Developing your own Artificial Intelligence (AI) model is a significant step that can enhance an organization’s capabilities and help in competing more effectively in the market. However, before embarking on this process, there are key considerations to carefully evaluate, to ensure that the investment and AI development are worthwhile and meet genuine needs.
- The Problem to Be Solved
AI development should start with a clear identification of the problem to be solved. It is essential to know the purpose of creating the AI model. For instance, existing market models may not sufficiently meet business needs, there might be concerns about data security, or there could be extremely high usage that makes existing services impractical. Analyzing the problem is a crucial step to ensure that the developed AI effectively addresses these issues. - Availability of Data
Data is the heart of training AI models. If the problem to be solved involves making the model specialized, the organization must ensure that sufficient and appropriate data is available to train the AI, to reach effective development. Thus, if data is not readily available, preparing the data is a necessary task that should be prioritized. - Experimenting with Market Solutions
Currently, there are various AI solutions available in the market, including open-source models and ready-made APIs. Experimenting with these solutions can help organizations visualize the possibilities and select the most suitable option, potentially discovering that there are solutions that can address the problem without needing to develop their own model. - Cost-Effectiveness
Building a specialized AI model generally incurs higher investment costs compared to using off-the-shelf AI solutions. Therefore, organizations must thoroughly consider the cost-effectiveness of the investment, which includes the costs of data preparation, development, testing, and maintenance. Long-term cost analysis should not be overlooked to maximize the benefits of this investment for the business. - Long-Term Maintenance
Once an AI system is developed and deployed, organizations must be prepared for long-term maintenance, to ensure that the AI system is always operational. Continuously improving the model with new data or enhancing capabilities with increased usage is essential for adapting to changes and ongoing development.
Developing your own AI can enable organizations to refine their business processes more accurately and specifically. Having an internally developed AI also enhances agility in updating and developing models for better response to rapidly changing market demands. Additionally, internal AI development reduces the risk of exposing sensitive information to external providers and allows for better control of long-term costs, as it does not rely on external services that become more expensive with increased usage.
Organizations looking to enhance efficiency and gain a competitive edge should seriously consider developing their own AI. Not only can this help meet market demands precisely, but also lead to more efficient internal operations in the long run. At MFEC, we have a business unit that provides consulting and AI model development. For more information, please contact ailab@mfec.co.th
