New research from the IBM Institute for Business Value reveals a significant shift in executive expectations about artificial intelligence’s (AI) role in business growth. A striking 79% of executives now foresee AI contributing substantially to their organizations’ revenue by 2030, nearly doubling the current 40%, demonstrating growing confidence in AI’s positive business impact. However, only 24% of these leaders have a clear strategy identifying exact revenue sources from AI, highlighting a common challenge in navigating AI adoption within business models. The study underscores how digital transformation influences executive perspectives, as industries increasingly use machine learning, automation, and advanced analytics to optimize operations, improve customer experiences, and innovate products. AI is expected to become a core growth and competitive advantage driver, not just a tool for cost or efficiency improvements. Yet, the gap between revenue expectations and clarity on sources suggests many organizations remain early in their AI journeys, facing hurdles such as system integration, viable AI business models, market alignment, and talent development. Experts emphasize that overcoming these challenges requires a strategic approach beginning with understanding market needs and applying AI accordingly.

Companies must move beyond pilots to scaling proven AI solutions that generate value and open new revenue streams, necessitating collaboration among business leaders, data scientists, technologists, and other stakeholders. Additionally, ethical considerations and governance frameworks are vital to building trust and ensuring AI deployments are transparent, fair, and regulatory-compliant, avoiding reputational risks that could threaten revenue. Continuous investment in AI talent and technology infrastructure is also critical. As AI becomes central to business strategies, organizations are expected to ramp up resources for workforce upskilling, acquiring AI tools, and partnering with startups and external innovators to accelerate progress. Overall, IBM’s findings depict a corporate landscape of excitement tempered by caution—while optimism about AI’s revenue potential is high, strategic ambiguity remains a key obstacle. To realize AI’s promise as a transformative force reshaping industries and market dynamics, leaders must adopt a vision that blends optimism with pragmatism. Grounding AI initiatives in solid business cases, supported by capable teams and ethical standards, will determine how fully AI can act as a principal revenue driver in the decade ahead.