 percent believe AI will redefine leadership roles across the organization, with two-thirds expecting the creation of entirely new leadership positions.
Workforce implications are equally significant. About 67 percent of respondents say job roles are becoming shorter-lived, while 57 percent expect most current employee skills to become obsolete by 2030. A similar share believes mindset will matter more than specific skills, and 67 percent expect AI to remove the resource and skills constraints that limit organizations today.
The analysis shows that AI-first organizations are better positioned for this transition. These companies are 48 percent more likely to create net-new job roles and 46 percent more likely to redesign their organizational structures to unlock greater AI-driven value.
Overall, the IBM study suggests that while confidence in AI’s revenue potential is rising rapidly, closing the gap between ambition and execution will be critical for enterprises seeking to succeed in the AI-defined economy of 2030.
RAJANI BABURAJAN
