From "most likely to be replaced by AI" to leading the charge against the trend: AI-driven customer service industry innovation

When AI knocks on the door, do you choose to fight or escape?

On the afternoon of July 23, I was at the [[AI Driven × Sustainable Innovation] Industry Trend Lecture] (https://www.cisanet.org.tw/Course/Detail/5705?ref=vista.tw). The opening remarks of Huang Shijun, Chairman of [Chengxi Information Group] (https://www.chainsea.com.tw/), immediately attracted my attention: “Our company is what everyone said will be affected by AI. The kind of company you should kill.” There was silence at first, followed by a burst of laughter. This is not self-deprecation, but an extremely frank confession of reality—Chairman Huang does not talk about AI as a distant trend, but as an imminent existential challenge.

As the largest customer service outsourcing company in Taiwan, Chengxi Information Group’s services cover important public utilities such as High Speed ​​Rail, Taiwan Railway, Taiwan Power and Taiwan Water, as well as the customer service centers of major banks. Chairman Huang said with a smile that in various media surveys on the “ranking of occupations that AI will replace”, customer service outsourcing is almost always on the list, often ranking among the top three. Faced with such a phenomenon, I am deeply impressed by Chairman Huang’s response: neither denying nor resisting, but taking the initiative to fight against it.

“If AI is really coming, I have to learn to coexist with it first, rather than waiting for it to take me out.” Behind this sentence is a forward-looking strategic thinking: turning challenges into opportunities and threats into competitive advantages. This is also what I think is the most valuable part of sharing this lecture - it is not just a theoretical discussion, but a valuable practical experience sharing; it is not just a future outlook, but also shows the current progress.

Redefine the logic of competition - AI is not a disaster, but a competitive lever

The anxiety of being named and the wisdom of changing your mind

At the beginning of the lecture, Chairman Huang opened the conversation with a simple question: “Have you ever checked which industries AI will kill?” The audience nodded, obviously this is a common anxiety among everyone. The guests present named them one by one, such as art design, audio and video editing, foreign language translation or customer service outsourcing… It is true that these industries have been marked as high-risk industries in various forecasts.

But Chairman Huang’s point of view was refreshing to me: “Our company is the largest customer service outsourcing company in Taiwan, so it should be quite representative for me to talk about this matter.” He did not avoid this label, but instead regarded it as proof that his company has the most say. This transformation of thinking is extremely important, that is, subtly changing from the threatened to the pathfinder, and on the other hand, from the original victim to the experimenter.

This reminds me that when I was working in the media, I often interviewed many companies facing digital transformation. When faced with the impact of new technologies, many business owners or middle- and high-level executives often have reactions such as denial, resistance or procrastination, and are eventually forced to respond hastily. Cheng Xi Information Group chose another path, taking the initiative, trying things first, and looking for opportunities in changes. I think this change in thinking may be more important than the adoption of any technology or tool.

From cost competition to efficiency revolution

The first strategic point emphasized by Chairman Huang is to reduce costs, which he believes is the first step to maintain competitiveness. This sentence sounds a bit cliché, but it has a new interpretation and connotation in the AI ​​era. Traditional cost control often means layoffs, salary cuts, or reduced benefits, but the benefits of AI are structural efficiency gains.

Cheng Xi Information’s logic is very clear: “If this market can survive for a while, at least my cost will be lower than others.” But the so-called low cost is not achieved by sacrificing quality or employee welfare, but by redesigning the work process through AI tools to make every link more accurate and efficient.

This reminds me of the “Productivity Paradox” (Productivity Paradox) in management science - the introduction of new technologies often does not immediately reflect productivity improvements in the initial stage, but once the learning curve is passed, the benefits will grow exponentially. Obviously, Cheng Xi Information’s approach is to start with the links that are easiest to standardize and have the most quantifiable effects, and gradually expand to the entire operating system.

Redefining Competitive Advantage

In the AI era, the definition of competitive advantage is being rewritten. In the past, advantages might have come from size, experience, or connections, but now they come more from the ability to learn, speed of adaptation, and proficiency in using tools. Chairman Huang used the example of Cheng Xi Information to explain: “We divided the company in 2018, with some manpower doing systems and other manpower doing services. If the systems are getting better and better, service organizations may be eliminated. This is a left-hand thing, but in the face of a fiercely competitive market, you have to get used to constantly challenging yourself.”

This kind of self-revolutionary thinking is impressive. Many companies are afraid that internal competition will cause a waste of resources, but Chengxi Information chooses to form healthy competition between different departments, forcing each unit to continuously improve. I think this organizational design concept is particularly important in the AI ​​era.

Recruitment revolution - let AI become the most accurate Bole

Pain points and cost black holes of traditional recruitment

When talking about specific AI applications, Chairman Huang first shared the transformation of the recruitment process. For a service industry company with thousands of employees, recruiting manpower is obviously one of the biggest cost black holes. He used specific figures to illustrate the seriousness of this problem: “We have spent a lot of money recruiting people from the beginning. After recruitment, we need to train, and after training, we need to continue to manage. It takes a lot of manpower and time to interview and select resumes. If the selected candidates are not ideal, or they leave after three months, the cost will be very, very high…”

Chairman Huang’s words reminded me of the dilemma faced by many companies, which is the vicious cycle of recruitment → training → resignation → recruitment again. In this cycle, not only are the direct costs (such as salaries, training costs, etc.) huge, but the indirect costs (team stability, service quality fluctuations, or management distraction, etc.) are even more difficult to estimate.

AI resume screening accuracy breakthrough

The first AI tool imported by Chengxi Information Group was a resume analysis model from abroad. Although it is expensive, the results are immediate. This system can not only understand the text information on the resume, but also analyze the potential personality traits, stability and learning ability, and even predict the possibility of the candidate becoming a mid-level supervisor in the future.

Chairman Huang shared two specific cases that impressed me deeply:

The first case is that AI recommended a junior employee with excellent qualities. System analysis shows that this person is well above average in indicators of motivation and responsibility, and has strong leadership potential. Although according to the traditional ranking of seniority, this person still needs to “work harder”, AI suggested that the company should rethink the promotion logic. As a result, this colleague performed extremely well and was successfully promoted to a supervisory position.

The second case is that AI reminded a senior employee who had been with the company for many years that although his work performance was stable, he lacked the talent for leadership and was more suitable for transfer to a technical support position. This kind of personnel arrangement not only avoids the problem of “employing the wrong person”, but also avoids the risk of resignation due to “not being reused”.

Breaking through the shackles of traditional thinking

The most enlightening aspect of these two cases is not how advanced AI technology is, but that it helps managers break through their thinking inertia. Chairman Huang’s reflection is very profound: “We Chinese are deeply influenced by Confucianism and attach great importance to ethics. But there are a lot of foreign CEOs in their thirties. Are we limited by the values of the past?”

This kind of reflection also touches on the deep-seated problem of business management: we are often bound by the existing framework and make decisions based on “what should be” instead of “how to be most effective”. The value of AI lies not only in its ability to process large amounts of data, but also in its ability to provide objective advice that is free from traditional biases.

This also reminds me of the blind spots that many companies often encounter when recruiting: overemphasis on academic background and neglect of actual abilities, overemphasis on seniority and neglect of potential, and even overemphasis on first impressions and neglect of deep-seated traits. The value of the AI ​​system lies in its ability to see through these superficial phenomena and directly analyze the core elements.

From human resources to talent capital

Through AI-assisted recruitment, Chengxi Information Group has achieved an important transformation: from human resources management to talent capital operation. The former focuses on how to manage existing employees, while the latter focuses on how to maximize each person’s value creation potential.

The direct benefits brought by this conversion are: employee retention days have been extended by half a year, training efficiency has been significantly improved, and management costs have also been significantly reduced. More importantly, this precise configuration allows each employee to exert his or her talents in the most suitable position, thereby improving the group’s overall job satisfaction and team stability.

Interview Training Robot - Let every supervisor become a recruitment expert

Interviewer’s professional problems

In a company of the size of Chengxi Information Group, the person actually responsible for interviews is often not the professional HR, but the middle-level supervisors of each department. Although these supervisors are very professional in their business, they often lack systematic training in interview skills. The result is that you ask intuitively, fail to dig deep into a candidate’s key attributes, and are easily misled by superficial appearances.

Chairman Huang mentioned that the average middle-level manager may have to supervise more than a dozen people, but if he is also responsible for interviews, he will inevitably be stretched. Because this supervisor may not be familiar with interviewing techniques and has no expertise in the field of human resources management, he may have some subjective biases in hiring talents.

This problem has actually been encountered in many companies: people with strong business capabilities may not be good interviewers, but the heads of business departments must participate in recruitment decisions. How to make these non-professional interviewers have professional standards has always been a problem in human resources management.

Use AI to create interview practice partners

How to solve this problem? Cheng Xi Information Group’s solution is to develop an interview simulation robot. This system is based on GPT technology and can play various types of job seekers and conduct simulated interview conversations with supervisors. What’s more, it provides detailed feedback and ratings after the interview.

Chairman Huang personally demonstrated the use of this system, which was impressive. The entire conversation process is very natural. The robot can not only answer various questions, but also provide corresponding details based on the resume content. After the interview, the system will give specific scores and suggestions for improvement: “Your interview skills in this part are not good enough. This person clearly has club experience but you didn’t ask, you didn’t ask why this person has changed jobs, or you didn’t discover what potential expertise this person has…”

The leap from theory to practice

The value of this training method is that it allows supervisors to practice repeatedly in a stress-free environment and gradually improve their interviewing skills. Traditional interview training is often theoretical, but there is often a huge gap between theory and practice. Simulation robots provide real conversation scenarios and instant feedback mechanisms.

Chairman Huang’s experience was obviously very positive, because when the supervisor started the interview, he found that he was able to grasp the key points of the interview. Why? Because with the assistance of AI, the conversation has already been simulated. Having said that, the value of this kind of rehearsal lies not only in the improvement of skills, but also in the sufficient psychological preparation.

I think of the concept of [mental simulation] (https://wawafinanceessais.blogspot.com/2020/11/blog-post_27.html) commonly used in sports training: excellent athletes will rehearse game scenarios in their minds over and over again, so that they can deal with it more calmly when they actually take the field. The service provided by the interview robot is exactly this opportunity for mental simulation.

Balance between standardization and personalization

Using interview robot training also brings an important value: while maintaining interview standardization, it can also reflect the personal style of each supervisor. The system provides a framework and methodology, but the specific application still retains room for human subjective judgment.

This balance is important. Excessive standardization will make the interview rigid and lose the real interaction between people; complete personalization will lead to inconsistent standards, affecting the fairness and effectiveness of recruitment. The role of AI tools is to provide professional support, not to replace human judgment.

Customer service training simulation system - making standard service an instinctive response

Complex challenges of customer service training

Customer service training has always been the core competitiveness of Cheng Xi Information, but it is also one of the biggest challenges. Customer service work may seem simple, but in fact it requires dealing with ever-changing situations, and every detail may affect the customer experience and even create legal risks. Chairman Huang used the credit card loss reporting service as an example to explain in detail the importance of standard procedures: “When reporting a loss for a customer, you can’t just say ‘I’ve reported the loss for you’ and end it. You must tell the customer: what is your card number, where you reported the loss, which system you used, what the case number is, and what time the loss was reported for you. All these must be made clear. The phone call is recorded, so that if there is a dispute, you can ensure there are no problems.”

This standardization requirement is not only to improve service quality, but also to prevent risks. In the customer service industry, a small oversight may turn into a customer complaint or even a legal dispute. But in order for new employees to quickly master these complex processes, traditional training methods often have limited effectiveness.

Immersive experience of AI simulation training

The customer service training simulation system developed by Chengxi Information Group provides an innovative solution to this problem. Their system is preset with various common service scenarios, such as credit card loss reporting, lost item inquiry or complaint handling, etc. Each scenario has detailed process requirements and standard speaking skills.

With this system in place, new employees can practice repeatedly in the system, and AI can play various types of customers and ask different questions and requirements. More importantly, the system will score in real time, pointing out which steps are done correctly and which areas are missing. It will even evaluate whether the tone is appropriate and whether it shows enough [empathy] (https://zh.wikipedia.org/zh-tw/%E5%90%8C%E7%90%86%E5%BF%83).

During his speech, Chairman Huang also personally showed a simulated scene of customers searching for lost items on the high-speed rail. After the conversation, the AI ​​system gave an evaluation of 94 points, which made Chairman Huang very satisfied. But the next advanced scenarios, such as helping others search for lost items, or complex situations involving multiple organizations, will be more difficult overall!

From knowledge transfer to skill internalization

When it comes to customer service, everyone is familiar with it. But what’s interesting is that this training method is revolutionary in that it not only imparts knowledge, but more importantly, develops reaction capabilities. Traditional training often stays at the level of “knowing what to do”, but what real customer service work requires is “being able to do it right naturally.”

AI simulation training provides a nearly real-life pressure environment, allowing students to internalize the correct process into conditioned reflexes through repeated practice. When facing real customers, they have experienced every possible situation and can naturally handle it calmly.

This also reminds me of the concept of “routine” in martial arts training: through repeated practice of standard movements, the body can remember the correct reaction method, so that it can perform naturally in actual combat. The same logic applies to customer service simulation training, which means that through a large number of standardized exercises, the correct service process becomes an instinctive reaction.

Double benefits of quality improvement and cost control

After introducing the AI training system, Chengxi Information Group has seen significant improvements in many aspects: the training cycle is shortened, newcomers can get started faster, service quality is more stable, and the customer complaint rate is reduced. More importantly, this approach greatly reduces reliance on trainers and allows high-quality training content to be replicated on a large scale.

This benefit is not only reflected in direct cost savings, but also in the improvement of overall operating efficiency. When each customer service staff can provide high-quality, standardized services, the performance of the entire team will be more stable and management difficulty will be reduced.

AI revolution in recording analysis and quality control

The labor-intensive dilemma of traditional quality control

In the customer service industry, quality control has always been the most labor-intensive but critical link. The traditional approach is to arrange for dedicated people to listen to recordings, score and write reports, but this approach is not only inefficient, but also difficult to achieve comprehensive coverage. Usually only random inspections are possible, which may result in some problems being missed.

Chairman Huang explained this dilemma: “It is too hard for people to check, and people are very subjective. If different people answer the same call, they may give different evaluations.”

In addition, there is a fundamental problem with this approach: the feedback cycle is too long. Usually you have to wait until the end of the month or quarter to get the quality analysis report, but customer service requires immediate feedback and adjustments.

The full coverage revolution of AI speech analysis

The AI quality control system introduced by Chengxi Information Group has completely changed this situation. The system first converts all customer service recordings into text, and then uses natural language processing technology to conduct a comprehensive analysis of each call.

The system can not only check whether standard procedures were followed, such as whether identity verification was carried out, whether case numbers were communicated, and whether empathy was expressed, but it can also calculate the time spent in each link, analyze the appropriateness of tone, and even identify changes in customer emotions.

The system interface shown by Chairman Huang is impressive: “It took 4.82 seconds to say the opening greeting and 21.42 seconds to confirm the identity. These lights are all normal green. But a red light appears here, indicating that there is a problem in the guidance link. The AI will tell us what the specific problem is and what aspects of training need to be strengthened.”

From sampling inspection to full analysis

The revolutionary nature of this approach lies in the leap from sampling inspection to full analysis. Every call is analyzed, every problem is discovered, and every improvement point is flagged. In this way, not only the coverage of quality control is greatly improved, but also the discovery and solution of problems become more timely.

More importantly, this analysis is objective and consistent. There will be no differences due to the subjective bias of the examiner or the mood of the day. Standards are standards, implementation is implementation, and the data will truthfully reflect the real situation.

This also reminds me of the concept of “Zero Defect Management” in the manufacturing industry: pursuing continuous improvement of product quality through systematic testing and improvement. AI quality control systems also bring the same possibility to the service industry.

Data-driven continuous improvement

What’s more valuable is that the large amount of data accumulated by the system can provide a basis for continuous improvement. For example, managers can see which types of problems occur most often, which periods of time have relatively low service quality, which customer service personnel need key training, and so on. These insights naturally provide scientific basis for the formulation of training plans and allocation of resources.

This transformation from experience-driven to data-driven can be said to be an important trend in modern enterprise management. With the assistance of AI tools, this transformation is possible in the service industry.

Business Card Robot - From Tool Application to Strategic Thinking

Emotional intelligence beyond functionality

Chairman Huang talked about many AI applications in this lecture. Among them, the business card recognition robot may be the most amazing one. It not only demonstrates information technology, but also reflects the huge potential of AI in business socialization.

The operation process shown by Chairman Huang seems to be very simple: take a business card, upload it to the system, let AI automatically identify the person’s name, position, company and other information, then ask about the occasion and background of the meeting, and finally generate a personalized greeting letter.

AI’s business wisdom and humanistic care

The cleverness of this letter is that it not only correctly identifies the basic information, but also infers a reasonable business relationship based on the conversation background, and even adds humanistic concerns about climate change. Many details not mentioned on the business card rely on AI to actively query and supplement them.

In my opinion, this demonstrates the three levels of AI capabilities in business scenarios:

1. Information processing ability: accurately identify and organize basic information
2. Logical reasoning ability: deduce business relationships based on background information
3. Emotional intelligence: Add humanistic care to make communication warmer

The leap from automation to intelligence

The significance of the business card robot is not how much typing time it can save, but that it demonstrates the transformation of AI from an automated tool to an intelligent partner with warmth and affection. In other words, it does not just execute instructions, but is able to understand intentions, supplement information and optimize expressions.

Chairman Huang said with a smile: “Now I even discuss strategies with AI.” When AI can handle complex business logic, supplement valuable information, and even display emotional intelligence, it is no longer just a dispensable tool, but a partner that can participate in decision-making.

Redefine the boundaries of work

This interesting case also made me think about a deep question: In the era of AI, where is the boundary between the work of humans and machines? Conventional wisdom holds that machines are good at standardized tasks and humans are good at creative and emotional work. But the capabilities demonstrated by business card robots have demonstrated surprising levels of creativity and emotional intelligence.

Of course, this does not mean that AI will completely replace humans, but it highlights that the human-machine collaboration model will be more profound and complex. The future of work may not be a division of labor between “what humans do and what machines do”, but rather a collaboration of “how humans and machines can collaborate to achieve the best results.”

Cost structure reorganization—the efficiency revolution brought by AI

Multi-dimensional efficiency improvement

Through the application of a series of AI tools, Chengxi Information has achieved all-round efficiency improvements. Several key indicators mentioned by Chairman Huang are impressive:

Improved personnel stability: employee retention time is extended by half a year, which means significant reductions in recruitment and training costs. More importantly, the improvement of team stability has brought about stable service quality, and customer satisfaction has also improved accordingly.

Double the training efficiency: The AI ​​simulation training system greatly shortens the induction period for new employees and makes the training effect more standardized. What originally required one-on-one personalized guidance from senior trainers can now be replicated on a large scale through the AI ​​system.

Reduced quality control costs: Full recording analysis replaces manual sampling inspection, which is not only lower cost, but also has wider coverage and more timely feedback.

Improved decision-making efficiency: From recruitment and selection to daily management, the data provided by AI makes decision-making more scientific and faster.

From linear costs to achieving exponential benefits

Traditional business expansion often faces the problem of linear cost growth: when business volume doubles, the manpower and costs required also double. But the characteristic of AI tools is that they only need to be developed once and can be copied and used indefinitely.

This characteristic allows Chengxi Information to avoid the fate of cost increasing simultaneously during the process of business expansion. The same AI training system can serve employees at various locations in the north, central and south at the same time; the same quality control system can analyze thousands of phone calls; the same recruitment system can evaluate any number of resumes.

I think of the concept of “economies of scale” in economics, but AI brings a more extreme scale effect: the marginal cost is close to zero, but the marginal benefit may be huge.

Cumulative Effect of Competitive Advantage

What’s more, these improvements are not a one-time event but are cumulative. This means that every use of AI will generate data, and the accumulation and iteration of this data will make AI smarter, thus forming a positive cycle.

Through early AI applications, Chengxi Information not only reduced current operating costs, but more importantly, established data and experience advantages. While competitors are still hesitant to import AI, they have already built moats that are difficult to cross with the help of AI.

This also reminds me of the “compound interest effect” in investment science: certain seemingly small advantages often produce huge differences through the accumulation of time. In the AI ​​era, this compounding effect may be even more pronounced.

Transformation mentality—ideas first, tools follow

Changing mentality from fear to embrace

During the whole sharing, what touched me the most was Chairman Huang’s change of mentality. Facing the possible impact of AI, most people’s first reaction is fear and resistance, but he chose to try it out of curiosity.

“If you usually read newspapers and TV, everyone tells you that AI is coming and will be the first to kill your company. Are you nervous? You must be nervous. Yes, I am nervous too. But being nervous alone is not enough, so the first thing I think about is… what should we do?” Chairman Huang narrated this mental journey, which also made the guests present understand the difficulty of corporate transformation.

Nervousness and anxiety are both normal reactions, but the key lies in the choice after being nervous: should you let fear dominate your actions, or should you turn anxiety into motivation? Obviously, Chairman Huang chose to face it bravely.

From tool thinking to system thinking

During digital transformation, many companies regard AI as a mere tool and expect that all problems can be solved by purchasing a certain software or system. However, it is not difficult to find from the experience of Chengxi Information that truly successful AI transformation is systematic and needs to be promoted from multiple dimensions such as process design, organizational structure, talent training and cultural construction. Chairman Huang mentioned: “In our company, from making reports, writing documents, designing processes, to the interviews, training and quality control just mentioned…all the processes are related to AI. Even when I make strategies, I will discuss them with AI.” It is not difficult to guess that Cheng Xi Information not only uses a few AI tools, but has built a complete AI ecosystem within the group.

The importance of this kind of systems thinking is that only when AI is truly integrated into all aspects of corporate operations can it achieve maximum benefits. Simply using a single or a few AI tools often has limited effects, and may even produce negative effects because they do not match existing processes.

From passive learning to active experimentation

In the past, we were accustomed to learning theory first and then applying it to practice. But in the age of AI, this model may no longer apply. Chairman Huang’s approach is to learn by doing and explore in practice.

Obviously, Chengxi Information Group did not wait until it fully understood the principles of AI before starting to apply it. Instead, it directly purchased mature AI services, learned through use, and improved while learning. This experimental learning method allows them to quickly keep up with the pace of technological development.

I think of the concept of “minimum viable product” that many people in the entrepreneurial field talk about: instead of pursuing a perfect plan, it is better to quickly prototype and make iterative improvements based on market feedback. This kind of thinking also applies to AI transformation.

From personal ability to organizational ability

More importantly, AI transformation is not only a technical issue, but also an organizational change issue. The success of Chengxi Information Group lies not only in their introduction of advanced AI tools, but also in the fact that the entire organization has AI thinking and literacy.

From top managers to front-line employees, and from technology departments to business units, everyone is starting to learn how to collaborate with AI. This kind of organizational-level capability building can be said to be the key to the success of AI transformation.

Chairman Huang not only attaches great importance to talent training, but also mentioned some available resources: “If your company needs training in this area, as long as it is a company with less than 30 people, the Ministry of Economic Affairs will provide subsidies.”

The future is now—become a transformer rather than a bystander

New competitive logic in the AI era

Through the personal statement of Chairman Huang of Chengxi Information Group, we can clearly see that the competition logic in the AI era has fundamentally changed. Competition in the past may have relied more on relatively fixed factors such as resource endowment, geographical location and historical accumulation. But now in the AI ​​era, the most important competitive factors are learning ability, adaptation speed and innovation energy.

Having said that, this change also provides many small and medium-sized enterprises with opportunities to overtake in corners. Even traditional labor-intensive industries may achieve efficiency breakthroughs and model innovation through the application of various AIs. The key lies in whether decision makers have the courage and wisdom to embrace these unknown opportunities and challenges.

The transition from survival to leadership

The transformation process of Chengxi Information Group can be said to reflect the change from passive response to active leadership. Initially, they were forced to transform because the industry was predicted to be replaced by AI; but now, they have become leaders in AI applications in the industry, and have even begun to export experience and services externally.

In my opinion, this role reversal is of great significance: AI transformation can not only help companies survive changes, but also help companies gain a leading edge in the new competitive landscape.

The possibility of inclusive AI

What particularly touched me was that Chairman Huang emphasized the accessibility of AI tools many times in his sharing. He mentioned that ChatGPT’s monthly fee is only US$20 (approximately NT$600), emphasizing that it is “really cheap.” He also introduced the government’s subsidy policy to encourage more small and medium-sized enterprises to participate in AI learning and application.

It is true that AI should not be just a patent for large companies, but should become a technology that benefits everyone. When the barriers to using AI tools continue to lower and costs continue to drop, every business or person has the opportunity to become a beneficiary of the AI ​​era.

Urgency of time window

However, opportunities don’t exist forever. As Chairman Huang said, in every technological revolution, the order of wealth will be reshuffled. Those who can take action at the early stage of change can often gain the greatest benefits; on the other hand, those who are still waiting and watching may miss the best opportunity for transformation.

Today is a critical period for the popularization of AI. The technology is mature and the cost is very low, but the market is not yet completely saturated. This time may not be too long, and if you miss it, it may be difficult to have the same opportunity again.

Everyone should be a transformer

Thinking revolution beyond technology

After listening to Chairman Huang Shijun’s sharing, my biggest feeling is not to lament the power of AI technology, but to admire their change in thinking. When facing uncertainty and challenges, choose to take the initiative rather than wait passively; when facing new technologies, choose to embrace learning instead of resisting rejection; when facing changes, choose to be a leader rather than a follower.

The value of this way of thinking goes far beyond mastering AI technology. It embodies a future-oriented survival philosophy: In an era of rapid change, the only constant is change itself, and the ability to adapt to change and lead change is the most important core competitiveness.

Demonstration effect from individuals to industries

The transformation practice of Chengxi Information Group undoubtedly provides valuable reference for the entire service industry. It proves that even industries that are predicted to be easily replaced by AI can turn around by proactively introducing AI applications. After listening to this lecture, I got a lot of inspiration. This demonstration effect is also of great significance. I believe it will inspire more companies to invest in AI transformation.

Many people always think that AI is a patent reserved for high-tech companies and requires a lot of capital and professional talents. However, judging from the introduction experience of Chengxi Information Group, the key to AI application lies not in the complexity of the technology, but in the openness of thinking and decisiveness of action.

Seizing the opportunities of the times

We are at a historic turning point. The development of AI technology provides every industry, every enterprise and even every person with the opportunity to redefine themselves. However, there is no guarantee that this kind of opportunity will definitely succeed. It requires us to take the initiative to identify, grasp and practice it.

“Even if the industry you are in may not be that dangerous, you must still pay attention to the vicissitudes of the times.” Chairman Huang’s words are worth pondering for everyone. This means that even if your industry has not been directly impacted by AI for the time being, it does not mean that you can sit back and relax. Because the impact of AI is all-encompassing, no industry can remain immune.

Actions speak louder than anything

After listening to this lecture, my most obvious realization is: in the AI era, the biggest risk is not doing something wrong, but doing nothing.

After listening to Chairman Huang’s sharing, I feel that the success of Cheng Xi Information Group mainly comes from their ability to act. They did not wait until AI technology was fully mature before importing it, nor did they wait until there was a perfect application solution on the market before starting research. Instead, they started trying amid uncertainty, accumulated experience in the attempt, and established advantages through repeated setbacks.

For each of us, the time to act is now. Whether you are a business manager, a technical worker, a service worker, or any other person, you should start paying attention to AI, learn AI, and apply AI. Because in this era of change, the biggest cost is not the cost of learning, but the cost of not learning.

Having said that, when we are in the AI ​​era, we cannot solve various problems just by being afraid or resisting. Only by actively participating can we reap the fruits of success. This is not only for the development of enterprises or individuals, but also to promote the progress of the entire society.

The future of AI must be created by everyone. Let’s work together to make the future better!

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