In a stark warning, Gartner has predicted that a significant portion of generative AI (GenAI) projects will falter after the initial proof-of-concept phase. The research firm estimates that by the end of 2025, at least 30% of these initiatives will be abandoned due to factors such as poor data quality, inadequate risk management, spiraling costs, or a lack of clear business value.
Speaking at the Gartner Data & Analytics Summit, Rita Sallam, Distinguished VP Analyst, emphasized the growing impatience among executives for tangible returns on their GenAI investments. Despite the technology hype, many organizations struggle to quantify and realize its benefits. As the scope of GenAI projects expands, the financial burden of developing and deploying these models is becoming increasingly apparent.
One of the primary challenges organizations face is justifying the substantial investment required for GenAI-driven productivity enhancements. While the technology holds immense potential to transform business models and create new opportunities, the associated costs can range from $5 million to $20 million. Gartner’s research highlights the variability of these costs, which are influenced by factors such as the scale of AI ambition, specific use cases, and deployment approaches.
Historically, CFOs have hesitated to invest in technologies that offer indirect future value rather than immediate returns on investment (ROI). This reluctance can skew investment allocation towards tactical outcomes rather than strategic ones. However, Gartner’s analysis suggests that GenAI requires a higher tolerance for indirect financial benefits.
Early adopters across various industries and business processes report improvements, including increased revenue, cost savings, and productivity gains. A recent Gartner survey found that respondents experienced an average revenue increase of 15.8%, cost savings of 15.2%, and productivity improvement of 22.6%. While this data provides valuable insights into GenAI’s potential business value, it’s important to note that the impact can vary significantly based on company-specific factors, use cases, roles, and workforce dynamics.
Organizations must carefully assess the business value and total costs associated with GenAI business model innovation to make informed investment decisions. Businesses can determine whether the outcomes align with their expectations by calculating the direct ROI and future value impact. If the benefits meet or exceed expectations, organizations may consider expanding their GenAI investments. Conversely, if they fall short, alternative innovation scenarios should be explored.
Gartner’s prediction is a cautionary tale for organizations considering embarking on GenAI projects. While the technology offers immense potential, success hinges on careful planning, robust data management, effective risk management, and a clear understanding of the desired business outcomes. By addressing these challenges, organizations can increase their chances of realizing the full value of GenAI and avoid the pitfalls of abandoned projects.
