In a recent interview, Kieran Gilmer, a notable AI strategist, discussed the reasons behind the high failure rates of AI projects. He reaffirmed that the main issues stem from fear, ignorance, and inadequate execution rather than the technology itself. Gilmer pointed out that many companies dive into AI without having precise business challenges identified or measurable success criteria established, leading to what he calls ‘Proof of Cost.’ He advocates for careful alignment between business goals and AI initiatives to avoid projects remaining in research phases.
Gilmer also stresses the importance of strong governance, quality data, and cross-functional collaboration in transitioning AI from the experimental phase to actual operational use. He argues that organizations must prioritize genuine business problems in AI projects and invest in responsible and ethical AI practices. With the growing accessibility of generative AI, he warns against the temptation to pursue every new trend without clear business justification, opting instead for applications that enhance efficiency and reduce complexity. According to Gilmer, building AI with a foundation of ethical guidelines and robust governance can foster trust and long-term success.
👉 Pročitaj original: CIO Magazine
