AI Agents Market by Agent Role (Productivity & Personal Assistants, Sales, Marketing, Customer Service, Code Generation), Agent Systems (Single Agent, Multi Agent), Product Type (Ready to Deploy Agents, Build Your Own Agents) - Global Forecast to 2030
[432 Pages Report] The AI agents market is projected to grow from USD 5.1 billion in 2024 to USD 47.1 billion by 2030. This notable expansion, characterized by a robust CAGR of 44.8% between 2024 and 2030, is mostly driven by technological advances in natural language processing. As the capabilities of AI agents such as GPT-4o, AgentGPT, and others become better at understanding and generating human language, they can handle more sophisticated and nuanced context-aware interactions with users. This enables a better user experience, which leads to wider acceptance in industries such as customer service, healthcare, and finance. The enhancement in Natural Language Processing (NLP) helps AI agents not only handle complicated queries but also make them easily adaptable to different dialects, hence increasing their global applicability and market reach. Along with NLP, “build your own agent” solutions are driving the industry, enabling companies to design AI agents that are specifically customized to meet their needs. The growing use of multi-agent systems, in which several AI agents cooperate to tackle challenging issues, is another important aspect driving market expansion.
AI agents are autonomous or semi-autonomous software designed to carry out certain assignments or make real-time decisions based on input data. These sophisticated AI tools often include NLP, machine learning, and computer vision. Specifically, these agents operate within limited environments with users, systems, or other agents to reach specific goals. From fully independent agents working without any human involvement to semi-autonomous agents who need occasional external guidance, these agents are used in customer service, automation of backend processes, and as assistive software for decision-making and data analysis.
Impact of Generative AI on AI Agents
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Market Dynamics
Driver: Increasing integration of AI agents with enterprise-level automation tools
The emergence of AI agent integration with enterprise-scale automation tools has become a key driver in the market for artificial intelligence agents, which greatly enhances enterprise capabilities across different business functions. Using AI agents, businesses can automate various complex processes and reduce manual interventions to avoid human errors. For example, in banking services, AI agents integrated into the automation platform perform tasks ranging from fraud detection and customer support to compliance monitoring in real-time. According to MarketsandMarkets’ estimation, productivity could rise by 20–30% through automation driven by AI, where a major part of such changes would be played by AI agents. The leading companies in this area, like UiPath and Blue Prism, have begun to incorporate artificial intelligence capabilities into their RPA tools so that automation projects can be extended across business boundaries without any disruption. This move will not only cut down on OPEX but also improve decision-making through real-time data analysis provided by these AI agents.
Restraint: Data privacy norms in highly regulated industries
Although there is great potential with AI agents, their wide uptake is hampered by the complications around data privacy and compliance. For AI agents to function properly, they inherently need access to large volumes of data, some of which may be personal or confidential. The utilization of such information is under tight scrutiny as per legislation, including GDPR (General Data Protection Regulation) within the European Union and the Health Insurance Portability and Accountability Act (HIPAA) in the US, which put conditions on the way data should be collected, stored, and manipulated. As per industry estimates, nearly 60% of companies expressed concerns over deploying AI agents because they do not want to risk noncompliance that might lead to huge fines or even legal complications. For global organizations that operate across multiple jurisdictions, this constraint becomes particularly difficult since it makes it almost impossible for them to scale up AI agent deployment activities due to a variety of contradictory statutory provisions.
Opportunity: Emergence of personalized virtual assistants tailored for niche business roles
A specific growth opportunity in the AI agents market is found in the expanding field of specialized virtual assistants designed for niche industries. Unlike their generic counterparts, special agents are created to satisfy the unique requirements of such industries as legal, healthcare, or finance. For instance, in the legal sector, AI agents assist in document drafting, research, and compliance monitoring, thus considerably reducing the workloads of lawyers. As per MarketsandMarkets estimates, the industry-specific AI solutions market would register a CAGR of about 35% over the next five years, owing to the increasing demand for highly specialized AI tools by specific sectors. Furthermore, this change is enhanced by the emergence of “hyper-personalization,” with AI assistants being not only industry-centric but also personalized according to user’s preferences and capabilities related to their occupations. Vendors that can produce and deliver these types of specialized intelligent agents competently ahead of others will have an added advantage because such systems are deeply integrated into a variety of enterprise business functions.
Challenge: Shortcomings of AI agents in achieving true contextual understanding under dynamic, real-world conditions
Achieving a real and contextual understanding of dynamic, everyday environments has become a pressing challenge in the AI agents market. In spite of their increasing effectiveness at handling language, AI agents sometimes fail to maintain context for long periods or when they are involved in multi-topic conversations. For example, in customer service or sales, an AI agent may handle a series of simple requests but struggle when the conversation suddenly changes, causing frustration to the user. In a 2022 survey by MIT Sloan Management Review, 75% of corporations that deploy AI agents experienced problems related to contextual accuracy, particularly in multi-turn dialogues. Such problems are further compounded by the fact that current models lack the capacity to understand different cultural nuances and domain-specific terminologies required by AI systems. This acts as a significant barrier to their adoption as organizations hesitate to use them in critical high-stakes contexts where an accurate interpretation may be necessary.
AI Agents Market Ecosystem
By agent system, multi-agent systems to experience fastest growth between 2024 and 2030
The multi-agent systems segment is projected to witness rapid growth in the next five years due to the rising demand for AI solutions capable of working in decentralized environments, especially in smart grids, autonomous vehicles, and distributed computing networks. The ability of multi-agent systems to scale and adapt to real complex problems is not only a technological advantage but a critical enabler for industries looking to leverage AI in a transformative way. The rapid growth of multi-agent systems is attributed to their unmatched competence in dealing with complex and dynamic tasks compared to that of single agents. This ability to handle multiple tasks simultaneously is crucial for addressing problems in environments where high coordination and adaptability are needed. For example, in the logistics field, a multi-agent supply chain operation can be worked out by realizing inventory management through one agent, planning the best route through a second, and monitoring real-time delivery conditions through a third. This will enable improved and effective problem-solving in industries where timing and precision matter.
By product type, ready-to-deploy agents to account for largest market share in 2024
The simplicity and immediate impact of “ready-to-deploy” agents have made them popular in the AI market among businesses of all sizes. These AI agents are essentially plug-and-play alternatives that require no complex development or customization processes before insertion into a company’s operations. This is a great advantage, especially for small- to medium-sized enterprises that require fast and efficient tools to remain competitive. A firm hoping to improve its customer support can install a pre-built chatbot within hours, hence optimally enhancing its customer interaction, instead of waiting for months to construct a tailored AI system. The real advantage here is that these agents not only solve problems right out of the box but also come with ongoing support, so businesses do not have to worry about maintenance. It is this combination of quick installation at cost-effective prices coupled with instant results that keeps ready-to-deploy agents leading in the market.
By agent role, coding & software developments poised to witness substantial CAGR during forecast period
Coding and software development agents face an uptick in their adoption as they can simplify the development process, increase productivity, and reduce time to market. These AI-based agents can create code automatically, debug problems, and suggest improvements, thus enabling developers to concentrate on more intricate and imaginative tasks. For instance, GitHub Copilot uses artificial intelligence to recommend sectional codes as well as complete lines of codes that its users input, thereby substantially hastening programming’s speed. Similarly, platforms like DeepCode provide instant code checks and make suggestions, reducing the chances of having bugs in the code while also improving code quality. This has created a high demand for these agents in different industries where the software development cycle has become rapid, with shorter timespans between new software generations. Coding agents not only just speed up the development processes but also make coding simpler for beginners, ensuring wider participation in creating programs to be employed across diverse sectors.
By end user, BFSI segment to hold largest market share in 2024
Due to its urgent requirement for better efficiency, security, and client engagement in a strictly controlled environment, the BFSI sector is the largest end user of AI agents. In real-time fraud detection, AI agents serve as an essential part of processing huge volumes of transaction data to detect suspicious patterns. For instance, advanced AI agent-driven monitoring systems by JPMorgan Chase can prevent frauds before they can affect users. With regards to customer care, AI-empowered virtual assistants like Erica from Bank of America carry out routine tasks like checking account balances and applying for loans, thereby allowing human agents to engage themselves in more complicated duties. Another important aspect of using these AI agents is automating compliance procedures and regulatory reporting, which play crucial roles in industries where accuracy and adherence to regulations are very important. In light of the current reforms in finance regulations, AI agents aid banks and other financial entities to maintain compliance effectively, reducing the burden of manual backend tasks.
By region, Asia Pacific market to experience fastest growth rate during forecast period
The rapid growth of the Asia Pacific AI agents market is being driven by advancements in technology, widespread digital transformation initiatives, and the increasing amount of R&D spending on AI by both private and public sectors. China, Japan, and South Korea are leading the pack in employing AI agents in various industries. For example, Ping An Insurance in China has integrated AI agents into its customer service system, which now handles over 60% of customer inquiries, helping reduce response time and increasing customer satisfaction. In Japan, Mitsubishi UFJ Financial Group (MUFG) has made use of AI agents to streamline crucial functions such as loan approval process and fraud detection, thereby making banking operations more efficient and secure. In addition to this, South Korea makes use of AI agents within its smart cities’ projects, which include traffic management optimization for energy usage and crime prevention - showing that the country is fully committed to combining AI within urban infrastructure. Singapore is also a major participant, with the government encouraging the use of artificial intelligence (AI) - for instance, by implementing such programs as the national AI strategy that has included but is not limited to establishing AI agents in healthcare facilities to help with diagnosis and patient management.
Key Market Players
The providers of AI agent solutions and services have implemented several types of go-to-market strategies, such as new product launches, product upgrades, partnerships and agreements, business expansions, and mergers and acquisitions, to strengthen their offerings in the market. Some major players in the AI agents market include Google (US), Amelia (US), IBM (US), OpenAI (US), and AWS (US), along with SMEs and startups such as Fluid AI (India), Stability AI (UK), Cognigy (Germany), Aisera (US), and Cognosys (Canada).
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Report Metrics |
Details |
Market size available for years |
2019–2030 |
Base year considered |
2023 |
Forecast period |
2024–2030 |
Forecast units |
USD Million |
Segments Covered |
Agent System, Product Type, Agent Role, End User, and Region |
Geographies covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
Companies covered |
Microsoft (US), IBM (US), Google (US), Oracle (US), AWS (US), NVIDIA (US), Meta (US), Salesforce (US), OpenAI (US), LivePerson (US), Tempus AI (US), Kore.ai (US), LeewayHertz (US), CS DISCO (US), Aerogility (UK), GupShup (US), HireVue (US), Helpshift (US), Fluid AI (India), Amelia (US), Irisity (Sweden), Cogito (US), SmartAction (US), Cognosys (Canada), Aisera (US), Markovate (US), Rasa (US), Stability AI (UK), Infinitus Systems (US), Sierra (US), Level AI (US), Sybill (US), Truva (US), Leena AI (US), Tars (US), Talkie.ai (US), HeyMilo AI (US), CUJO AI (US), K Health (US), Locale.ai (US), Newo.ai (US), Beam AI (US), and Cognigy (Germany). |
This research report categorizes the AI agents market based on agent system, product type, agent role end users, and region:
By Agent System:
- Single Agent Systems
- Multi Agent Systems
By Product Type:
- Ready-to-Deploy Agents
- Build-Your-Own Agents
By Agent Role:
-
Productivity & Personal Assistants
- Creativity Assistants
- Workflow Automation
- Meeting Assistants
-
Sales
- Prospecting
- Lead Generation
- Sales Automation
- Customer Relationship Management
-
Marketing
- Content Creation & SEO
- Campaign Management
- Marketing Personalization
-
Legal
- Legal Research
- Document Review & Management
- Legal Compliance
-
Customer Service & Support
- Self Service Chatbots
- Sentiment Analysis
-
Coding & Software Development
- Code Generation
- Code Debugging
- Continuous Integration/Continuous Delivery (CI/CD)
-
Product Management
- Market Research
- Product Development
- Project Task Automation
- Resource Allocation
-
Accounting
- Transaction Failure Management
- Fraud Management
-
Human Resources
- Hiring & Recruitment
- Employee Engagement
-
Business Intelligence
- Data Analytics & Insight Generation
- Predictive Analytics & Forecasting
- Automated Reporting & Dashboards
- Data Cleaning & Preparation
- Others
By End User:
-
Enterprises
-
BFSI
- Banking
- Financial Services
- Insurance
- Telecommunications
- Government & Public Sector
- Healthcare & Life Sciences
- Manufacturing
-
Media & Entertainment
- Advertising
- Music
- Film
- Gaming
- Journalism
- Retail & E-Commerce
- Technology Providers
-
Professional Service Providers
- Consulting Service Providers
- KPOs
- BPOs
- Recruitment
- Law Firms
- Other Enterprises
-
BFSI
- Consumers
By Region:
-
North America
- United States
- Canada
-
Europe
- UK
- Germany
- France
- Italy
- Spain
- Netherlands
- Rest of Europe
-
Asia Pacific
- China
- India
- Japan
- South Korea
- Singapore
- Australia and New Zealand (ANZ)
- Rest of Asia Pacific
-
Middle East and Africa
- Saudi Arabia
- UAE
- Turkey
- Qatar
- Rest of Middle East
- Africa
-
Latin America
- Brazil
- Mexico
- Argentina
- Rest of Latin America
Recent Developments:
- In July 2024, Salesforce announced Einstein Service Agent, Salesforce’s first fully autonomous AI agent. Einstein Service Agent makes conventional chatbots obsolete with its ability to understand and act on a broad range of service issues without preprogrammed scenarios, helping make customer service far more efficient.
- In May 2024, IBM and Salesforce announced an expanded strategic partnership that will bring together IBM watsonx AI and Data Platform capabilities with the Salesforce Einstein Platform for greater customer choice and flexibility in AI and data deployment. This will empower teams to make data-driven decisions and take actions directly in their flow of work.
- In May 2024, Microsoft announced its ‘Team Copilot,’ which integrates seamlessly into platforms like Microsoft Teams, Loop, and Planner, providing a range of capabilities that go beyond what individual users typically get from AI tools. Microsoft’s Team Copilot is an advanced AI feature designed to enhance collaboration and productivity within teams by acting as a valuable team member rather than just a personal assistant.
- In April 2024, IVeS, Sopra Steria, and IBM collaborated to create IRIS, the world’s first conversational assistant for the deaf and hard of hearing. This innovative “signbot” leverages the power of AI to enable digital sign language communication, marking a significant milestone in the field of accessibility.
- In April 2024, Google made Gemini 1.5 Pro available in 180+ countries via the Gemini API in a public preview. It features the first-ever native audio (speech) understanding capability and a new File API to make it easy to handle files. The company also launched new features like system instructions and JSON mode to give developers more control over the model’s output.
- In April 2024, Microsoft launched its Copilot for Security. The solution will help security and IT professionals catch what others miss, move faster, and strengthen team expertise. Copilot is informed by large-scale data and threat intelligence, including more than 78 trillion security signals processed by Microsoft each day, and coupled with large language models to deliver tailored insights and guide the next steps.
Frequently Asked Questions (FAQ):
What are AI agents?
AI agents are software entities that autonomously or semi-autonomously execute tasks and make decisions, leveraging machine learning, NLP, and other AI technologies. They operate within specific environments, interfacing with users, systems, or other agents, and are characterized by their capacity for adaptive learning, context-aware processing, and autonomous function across varied applications.
What is the total CAGR expected to be recorded for the AI agents market during 2024-2030?
The AI agents market is expected to record a CAGR of 44.8% from 2024 to 2030.
How are generative AI and cybersecurity amalgamating into a converged technology?
Generative AI is revolutionizing the AI agents market by significantly enhancing their ability to create, adapt, and respond in more human-like and contextually nuanced ways. Integrating generative models like GPT-4/4o allows AI agents to engage in more natural and dynamic interactions, whether it is crafting personalized customer service responses, generating content, or even writing complex code. This capability is expanding the applications of AI agents across industries, making them more versatile and effective, and driving their adoption as they can now offer more sophisticated, tailored solutions that were previously beyond the reach of traditional AI agents?.
What are the key drivers supporting the growth of the AI agents market?
The key factors driving the growth of the AI agents market include the accelerated development of natural language processing (NLP) technologies enhancing AI agents’ understanding and interaction capabilities, demand for hyper-personalized digital experiences driving higher adoption of AI agents in customer-facing roles, and the integration of AI agents into enterprise business process automation to improve operational efficiency and reduce costs.
Which are the top end-users prevailing in the AI agents market?
The leading enterprise end-users in the AI agents market include BFSI, healthcare and life sciences, and professional service providers.
Who are the key vendors in the AI agents market?
Some major players in the AI agents market include Microsoft (US), IBM (US), Google (US), Oracle (US), AWS (US), NVIDIA (US), Meta (US), Salesforce (US), OpenAI (US), LivePerson (US), Tempus AI (US), Kore.ai (US), LeewayHertz (US), CS DISCO (US), Aerogility (UK), GupShup (US), HireVue (US), Helpshift (US), Fluid AI (India), Amelia (US), Irisity (Sweden), Cogito (US), SmartAction (US), Cognosys (Canada), Aisera (US), Markovate (US), Rasa (US), Stability AI (UK), Infinitus Systems (US), Sierra (US), Level AI (US), Sybill (US), Truva (US), Leena AI (US), Tars (US), Talkie.ai (US), HeyMilo AI (US), CUJO AI (US), K Health (US), Locale.ai (US), Newo.ai (US), Beam AI (US), and Cognigy (Germany). .
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The AI agents market research study involved extensive secondary sources, directories, journals, and paid databases for secondary research. Primary sources were mainly industry experts from the core and related industries, preferred cybersecurity providers offering generative AI-infused solutions, third-party service providers, consulting service providers, end users, and other commercial enterprises. In-depth interviews were conducted with various primary respondents, including key industry participants and subject matter experts, to obtain and verify critical qualitative and quantitative information, and assess the market’s prospects.
Secondary Research
In the secondary research process, various sources were referred to, for identifying and collecting information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers, journals, and certified publications; and articles from recognized authors, directories, and databases. Additional data was gathered by utilizing other secondary sources, such as blogs, government whitepapers, journals, and vendor websites. The spending on AI agents by different nations was gathered from the corresponding sources. Secondary research was mainly used to obtain key information related to the industry’s value chain and supply chain to identify key players based on solutions, services, market classification, and segmentation according to offerings of major players, industry trends related to agent systems, product type, agent roles, end users, and region, and key developments from both market- and technology-oriented perspectives.
Primary Research
In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief Experience Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and AI agents expertise; related key executives from AI agents solution vendors, SIs, professional service providers, and industry associations; and key opinion leaders.
Primary interviews were conducted to gather qualitative and quantitative insights, which include but are not limited to market statistics, revenue data collected from solutions and services, market breakups, market size estimations, market forecasts, and data triangulation. Primary research was also deployed to assist in understanding various trends related to technologies, applications, deployments, and regions. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Strategy Officers (CSOs), and end users using AI agents solutions, were interviewed to understand the buyer’s perspective on suppliers, products, service providers, and their current usage of AI agents solutions and services, which would impact the overall AI agents market.
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Market Size Estimation
Multiple approaches were adopted for estimating and forecasting the AI agents market. The first approach involves estimating the market size by summation of companies’ revenue generated through the sale of solutions and services.
Market Size Estimation Methodology-Top-down approach
In the top-down approach, an exhaustive list of all the vendors offering solutions and services in the AI agents market was prepared. The revenue contribution of the market vendors was estimated through annual reports, press releases, funding, investor presentations, paid databases, and primary interviews. Each vendor's offerings were evaluated based on breadth of software and services according to agent systems, product type, agent role, and end users. The aggregate of all the companies’ revenue was extrapolated to reach the overall market size. Each subsegment was studied and analyzed for its global market size and regional penetration. The markets were triangulated through both primary and secondary research. The primary procedure included extensive interviews for key insights from industry leaders, such as CIOs, CEOs, VPs, directors, and marketing executives. The market numbers were further triangulated with the existing MarketsandMarkets’ repository for validation.
Market Size Estimation Methodology-Bottom-up approach
In the bottom-up approach, the adoption rate of AI agents solutions and services among different end users in key countries with respect to their regions contributing the most to the market share was identified. For cross-validation, the adoption of AI agents solutions and services among industries, along with different use cases with respect to their regions, was identified and extrapolated. Weightage was given to use cases identified in different regions for the market size calculation.
Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the AI agents market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major AI agents providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primary interviews, the exact values of the overall AI agents market size and segments’ size were determined and confirmed using the study.
Global AI Agents Market Size: Bottom-Up and Top-Down Approach:
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Data Triangulation
After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Market Definition
AI agents are autonomous or semi-autonomous software entities designed to perform specific tasks or roles within a digital environment by leveraging artificial intelligence techniques such as machine learning, natural language processing, and decision-making algorithms. These agents operate independently or in conjunction with other agents and systems to achieve predefined goals, often mimicking human behaviors such as understanding, reasoning, learning, and interacting with users or other systems. AI agents can range from simple rule-based bots to complex, multi-agent systems capable of sophisticated interactions and collaboration. They are widely used across various industries for tasks like customer service automation, data analysis, process optimization, and personalized recommendations, offering scalability, efficiency, and enhanced user experiences.
Stakeholders
- Ready-to-deploy AI Agent vendors
- AI Agent Development Platform Vendors
- Business analysts
- Cloud service providers
- Build-Your-Own Agent Service Providers
- Enterprise end-users
- Distributors and Value-added Resellers (VARs)
- Government agencies
- Independent Software Vendors (ISV)
- Managed service providers
- Market research and consulting firms
- Support & maintenance service providers
- System Integrators (SIs)/migration service providers
- Technology providers
Report Objectives
- To define, describe, and predict the AI agents market by agent systems, product type, agent roles, end users, and region
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
- To analyze the micro markets with respect to individual growth trends, prospects, and their contribution to the total market
- To analyze the opportunities in the market for stakeholders by identifying the high-growth segments of the AI agents market
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific, Middle East Africa, and Latin America
- To profile key players and comprehensively analyze their market rankings and core competencies.
- To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the AI agents market
- To analyze the impact of recession across all the regions across the AI agents market
Available customizations
With the given market data, MarketsandMarkets offers customizations as per your company’s specific needs. The following customization options are available for the report:
Product analysis
- Product quadrant, which gives a detailed comparison of the product portfolio of each company.
Geographic analysis
- Further breakup of the North American AI agents market
- Further breakup of the European AI agents market
- Further breakup of the Asia Pacific AI agents market
- Further breakup of the Middle Eastern & African AI agents market
- Further breakup of the Latin America AI agents market
Company information
- Detailed analysis and profiling of additional market players (up to five)
Growth opportunities and latent adjacency in AI Agents Market