“The impact of artificial intelligence is immense, and it is likely the greatest invention since the invention of electricity, as the world is different with electricity and without it, just as it is with AI and without AI.”
This is the viewpoint presented by Dr. Zhang Weining, Associate Professor and Academic Director of the MBA program at Cheung Kong Graduate School of Business, during the public lecture on “AI-Driven Business Transformation”. So:
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What value does AI actually have?
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What steps must businesses take to truly implement AI?
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What will the relationship between AI and humans look like?
Today, I would like to share the highlights from this public lecture, hoping it can provide you with some references.
01
What Value Does AI Actually Have?
AI has three core characteristics that play a fundamental role in organizational transformation.
Firstly, AI is interdisciplinary. This means AI can handle tasks across multiple fields, whether in marketing, human resources, or programming. This interdisciplinary characteristic breaks traditional job boundaries, leading to profound changes in internal process design. The originally specialized divisions of labor have become more flexible and efficient due to AI’s involvement, making process integration possible. For example, AI agents, such as intelligent products, are typical representatives of process-oriented AI, capable of executing complex process-level tasks and significantly enhancing work efficiency.
Secondly, AI can provide personalized responses. Among the seemingly contradictory elements of cost, scale, and personalization, AI finds a balance. It can deliver large-scale and personalized services at a low cost. This means everyone can receive rapid responses and precise answers from AI, and each answer comes at the same cost, which is difficult for humans to achieve. This capability allows organizations to provide personalized services without being constrained by cost and scale, offering more possibilities for innovation.
Finally, AI has the characteristic of rapid response. This rapid response is not limited to interactions under standardized conditions but can also be achieved under personalized conditions. This changes how we interact with machines, enabling organizations to respond more quickly to market changes and customer needs. Under the organizational principle of pursuing efficiency, AI’s rapid response capability addresses efficiency issues under uncertain conditions while also reducing costs. Therefore, in the pursuit of efficiency and cost optimization, AI is undoubtedly a highly valuable tool.
This value may manifest in two major systems:
1. Dialogue Systems
2. Operational Systems
Dialogue Systems: Many companies currently introducing systems like GPT and Wenxin Yiyan mainly focus on “dialogue systems”. These systems execute tasks by receiving commands, such as Stable Diffusion, which can generate corresponding outputs based on input information. However, when using such dialogue systems, we must pay attention to the knowledge ratio issue, which is the integration of human knowledge with machine knowledge.
For instance, with ChatGPT, to obtain an ideal answer, one usually needs to provide detailed background information, requirements, and output formats. This process requires not only machine intelligence but also a high level of knowledge and experience from humans. Therefore, I believe the current model leans more towards human + AI rather than AI + human.
As technology continues to develop, the relationships within organizations will gradually shift towards human-machine collaboration. We need to clarify the roles and positions of machines and humans in work to effectively leverage each other’s strengths. In the past, the core of organizational management was the relationships, communication, and supervision between people, but in the future, human-machine collaboration will be key to driving efficient organizational operations.
In the future, machines may become the most critical productivity. The relationship between humans and machines can be summarized in two models:
1. Human + AI
2. AI + Human
In the human + AI model, human knowledge accounts for a large proportion, with machines assisting humans in completing tasks, as existing dialogue systems rely on human knowledge input. In the AI + human model, machines possess vast amounts of information, constructing company-specific knowledge bases, allowing machines to understand the company better than ordinary employees.
Furthermore, we are developing operational systems, process-oriented AI systems.
This means integrating multiple AI capabilities into a single process, such as one-click generation of PPTs, marketing plans, etc. Such integrated products can significantly improve work efficiency.
If AI can connect to systems like ERP and SAP, it can directly analyze historical sales data and automatically formulate marketing plans. This integrated product acts like an intelligent “operational system,” capable of greatly enhancing work efficiency.
02
What Steps Must Businesses Take to Truly Implement AI?
When introducing AI, businesses need to go through three stages. Understanding how to truly leverage AI and planning its roadmap is crucial.
Step One: Access.
First, businesses need to achieve workstation-level access, ensuring that every employee can easily use AI systems like GPT or Wenxin Yiyan. However, mere access is not enough; the real challenge lies in how to enable employees to fully utilize these tools. We have found that many companies, although they have introduced AI systems, have very low usage rates, which is undoubtedly a waste of resources.
Step Two: Training.
Training is key to enhancing the effectiveness of AI usage. This includes teaching employees how to ask effective questions and fostering their deep understanding of business logic. In traditional work modes, the boss is responsible for posing questions, employees provide answers, and the boss selects answers; however, in the AI era, every employee needs to be capable of asking good questions and selecting the best answers. Employees ask questions, AI provides answers, and then employees select the best answer. To ask good questions and choose good answers, employees need a comprehensive understanding of the entire business logic; those who focus only on their part of the business without a global perspective cannot identify truly beneficial answers for the company.
Step Three: Establishing an “AI-First” Corporate Culture.
Promoting an “AI-first” approach means encouraging employees to seek AI assistance first when facing problems, as AI is backed by a vast database, and its knowledge reserves are often superior to those of employees. Therefore, asking AI first can greatly enhance efficiency. Employees should focus their time and attention on asking the right questions and selecting the answers provided by AI.
In summary, accessing AI is just the starting point of digital transformation; the real challenge lies in how to effectively utilize these tools to enhance the competitiveness and innovative capacity of the enterprise. This requires us to think and work on multiple levels, including technology, training, and culture.
Conclusion
The impact of artificial intelligence is immense, and it is likely the greatest invention since the invention of electricity, as the world is different with electricity and without it, just as it is with AI and without AI. Moreover, as AI is presented in the form of a brain, we will see more and more robots entering our lives, production, and various scenarios.
Students often ask what the future will hold, but we dare not predict what will happen in five years, as technological development is rapid and full of variables; ten years is even more unpredictable. However, currently, we are like in a newbie protection period in a game, where the government still aims to protect employment, but how long this protection period will last is still unknown. For businesses, efficiency and cost are key; if they can improve efficiency and reduce costs, they will undoubtedly adopt new methods, or they will fall behind their competitors.
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