Tesla Innovation Strategy
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Introduction
Tesla Inc. is an American electric-automobile manufacturer that was founded in 2003 by Martin Eberhard and Marc Tarpenning. The company was developed with the goal of developing electric vehicles, and the first car was released in 2008 when the Tesla Roadster, the first electric sports car, was created. Tesla has also developed other efficient vehicles such as the Tesla Model S that has become one of the best-selling plug-in electric vehicles. Besides, it is critical to note that Tesla has critically invested in designing, developing, and manufacturing other electric cars such as the batteries. Most importantly, techno9logy has also been integrated into vehicle service centers and supercharger stations. Also, Tesla has integrated artificial intelligence (AI) and big data, which has made it possible for the company to facilitate a strong customer base. This literature examines how artificial intelligence has become a source of competitive advantage for Tesla and evaluates the opportunities and threats associated with AI.
Product innovation is a crucial strategy for all new technology ventures because the performance of new technologies is often inconclusive. Product innovation strategy is fundamental for new technology ventures because innovation is relatively high-risk area and is also resource consuming (Li and Atuahene-Gima, 2001). For newly founded companies, development and competitiveness is limited by both managerial and financial resources. The success of new technology venture is dependent on various factors such as ability to control environmental turbulence, the use of product innovation strategy and government support. Companies may also use reverse innovations that are aimed t producing simple and affordable products capable for meeting needs and wants for resource-constrained customers. These technologies often appear inferior to existing Western-based solutions because they utilize customary technologies and materials (Zeschky, Widenmayer & Gassmann, 2014). The business models for Western multinational companies are designed address the needs for an average customer with average purchasing power. The research and development structures for companies should reflect and accommodate frugal product innovation based on development process, decision power and the mindset of the company.
Artificial intelligence has played a critical role in making long-lasting electric vehicles batteries that can charge faster and that can last for a long-range. The integration of AI in electric vehicle manufacturing is critical for optimizing the batteries and maximizing the battery's lifespan; this is a clear indication that AI has helped generate energy-efficient systems that are ideal for improving car owners' experience and may also facilitate reuse (Wahab et al., 2008). Additionally, AI helps in the recreation of the energy by making it possible for the car to generate energy upon breaking (Rigas, Ramchurn & Bassiliades, 2015). Other benefits associated with electric vehicles include promoting sustainability by minimizing environmental pollution by reducing pollutants and emissions to the environment.
In highly competitive industries, the underlying drivers that influence company’s profitability are similar and the firm may be required to analyze the industry to determine the forces that can influence the profitability of the business. The Porter’s five forces analysis helped in determining the competitive forces that would influence and threaten a company’s healthy structure (Porter, 2008). The five forces that are likely to influence the shape of industry competition include the treat associated with new entrants, the bargaining power of both suppliers and buyers and the threat of substitute products and services.
Some vehicle manufacturing companies such as Tesla have gone a step further and utilized artificial intelligence in promoting the development of autonomous vehicles. Although AI has been expansively implemented in other industries such as agriculture and the military, the technology has been adopted in the transport industry where the car makers are ensuring that most of the operations that vehicles perform are based on sensor information and artificial intelligence algorithms (Hristozov, 2020). It is critical to note that autonomous vehicles require sophisticated approaches since replacing the cognitive and motor abilities of a human may not be easy (Bayyou, 2019). Thus, the use of AI algorithms that are computationally intensive has helped in the development of practical self-driving cars.
Tesla and other vehicle manufacturing companies that have adopted the development of electric vehicles and autonomous cars that offer seamless connectivity to personalization through the use of artificial intelligence are putting the automotive industry in a state of disruptive transition (Sen, 2018). This technological change has been critical in enabling the auto manufacturers to explore new digital solutions across the different value chains and establish different new efficient models to help the company remain competitive. Tesla is not only focused on building vehicles but is also critical about its innovative models that are aimed at meeting the needs of the hyper-demanding customers. The new generation of automotive products is determined to improve transport network efficiencies and promoting better freedom of car owners and commuters.
However, there are challenges and disadvantages that new technology has brought to electric and autonomous car manufacturers. For example, Tesla may find problems commercializing autonomous vehicles because it becomes difficult to clarify and influence other existing frameworks such as insurance for covering accidents. Additionally, the technological change has also facilitated the need for revising the requirements to hold drivers' licenses; this is critical since the drivers need to be competent in handling the high-technology dependent cars. Further, the new technology may also f...