Generative AI is still immature. What does this mean for companies that adopt this technology now? What are the constraints and risks, and can they be managed?
There is no doubt that generative AI technology is incredibly important, extremely powerful, and will have a significant and disruptive effect on how businesses operate. The release of ChatGPT by OpenAI exposed Gen AI to the world and allowed people to experiment with it. This caught the attention and imagination of every business and every board of directors. It is certainly top of mind today for most senior executives.
New and impressive cyber offerings have come on the market to address these issues. However, regardless of their quality, the immaturity of the technology also extends to cybersecurity. The need to adequately protect a company against the ever-growing cyber threat further complicates where and how it can deploy Gen AI. At this time, this stands as one of the major constraints inhibiting broad adoption.Perhaps the most significant constraint limiting faster adoption of Gen AI is the cost.
What sets Gen AI apart from most IT investments is the very substantial cost to operate. There is no getting around it. Generative AI is a tremendous resource hog and extremely expensive to operate once implemented. As we talk with our Everest Group clients, one of the most productive ways to uncover the opportunities is to look at the existing tech stacks already in operation within a company. An example is the technology stack that is devoted to supporting the marketing or sales function. In past articles, I referred to these tech stacks as platforms. In today’s digital world, each business function has a supporting tech stack that supports operations.
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