Hybrid approach dominates IT decision-makers’ adoption of generative AI

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A study by Morning Consult on behalf of Dell Technologies found that generative AI adoption is accelerating, with most IT decision-makers (38%) choosing a hybrid approach that mixes public and private models. This hybrid approach is appealing because it matches companies’ needs to protect data, maintain control over AI models and results, and manage costs.

The study surveyed 500 IT decision-makers involved in generative AI initiatives in the U.S., U.K., France, and Germany. Judging from the respondents whose organizations have moved beyond a pilot stage with generative AI, 80% use centralized decision-making and/or a center of excellence in their strategic approach. Among people whose organization has moved past a pilot program, 87% believe generative AI is on track to deliver meaningful results, and 76% are increasing their budgets to include AI.

Other factors respondents value highly when making decisions about how to buy and implement generative AI are security and protecting the value of data, more control over models and better output results, and cost.

Security, control, and cost are the top three factors influencing whether IT decision-makers use public models, build their own models, or choose something in between. Of surveyed IT decision-makers, 38% plan to approach generative AI by classifying their data and using a hybrid approach.

Another 21% plan to retrain an existing model using their own data in their own environment. Some 16% prefer to purchase public models in the cloud, while just 14% prefer to use open source or other models on-premises for inferencing. Finally, 9% prefer to build their own model from scratch.

Many respondents (44%) are at an early to midpoint in the adoption of generative AI. This means they either have no strategy around generative AI or established core use cases, and they have not yet deployed solutions. Another 42% of respondents say their organization is not too hesitant about generative AI adoption, while 29% are somewhat hesitant. On the extremes, 8% are very hesitant, and 21% are not hesitant at all.

Many respondents whose organizations moved beyond pilot programs (49%) expect value within six months to a year. Of the people surveyed, 76% felt generative AI impact will be “significant if not transformative.” In particular, they expect it to provide productivity gains, streamline processes, and achieve cost savings.

The top reasons why respondents are hesitant to implement generative AI are security risks such as data or intellectual property leakage, technical complexity, data governance concerns such as regulations or compliance, cost of implementation, and concerns around ethical or responsible implementation. A small number of organizations surveyed (5%) ban the use of generative AI. Of the four countries surveyed, the number of organizations which ban generative AI is highest in the U.S. (6%) and lowest in the U.K. (2%).

The sources for this piece include an article in TechRepublic.

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