One-third of AI projects will go bankrupt by the end of next year

Reputable market analysis company Gartner has made a very remarkable prediction in the context of the extremely lively and bustling AI market picture.

According to Gartner experts, it is expected that about 30% of existing generative AI projects in the entire market will be abandoned by businesses by the end of next year, after a period of proving their effectiveness and ability to keep profits. . Some reasons for forecast abandonment include poor data quality, inadequate risk controls, rising costs, or unclear business value.

Gartner gave several examples of how generative AI models are being deployed. Some applications include coding assistants, creating personalized sales content, searching documents with Retrieval-Augmented Generation (RAG), virtual assistants, and LLMs in health, insurance, or financial services .

Coding Assistant (code assistant) is the most economical app with an upfront cost of $100,000 to $200,000, and a recurring cost per user per year of $280 to $550. Costs will skyrocket as companies start building large language models (LLMs) from scratch to serve in healthcare, insurance or financial services, with upfront costs ranging from $8 million to $20 million dollars and recurring costs of $11,000 to $21,000.

One-third of AI projects will go bankrupt by the end of next year Picture 1One-third of AI projects will go bankrupt by the end of next year Picture 1

Commenting on this prediction, Gartner Vice President Rita Sallam, said:

After last year's craze, executives are starting to lose patience in waiting to see returns on their GenAI investments, but at the same time their businesses are struggling to prove and realize value. As the scope of initiatives expands, the financial burden of developing and deploying GenAI models is increasingly felt.

Unfortunately, there is no one-size-fits-all GenAI solution, and investment costs are much more unpredictable than with other technologies. What you spend, the use cases you invest in, and the deployment approaches you take all determine the cost. Whether you're a market disruptor and want to bring AI everywhere, or you're more conservatively focused on increasing productivity or scaling existing processes, each solution has costs, risks, etc. risks, possibilities of change and different strategic impacts.

It's not surprising that some businesses will stop implementing generative AI projects over time. In the age of digital technology, artificial intelligence (AI) has become an inevitable trend. From chatbots, virtual assistants to self-driving cars, AI has permeated every area of ​​life. However, this development has, is, and will create a strong purification in the entire market.

5 ★ | 1 Vote