Hong said many companies are delaying the adoption of new technologies. In the past eight years that TMA has provided solutions for implementing AI, less than 10 percent of companies, including foreign companies, have done this systematically. Reasons for this include lack of preparedness, difficulty arranging capital, and labor shortages.
In the past, companies did not rush to digitize until faced with a crisis, but now companies will not apply AI unless they feel pressure from rivals.
However, Hong pointed out that the advent of ChatGPT has created competition among companies in applying AI to their operations. The number of companies leveraging AI has tripled.
However, not all companies can apply AI right away. In general, companies need to develop a strategy around data. Only once this is in place can you start applying AI. The quality of AI depends on the quality of the input data.
Companies should apply AI where the data infrastructure is ready at a reasonable cost and where it can help solve business problems.
AI reduces costs, saves time, and improves efficiency. But he said data strategy needs to be prioritized first, and businesses need consulting to help them choose the best AI solution.
Nguyen Kim Anh from VinBigData said many companies were hesitant to incorporate AI into key tasks due to fear of high costs. But now, generative AI with optimal models can help solve problems in AI application strategies.
VinBigData introduced ViGPT – 1.6B, a Vietnam-made generative AI model, in late 2023. Just a few months after its release, this model joined his VMLU (Vietnamese Multitasking Language Understanding) top four language models.
McKinsey's 2023 report shows that a company's sales and marketing, research and development, customer care and operations will benefit the most from AI applications.
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