A new survey conducted by cnvrg.io, an Intel company, has shed light on the current state of enterprise adoption of artificial intelligence (AI) solutions. Despite the widespread coverage of generative AI in the media, the survey shows that many organizations are still hesitant to fully embrace this technology due to various challenges they face.
Challenges in AI Adoption
The survey, called the 2023 ML Insider survey, draws insights from a global panel of data scientists and AI professionals. It highlights that only 10% of organizations have successfully launched generative AI solutions into production. This figure is significantly lower than the optimistic expectations for this technology.
Infrastructure and skill gaps are major hurdles to widespread adoption. Many organizations struggle with setting up the necessary infrastructure to support AI implementations. Additionally, there is a lack of skilled professionals who can effectively manage and leverage AI technology.
In terms of industry adoption, the financial services, banking, defense, and insurance sectors emerge as the leaders in implementing AI solutions. These industries recognize the potential for enhanced efficiency and improved customer experiences through AI integration. On the other hand, sectors such as education, automotive, and telecommunications seem more hesitant in their AI initiatives, with implementation still in the early stages.
“The survey suggests organizations may be hesitant to adopt generative AI due to the barriers they face when implementing large language models (LLMs),” said Markus Flierl, corporate VP for the developer cloud at Intel.
Overcoming these barriers requires greater access to cost-effective infrastructure and services. This includes solutions provided by cnvrg.io and the Intel Developer Cloud, which can help organizations fine-tune, customize, and deploy existing large language models without relying heavily on AI experts to manage the complexity.
Key Findings from the Survey
- Despite the buzz around AI, enterprise adoption of generative AI still faces significant challenges.
- Companies are still in the experimentation phase with generative AI rather than fully integrating it into their operations.
- Factors such as lack of technical skills, regulatory concerns, reliability issues, and inadequate infrastructure hinder the rapid scaling of AI.
“The 2023 ML Insider Survey shows that a majority of AI developers say lack of technical skills is slowing down their organization’s adoption of machine learning and large language models, which puts pressure on businesses striving to implement generative AI capabilities,” said Tony Mongkolsmai, Software Architect and Technical Evangelist at Intel.
Recognizing these challenges, the industry as a whole must work towards simplifying AI implementation. Removing complexity and providing easier tasks for developers will help accelerate adoption and enable organizations to fully benefit from the capabilities of generative AI.
To delve deeper into the insights of the survey, you can access the full ML Insider 2023 report on the company’s website.
