ENG
Robotic Process Automation (RPA) in Automotive Market: Key Growth Potential and Forecast Analysis (2024-2030) by Type, Solutions, and Region
Robotic Process Automation (RPA) in Automotive Market size was valued at US$ 3.51 Billion in 2023 and the total Robotic Process Automation (RPA) in Automotive Market revenue is expected to grow at 32.6% through 2024 to 2030, reaching nearly US$ 25.32 Billion.
Format : PDF | Report ID : SMR_493
Robotic Process Automation (RPA) in Automotive Market Overview:
Automation has end up synonymous with the car industry. Nowadays, business robots carry out a extensive type of meeting-line obligations such as welding, wheel mounting, windshield installation, painting, etc. With the mass adoption of those automation tools, car producers at the moment are capable of produce heaps of automobiles in step with day even as reducing operational costs, growing reliability, and releasing up employees from appearing labor-in depth obligations. However, the scope of operations that car organizations want to carry out is going manner past the meeting line. Nowadays, businesses want to manipulate a myriad of different operations such as provider community management, price processing, stock management, coverage claims processing, and more. This is in which robot manner automation (RPA) comes into play. Robotic Process Automation (RPA) in automotive market is expected to register CAGR of 17.5% during the forecast period.
-in-Automotive-Industry.PNG)
To get more Insights: Request Free Sample Report
Robotic Process Automation (RPA) in Automotive Market Dynamics:
RPA is a way to automate business processes through robots that perform tasks based on pre-programmed rule sets. With optical character recognition, keystrokes, and application integration, RPA can perform a wide range of previously manual tasks. RPA continues to prove itself in many areas of the automotive industry. Much of the repetitive and time-consuming work that is prone to human error can be done by RPA tools. Their most appreciated advantage is ease of implementation and quick return on investment. While the possibilities of rule-based RPA are not endless, businesses can expand their reach by augmenting RPA with machine learning to harness data-driven decision making. Intelligent Process Automation (IPA) is the next logical step for companies looking to transform into a digital business: The economic pressure created by the COVID19 pandemic has increased the demand for RPA consulting services with the opportunity to increase process efficiency and reduce costs.
Increasing Inventory management Needs:
Streamlined inventory control is at the heart of effective supply chain management. Traditionally, automakers have hired custodians to make sure their inventory is in line with demand. In essence, it is a manual work with low added value, which is also very prone to human error. With the growing adoption of industrial IoT and abundant customer and partner data at their fingertips, auto manufacturers can maintain sufficient inventory balance by integrating RPA.
For example, a Fortune 500 auto company asked demand planners to manually enter their estimates into an ERP system. The organization decided to implement a bot, developed by Birlasoft that now extracts key data points from demand planners' emails and updates safety levels in the warehouse without any intervention. Which is human. To go further, other tasks of these needs planners can also be automated. Although not possible with the rule-based approach, a simple ML algorithm can accurately compute the safety margin.
Auto Insurance industry:
In the automobile insurance industry, the speed and accuracy of claim processing are important factors in customer satisfaction. Customer expectations are rising and optimized billing is paramount to the success of the business as a whole. However, manual billing is a very tedious and error-prone task. Adjusters typically need to collect relevant data from various sources, analyze it, and transfer it to the policyholder's digital file. In this case, reformatting and transferring data requires repetitive actions, so RPA can provide additional benefits to document management.
Today, thanks to the pervasive digitization, it has become common practice to file an insurance claim immediately after an incident has occurred. In many cases, towing is necessary. Since the majority of auto insurance companies pay for roadside assistance, speed of handling becomes very important. However, by the time employees process the data themselves, transfer it to a contracted auto mechanic company, and the trailer arrives at the scene of the accident, the satisfaction of the insured is certain. RPA can cover this entire process while improving the customer experience, saving man-hours and ensuring accurate data entry.
Similarly, RPA can speed up underwriting. For example, auto insurers often need to browse public databases to check claimants` criminal records. RPA can autonomously access these records and transfer data to the company`s internal system. However, despite the auto insurance industry is seemingly perfect for RPA, it`s critical to note that a bot will be stuck if there are even minor deviations from the preprogrammed process. For example, if some data from public records is moved to a different page, RPA wouldn`t be able to complete the task. That is why adopting strong governance practices is crucial to the long-term success of RPA. On the other hand, if an RPA solution needs to be reconfigured multiple times due to changes in the external system layout, augmenting RPA with machine learning might be a better solution.
Robotic Process Automation (RPA) in Automotive Market Segmentation:
Vehicle Financing is dominating the market in terms of user base:
Automation also helps to raise money for cars. Today, the vast majority of car lenders use complex legacy systems that often require tedious manual processes. Similar changes can be expected in the car loan industry, just as car manufacturing has become unimaginable without automation of assembly lines. Car loan offers are very similar, so it is the quality of service and the speed of the company's operations that help to gain a competitive advantage. RPA is often seen as a tool for automating iterative back office processes, but in a broader sense it can also improve the customer and seller experience.
To execute specific procedures, auto lenders frequently need to access many siloed systems and databases at the same time. While merging these key systems into one is the most logical solution, it rarely produces a satisfactory return on investment due to the lengthy integration process and associated costs.
RPA can be used to automatically aggregate data from several systems into a single interface, allowing analysts to make faster decisions and, as a result, improve customer satisfaction. Most importantly, RPA is far faster and easier to execute than traditional automation programmes since contemporary systems require far less code. As a result, car lenders can reduce the risk of human error and give workers more time to do value-adding and mentally demanding work.
-in-Automotive-Industry1.png)
Based on type, the market is segmented into Attended automation, unattended Automation, and Hybrid RPA. Attended Automation is dominating the market with 52% market share as this type of bot is installed on the user's computer and is typically activated by the user. Attended automation is excellent for jobs that are initiated at locations that are difficult to identify programmatically. Let's imagine a customer support agent generally needs to go through three screens and five manual steps to complete a transaction. Instead of going through each one, the customer support representative can use an automation code to automate the process. RPA bots can function in the role of a customer service representative, performing required tasks and requesting assistance from the representative when necessary. Attendant automation can be used to supplement manual tasks for staff who interact with consumers but must still do manual chores.
Robotic Process Automation (RPA) in Automotive Market Regional Insights:
North America dominated the market in 2023, accounting for more than 45 percent of global sales. Asia Pacific, Europe, and North America are home to the majority of robotic process automation (RPA) in automobile car manufacturing. These businesses make money by selling their products all around the world, either via their own channels or through OEMs. Governments in nations such as the United States and Canada are developing standards and regulations for vehicle charging infrastructure, which is expected to drive regional market growth. Furthermore, Asia Pacific is predicted to be the fastest-growing regional market over the forecast period.
Because the software does not store any process-related data, the information remains secure throughout automation. According to The Manufacturing Institute, compliance with standards in a variety of nations can add 11% to annual expenses for a large North American automotive firm with a global customer and supplier base. By simulating a human user, software robots interact with the presentation layer. The software may be seamlessly integrated with current programmes like as online, desktop, CRM, ERP, Helpdesk, and Citrix applications because it is process and application agnostic. Manufacturers can also digitize their paper files and integrate physical data into their existing digital operations with the help of extra technologies. Owing to this increasing concern over technology, North American Market is expected to register highest CAGR during the forecast period.
The objective of the report is to present a comprehensive analysis of the Robotic Process Automation (RPA) in Automotive Market to the stakeholders in the industry. The report provides trends that are most dominant in the Robotic Process Automation (RPA) in Automotive Market and how these trends will influence new business investments and market development throughout the forecast period. The report also aids in the comprehension of the Robotic Process Automation (RPA) in Automotive Market dynamics and competitive structure of the market by analyzing market leaders, market followers, and regional players.
The qualitative and quantitative data provided in the Robotic Process Automation (RPA) in Automotive Market report is to help understand which market segments, regions are expected to grow at higher rates, factors affecting the market, and key opportunity areas, which will drive the industry and market growth through the forecast period. The report also includes the competitive landscape of key players in the industry along with their recent developments in the Robotic Process Automation (RPA) in Automotive Market. The report studies factors such as company size, market share, market growth, revenue, production volume, and profits of the key players in the Robotic Process Automation (RPA) in Automotive Market.
The report provides Porter's Five Force Model, which helps in designing the business strategies in the market. The report helps in identifying how many rivals are existing, who they are, and how their product quality is in the Market. The report also analyses if the Robotic Process Automation (RPA) in Automotive Market is easy for a new player to gain a foothold in the market, do they enter or exit the market regularly if the market is dominated by a few players, etc.
The report also includes a PESTEL Analysis, which aids in the development of company strategies. Political variables help in figuring out how much a government can influence the Market. Economic variables aid in the analysis of economic performance drivers that have an impact on the Market. Understanding the impact of the surrounding environment and the influence of environmental concerns on the Robotic Process Automation (RPA) in Automotive Market is aided by legal factors.
Robotic Process Automation (RPA) in Automotive Market Scope:
|
Robotic Process Automation (RPA) in Automotive Market |
|
|
Market Size in 2023 |
USD 3.51 Bn. |
|
Market Size in 2030 |
USD 25.32 Bn. |
|
CAGR (2024-2030) |
32.6% |
|
Historic Data |
2018-2022 |
|
Base Year |
2023 |
|
Forecast Period |
2024-2030 |
|
Segment Scope |
by Type
|
|
by Solutions
|
|
|
Regional Scope |
North America- United States, Canada, and Mexico Europe – UK, France, Germany, Italy, Spain, Sweden, Austria, and Rest of Europe Asia Pacific – China, India, Japan, South Korea, Australia, ASEAN, Rest of APAC Middle East and Africa - South Africa, GCC, Egypt, Nigeria, Rest of the Middle East and Africa South America – Brazil, Argentina, Rest of South America |
Robotic Process Automation (RPA) in Automotive Market Players:
- Blue Prism PLC (UK)
- Kofax, Inc. (USA)
- Automation Anywhere (USA)
- Nice Systems Ltd. (Israel)
- IPsoft, Inc. (USA)
- Pegasystems, Inc. (USA)
- NTT Asvanced Technology Corporation (Japan)
- UiPath SRL (USA)
- Redwood Software (Netherlands)
- Onvesource, Inc. (USA)
Frequently Asked Questions
North America region have the highest growth rate in the Robotic Process Automation (RPA) in automotive market.
Blue Prism PLC (UK), Kofax, Inc. (USA), Automation Anywhere (USA), Nice Systems Ltd. (Israel), IPsoft, Inc. (USA), Pegasystems, Inc. (USA), NTT Asvanced Technology Corporation (Japan), UiPath SRL (USA), Redwood Software (Netherlands), Onvesource, Inc. (USA) and others are the key players in the Robotic Process Automation (RPA) in Automotive market.
Attended automation segment is dominating the market owing to high customer support and integrated RPA bots in the market.
Chapter 1 Scope of the Report
Chapter 2 Research Methodology
2.1. Research Process
2.2. Global Robotic Process Automation (RPA) in Automotive Market: Target Audience
2.3. Global Robotic Process Automation (RPA) in Automotive Market: Primary Research (As per Client Requirement)
2.4. Global Robotic Process Automation (RPA) in Automotive Market: Secondary Research
Chapter 3 Executive Summary
Chapter 4 Competitive Landscape
4.1. Market Share Analysis, By Value, 2023-2030
4.1.1. Market Share Analysis, By Region, By Value, 2023-2030 (In %)
4.1.1.1. North America Market Share Analysis, By Value, 2023-2030 (In %)
4.1.1.2. Europe Market Share Analysis, By Value, 2023-2030 (In %)
4.1.1.3. Asia Pacific Market Share Analysis, By Value, 2023-2030 (In %)
4.1.1.4. South America Market Share Analysis, By Value, 2023-2030 (In %)
4.1.1.5. Middle East and Africa Market Share Analysis, By Value, 2023-2030 (In %)
4.1.2. Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.1. North America Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.1.1. USA Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.1.2. Canada Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.1.3. Mexico Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2. Europe Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2.1. UK Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2.2. France Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2.3. Germany Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2.4. Italy Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2.5. Spain Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2.6. Sweden Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2.7. Austria Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.2.8. Rest of Europe Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.3. Asia Pacific Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.3.1. China Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.3.2. India Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.3.3. Japan Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.3.4. South Korea Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.3.5. Australia Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.3.6. ASEAN Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.3.7. Rest of APAC Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.4. South America Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.4.1. Brazil Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.4.2. Argentina Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.4.3. Rest of South America Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.5. Middle East and Africa Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.5.1. South Africa Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.5.2. GCC Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.5.3. Egypt Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.5.4. Nigeria Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.2.5.5. Rest of Middle East and Africa Market Share Analysis, By Type, By Value, 2023-2030 (In %)
4.1.3. Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4. North America Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.1.1. USA Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.1.2. Canada Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.1.3. Mexico Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2. Europe Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2.1. UK Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2.2. France Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2.3. Germany Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2.4. Italy Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2.5. Spain Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2.6. Sweden Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2.7. Austria Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.2.8. Rest of Europe Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.3. Asia Pacific Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.3.1. China Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.3.2. India Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.3.3. Japan Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.3.4. South Korea Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.3.5. Australia Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.3.6. ASEAN Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.3.7. Rest of APAC Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.4. South America Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.4.1. Brazil Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.4.2. Argentina Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.4.3. Rest of South America Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.5. Middle East and Africa Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.5.1. South Africa Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.5.2. GCC Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.5.3. Egypt Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.5.4. Nigeria Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.1.4.5.5. Rest of Middle East and Africa Market Share Analysis, By Solutions, By Value, 2023-2030 (In %)
4.2. Stellar Competition matrix
4.2.1. Global Stellar Competition Matrix
4.2.2. North America Stellar Competition Matrix
4.2.3. Europe Stellar Competition Matrix
4.2.4. Asia Pacific Stellar Competition Matrix
4.2.5. South America Stellar Competition Matrix
4.2.6. Middle East and Africa Stellar Competition Matrix
4.3. Key Players Benchmarking
4.3.1. Key Players Benchmarking by Product, Pricing, Market Share, Investments, Expansion Plans, Physical Presence and Presence in the Market.
4.4. Mergers and Acquisitions in Industry
4.4.1. M&A by Region, Value and Strategic Intent
4.5. Market Dynamics
4.5.1. Market Drivers
4.5.2. Market Restraints
4.5.3. Market Opportunities
4.5.4. Market Challenges
4.5.5. PESTLE Analysis
4.5.6. PORTERS Five Force Analysis
4.5.7. Value Chain Analysis
Chapter 5 Global Robotic Process Automation (RPA) in Automotive Market Segmentation: By Type
5.1. Global Robotic Process Automation (RPA) in Automotive Market, By Type, Overview/Analysis, 2023-2030
5.2. Global Robotic Process Automation (RPA) in Automotive Market, By Type, By Value, Market Share (%), 2023-2030 (USD Million)
5.3. Global Robotic Process Automation (RPA) in Automotive Market, By Type, By Value,
5.3.1. Attended Automation
5.3.2. Unattended Automation
5.3.3. Hybrid RPA
Chapter 6 Global Robotic Process Automation (RPA) in Automotive Market Segmentation: By Solutions
6.1. Global Robotic Process Automation (RPA) in Automotive Market, By Solutions, Overview/Analysis, 2023-2030
6.2. Global Robotic Process Automation (RPA) in Automotive Market Size, By Solutions, By Value, Market Share (%), 2023-2030 (USD Million)
6.3. Global Robotic Process Automation (RPA) in Automotive Market, By Solutions, By Value,
6.3.1. Inventory management
6.3.2. Auto insurance
6.3.3. Vehicle financing
6.3.4. Supplier onboarding
6.3.5. Freight management
Chapter 7 Global Robotic Process Automation (RPA) in Automotive Market Segmentation: By Region
7.1. Global Robotic Process Automation (RPA) in Automotive Market, By Region – North America
7.1.1. North America Robotic Process Automation (RPA) in Automotive Market Size, By Type, By Value, 2023-2030 (USD Million)
7.1.2. North America Robotic Process Automation (RPA) in Automotive Market Size, By Solutions, By Value, 2023-2030 (USD Million)
7.1.3. By Country – U.S.
7.1.3.1. U.S. Robotic Process Automation (RPA) in Automotive Market Size, By Type, By Value, 2023-2030 (USD Million)
7.1.3.2. U.S. Robotic Process Automation (RPA) in Automotive Market Size, By Solutions, By Value, 2023-2030 (USD Million)
7.1.3.3. Canada Robotic Process Automation (RPA) in Automotive Market Size, By Value, 2023-2030 (USD Million)
7.1.3.4. Mexico Robotic Process Automation (RPA) in Automotive Market Size, By Value, 2023-2030 (USD Million)
7.2. Europe Robotic Process Automation (RPA) in Automotive Market Size, By Value, 2023-2030 (USD Million)
7.2.1. UK
7.2.2. France
7.2.3. Germany
7.2.4. Italy
7.2.5. Spain
7.2.6. Sweden
7.2.7. Austria
7.2.8. Rest of Europe
7.3. Asia Pacific Robotic Process Automation (RPA) in Automotive Market Size, By Value, 2023-2030 (USD Million)
7.3.1. China
7.3.2. India
7.3.3. Japan
7.3.4. South Korea
7.3.5. Australia
7.3.6. ASEAN
7.3.7. Rest of APAC
7.4. Middle East and Africa Robotic Process Automation (RPA) in Automotive Market Size, By Value, 2023-2030 (USD Million)
7.4.1. South Africa
7.4.2. GCC
7.4.3. Egypt
7.4.4. Nigeria
7.4.5. Rest of Middle East and Africa
7.5. South America Robotic Process Automation (RPA) in Automotive Market Size, By Value, 2023-2030 (USD Million)
7.5.1. Brazil
7.5.2. Argentina
7.5.3. Rest of South America
Chapter 8 Company Profiles
8.1. Key Players
8.1.1. Blue Prism PLC (UK)
8.1.1.1. Company Overview
8.1.1.2. Type Portfolio
8.1.1.3. Financial Overview
8.1.1.4. Business Strategy
8.1.1.5. Key Developments
8.1.2. Kofax, Inc. (USA)
8.1.3. Automation Anywhere (USA)
8.1.4. Nice Systems Ltd. (Israel)
8.1.5. IPsoft, Inc. (USA)
8.1.6. Pegasystems, Inc. (USA)
8.1.7. NTT Asvanced Technology Corporation (Japan)
8.1.8. UiPath SRL (USA)
8.1.9. Redwood Software (Netherlands)
8.1.10.Onvesource, Inc. (USA)
8.2. Key Findings
8.3. Recommendations
