Is a key factor in learning with critical in-house data the key to surviving the future of AI utilization in on-premise environments?

With the evolution of “generative AI,” the use of AI in business is accelerating, and AI technology will play a wide range of roles, such as creating new businesses to meet market needs and addressing the growing labor shortage.
In the future, it will be difficult to maintain competitiveness without the use of AI.

Nevertheless, companies have long used “predictive AI,” which uses machine learning and deep learning to make future predictions based on current and past data, for product development and business decisions,
With a mix of companies seeking effective ways to use AI in the wake of the generative AI boom, finding the optimal solution for AI utilization is an extremely challenging mission.
The most important factor in utilizing AI is the data accumulated within a company, and the same is true for both predictive and generative AI, where models need to be trained.

In particular, when used to guide management decisions, it is required to train using critical data within the company, not public data.
Therefore, it will be more important than ever to build an AI environment in a local environment, i.e., on-premise.

Most companies considering AI applications may consider deploying AI services provided in the public cloud.
However, to gain deeper insights from this data, it will be necessary to incorporate sensitive data within the company.
When this happens, we expect to see more companies adopting the approach of running AI on on-premise infrastructure, rather than AI in the public cloud, which takes data outside the company.

Building an AI infrastructure on-premise poses the challenge of increasing the scale of the solution.
This will make it even more difficult for companies to implement AI due to cost considerations.

In light of the increasing number of companies wishing to utilize AI on-premise, we will introduce the significance of implementing AI, challenges in implementing AI, and how to proceed with efforts for companies wishing to start utilizing AI on a small scale.
We hope you will find out more about using AI on-premise, including the latest trends in the AI market.