Only 10 Percent Of Organizations Launched GenAI Solutions in 2023, According to an Intel Company

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While 2023 is widely touted as the year of generative artificial intelligence (GenAI), a recent study by an Intel company reveals a different reality. The findings of the 2023 ML Insider by cnvrg.io shows that only 10 percent of organizations launched GenAI solutions this year. This underscores a seemingly paradoxical trend. 

cnvrg.io is an intel company that specializes in AI and large language model (LLM) platforms. The annual survey by cnvrg.io offers insights into the latest trends in the AI and ML industry. The latest report is based on a survey of 430 professionals who were asked about how GenAI is being used in their organizations and what plans they have in store for AI development in the future. 

According to Markus Flierl, Corporate Vice President and General Manager of Intel Cloud Services, one the reasons why organizations are hesitant to adopt GenAI is due to “the barriers they face when implementing LLMs”. 

Fleirl further added, “With greater access to cost-effective infrastructure and services, such as those provided by cnvrg.io and the Intel Developer Cloud, we expect greater adoption in the next year as it will be easier to fine-tune, customize, and deploy existing LLMs without requiring AI talent to manage the complexity.”

Another key finding of the report was the surprisingly low adoption rate for GenAI technology within businesses. Around three-quarters of respondents reported that their organization has yet to deploy GenAI models to production. 

While the adoption rate might still be low, the organizations that have adopted GenAI are experiencing benefits such as improved customer experiences (58 percent), improved efficiency (53 percent), and enhanced product capabilities (52 percent). 

The 2023 ML Insider indicates that a majority of businesses approach GenAI by building their own LLM models and fine-tuning them to their use cases. However, the survey also shows that one of the key challenges to this approach is not having the infrastructure to develop LLMs into products. There is also a lack of AI talent, high costs of implementation, and compliance issues that hinder progress. 

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The survey respondents are aware of the rise in demand for specialized AI skills. Eighty-four percent shared that they need to enhance their skills and interest in LLM technology. Only 19 percent are confident about their current understanding of how LLM technology works. 

While there are some serious challenges to the adoption of GenAI, the report shows that GenAI is having a major impact on the industry. Compared to last year, the use case of chatbots or virtual agents has soared by 26 percent. Text generation and translation have increased by 12 percent compared to 2023. 

The findings of the cnvrg.io could be explained by a recent study by KPMG US that revealed that around two-thirds (65 percent) of U.S. executives surveyed believe that the biggest impact of GenAI would be in about 3 to 5 years, and that is why they are still a year or two away from implementing their first GenAI solution. 

According to a Teradata report on GenAI adoption, another reason for slow GenAI adoption could be that enterprises are not ready for mass deployment. The Teradata study shows that global executives feel confident in the capabilities of GenAI technology for future offerings and operations, however, they believe a lot more work needs to be done before a large-scale deployment can take place. 

The projected spending on GenAI initiatives is set to rise significantly in the coming year, with some projecting it to reach $143 billion in 2027. To help increase the rate at which companies are putting GenAI into production, businesses may want to consider using third-party development services, or if they want to build their own AI models, they will need significant investment in their infrastructure and AI skills. 

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