McKinsey's survey reveals the swift implementation potential of generative AI, but Gartner analysts warn of struggling organizations to prove value and increasing financial burdens. The text explores the limitations of generative AI, particularly in complex tasks requiring expert knowledge, and highlights both the cost-saving potential and risks associated with its widespread adoption.
According to McKinsey's 2024 Global Survey on AI, most companies can set up generative AI systems in 1-4 months, and analysts expect that by 2025, AI will automate half of all digital work. An estimated 30% of generative AI projects will fail after initial testing by the end of 2025. 'After last year's hype, executives are impatient to see returns on GenAI investments, yet organizations are struggling to prove and realize value,' says Rita Sallam, Distinguished VP Analyst at Gartner.
'As the scope of initiatives widen, the financial burden of developing and deploying GenAI models is increasingly felt.' The success rate drops to nearly zero for complex tasks that need expert knowledge. This poor performance raises red flags about using the technology for essential business operations. Recently, a major company gave AI assistants to 60,000 employees. This widespread rollout shows both possible cost savings and major companies' willingness to try generative AI despite its flaws. Experts say that while generative AI is new, it needs to be handled much differently than handling traditional AI and machine learning systems.
GENERATIVE AI AI IMPLEMENTATION BUSINESS OPERATIONS AI CHALLENGES TECHNOLOGY TRENDS
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