Generative artificial intelligence (GenAI) has reached a critical point in the Gartner hype cycle but has fallen short of expectations, according to analysts at the European Gartner Symposium in Barcelona.
During the opening keynote, Alicia Mullery, a vice-president for research at Gartner, discussed the two AI races: the competition among tech providers and the race to deliver AI outcomes safely and securely. She emphasized to the audience of IT executives that the latter race is crucial for their organizations.
One key takeaway from the session was the potential for wasteful spending with GenAI. Mullery and co-presenter Daryl Plummer, chief research analyst at Gartner, warned about the importance of understanding and monitoring costs associated with GenAI projects.
Gartner’s research reveals that most organizations are not adequately prepared for AI adoption in terms of emotional readiness, technological capabilities, organizational structure, and management readiness.
To prevent failures, Gartner recommended two approaches: one focused on productivity improvement and the other on driving transformational change through AI.
Gartner data shows that running a proof of concept project for AI can range from $300,000 to over $2 million. Plummer highlighted the high costs associated with training AI models on GPU hardware and the potential for escalating costs related to AI inference.
Plummer also cautioned that tech providers are overly focused on showcasing the advancements of AI without considering the practical implications for customers. He emphasized the importance of guiding organizations on the journey towards achieving their AI objectives.
Many organizations are spending a significant portion of their budgets on IT consulting to understand how AI technology can benefit their operations, as they are not yet ready to fully leverage the advanced AI solutions offered by major providers.
IT leaders must carefully consider the desired outcomes when deploying AI, whether for business efficiency improvements or industry transformation. Gartner categorizes organizations as “AI-steady” or “AI-accelerated” based on their approach to AI adoption and the number of pilot initiatives they run.
Gartner predicts the emergence of TRiSM (trust, risk, and security management) technology to ensure compliance and manage the complex AI systems that AI-accelerated organizations seek to deploy.
