In brief

In brief

  • A decade ago, deep learning marked the breakthrough in computer vision and tech players started to invest in autonomous driving (AD) technology.
  • Most observers expected a quick market shakeout with new entrants taking the lead.
  • After 10 years of increasing investments, however, it is clear that deep learning alone will not be able to make full AD possible.
  • Business leaders need to better understand these technical ramifications—at least on a high level—to make value-driven decisions.


Wrangling a late-blooming disruptor

While Autonomous Driving (AD) has not lived up to the promise of its most ardent promoters, it still has big transformational potential. As it looks today, the market will be shaped by evolutionary approaches, not a big bang disruption. Evolution is in line with the strengths of established vehicle manufacturers rather than disruptive tech startups—if they play their cards right.

Four trends in the automotive market are forcing original equipment manufacturers (OEMs) to rethink their products and business models: Connectivity, Autonomous Driving (AD), Shared Mobility and Electrification.

Connectivity

Connectivity is considered the prerequisite for everything from new business models to customer experiences.

Autonomous Driving (AD)

Technical progress is taking longer and investments are higher than previously expected for level 4 and level 5 autonomy.

Shared Mobility

Cautious consumer behavior and social distancing practices have a disruptive impact on shared mobility in the short and medium term.

Electrification

Core drivers of electric vehicle (EV) adoption continue to be purchase incentives and charging infrastructure availability.

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Out of all these megatrends, arguably, AD—combined with car sharing—has the most far-reaching potential to substantially disrupt the traditional automotive business model.

“AD has a lot of uncertainties coming from sensing or sensor data. That’s the biggest flaw.”

— Leading Semiconductor Company, Product Manager

If unrestricted driverless cars were to become a reality, the current car ownership model would lose commercial viability. Similar to the market disruption that online streaming caused the video rental business, today’s ownership model would endure a significant shakeup. In mobility’s case, ownership of individual assets would be replaced by access to managed devices. A fleet of autonomous vehicles could permanently circle through metropolitan areas, picking up and dropping off passengers or goods as needed.

However, full AD (the kind envisioned in futuristic books and movies) is still a long way from becoming a reality—if it ever happens. Daunted by complex technical and regulatory challenges—not to mention staggering investment needs—many OEMs have scaled back research and development in recent years. At the same time, abandoning AD altogether risks misreading the market and missing out on a strategic opportunity. This situation presents complications. While full AD is far off, the disruptive potential can still unleash its power of “creative destruction” in smaller increments by reinventing selected operational areas like logistics or valet parking. Such innovations could completely reshuffle these market segments within a few years, and vehicle manufacturers would lose their grip on monetization if their products could not cater to the right use cases.

Restarting the race for incumbent OEMs

It is highly likely that the established, ownership-based automotive business model will remain intact, especially without fundamentally eliminating the human factor from the driving process. There will arguably be no access-based business model disruption in the foreseeable future. This forecast also applies to the market outlook for autonomous vehicles in terms of yearly new vehicle sales. While vehicle sales are likely to grow over the coming decades, it’s anticipated that vehicles equipped with advanced driver assistance features (Level 1 and Level 2) will take the majority share.

Today, the market share of Level 2 vehicles is only about 15%. In the next generation, every fourth new vehicle sold will be capable of Level 2 driving. By 2030, Level 2 cars are expected to comprise 60% of the market. At the same time, Level 3 and Level 4 vehicles will only account for a cumulated share of about 5% of the total market by 2030. This disparity in market share is because Level 3 functionality is largely restricted to the highest premium vehicle space, which is relatively small. Beyond 2030, the advanced technology will spread into lower market segments, helping commoditize the respective hardware and software technologies.

15%

Current market share of Level 2 vehicles.

1OUT OF4

New vehicles sold in the next generation will be capable of Level 2 driving.

60%

Level 2 vehicle market share by 2030.

5%

Level 3 and 4 vehicle market share by 2030.

“Standalone AI technology will not make real AD come true. Infrastructure is needed—otherwise it cannot be 100% safe and intelligent. Even L3 or L4 is very hard to be achieved in high degrees of complexity like high speed.”

— German Automotive Supplier, Management Member

Imperatives for incumbent OEMs

The road towards software-defined vehicles will not end in a major business model disruption for incumbent OEMs, but a process disruption that will turn current organizational and technological structures upside down. Manufacturers will have to transform themselves into software companies, building up data knowhow and enabling closed loop vehicle updating processes. Mastering this challenge can hardly be achieved alone. This is one reason for OEMs to form alliances and establish partnerships—so they can share development efforts and build up specific capabilities along their transformational journey.

There are five essential, practical measures OEMs can take—and principles to observe—to start down the road toward autonomy:

AI

Start investing iteratively in AI.

Software-defined

Get the preconditions right by becoming software-defined.

Fleet analytics

Use fleet analytics to develop relevant big data and edge cases.

AD

Actively develop and define the AD market based on the insights from analytics, big data and edge cases.

Partnerships

Form partnerships to help speed time to market and reliability.

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The AD market will likely develop in small increments—drivers are not seeking higher levels of autonomous driving. On the contrary, the consumer climate ranges from deep skepticism to outright opposition. Car manufacturers will have to work to actively develop the market, which is much easier by deploying driver-assistant systems with incrementally increasing capabilities.

About the Authors

Axel Schmidt

Senior Managing Director – Global Industry Sector Lead Automotive


Gabriel Seiberth

Managing Director – Digital Automotive, Industry X and Innovation

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