AI Is Demolishing the “Moats” of Large Enterprises
When a technology becomes as ubiquitous as air and no one can monopolize it, artificial intelligence is bringing potential shocks to the business world. Once upon a time, a large enterprise scale and abundant resources were symbols of competitiveness, but now the power of AI is quietly changing all this.
In the past decade, the global economic landscape has changed with technological development. Now, the widespread application of AI has set off a subversive storm. Although large enterprises have more resources to deploy AI, they may not necessarily truly benefit.
1. Accumulated resources cannot withstand the impact of flexible innovation.
“Scale effect” used to be the key to the success of large enterprises. But now, the core of AI is information processing ability and innovative flexibility. Although large enterprises have a large amount of data, if it is not analyzed and utilized, it is just unprocessed ore and may even become a burden. Small enterprises, relying on flexible innovation, can quickly use AI to achieve deep data analysis and business process optimization and become “dark horses”. For example, traditional retail giant Walmart has fallen into difficulties under the impact of Internet e-commerce, while Amazon and Taobao have risen顺势. Now they are facing the challenge of the rise of independent stations. The independent station play is more flexible, the use of AI is more radical, and the traffic acquisition is more accurate. This flexibility will give rise to explosive companies in retail sub-sectors.
2. The management structure of large enterprises is difficult to adapt to the rapid changes brought about by AI.
The complex management hierarchy and strict decision-making process of large enterprises make every decision require layers of approval, making it difficult to respond quickly to market changes. And AI has the characteristics of rapid feedback and iteration. If enterprises cannot respond quickly, they will lose innovation opportunities and their competitiveness will decline. For example, when traditional automotive giants face electric vehicles and autonomous driving technologies, their pace of adaptation is far behind that of Tesla. Tesla’s success lies not only in innovative electric technologies, but also in the rapid iterative optimization of production processes and AI-driven autonomous driving technologies and rapid response services. In the financial industry, small fintech companies, with AI’s precision services and rapid decision-making, have amplified their capabilities in customer acquisition and customer satisfaction optimization and quickly seized market share.
3. Personalization and customization will surpass mass production.
AI can provide users with highly personalized experiences based on big data, subverting the traditional enterprise competition model based on mass production. Take clothing retail as an example. Traditional retailers rely on mass production to reduce costs and rely on advertising promotions to attract consumers, but they cannot meet the personalized market demand. The powerful data analysis and personalized recommendation system of AI can provide accurate product recommendations and customization services according to users’ historical behaviors and interest preferences. SHEIN has won consumers and seized market share in Europe and America by relying on this logic. AI will enable this logic to be achieved at lower cost and with better results and empower more retail sub-sectors. Small and flexible companies can compete with traditional large enterprises through rapid AI deployment and accurate data analysis, while large enterprises find it difficult to quickly adapt to market changes.
4. The innovation anxiety of large enterprises and the difficulty of implementing AI.
Large enterprises have abundant resources, but it is not easy to implement AI and innovate. Traditional large enterprises have innovation anxiety because innovation means risk and uncertainty. Many large companies are still in the experimental stage in AI application. Although they have invested a lot of funds, due to the lack of agility and innovation culture, they can only improve traditional businesses and it is difficult to achieve breakthrough innovations. Startups can adopt a more radical strategy and quickly seize the technological dividend and occupy the market. For example, in the healthcare industry, traditional medical institutions are slow to innovate and need to balance medical safety and technological risks, while startups focusing on AI healthcare can quickly test in marginal areas and break through traditional industry barriers. Large enterprises are thinking about layoffs to cut costs and increase efficiency. In the future, with just a few people and AI doing things, small companies may have a greater chance of winning.
5. How can small enterprises stage a comeback with the help of AI?
Small enterprises, with their flexibility and rapid execution ability, can effectively stage a comeback with the help of AI technology. Different from the庞大体制 and processes of large enterprises, the advantage of small enterprises lies in being able to quickly adjust strategies, quickly try and error and implement new technology applications, and seize market opportunities. Through AI, small enterprises can not only improve efficiency, but also accurately tap market demands, flexibly adjust products or services, and meet the needs of specific user groups. Through in-depth data analysis, AI helps them discover market gaps overlooked by large enterprises and provide personalized services or product customization. For example, in the field of e-commerce, small online merchants optimize personalized recommendations and pricing strategies through AI and quickly respond to changes in consumer demands. With AI-driven automated marketing
