Agentic AI Applications in Vector Database Market Report is Segmented by Deployment Mode (Cloud-Managed, Self-Hosted, and More), Vector Database Type (Purpose-Built Vector Databases, and More), Application (Conversational AI and RAG, Fraud Detection and Anomaly Analytics, and More), End-User Industry (IT and Telecom, BFSI, and More), and Geography (North America, and More). The Market Forecasts are Provided in Terms of Value (USD).

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Agentic AI For Data Engineering Market Size 2025-2029

The agentic ai for data engineering market size is valued to increase by USD 3.77 billion, at a CAGR of 39.2% from 2024 to 2029. Increasing demand for real-time data processing and analytics will drive the agentic ai for data engineering market.

Major Market Trends & Insights

North America dominated the market and accounted for a 33% growth during the forecast period.
By Deployment - Cloud segment accounted for the largest market revenue share in 2023
CAGR from 2024 to 2029 : 39.2%

Market Summary

The market is experiencing significant growth, driven by the increasing demand for real-time data processing and analytics. This trend is fueled by businesses' need to make informed decisions quickly and effectively in today's competitive landscape. Autonomous data pipelines and self-optimizing Extract, Transform, Load (ETL) processes are emerging as key solutions, enabling continuous data flow and reducing manual intervention. However, this evolution brings new challenges, such as data governance and compliance complexities. As businesses navigate these complexities, Agentic AI becomes increasingly essential, offering advanced capabilities to manage and secure data while ensuring regulatory compliance.
Agentic AI systems leverage machine learning and natural language processing to understand context and intent, enabling them to automate data engineering tasks and improve overall data management efficiency. With their ability to learn and adapt, these systems offer a promising future for businesses seeking to maximize the value of their data assets.

What will be the Size of the Agentic AI For Data Engineering Market during the forecast period?

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How is the Agentic AI For Data Engineering Market Segmented and what are the key trends of market segmentation?

The agentic ai for data engineering industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Solutions
  Services


Deployment

  Cloud
  On-premises


End-user

  BFSI
  Healthcare
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Component Insights

The solutions segment is estimated to witness significant growth during the forecast period.

The market continues to evolve, driven by the increasing demand for scalable data infrastructure and intelligent data processing solutions. Solutions in this segment primarily comprise software platforms, specialized tools, and integrated applications that enable agentic AI capabilities for data engineering. These solutions offer autonomous data management and processing, featuring intelligent data discovery, automated schema inference, adaptive data pipelines, and predictive maintenance for data quality.

In February 2024, Databricks announced the public preview of Delta Sharing's storage optimization feature in its Lakehouse Platform, allowing for more efficient data sharing. With organizations facing growing data volumes and complexity, the need for robust, intelligent solutions is accelerating. The market for agentic AI in data engineering is projected to grow by 25% in the next year, underscoring its importance in the modern data landscape.

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The Solutions segment was valued at USD 0.00 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 33% to the growth of the global market during the forecast period.Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

See How Agentic AI For Data Engineering Market Demand is Rising in North America Request Free Sample

Agentic AI in data engineering is experiencing significant growth in North America, fueled by advanced technological infrastructure, a high concentration of AI research and development, and a culture of innovation. The United States, in particular, leads in the adoption of data solutions across industries such as technology, finance, and healthcare. The increasing complexity and volume of datasets necessitate automated, self-optimizing data pipelines, a key offering of agentic AI. North America's mature venture capital ecosystem actively funds AI startups, fostering a competitive and dynamic market landscape.

According to recent studies, the agentic AI market in North America is projected to grow at an impressive pace, with the number of AI-powered data engineering projects increasing exponentially. This regio

Agentic Coding Dataset for Tessa

A comprehensive dataset for training coding agents with tool-use, reasoning, and software engineering capabilities.

  Dataset Composition

This dataset combines multiple high-quality sources:

hermes_reasoning (20.0%): Tool-use and reasoning dataset - interstellarninja/hermes_reasoning_tool_use search_arena (15.0%): Search and retrieval tasks - lmarena-ai/search-arena-24k arena_human_pref (15.0%): Human preference data for alignment -… See the full description on the dataset page: https://huggingface.co/datasets/smirki/Agentic-Coding-Tessa.

Artificial intelligence agents are poised to revolutionize business operations in the coming years. While many organizations are planning to integrate AI agents within the next three years, a significant portion anticipate longer-term implementation for more complex tasks. This shift towards AI-driven business processes reflects the growing importance of automation and data-driven decision-making in the corporate world. Near-term focus on modernization and quality assurance By 2025, businesses are prioritizing the upgrade and modernization of functions and integrations, with ** percent of organizations planning to implement these changes within the next three years. Quality assurance of digital functions and systems is also a key near-term objective, with ** percent of companies focusing on this area. These initiatives indicate a strong emphasis on laying the groundwork for more advanced AI integration in the future. Long-term vision for comprehensive AI integration Looking beyond the immediate future, organizations have ambitious plans for AI agent integration. Many businesses expect to implement workflow automations that span across the organization and access functions from third-party systems within **** or more years. This long-term outlook aligns with executive beliefs that the general public will be using AI agents more than websites or apps from 2031 onwards, with most anticipating this shift to occur from 2036 and later. As research in agentic systems continues to grow exponentially, businesses are preparing for a future where AI agents play a central role in their operations.

Agentic AI Market Outlook

According to our latest research, the global Agentic AI market size reached an impressive USD 6.9 billion in 2024, reflecting robust demand and rapid technological advancements. The market is projected to grow at a compelling CAGR of 34.2% from 2025 to 2033, positioning the industry to achieve an estimated USD 85.2 billion by 2033. This remarkable expansion is being fueled by the increasing integration of autonomous, goal-oriented AI systems across diverse industries and the growing need for intelligent automation to drive operational efficiency and innovation.

The primary growth factor for the Agentic AI market is the escalating adoption of advanced AI-driven solutions that empower machines to act independently, make decisions, and achieve complex objectives with minimal human intervention. Organizations across sectors such as healthcare, finance, and manufacturing are leveraging Agentic AI to automate intricate workflows, enhance productivity, and reduce operational costs. The proliferation of big data, advancements in machine learning algorithms, and the availability of high-performance computing resources have further accelerated the deployment of Agentic AI systems. As a result, enterprises are increasingly investing in AI-powered tools that not only augment human capabilities but also deliver strategic value by enabling autonomous decision-making and adaptive problem-solving.

Another significant driver propelling the Agentic AI market is the surge in demand for personalized customer experiences and intelligent digital assistants. Businesses in retail, media, and telecommunications are utilizing Agentic AI to analyze customer behavior, predict preferences, and deliver tailored recommendations in real-time. The ability of Agentic AI to process vast amounts of data, learn from interactions, and autonomously refine its strategies has transformed customer engagement models and fostered deeper brand loyalty. Furthermore, the integration of Agentic AI in cloud-based platforms has democratized access to advanced AI capabilities, enabling small and medium enterprises (SMEs) to compete effectively with larger counterparts and drive innovation at scale.

In addition to the expanding use cases, regulatory support and industry collaboration have played a pivotal role in shaping the growth trajectory of the Agentic AI market. Governments and industry bodies are actively promoting the ethical deployment of Agentic AI, establishing frameworks to ensure transparency, accountability, and data privacy. These initiatives have bolstered stakeholder confidence and accelerated the adoption of AI-driven automation solutions across critical sectors such as BFSI, healthcare, and manufacturing. As organizations continue to prioritize digital transformation and resilience, the demand for intelligent, agentic systems is expected to witness sustained growth throughout the forecast period.

Regionally, North America remains the dominant market for Agentic AI, driven by substantial investments in research and development, a mature technology ecosystem, and early adoption by key industry verticals. Europe closely follows, benefiting from strong regulatory frameworks and a focus on digital innovation. The Asia Pacific region is emerging as a high-growth market, fueled by rapid industrialization, expanding digital infrastructure, and increasing government initiatives to promote AI adoption. Latin America and the Middle East & Africa are also witnessing steady growth, albeit at a slower pace, as businesses in these regions gradually embrace advanced AI technologies to enhance competitiveness and operational efficiency.

AI Storage is becoming increasingly critical as the demand for Agentic AI systems continues to rise. With the exponential growth of data generated by these systems, efficient storage solutions are essential to manage and process information effectively. AI Storage solutions are designed to handle vast amounts of data, ensuring quick access and retrieval, which is crucial for real-time decision-making and autonomous operations. These storage systems are optimized for AI workloads, providing the scalability and speed necessary to support complex algorithms and large datasets. As organizations adopt more AI-driven technologies, the role of AI Storage in maintaining seamless operations and enhancing system performance becomes indispensable.

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Agentic AI Market Size 2025-2029

The agentic ai market size is valued to increase by USD 22.27 billion, at a CAGR of 38.7% from 2024 to 2029. Maturation and proliferation of advanced foundation models will drive the agentic ai market.

Major Market Trends & Insights

North America dominated the market and accounted for a 40% growth during the forecast period.
By Component - Solutions segment was valued at USD 368.40 billion in 2023
By Deployment - Cloud segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 5.00 million
Market Future Opportunities: USD 22272.60 million
CAGR from 2024 to 2029 : 38.7%

Market Summary

The market is experiencing significant growth, with recent estimates suggesting it will reach a value of USD12.5 billion by 2025. This expansion is driven by the maturation and proliferation of advanced foundation models, which have enabled the development of increasingly sophisticated agentic AI systems. These agents, designed to perform tasks autonomously and adapt to new environments, are moving beyond general-purpose applications and into specialized, vertical markets. However, the evolution of agentic AI is not without challenges. The reliability and control dilemma persists, as organizations grapple with ensuring these autonomous systems make decisions that align with their strategic objectives. Balancing the benefits of agentic AI's adaptability and efficiency with the need for human oversight and accountability remains a critical issue. Despite these challenges, the future direction of agentic AI is clear: towards increasingly autonomous, intelligent systems that can drive business growth and innovation.

What will be the Size of the Agentic AI Market during the forecast period?

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How is the Agentic AI Market Segmented ?

The agentic ai industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ComponentSolutionsServicesDeploymentCloudOn-premisesEnd-userHealthcareIT and telecomBFSIOthersGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW)

By Component Insights

The solutions segment is estimated to witness significant growth during the forecast period.

The market continues to evolve, driven by advancements in data privacy regulations, generative adversarial networks, and cloud-based AI solutions. This market segment, comprising software, platforms, and frameworks, is characterized by rapid innovation and intense competition. Agent development frameworks, such as those offering logic orchestration, memory modules, and tool integration interfaces, are foundational, enabling developers to build customized and flexible agentic systems. Reinforcement learning methods, API integrations, and natural language processing are integral to AI infrastructure, which includes large language models, algorithmic bias mitigation, and model evaluation metrics. Data augmentation techniques, deep learning algorithms, and machine learning models are employed in data preprocessing methods, while AI ethics guidelines, hybrid AI architectures, and distributed computing facilitate responsible AI development. Performance optimization, software development kits, parallel computing, and on-premise AI deployments are essential for scaling agentic capabilities. Explainable AI techniques, transfer learning approaches, and model interpretability methods enhance model training pipelines and supervised/semi-supervised learning tasks. Neural network architectures, unsupervised learning tasks, and hardware acceleration underpin computer vision systems and model deployment strategies. Overall, the market is a dynamic and intricate ecosystem, with ongoing activities and evolving patterns shaping its future trajectory. According to recent reports, The market is projected to grow at a compound annual growth rate of 40.2% between 2021 and 2028.

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The Solutions segment was valued at USD 368.40 billion in 2019 and showed a gradual increase during the forecast period.

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Regional Analysis

North America is estimated to contribute 40% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

See How Agentic AI Market Demand is Rising in North America Request Free Sample

The market is currently undergoing rapid evolution, with North America leading the charge. The region, primarily driven by the United States, is the global hub for agentic AI research, investment, and inno

Discover how Agentic AI is revolutionizing data engineering. The market will hit USD 71.4 Bn by 2034, driven by automation, real-time insights, and innovation.

Agentic AI Platform Market Outlook

According to our latest research, the global Agentic AI Platform market size reached USD 5.8 billion in 2024, driven by accelerating digital transformation and automation initiatives across industries. The market is expected to post a robust CAGR of 24.7% from 2025 to 2033, with the total market value forecasted to reach USD 43.2 billion by 2033. Key growth factors fueling this expansion include the increasing adoption of autonomous AI agents, advancements in machine learning algorithms, and the growing need for scalable, intelligent automation solutions in both large enterprises and SMEs.

One of the primary growth drivers of the Agentic AI Platform market is the rapid evolution of artificial intelligence technologies, particularly those enabling agentic behaviors such as autonomous decision-making, adaptive learning, and proactive task execution. As organizations strive to streamline operations, reduce human intervention, and enhance productivity, agentic AI platforms are increasingly being integrated into core business processes. These platforms empower digital agents to autonomously manage workflows, optimize resource allocation, and deliver personalized customer experiences, thus enabling organizations to achieve greater operational efficiency and agility. Additionally, the continuous influx of venture capital and strategic investments in AI startups is accelerating the pace of innovation, further propelling market growth.

Another significant growth factor is the surge in demand for intelligent automation across diverse industry verticals. Sectors such as healthcare, finance, manufacturing, and retail are leveraging Agentic AI Platforms to automate complex tasks, enhance data-driven decision-making, and improve service delivery. For instance, in healthcare, agentic AI is being used for patient monitoring, diagnostics, and personalized treatment planning, while in finance, it supports fraud detection, algorithmic trading, and customer service automation. The ability of agentic AI to process vast amounts of data, learn from real-time interactions, and deliver actionable insights is revolutionizing traditional business models and creating new avenues for revenue generation and competitive differentiation.

Furthermore, the proliferation of cloud computing and the increasing adoption of hybrid and multi-cloud environments are providing a significant boost to the Agentic AI Platform market. Cloud-based deployment offers scalability, flexibility, and cost-efficiency, enabling organizations of all sizes to implement sophisticated agentic AI solutions without the need for substantial upfront investments in infrastructure. This trend is particularly beneficial for small and medium enterprises (SMEs), which are now able to harness the power of advanced AI technologies previously accessible only to larger corporations. The integration of agentic AI with cloud-native architectures, edge computing, and IoT ecosystems is further expanding the application scope of these platforms, driving sustained market growth over the forecast period.

From a regional perspective, North America currently dominates the Agentic AI Platform market, accounting for the largest market share in 2024, followed closely by Europe and Asia Pacific. The strong presence of leading technology providers, robust R&D investments, and early adoption of AI-driven automation solutions are key factors contributing to North America's leadership position. Meanwhile, Asia Pacific is emerging as the fastest-growing region, fueled by rapid industrialization, digitalization initiatives, and increasing government support for AI innovation. Latin America and the Middle East & Africa are also witnessing steady growth, albeit from a smaller base, as organizations in these regions gradually embrace agentic AI to enhance competitiveness and operational efficiency.

Component Analysis

The Agentic AI Platform market by component is segmented into software, hardware, and services, each playing a pivotal role in the overall ecosystem. The software segment currently holds the largest market share, driven by the proliferation of AI development frameworks, agent orchestration tools, and autonomous decision-making engines. These software solutions enable organizations to design, deploy, and manage intelligent agents capable of executing complex tasks with minimal human intervention. The continuous evolution of AI algorithms, natural language pro

Dataset

This dataset was created by Maham9

Released under CC0: Public Domain

Contents

Market Insights

Based on insights provided by Market.us, the Agentic AI in HR & Recruitment market is projected to witness substantial growth, reaching approximately USD 23,172.8 million by 2034, up from USD 842.3 million in 2024, expanding at an impressive compound annual growth rate (CAGR) of 39.3% during the forecast period from 2025 to 2034. The rapid adoption of AI-driven recruitment solutions, automation in HR processes, and demand for data-driven talent acquisition strategies are key drivers fueling this market expansion.

In 2024, North America led the market, capturing over 37.1% of the total revenue, which amounted to USD 312.4 million. The region’s strong position is driven by the widespread adoption of AI-powered HR technologies among large enterprises, the increasing need for efficient hiring processes, and the presence of major AI solution providers. The integration of AI in talent acquisition, employee engagement, and workforce analytics is significantly transforming HR operations across industries.

As organizations continue to prioritize efficiency, diversity, and unbiased recruitment, the demand for AI-driven HR solutions is expected to surge. The expansion of generative AI, machine learning algorithms, and natural language processing in HR applications will further accelerate market growth. With advancements in AI-based predictive hiring, candidate assessment, and workforce management, the Agentic AI in HR & Recruitment market is set to redefine the future of talent acquisition and employee experience globally.

AI Training Data | Annotated Checkout Flows for Retail, Restaurant, and Marketplace Websites Overview

Unlock the next generation of agentic commerce and automated shopping experiences with this comprehensive dataset of meticulously annotated checkout flows, sourced directly from leading retail, restaurant, and marketplace websites. Designed for developers, researchers, and AI labs building large language models (LLMs) and agentic systems capable of online purchasing, this dataset captures the real-world complexity of digital transactions—from cart initiation to final payment.

Key Features

Breadth of Coverage: Over 10,000 unique checkout journeys across hundreds of top e-commerce, food delivery, and service platforms, including but not limited to Walmart, Target, Kroger, Whole Foods, Uber Eats, Instacart, Shopify-powered sites, and more.

Actionable Annotation: Every flow is broken down into granular, step-by-step actions, complete with timestamped events, UI context, form field details, validation logic, and response feedback. Each step includes:

Page state (URL, DOM snapshot, and metadata)

User actions (clicks, taps, text input, dropdown selection, checkbox/radio interactions)

System responses (AJAX calls, error/success messages, cart/price updates)

Authentication and account linking steps where applicable

Payment entry (card, wallet, alternative methods)

Order review and confirmation

Multi-Vertical, Real-World Data: Flows sourced from a wide variety of verticals and real consumer environments, not just demo stores or test accounts. Includes complex cases such as multi-item carts, promo codes, loyalty integration, and split payments.

Structured for Machine Learning: Delivered in standard formats (JSONL, CSV, or your preferred schema), with every event mapped to action types, page features, and expected outcomes. Optional HAR files and raw network request logs provide an extra layer of technical fidelity for action modeling and RLHF pipelines.

Rich Context for LLMs and Agents: Every annotation includes both human-readable and model-consumable descriptions:

“What the user did” (natural language)

“What the system did in response”

“What a successful action should look like”

Error/edge case coverage (invalid forms, OOS, address/payment errors)

Privacy-Safe & Compliant: All flows are depersonalized and scrubbed of PII. Sensitive fields (like credit card numbers, user addresses, and login credentials) are replaced with realistic but synthetic data, ensuring compliance with privacy regulations.

Each flow tracks the user journey from cart to payment to confirmation, including:

Adding/removing items

Applying coupons or promo codes

Selecting shipping/delivery options

Account creation, login, or guest checkout

Inputting payment details (card, wallet, Buy Now Pay Later)

Handling validation errors or OOS scenarios

Order review and final placement

Confirmation page capture (including order summary details)

Why This Dataset?

Building LLMs, agentic shopping bots, or e-commerce automation tools demands more than just page screenshots or API logs. You need deeply contextualized, action-oriented data that reflects how real users interact with the complex, ever-changing UIs of digital commerce. Our dataset uniquely captures:

The full intent-action-outcome loop

Dynamic UI changes, modals, validation, and error handling

Nuances of cart modification, bundle pricing, delivery constraints, and multi-vendor checkouts

Mobile vs. desktop variations

Diverse merchant tech stacks (custom, Shopify, Magento, BigCommerce, native apps, etc.)

Use Cases

LLM Fine-Tuning: Teach models to reason through step-by-step transaction flows, infer next-best-actions, and generate robust, context-sensitive prompts for real-world ordering.

Agentic Shopping Bots: Train agents to navigate web/mobile checkouts autonomously, handle edge cases, and complete real purchases on behalf of users.

Action Model & RLHF Training: Provide reinforcement learning pipelines with ground truth “what happens if I do X?” data across hundreds of real merchants.

UI/UX Research & Synthetic User Studies: Identify friction points, bottlenecks, and drop-offs in modern checkout design by replaying flows and testing interventions.

Automated QA & Regression Testing: Use realistic flows as test cases for new features or third-party integrations.

What’s Included

10,000+ annotated checkout flows (retail, restaurant, marketplace)

Step-by-step event logs with metadata, DOM, and network context

Natural language explanations for each step and transition

All flows are depersonalized and privacy-compliant

Example scripts for ingesting, parsing, and analyzing the dataset

Flexible licensing for research or commercial use

Sample Categories Covered

Grocery delivery (Instacart, Walmart, Kroger, Target, etc.)

Restaurant takeout/delivery (Ub...

Discover why data quality trumps code in modern AI applications vs SaaS. Key insights on how structured enterprise data drives superior AI workflows and outcomes.

Banking executives cited governance, risk, and compliance as the biggest challenge to creating value from agentic AI in 2025, with ** percent naming it a top-three concern. More than half also pointed to a lack of technology skills and capabilities (** percent) and poor data quality and integration (** percent). Fewer see prioritization of use cases (** percent) or change management processes (** percent) as major hurdles. Overall, the survey indicated that organizational readiness and data foundations were the main barriers to scaling agentic AI effectively.

xDAN-Vision/xDAN-Agentic-Data-Instruct-v1-sample dataset hosted on Hugging Face and contributed by the HF Datasets community

This dataset contains the predicted prices of the asset AGENTIC github.com/transitive-bullshit/AGENTIC over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

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Agentic AI For Financial Services Market Size 2025-2029

The agentic AI for financial services market size is forecast to increase by USD 10.95 billion, at a CAGR of 44.2% between 2024 and 2029.

The market is experiencing significant growth, driven by the imperative for enhanced operational efficiency and the emergence of orchestrated multi-agent ecosystems. These advanced AI systems are revolutionizing the financial sector by automating complex processes, improving risk management, and enhancing customer experience. However, the market faces challenges in navigating complex regulatory and compliance frameworks. These obstacles necessitate a deep understanding of evolving regulations and the ability to adapt quickly to changing requirements. Robo-advisory platforms leverage deep learning finance for personalized financial advice, and chatbots provide customer service with natural language processing.
The strategic landscape of the market is dynamic and competitive, with ongoing innovation and advancements shaping the future of the industry. Companies must stay informed of emerging trends and be prepared to adapt quickly to remain competitive and deliver value to their customers. Companies seeking to capitalize on market opportunities must invest in AI technologies that can effectively address these challenges while ensuring data security and privacy.

What will be the Size of the Agentic AI For Financial Services Market during the forecast period?

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The agentic AI market in financial services continues to evolve, with innovative applications emerging across various sectors. Decentralized finance AI is revolutionizing peer-to-peer transactions, while anti-money laundering AI enhances regulatory compliance. Fraud detection models employ machine learning finance to identify anomalous patterns, and algorithmic trading strategies optimize portfolio performance. Predictive analytics finance and explainable AI finance offer insights into market trends and investment decisions. Credit scoring models and financial data analytics drive risk assessment, while blockchain financial services secure transactions.
Sentiment analysis finance monitors market sentiment, and high-frequency trading AI executes trades in real-time. Portfolio optimization AI maximizes returns, and financial inclusion AI expands access to financial services. Agent-based modeling finance simulates complex financial systems, and investment decision support uses reinforcement learning finance to make informed choices. Regulatory compliance AI ensures adherence to industry standards, and algorithmic risk management mitigates potential losses. Predictive analytics and data analytics are enabling financial institutions to make informed decisions, while computer vision and image recognition are enhancing risk management and anti-money laundering (AML) efforts.

How is this Agentic AI For Financial Services Industry segmented?

The agentic AI for financial services industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Enterprise agentic AI
  Personal agentic AI


Deployment

  Embedded standalone agents
  Orchestrated agentic ecosystems


Application

  Fraud detection and prevention
  Financial crime and compliance
  Credit and loan processing
  Automated trading and portfolio management
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The Enterprise agentic AI segment is estimated to witness significant growth during the forecast period. The agentic AI market in financial services is experiencing significant growth, with enterprise adoption increasing by 21% in the past year. This trend is expected to continue, as industry experts predict a 25% rise in AI integration across financial institutions within the next five years. Decentralized finance, robo-advisory platforms, and chatbots are leading the charge, utilizing AI for fraud detection, risk assessment, and predictive analytics. Deep learning finance models are revolutionizing algorithmic trading strategies and AI-driven investment strategies, enabling real-time market analysis and personalized financial advice. AI-powered trading, agent-based modeling, and explainable AI are transforming financial modeling and investment decision support. The future of AI in financial services is bright, with ongoing innovation and integration set to reshape the industry landscape.

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The Enterprise agentic AI segment was valued at USD 344.60 million in 2019 and showed a gradua

This dataset contains the predicted prices of the asset Agentic Studio over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset contains the predicted prices of the asset Agentic Economy over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Dataset

This dataset was created by Keeby1237(Smilyai labs)

Released under Apache 2.0

Contents

This dataset contains the predicted prices of the asset WAV3 Agentic Music Discovery by Virtuals over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.