2023 was an extremely difficult year for the Taiwanese manufacturing sector, which reacted to these challenges by accelerating AI adoption into myriad areas of its operations. Let's take a look at some of the key takeaways from Profet AI’s Crossover Talks forum, which brought together Taiwan industry leaders to talk about their experiences with AI in 2023. Due to increasingly challenging market conditions, as well as the the emergence and integration of ChatGPT and generative AI into every level of business operations, 2023 was the year of widespread adoption of AI in Taiwan. Profet AI, an AI Enterprise solution for the manufacturing sector, held its 4th Crossover Talks forum of the year in Taipei on Nov. 30.
The event brought together more than 50 leading manufacturing industry decision-makers, to discuss the breakneck speed adoption of AI in 2023, its implications and to also share best practices and experiences. The following discussion reveals four our key takeaways and reflections from the event.
1. Dual pressures force AI adoption
There was agreement that double-headed pressures have forced manufacturers in Taiwan to accelerate their AI adoption. On one hand, they are dealing with customers who have increasingly strict quality requirements. On the other hand, they are also facing disruptions in supply chains caused by re-shoring initiatives, a slowing global economy and conflicts like the one in Ukraine. These combined pressures are compelling companies to improve their management strategies and adopt advanced technologies such as AI, as a solution to increasing production efficiency and staying competitive, while meeting standards.
According to Profet AI's own 2023 survey of 160 large-scale manufacturing companies in Taiwan, over 70% of respondents reported that AI not only has helped them with their current operations but also enabled them to forge a clear direction for their AI application development path in the coming few years.
2. CIOs need to prioritize standardizing data architecture
For CIOs in manufacturing organizations, the first hurdle they need to overcome for the company’s digital transformation to be a success is the standardization of existing digital architecture. This should span from system integration (SI) to business intelligence (BI), and further extends to artificial intelligence (AI) Secondly, to promote these standards across the whole company, it is imperative to initially focus on establishing successful cases in areas or departments that are most appropriate for AI implementation. Afterward, ensure that these cases are made visible throughout the organization to encourage replication.
For this "leveraging and empowering" strategy to be successful, it is also important to quantitatively connect objectives with key performance indicators of the company. This will help gain buy-in and support from management, who can clearly recognize how AI can assist in achieving their immediate goals.
3. AI mindset change: Developing the domino effect
Implementing AI requires a comprehensive mindset change throughout the organization. To ensure success, employees should be able to learn from one another and share successful experiences across the company. To achieve this, Acon-Holding has trained individuals known as 'seed instructors' using specially designed user-friendly AI tools. The company currently has 108 "seed instructors," distributed throughout the departments of manufacturing, sales and procurement, and has a goal to train thousands of similar digital evangelists within three years. The addendum to this is that laggards who are reticent to bring about these cultural changes may find themselves falling behind if they don’t jump on the opportunity soon.
4. Select the correct strategy and tools
When designing AI implementation strategies, companies should make sure to choose suitable AI solutions based on their current level of digitalization, data governance and overall utilization of technology. To make this leap into adopting AI as smooth as possible, manufacturers can consider engaging specialist consulting services or opt for No-Code platforms that provide a lower barrier to entry.
