Autonomous Driving Software and AI in Automotive 2026-2046: Technologies, Markets, Players

This report provides an analysis of the software market for ADAS and autonomous driving software. Topic coverage includes business models, hardware, and software paradigms and trends developing in the market for ADAS and autonomous driving. IDTechEx provides 20-year forecast lines for cars by SAE level, software revenue from robotaxis, and global vehicle ADAS and autonomous driving software, split by region and SAE level. Forecasts are in unit sales and US$.

 

The automotive sector has been a traditionally hardware-centric industry. However, with the transition to software-defined vehicles and software-driven revenue, automotive OEMs and tier-one suppliers have looked to develop technologies to supply into an increasingly competitive market.

 

IDTechEx's report, "Autonomous Driving Software and AI in Automotive 2026-2046: Technologies, Markets, Players", analyzes the software market for ADAS (advanced driver assistance systems) and autonomous driving (AD), providing forecasts of unit sales and yearly market size. Alongside the main software stack for these features, the report also goes into detail on trends seen in the ADAS and AD software market, including the applications of X-by-wire technologies, HD maps, and OTA (over-the-air) updates. The inclusion of more advanced technologies is paramount to the success of higher SAE levels of autonomous driving, whether that is in private vehicles or robotaxis. Robotaxis, by definition, are required to be at least SAE level 4, with IDTechEx forecasting a rapid growth of software-derived revenue from the sector, making it an almost US$1 billion market by 2046, at a CAGR of almost 50%.

 

Adaptive cruise control has been in vehicles for over two decades, with other features such as autonomous emergency braking and lane-keeping assistance following on a few years later. These were enabled with a combination of hardware (such as front-facing cameras, radar, and ultrasonic sensors) and software that allowed the vehicle to maintain a path or intervene where necessary. These features are now commonplace in the majority of new cars and use rule-based algorithms to objectively define the actions required by the vehicle without the driver constantly adjusting.

 

While machine learning methods were used for such features in tasks such as object recognition, the dawn of more advanced ADAS features and L2+ (such as Tesla's FSD) in private vehicles, combined with higher performance requirements, has driven the computing power required up, and increased the applications of deep learning and AI, for both training models and in active driving. IDTechEx forecasts the mature ADAS software market (defined as SAE level 1 to 2+) to continue to dominate the ADAS and AD market as a whole for the next ten years.

 

 

The transition from SAE level 2+ to level 3 is a significant one. While many level 2+ systems have proven popular and, for the most part, effective, level 3 vehicles mean that, in some situations, eyes can be taken off the road. Generally, this would result in the accountability of any accident occurring while level 3 is operational falling onto the manufacturer, not the driver. As a result, the overall reliability, defined by both the hardware and software, has to be much greater. This is reflected in the significantly greater computing power required, the inclusion of more sensors, but also in the software. Performance of such software has increased with the help of AI and machine learning methods such as convolutional neural networks and transformers. It has been stated by major players such as Mobileye that the proportion of software-related revenue increases significantly at higher levels of autonomy.

 

IDTechEx forecasts that in ten years, level 3 cars will become more commonplace on the roads, both in number and in operational areas. As a result, IDTechEx expects that features such as over-the-air (OTA) updates, HD maps, and X-by-wire technologies will gain further traction to accompany this transition. Currently, most OTA updates are for non-safety-critical functions, such as infotainment software. Cybersecurity will be paramount to making sure that vehicles can update and also drive safely without risk of cyberattack. By the late 2030s, IDTechEx expects level 3 and level 4 software to make up the majority of the market for private vehicles.

 

2025 has been a momentous year for robotaxis so far. Market leaders Waymo now have a fleet of over 1,500 vehicles and has expanded its areas of operations to cities such as Phoenix and San Francisco. Baidu Apollo also has an established fleet of over 1,000 cars, while other players such as Wayve, Tesla, and Volkswagen with Mobileye have begun testing and demonstrations. While private vehicles will be able to provide continuous revenue from subscription fees and optional extras, robotaxis are a guaranteed way to gain revenue through daily rides. It should be noted, however, that to IDTechEx's best knowledge, no singular robotaxi service has turned a profit yet, as of June 2025.

 

However, robotaxis are still in an extremely nascent stage. As companies look to scale up to tens of thousands to potentially millions, any small error or delay could prove extremely dangerous. Robotaxis are where IDTechEx expects most companies to develop advanced autonomous driving technology, with deep learning training methods, transformers, and end-to-end software being key drivers to developing and scaling this. If a company can prove the reliability of its level 4 technology, then these capabilities can be translated to lower levels of autonomy in passenger cars.

 

IDTechEx's report, "Autonomous Driving Software and AI in Automotive 2026-2046: Technologies, Markets, Players", provides coverage of both the private car and robotaxi software markets, up to SAE level 4, and forecasts the market for the next twenty years. In its coverage, it has identified key trends and approaches, including end-to-end software, sensor fusion, and the importance of tangential technologies such as steer-by-wire. It analyzes regional regulations for autonomous driving and provides insight into the applications of generative AI in other automotive applications.

This report provides an analysis of the autonomous driving and ADAS software market for both private cars and robotaxis, including:

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