42% of the organizations contemplate developing their own proprietary large language model pointers from a US-based CIO survey for Indian enterprises looking to adopt Gen AI.
Recognize, a technology investment platform that focuses exclusively on the tech services industry, has shared some interesting findings from its recent CIO survey. The Recognize CIO Survey series is a regular panel of 500 CIOs in the US. The data from this survey helps track spending intentions, changes in technology, product preferences, strategic priorities, and talent challenges.
Most utilized Gen AI products in organizations
Regarding the most utilized Generative AI products within organizations, Recognize’s CIO survey results show that 82% of the organizations use ChatGPT most frequently. This is followed by Copy.ai at 29%, with open-source solutions close behind at 28%. Bard and Claude are utilized by 27% and 25% of respondents, respectively, while Jasper is used by 24%. Chatsonic, however, appears less frequently used, with just 16% of organizations implementing it.
Approach towards Generative AI
The survey also delved into organizations’ approach to Generative AI technologies such as ChatGPT and Bard. 43% of organizations report having already deployed them in an enterprise application or process. Meanwhile, 21% of respondents have individuals experimenting on their own. Prototyping for enterprise use and large projects underway account for 17% and 13%, respectively.
Interestingly, only 4% of organizations are not using Generative AI at all, and only 1% have explicitly banned its use.
Concerns- accelerating the deployment of Generative AI
When asked about the main concerns related to accelerating the deployment of Generative AI, security tops the list, with 52% of organizations expressing this concern. Complexity is the second primary concern at 39%. The need for hardware resources and the potential for inaccurate results garnered 33% of responses. The impact on jobs and sourcing talent to manage these systems is 31%. Lower return on investment is a worry for 20% of respondents.
Interestingly, 8% express no material concerns or feel all concerns are manageable.
Building proprietary LLM
This survey reveals that many organizations are contemplating developing their proprietary large language models. A significant portion of respondents, 42%, confirmed they plan to do so, while another 41% still evaluate or consider this possibility. Only 7% indicated they have yet to make plans to build their own proprietary large language model.
Future of AI- impact of AI on companies in the next two years
Respondents hold largely positive views when asked about the expected impact of AI on their organization over the next two years. 46% of the companies predict AI will lead to significant use cases that drive productivity. 24% foresee select use cases without a major impact. A significant 22% expect a transformational impact from AI. Conversely, a small fraction of organizations, 7%, do not anticipate much impact from AI.