Autonomous Enterprise Market by Solutions (Robotic Process Automation, Autonomous Networks, Accounts Automation, Security Automation), Business Functions (IT, Sales & Marketing, Supply Chain & Operations, Accounting & Finance) - Global Forecast to 2029
[276 Pages Report] The autonomous enterprise market is projected to expand from USD 50.5 billion in 2024 to USD 114.0 billion by 2029, at a CAGR of 17.6% from 2024 to 2029.
The constant growth and development of AI and ML are the primary reasons fueling the autonomous enterprise market. AI and ML technologies present in modern business applications have evolved, and companies can now automate complex processes that used to require input from the system. Most of these technologies not only automate actions but also perform predictive analytics, make decisions, and learn from events. This is especially true for new AI or ML models with enhanced accuracy and better handling of big data. The more enterprises can automate complex processes, the more they can enhance efficiency and accuracy. This technological advancement assists corporations in making independent decisions and taking actions without significant human interference.
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IMPACT OF AI/GEN AI ON AUTONOMOUS ENTERPRISE MARKET
The incorporation of generative Al in autonomous enterprises is a major step toward enhancing functionality and empowering innovation. Generative Al applies to the creation of brand-new content, designs, models, and solutions, providing a cognitive boost to the decision-making power of autonomous systems. By adopting generative Al, several activities that demand creativity can be accomplished through machine intervention; these include product design, business process redesign, and specific marketing campaigns. This integration enables autonomous enterprises to perform at a level beyond the simple automation of existing processes, helping them work more innovatively and be more predictive and responsive to change than before. Additionally, generative Al can apply sophisticated business models for various scenarios. It can aid businesses in gaining more insights into an enterprise and help them make accurate decisions based on data.
AUTONOMOUS ENTERPRISE MARKET DYNAMICS
Driver: Convergence of cloud, data, and IoT infrastructures
The integration of cloud, data, IoT, and AI applications has been enhancing the idea of automated systems across different sectors. This is where convergence takes place, leading to the emergence of a wholly new environment where physical environments, business processes, and IT operations are being revolutionized. In the physical world, autonomy systems are set to transform sectors such as logistics, manufacturing, and mining with enhanced performance, lowered risk, and improved value creation. At the same time, a digital transformation is taking place within business organizations. Robotic process automation or RPA, when underpinned by Al-based intelligent process automation, automates repetitive activities and responds to changes in business conditions. Sophisticated automation, aided by process intelligence tools, will lead the way toward establishing autonomous enterprises.
In aggregate, the outcomes of these technological developments lay the groundwork for creating self-sustaining organizations where intelligent systems can operate on their own and self-optimize in a range of fields.
Restraint: Concerns related to data privacy
Personal data protection is a critical consideration in management within autonomous enterprises. The tremendous amount of data that is gathered for Al-powered processes gives rise to concerns about data minimization and its retention. Engaging with third-party providers and transferring information to them generates more risk of a breach. In addition, many Al algorithms are black-box models, making it hard to track how an individual’s personal data is used. Some unique and significant tasks include the protection of data and safeguarding them against any forms of access from unauthorized personnel, in addition to the difficult and cumbersome reality of meeting rigorous and stringent data protection regulations. Solving such problems is a complex task that involves the use of good data management practices, proper ethical frameworks for the creation of Al, and ongoing risk evaluation.
Opportunity: Generative Al revolution creating next phase of autonomous enterprises
Generative AI is a relatively new technology that has received a lot of funding, with over USD 2 billion capital outlay in 2022. The valuation of OpenAl at USD 29 billion proved its worth and indicated how much investors and companies spend on this type of innovation. With advancements in technology and automation, organizations are seeking new applications of generative Al to develop fully automated self-sustainable enterprises that can interact with humans seamlessly. Businesses are increasingly implementing generative Al in marketing, customer service, sales, and client relationships. Generative Al can create marketing messages, sales proposals, product concepts, and new advertisements to increase conversion and profitability. Its uses extend beyond business and consumer contexts, encompassing customer relationship management systems, health informatics, and software development. Thus, as generative Al becomes a reality, the prospects of autonomous enterprises are significant and immeasurable.
Challenge: Ethical and legal constraints
As the concept of autonomous enterprise evolves and spreads in society, a number of ethical issues have emerged. The issue of liability or who is to blame when an accident happens in relation to the use of revolutionized systems generates legal concerns. In case something goes wrong with regard to non-adherence to sustainable principles, the guidelines concerning accountability and responsibility must be clearly outlined. Other ethical dilemmas present in this concept include privacy and data security. A rising awareness of data harvesting and analysis outcomes increases the phobias concerning the protection of personal data and their improper use. To address these problems, firms have to employ proper data protections and declare policies for managing data. Ethical decision-making should, therefore, not be restricted to main managerial decisions but also include decision-making logic in intelligent systems. On the one hand, there are problems with the transparency and fairness of the algorithms, and on the other, there are problems with their accountability. These have not lost their relevance as far as the requirements for maintaining public trust in autonomous enterprise systems are concerned.
MARKET ECOSYSTEM
The autonomous enterprise market is highly competitive and comprises many vendors who offer solutions to a specific segment or a niche segment of the market. In recent years, several changes have occurred in the autonomous enterprise market. Currently, the vendors are involved in various partnerships and collaborations to develop comprehensive solutions that address a wide range of requirements. Microsoft (US), IBM (US), PTC (US), AWS (US), SAP (Germany), Cisco (US), HPE (US), and Oracle (US) are some of the major players operating in this ecosystem.
The process automation application is estimated to lead the autonomous enterprise market during the forecast period.
Process automation refers to the use of technology to automate complex business processes and tasks within an organization. It entails the use of systems and tools, including Robotic Process Automation(RPA), Artificial Intelligence(AI), and Machine Learning(ML) through the automation of combined tasks with little or no human interconnection. Business process automation is also not limited to workflow automation but also applies to the subsequent automation of the processes that occur in different departments of the company. This can range from accounting and staff management to inventory and sales-related services. The integration of AI & ML facilitates these automated procedures to become more refined and efficient over a period of time. When it comes to the application of autonomous enterprises, process automation is critical for improving efficiency, decreasing costs, and maintaining quality.
By region, North America is expected to account for the largest share of the autonomous enterprise market during the forecast period
North America holds the largest revenue share in the autonomous enterprise market. Enterprises in this region are the early adopters of technologies, and most of the North American industry verticals have already gone through digital transformation. This rapid adoption of technologies has led to the generation of huge amounts of data by North American companies, presenting an opportunity for the deployment of autonomous enterprise solutions to maintain and manage such data. The automation of business processes results in less need for manpower and saves a lot of time and cost, enabling companies to focus on business-critical decisions. Industries such as BFSI, telecommunications & IT, transportation & logistics, manufacturing, and media & entertainment are at the forefront of adopting autonomous enterprise solutions. The presence of key players in North America, such as Microsoft, IBM, NICE, and Pegasystems, is also one of the key factors driving the adoption of autonomous enterprise solutions in the region.
Market Players:
The major players in the autonomous enterprise market include Microsoft (US), IBM (US), Pegasystems (US), Cisco (US), SAP (Germany), and HPE (US). These players have adopted various growth strategies, such as partnerships, agreements, and new product launches & enhancements, to expand their footprint in the autonomous enterprise market.
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Report Metrics |
Details |
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Market size available for years |
2019-2029 |
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Base year considered |
2023 |
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Forecast period |
2024–2029 |
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Forecast units |
Value (USD) Million/Billion |
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Segments covered |
By Offering, Business Function, Application, Vertical, and Region |
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Regions covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
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Companies covered |
Microsoft (US), IBM (US), Check Point (US), Pegasystems (US), Cisco (US), SAP (Germany), Atos (France), AWS (US), Oracle (US), HPE (US), Sage (UK), NICE (Israel), Palo Alto Networks (US), Blue Prism (UK), UiPath (New York), Appian (US), Automation Anywhere (US), Tangentia (Canada), Drivenets (Israel), Nintex (US), Synder (US), Fetch.ai (England), AutomationEdge (US), Rocketbot (Chile), Rossum (UK), Digitate (US), and Mendix (US). |
This research report categorizes the autonomous enterprise market to forecast revenues and analyze trends in each of the following submarkets:
Based on Offering:
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Solutions
- Robotic Process Automation
- Autonomous Networks
- Accounts Automation
- Security Automation
- Autonomous Agents
- Other Solutions
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Services
- Professional Services
- Managed Services
Based On Business Functions:
- Accounting and Finance
- IT
- Human Resource
- Sales and Marketing
- Supply Chain and Operations
Based On Applications:
- Process Automation
- Customer and Employee Engagement
- Order Management
- Credit Evaluation and Management
- Predictive Maintenance
- Other Applications
Based On Vertical:
- BFSI
- IT & ITeS
- Telecom
- Retail & Ecommerce
- Media & Entertainment
- Healthcare
- Transportation & Logistics
- Manufacturing
- Government & Defence
- Other Verticals
By Region:
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North America
- United States (US)
- Canada
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Europe
- United Kingdom (UK)
- Germany
- France
- Italy
- Spain
- Nordics
- Rest of Europe
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Asia Pacific
- China
- Japan
- India
- Australia & New Zealand
- South Korea
- Rest of Asia Pacific
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Middle East and Africa
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Middle East
- UAE
- KSA
- Bahrain
- Kuwait
- Rest of Middle East
- Africa
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Middle East
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Latin America
- Brazil
- Mexico
- Rest of Latin America
Recent Developments
- In June 2024, Telefónica Tech and IBM signed a new collaboration agreement to drive the development of AI, analytics, and data management solutions for enterprises.
- In April 2024, Cloud Software Group and Microsoft signed an eight-year strategic partnership agreement. The agreement will strengthen the go-to-market collaboration for the Citrix virtual application and desktop platform and support the development of new cloud and AI solutions with an integrated product roadmap.
- In April 2024, Cisco acquired Isovalent, a leader in open-source cloud-native networking and security. Isovalent’s innovative technologies will become a cornerstone of the Cisco Security Cloud vision, an AI-driven, cloud-delivered, integrated security platform designed to accommodate organizations of any size, offering cutting-edge protection against threats in a multi-cloud world.
- In November 2023, Atos announced the extension of its long-standing partnership with Microsoft to help clients unlock and scale their Microsoft 365 Copilot and generative AI deployments.
Frequently Asked Questions (FAQ):
What is the definition of the autonomous enterprise market?
The autonomous enterprise market refers to an ecosystem of organizations, technologies, and solutions that help a business run with minimum human involvement. This comes through leveraging automation, AI, ML, and data-driven decision-making. Enterprises in this market deploy advanced technologies to automate routine tasks in business processes, optimize them, and enhance capabilities pertaining to decision-making toward the realization of efficient, responsive, and scalable operations.
What is the size of the autonomous enterprise market?
The autonomous enterprise market is projected to grow from USD 50.5 billion in 2024 to USD 114.0 billion by 2029, at a CAGR of 17.6% during the forecast period.
What are the major drivers in the autonomous enterprise market?
One of the key factors driving the growth of the autonomous enterprise market is AI and ML, as these technologies provide complex automation and real-time decision-making. There is increasing demand for operation, real-time data analysis, and digital transition that force organizations to use autonomous solutions. Furthermore, the emergence of IoT and edge computing and the need to implement strong and efficient cybersecurity systems promote the market’s advancement as businesses aim to be viable, legal, and environmentally friendly.
Who are the key players operating in the autonomous enterprise market?
The major players in the autonomous enterprise market are Microsoft (US), IBM (US), Check Point (US), Pegasystems (US), Cisco (US), SAP (Germany), Atos (France), AWS (US), Oracle (US), HPE (US), Sage (UK), NICE (Israel), Palo Alto Networks (US), Blue Prism (UK), UiPath (New York), Appian (US), Automation Anywhere (US), Tangentia (Canada), Drivenets (Israel), Nintex (US), Synder (US), Fetch.ai (England), AutomationEdge (US), Rocketbot (Chile), Rossum (UK), Digitate (US), and Mendix (US). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches/enhancements, and acquisitions to expand their footprint in the autonomous enterprise market.
What are the opportunities for new entrants in the autonomous enterprise market?
New entrants have the opportunity to leverage autonomous enterprise market growth and compete for market share by creating a unique value proposition based on areas of strength such as AI process automation, predictive analytics, and IoT connectivity. These companies can use new specific technologies like edge computing and blockchain technologies to develop unique solutions that are unique to the industries they serve. .
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The research study involved four major activities in estimating the autonomous enterprise market size. Exhaustive secondary research has been done to collect important information about the market and peer markets. The next step has been to validate these findings and assumptions and size them with the help of primary research with industry experts across the value chain. Both top-down and bottom-up approaches have been used to estimate the market size. Post which the market breakdown and data triangulation have been adopted to estimate the market sizes of segments and sub-segments.
Secondary Research
The market size of the companies offering autonomous enterprise solutions to various end users was arrived at based on the secondary data available through paid and unpaid sources and by analyzing the product portfolios of major companies in the ecosystem and rating the companies based on their performance and quality. In the secondary research process, various sources were referred to identify and collect information for the study. The secondary sources included annual reports, press releases, investor presentations of companies, white papers, journals, certified publications, and articles from recognized authors, directories, and databases.
Secondary research was mainly used to obtain critical information about industry insights, the market’s monetary chain, the overall pool of key players, market classification, and segmentation according to industry trends to the bottom-most level, regional markets, and key developments from both market- and technology-oriented perspectives.
Primary Research
In the primary research process, various sources from the supply and demand sides were interviewed to obtain qualitative and quantitative information for the report, Such as Chief Experience Officers (CXOs), Vice Presidents (VPs), directors from business development, marketing, and product development/innovation teams, and related key executives from autonomous enterprise solution vendors, system integrators, professional and managed service providers, industry associations, independent consultants, and key opinion leaders.
Primary interviews were conducted to gather insights, such as market statistics, data on revenue collected from software and services, market breakups, market size estimations, market forecasts, and data triangulation. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Finance Officers (CFOs), Chief Strategy Officers (CSOs), and the installation team of end users who use autonomous enterprise, were interviewed to understand buyers’ perspectives on suppliers, products, service providers, and their current usage of Autonomous enterprise solutions which is expected to affect the overall autonomous enterprise market growth.
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Market Size Estimation
In the market engineering process, the top-down and bottom-up approaches were used along with multiple data triangulation methods to estimate and validate the size of the autonomous enterprise market and other dependent submarkets. The research methodology used to estimate the market sizes includes the following:
- Initially, MarketsandMarkets focuses on top-line investments and spending in the ecosystems. Further, significant developments in the critical market area have been considered.
- Tracking the recent and upcoming developments in the autonomous enterprise market that include investments, R&D activities, product launches, collaborations, mergers and acquisitions, and partnerships, as well as forecasting the market size based on these developments and other critical parameters.
- Conduct multiple discussions with key opinion leaders to learn about the diverse types of authentications and brand protection offerings used and the applications for which they are used to analyze the breakdown of the scope of work carried out by major companies.
- Segmenting the market based on technology types concerning applications wherein the types are to be used and deriving the size of the global application market.
- Segmenting the overall market into various market segments
- Validating the estimates at every level through discussions with key opinion leaders, such as chief executives (CXOs), directors, and operation managers, and finally with the domain experts at MarketsandMarkets
Market Size Estimation Methodology-Bottom-up approach
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Market Size Estimation Methodology-top-down approach
Data Triangulation
After arriving at the overall market size from the above estimation process, the autonomous enterprise market has been split into several segments and sub-segments. To complete the overall market engineering process and arrive at the exact statistics for all segments and sub-segments, data triangulation and market breakdown procedures have been used, wherever applicable. The data has been triangulated by studying various factors and trends from both the demand and supply sides.
The autonomous enterprise market size has been validated using top-down and bottom-up approaches.
Market Definition
Autonomous Enterprise is a self-optimizing business that applies AI and automation to decisions, operations, and servicing across the organization. It is a collection of various solutions that enable business functions such as supply chain and operations, IT, HR, accounting & finance, and sales & marketing in an enterprise.
Stakeholders
- Managed service providers
- Support and maintenance service providers
- System Integrators (Sls)/migration service providers
- Value-Added Resellers (VARs) and distributors
- Distributors and Value-added Resellers (VARs)
- System Integrators (Sls)
- Independent Software Vendors (ISV)
- Third-party providers
- Technology providers
Report Objectives
- To determine and forecast the global autonomous enterprise market by offering (solution and services), business functions, applications, vertical, and region from 2024 to 2029, and analyze the various macroeconomic and microeconomic factors affecting the market growth.
- To forecast the size of the market segments concerning five central regions: North America, Europe, Asia Pacific (APAC), Middle East & Africa (MEA), and Latin America.
- To provide detailed information about the major factors (drivers, restraints, opportunities, and challenges) influencing the growth of the autonomous enterprise market.
- Analyze each submarket concerning individual growth trends, prospects, and contributions to the overall Autonomous enterprise market.
- To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the autonomous enterprise market.
- To profile the key market players; provide a comparative analysis based on business overviews, regional presence, product offerings, business strategies, and key financials; and illustrate the market’s competitive landscape.
- Track and analyze competitive developments in the market, such as mergers and acquisitions, product developments, partnerships and collaborations, and Research and Development (R&D) activities.
Available Customizations
With the given market data, MarketsandMarkets offers customizations per the company’s specific needs. The following customization options are available for the report:
Geographic Analysis
- Further break-up of the Asia Pacific market into countries contributing 75% to the regional market size
- Further break-up of the North American market into countries contributing 75% to the regional market size
- Further break-up of the Latin American market into countries contributing 75% to the regional market size
- Further break-up of the Middle East African market into countries contributing 75% to the regional market size
- Further break-up of the European market into countries contributing 75% to the regional market size
Company Information
- Detailed analysis and profiling of additional market players (up to 5)
Growth opportunities and latent adjacency in Autonomous Enterprise Market