For more than two years, the automotive industry has been talking about four disruptive and mutually reinforcing major trends – autonomous driving, connectivity, electrification and shared mobility. It is expected that these trends will drive the growth of the mobile market and change the rules of the mobile sector. And led to the transformation from traditional technologies to disruptive technologies and innovative business models.
Artificial intelligence (AI) is a key technology for these four trends. For example, automatic driving relies on artificial intelligence because it is the only technology that can reliably and reliably recognize objects around the vehicle. For the other three trends, AI has created There are plenty of opportunities to reduce costs, improve operations, and create new revenue streams. For example, for shared mobile services, artificial intelligence can help optimize pricing by predicting and matching demand and supply. It can also be used to improve maintenance planning and fleet management. Improvements in artificial intelligence will play an important role for auto companies so that they can fund innovation and respond to future trends.
One of the expected results of the four major trends is a significant shift in the industry value pool. This change will have a particularly significant impact on large automotive OEMs and their business models, but its impact will affect the entire industry and other areas. The products and services brought by these trends not only affect the business of all existing and traditional industry participants, but also open up markets for new entrants. Many companies, such as those who previously focused on other industries, are investing heavily in mobile. Trends and low-level technologies. As a result, a new player ecosystem is emerging. New participants will become important partners of traditional car companies. Although automotive OEMs can use the technical expertise of new players to release the potential value of artificial intelligence. , But new players will have access to their share in the automotive and mobile markets. In order to grasp these four trends, OEMs need to invest heavily in each trend and successfully integrate them.
Some of McKinsey’s previous work focused on artificial intelligence in liquidity and industry. The report based on this article continues this effort and draws on multiple methodological insights. First, it provides automotive OEMs with the value of artificial intelligence. Opportunities, covering process, driver or vehicle characteristics, and mobile services are three areas of application. Next, it breaks down and quantifies these opportunities. Finally, the report outlines the strategic actions that OEMs should take to capture AI in the short and long term. Supported value opportunities.
McKinsey's analysis yielded the following key insights:
In the short to medium term, by 2025, there will be a substantial, industry-wide artificial intelligence opportunity globally, which will create approximately $215 billion worth of value annually for global automotive OEMs (see chart below). This is equivalent to nine percentage points of the pre-tax profit of the entire automotive industry, or, theoretically, an average annual increase of about 1.3% in seven years, which is of great value in raising the industry's normal productivity target of about 2% per year. Optimization from the core process of the value chain.
Even in the short term, artificial intelligence can improve the efficiency and cost savings of the entire value chain. It can also generate additional revenue from car sales and aftermarket sales. Most of the value is generated in four core processes. In terms of supply chain management and manufacturing, efficiency has saved 51 billion U.S. dollars, 22 billion U.S. dollars, and 61 billion U.S. dollars, respectively. In terms of marketing and sales, artificial intelligence-based efficiency can both reduce costs and generate revenue. The total value potential of 31 billion U.S. dollars.
Although AI-enabled drivers or vehicle functions and mobile services can generate substantial industry-wide value in the long-term, these will create limited value at the industry level in the short term. However, a single OEM's driver or vehicle functions and Mobile services outperform the competition and gain considerable market share. However, these technological leaders’ gains in market share compare with the risks of those important parts of the customer base that lag behind these functions. It is insignificant.
The four major success factors enable OEMs to prepare for AI transformation and capture the value of artificial intelligence in the short term: Collect and coordinate data from different sources, establish a partner ecosystem, build an artificial intelligence operating system, and establish core AI functionality and An AI team drives the transformation required.
Original equipment manufacturers need to implement pilots to acquire knowledge and gain short-term value to begin the transition. Then, they should establish an artificial intelligence core in order to form a comprehensive view of artificial intelligence across the organization. This will enable OEMs to Expand and introduce an end-to-end transformation to systematically capture the full potential value of artificial intelligence and build capabilities for its long-term strategy to address four disruptive trends.
