Business Leaders Make AI Breakthroughs, But Most Remain in Experimentation Limbo

Business Leaders Struggle to Realize Value from AI Investments According to a recent survey of 1,775 IT leaders by HPE, nearly a quarter of organizations have successfully operationalized AI, up from 15% the previous year. However, the majority of companies remain stuck in experimentation, failing to translate AI training into meaningful business outcomes. This trend highlights the significant challenge businesses face in realizing value from their AI investments. The survey findings underscore the importance of "trusted AI inferencing at scale and in production," a concept championed by Craig Partridge, senior director worldwide of Digital Next Advisory at HPE. Partridge emphasizes that the true value of AI lies in inference, where AI earns its keep by putting trained models to use in real-world workflows. Inference is the operational layer that enables businesses to reap the benefits of AI, driving significant returns on investment. The survey reveals that only 22% of organizations have successfully operationalized AI, while the remaining 78% are struggling to bridge the gap between AI training and business outcomes. This disparity highlights the need for a structured approach to AI adoption, which HPE recommends as a three-part process: establishing trust in AI models, scaling AI inferencing, and integrating AI into production workflows. Establishing trust in AI models requires addressing concerns around data quality, model accuracy, and explainability. Scaling AI inferencing demands significant computational resources, often necessitating the deployment of specialized hardware and software solutions. Integrating AI into production workflows requires seamless integration with existing systems and processes, ensuring that AI-driven insights are actionable and impactful. HPE's Digital Next Advisory team has worked with numerous clients to overcome these challenges and achieve meaningful business outcomes from AI investments. By providing expert guidance and support, HPE has helped organizations unlock the full potential of AI, driving significant improvements in efficiency, productivity, and profitability. The market for AI solutions is rapidly evolving, with increasing demand for trusted AI inferencing at scale and in production. As businesses continue to grapple with the challenges of AI adoption, HPE is well-positioned to capitalize on this trend, offering a comprehensive suite of AI solutions and services that address the needs of organizations at every stage of their AI journey. In conclusion, while AI investments hold tremendous promise for businesses, realizing value from these investments requires a structured approach that prioritizes trusted AI inferencing at scale and in production. By understanding the challenges and opportunities associated with AI adoption, organizations can unlock the full potential of AI, driving meaningful business outcomes and significant returns on investment.