How to Make a Successful Artificial Intelligence Business project
In the era of Internet and mobile Internet entrepreneurship, many business projects have been streamlined. Big giants like Google, Amazon, and Microsoft have all launched their own artificial intelligence infrastructure, APIs and open source frameworks, including computer vision, speech, language, knowledge graph, search and other categories. Some of the frontier areas of artificial intelligence technology are unmanned retail stores whose current applications are based on artificial intelligence and big data in the US retail industry.
“Retail stores” are the most important part of contact with consumers, and what is needed behind “Nobody” is the overall optimization of the entire chain based on data. The emergence of unmanned retail today reflects the current technological progress, and this new way of meeting consumer needs has emerged. Amazon launched Amazon Go, and Alibaba also launched the “Tao Coffee” unmanned retail store before. Computer vision, machine learning, artificial intelligence and other black technologies, as well as “black technologies” that integrate portrait recognition, product recognition, self-service payment, big data analysis, IOT (Internet of Things), and blockchain behind “Buy Now” The system has become the technical support for unmanned stores.
In future, artificial intelligence will be helpful not only in online business but it will also facilitate in the offline business scenarios. Therefore, new retail is actually a combination of online and offline scenarios with big data and AI to jointly promote the application of the ecosystem. “
Human Intelligence vs Artificial Intelligence
Artificial intelligence is different from the human brain. It can be a discontinuous and intermittent digital reflection mode. If our company keeps purchasing and does not know the needs of customers, there will be a large backlog of inventory; for data processing, artificial intelligence is a modular program. The calculation method of the transformation, whenever you want to extract data, you must search from the module. For example, in the United States, some operating departments are sometimes unwilling to share their data with the financial department because they are afraid of getting involved in a conflict of interests. But in fact, the financial department must know these data, otherwise they will allocate funds and the calculation and investment will not be very accurate. The two departments coordinate with each other like the left and right brains of a person. Only when we design a set of plans and implement them will it be more efficient.
The application of artificial intelligence was born in 1956 to a long time after it was born. The processing and integration of the collected data was very backward, and it was basically completed by the human brain. It was not until 2000 until now, with the gradual development of computer software and hardware. The development is mature, all aspects of big data are gradually being prepared, coupled with the development of other applications, artificial intelligence suddenly broke out.
People say that artificial intelligence can do a lot of things, but have you ever thought about what artificial intelligence can’t do? Artificial intelligence can never imitate human stupidity, so development is to make our business smarter and smarter the foundation of artificial intelligence. The retail industry will face the post-90s generation in the future. In the future, 40%-70% of the population will have more and more personal needs based on digitalization. New retail must be a scene of offline and online integration based on big data. While improving the user experience, it is also for more precise marketing. Promote the application of the ecosystem together online and offline.
In fact, artificial intelligence projects are not necessarily big. More important is how you use them. For example, based on a person’s usual buying habits, you can recommend some other similar products, and the computer will automatically help you organize what you need , And then confirm, without affecting sales because of the current status of the shopping guide.
Application of artificial intelligence in U.S. retail catering
Retail industry: operating big data AI technology can realize the optimal plan of purchasing and inventory. Provide personalized service Chabot services based on customer big data. Wal-Mart/Amazon’s marketing model based on big data AI provides company executives with accurate marketing forecasts and customer service activities.
Catering industry: Giants like Starbucks/Burger King, have launched a new Mobile Chat app with “AI Interaction” to assist in customer orders. McDonald’s uses Microsoft’s AI voice recognition system, which makes it more convenient for driving customers to place orders and pick up meals. Dunkin’ Donuts uses big data AI technology to build smart-driven businesses, from mobile apps to AI customer demand prediction models, and significantly transforms its operating model. According to your habits, you already know what you need even before you order, and it has been prepared for you, just because of your previous repurchase rates. This is the precision marketing of artificial intelligence. The most important thing is that we should treat artificial intelligence as a tool instead of replacing our current business. This should be recognized by the company. It must be based on the business to find technology suitable for the company, and use artificial intelligence to solve the company’s pain points and Promote business.
How to make a successful artificial intelligence project
1. Enterprise project decision-makers fully understand the “capability” and “inability” of AI for the company’s specific business;
2. Regard artificial intelligence as a work to solve business pain points and promote business rather than hype;
3. Identify the company’s pain points and problems that need to be resolved, and evaluate the feasibility of AI solutions;
4. Have a detailed understanding of all the technologies, talents and requirements needed to implement artificial intelligence projects;
5. Formulate a reasonable budget and detailed product/service innovation plan based on artificial intelligence projects;
6. Choose the entry point that is easy to break through from all business pain points, determine the corresponding AI technology and algorithm, fast iterative research and development, rapid trial and error, and steadily promote artificial intelligence projects;
7. By testing small batch data samples, verify the AI project’s algorithm research and effect at this entry point, whether there is any promotion value, and adjust the initial algorithm and analysis methods according to the test results;
8. Continue trial and error iterative research and development, adjust product and service design, and gradually expand the scope of application to meet project requirements.
How to measure the success of an artificial intelligence project
1. The ROI forecast of AI projects must have a strategic impact significantly higher than the impact of liquidity within 1-3 years, or both the strategic impact and the impact of liquidity are positive;
2. AI projects should play a significant role in promoting the transformation and value of the entire enterprise’s business;
3. The AI project must be able to meet and improve the overall KPI indicators or core indicators;
4. AI projects should significantly improve the level of enterprise intelligence and decision-making;
5. The completion of the AI project should motivate the entire enterprise to try innovation, tolerate trial and error failure, and establish a continuous innovation mechanism.
How to treat unmanned vending stores
The purpose of the unmanned store is basically to sell and sell things, not to be an unmanned store and to hype. In March 2017, Amazon temporarily abandoned unmanned vending stores due to “technical reasons”; in August 2017, Alibaba’s Hema fresh store was also complained by customers for not accepting cash, so the reality of investing in unmanned stores still needs to be considered. Judging whether an unmanned vending store has practical significance depends on several factors:
1. Whether the labor and customer experience saved by big data and artificial intelligence in unmanned vending stores can achieve the expected ROI return and customer satisfaction;
2. Whether big data and artificial intelligence technology themselves are stable in the operation of unmanned vending stores;
3. What is the profit forecast and actual income of the unmanned vending shop in 1-2 years?
4. Is the current unmanned vending shop established for capital speculation?
How to do artificial intelligence in world today
1. Today, when technologies such as big data, artificial intelligence, and the Internet of Things, represented by the fourth industrial revolution, have begun to be widely used, adapting and participating in this megatrend is related to the transformation and life and death of commercial enterprises, and corporate executives have to check.
2. Investing in AI-related projects must take the business needs and pain points as the starting point, do a good job of feasibility studies, choose the right entry point, start from the project that is easy to succeed, choose the right team, and obtain high-level support and consensus.
3. Set up reasonable project success expectations and measurement criteria, and use this as the goal and means of project success.
4. Bold trial-and-error adjustments in iterations, and steady progress in the project.
5. Learn the lessons of artificial intelligence projects committed by Western commercial companies.