Breaking Down AI Dependency: A Growing Concern
OpenAI has quickly become a giant in the realm of generative artificial intelligence(AI). Its tool, ChatGPT, is luring companies with the charm of cost savings and productivity gains. But there's a catch. Companies might be walking into a dependency trap, significantly similar to the ones set by cloud services. This growing reliance and the consequential lock-in scenarios have set the alarm bells ringing in the business world.
ChatGPT was virtually unknown barely 18 months ago. Fast forward to now, and enterprises are swooning over it. As the list of clients expands with big names like PricewaterhouseCoopers, Amgen Inc., JetBlue Airways Corp., Riot Games Inc., and Klarna Bank AB., so does the apprehension over complete reliance on a singular, dominant AI model. On one side, businesses are thrilled by the productivity gains and cost savings. On the other side, they are uneasy about the possible repercussions of dependency.
Industry rivals of OpenAI, such as Alphabet Inc., Meta Platforms Inc., Anthropic, and others, are scrambling to catch up in the race. The appeal of these tools is so compelling that companies are thrilled with the value they derive, inspiring questions about the AI companies’ underpricing strategies. Companies are left wondering about the eventual hike in prices and how they should react when that happens.
The journey into the vast expanse of AI bears significant comparisons to the early growth stages of cloud services. After a strong growth period, the rates began to soar, and companies seeking an alternative faced contract renegotiation, programming, and data management issues, echoing the warning signs with AI.
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Do you think AI dependency could lead to an uncontrollable monopoly? How should businesses respond to the potential lock-in scenario and fee increment?
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