AI Agents Market

[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

To know about the assumptions considered for the study, Request for Free Sample Report

To know about the assumptions considered for the study, download the pdf brochure

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).

Want to explore hidden markets that can drive new revenue in AI Agents Market?

Unlock Insights

Click on image to enlarge

Scope of the Report

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
• 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):

To speak to our analyst for a discussion on the above findings, click Speak to Analyst