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Agentic AI Revolution: Market Growth, Technological Trends, and Business Impact in 2025

General Report June 4, 2025
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TABLE OF CONTENTS

  1. Emergence of Agentic AI in Enterprise Operations
  2. Market Forecasts for Agentic AI Solutions and AI Agents
  3. AI Chip Market Dynamics and Supply Chain
  4. Industry Adoption and Strategic Investments
  5. Sector-Specific Applications and Opportunities
  6. Conclusion

1. Summary

  • Agentic AI, defined as autonomous decision-making software agents capable of interpreting data and acting independently, has grown to be a focal point within enterprise operations by June 4, 2025. Its integration marks a pivotal evolution from traditional AI, which relied predominantly on providing insights without the capacity for autonomous action. Rising from its inception, Agentic AI effectively enhances operational efficiency and responsiveness in various sectors, thanks to advancements in large language models (LLMs) facilitating real-time decision-making. With a significant 82% of enterprises planning to deploy these AI agents by 2027, the trajectory indicates a robust commitment towards operational transformation across industries.

  • Various impactful use cases have emerged across sectors with Agentic AI, particularly in customer service, where it is projected that up to 80% of common issues could be resolved autonomously by 2029. This significant shift not only streamlines operations but also allows human resources to focus on more complex tasks. Financial services leverage these systems to create personalized investment strategies and optimize fraud detection. Manufacturing sectors utilize Agentic AI for real-time inventory management, further highlighting its broad applicability in enhancing operational workflows.

  • Market forecasts paint a positive picture for the future of Agentic AI, particularly in predictive analytics, with expectations for the AI Agents for Predictive Analytics market to climb from USD 2.7 billion in 2024 to USD 50.8 billion by 2034. Such expansive growth reflects a compound annual growth rate (CAGR) of 34.1% from 2025 to 2034. Driving factors for this expansion include the escalating need for real-time insights across various industries, effectively positioning AI agents as indispensable components in the digital landscape. Furthermore, the OSINT market is on track to reach USD 46.12 billion by 2034, emphasizing the necessity of integrating AI solutions for actionable intelligence.

  • In terms of strategic investments, Salesforce's recent acquisition of Informatica for $8 billion marks a significant step towards enhancing its AI capabilities. Additionally, insights from a Microsoft-sponsored IDC report reveal that organizations are achieving a 3.7 times return on investment with Generative AI (GenAI), emphasizing this technology's importance in operational frameworks. Coupled with the projected 327% surge in AI agent adoption by 2027, businesses need to realign their digital strategies to incorporate these emerging technologies effectively.

2. Emergence of Agentic AI in Enterprise Operations

  • 2-1. Definition and evolution of Agentic AI

  • Agentic AI refers to advanced autonomous decision-making systems capable of interpreting data, making decisions, and taking actions without human intervention. This evolution marks a significant departure from earlier forms of artificial intelligence, such as traditional predictive analytics and robotic process automation. Where traditional systems provided insights or forecasts, Agentic AI operates with a level of autonomy akin to that of a human decision-maker. As of June 4, 2025, it is increasingly recognized as a critical asset for enterprise operations, enhancing responsiveness and operational efficiency.

  • The transition towards Agentic AI has been accelerated by advancements in large language models (LLMs) and their applications in real-time, adaptive decision-making. Previously considered theoretical, the integration of these autonomous agents into business processes is now being recognized as a transformative step for organizations. As reflected in TechRadar’s June 3 analysis, a vast majority of enterprises—approximately 82%—plan to incorporate some form of AI agents by 2027.

  • 2-2. Autonomous decision-making use cases

  • The implementation of Agentic AI has led to numerous use cases across various sectors. In customer service, for example, AI agents are expected to resolve up to 80% of common issues autonomously by 2029, significantly reducing wait times for customers and alleviating the burdens on human support staff. This transformation reflects broader trends within the enterprise landscape, where repetitive tasks are increasingly automated, freeing employees to focus on complex, judgment-based responsibilities.

  • In addition to customer service, applications in financial services include agents designing personalized investment strategies and detecting fraudulent transactions. Manufacturing sectors leverage Agentic AI for inventory management and supply chain optimization, with agents able to autonomously analyze production data and adjust operations in real-time based on conditions and demands.

  • 2-3. Transition from insights to execution

  • Agentic AI exemplifies a crucial shift from merely generating insights to executing actions based on those insights, thus driving greater operational efficiencies. As described by ET Edge Insights in June 2025, traditional analytical methodologies often culminated in reports that required human interpretation and action. In contrast, Agentic AI systems autonomously initiate decisions based on real-time data interpretation. This capability is paramount in dynamic environments where immediate responses are necessary.

  • For instance, consider a retail scenario where an AI-driven system identifies a significant drop in transaction volumes due to a technical issue. Instead of alerting a human operator to intervene, Agentic AI would autonomously engage backup systems to rectify the problem while notifying the relevant technical teams. This level of operational intelligence marks a historical turning point in how enterprises will function in real-time markets.

  • 2-4. Core architectures and data requirements

  • The architecture underpinning Agentic AI relies on multifaceted frameworks that facilitate autonomous decision-making through real-time data access and integration. A pivotal structure is the event-driven architecture that supports dynamic data flow, enabling agents to react to changing circumstances swiftly. As noted by Edward Funnekotter from Solace, effective Agentic AI requires an event mesh to link disparate data sources and ensure that agents can operate with the most current information available.

  • This architecture enables agents to perform complex tasks by collaborating across a network, each contributing unique capabilities—whether it involves processing natural language, executing orders, or managing inventories. The modular nature of Agentic systems allows organizations to scale operations fluidly and adaptively.

  • 2-5. Key differentiators between AI agents and Agentic AI

  • The distinction between traditional AI agents and Agentic AI lies primarily in operational autonomy and adaptability. While conventional AI agents are designed to execute predefined tasks based on explicit instructions, Agentic AI employs advanced reasoning capabilities that empower it to adjust actions based on real-time insights and objectives. This distinction not only enhances efficiency but also mitigates delays associated with human oversight.

  • As an example, in B2B environments, Agentic AI can manage intricate order processing, handling everything from data extraction to final delivery notifications without human input. Additionally, the self-organizing nature of Agentic AI allows for the creation of multi-agent systems, where specialized agents can cooperate to tackle complex workflows—making them significantly more efficient than traditional, singular AI frameworks.

3. Market Forecasts for Agentic AI Solutions and AI Agents

  • 3-1. Predictive analytics agents market size and CAGR

  • The market for AI agents focused on predictive analytics is experiencing significant growth. As projected, the global AI Agents for Predictive Analytics market is expected to expand from approximately USD 2.7 billion in 2024 to USD 50.8 billion by 2034, marking a remarkable compound annual growth rate (CAGR) of 34.1% during the forecast period from 2025 to 2034. North America, which constituted over 38% of the market share in 2024 with around USD 1 billion in revenue, is anticipated to remain a dominant region due to high demand across sectors such as finance, healthcare, and retail.

  • This growth can be attributed to the increasing need for real-time insights and the ability of AI agents to process large datasets effectively. Industries are leveraging AI agents to enhance decision-making processes, manage risks, and optimize operations, all of which are critical in today’s data-driven landscape.

  • 3-2. OSINT market outlook to 2034

  • The Open Source Intelligence (OSINT) market is projected to experience robust growth over the next several years, with estimates indicating it may reach USD 46.12 billion by 2034. The market was valued at USD 8.69 billion in 2024, which translates to an impressive CAGR of 18.01% during the forecast period. Drivers of this growth include increasing cyber threats and a heightened reliance on real-time data analytics by both government agencies and private enterprises.

  • North America, particularly the United States, is leading this trend with significant investments from federal agencies into OSINT tools that bolster national security and cyber threat monitoring. As organizations strive for comprehensive data-driven insights, OSINT's role in sectors like cybersecurity, fraud detection, and corporate risk management is only expected to intensify.

  • 3-3. AI for sales and marketing segment forecasts

  • The AI for sales and marketing market is poised for exponential growth, with projections indicating it will expand from USD 57.99 billion in 2025 to USD 240.58 billion by 2030, representing a staggering CAGR of 32.9%. This anticipated growth stems largely from increasing automation demands and the rising necessity for personalized customer engagement and data-driven insights.

  • Moreover, the rapid implementation of AI-driven chatbots and virtual assistants is transforming the sales landscape by enhancing lead generation and optimizing marketing strategies. The sector is evolving swiftly, and organizations that effectively leverage these digital tools are likely to achieve significant return on investment.

  • 3-4. Adoption surge projections through 2027

  • The adoption of AI agents is set to surge dramatically, with projections suggesting an increase of 327% in deployment by the year 2027. This explosive growth is expected to reshape enterprise automation across various functions, including customer engagement, supply chain management, and cybersecurity.

  • As AI agents transition from simple rule-based systems to sophisticated autonomous collaborators, organizations must realign their digital strategies. The anticipated demand for these agents is driven by the need for enhanced operational efficiency and the ability to respond proactively to market dynamics.

  • 3-5. Comparative analysis of market reports

  • Recent market analysis reports present a consistent picture of accelerated growth across several sectors influenced by AI agents and solutions. For example, while the AI Agents for Predictive Analytics market and the OSINT economy indicate strong CAGRs of 34.1% and 18.01%, respectively, the broader AI-driven sales and marketing sector showcases an even more aggressive anticipated growth rate of 32.9%.

  • This comparative analysis underscores the diverse applications and transformative potential of AI technologies across multiple domains, reinforcing the notion that organizations poised to embrace these advancements will benefit significantly from enhanced operational agility and strategic innovation.

4. AI Chip Market Dynamics and Supply Chain

  • 4-1. Global AI chip market valuation and CAGR

  • The global AI chip market was valued at approximately USD 39.27 billion in 2024 and is projected to grow significantly, reaching about USD 501.97 billion by 2033. This growth reflects a robust compound annual growth rate (CAGR) of around 35.50% during the forecast period of 2025 to 2033. Various factors fuel this expansion, including the increasing demand for specialized hardware that enhances AI capabilities, faster data processing, and improved decision-making across industries.

  • 4-2. Projections to 2029, 2033, and 2035

  • According to various forecasts, the AI chip market is expected to exhibit significant growth in the coming years. A report published on June 3, 2025, indicated that the market is forecasted to reach USD 117.50 billion by 2029, with a CAGR of 31.06%. Moreover, projections estimate that the market could rise to approximately USD 846.8 billion by 2035, growing at a CAGR of 34.84%. These optimistic forecasts underscore the sector's potential and the urgency for enterprises to invest in AI chip technologies to remain competitive.

  • 4-3. Role of ASICs vs GPUs in Agentic AI

  • Within the AI chip landscape, application-specific integrated circuits (ASICs) and graphics processing units (GPUs) play pivotal roles. ASICs are designed for specific tasks, such as optimizing deep learning algorithms, offering unparalleled efficiency and performance for data-intensive applications. In contrast, GPUs, which were originally developed for rendering graphics, have evolved into versatile processors capable of handling a broad range of AI workloads. They are especially favored for applications requiring substantial parallel computing capabilities, such as training large-scale neural networks.

  • 4-4. Key vendors and competitive landscape

  • The competitive landscape of the AI chip market is characterized by prominent players such as NVIDIA, AMD, and Intel, each driving significant innovations and capturing substantial market shares. As of 2024, NVIDIA held a commanding 70% share of the AI semiconductor sales, with their latest GPU models like the B100 solidifying their leadership position. AMD is expanding rapidly in this field, particularly with products such as the MI300 series, which aim to compete directly with NVIDIA's offerings. Intel has also made substantial investments, notably through acquisitions like Habana Labs, which bolster its capabilities in deep learning applications.

  • 4-5. Impact of chip advances on AI performance

  • Advancements in AI chip technology significantly enhance overall AI performance. For example, the transition to smaller nodes in chip manufacturing—such as 5 nm and 3 nm processes—allows for increased transistor density, leading to higher energy efficiency and better computational power. These improvements are critical in meeting the computational demands required for AI applications. Enhanced performance metrics have been documented across various sectors from healthcare, where AI chips have improved diagnostic accuracy, to finance, where they enable faster fraud detection and risk assessment.

5. Industry Adoption and Strategic Investments

  • 5-1. Salesforce’s $8 billion Informatica acquisition

  • On May 27, 2025, Salesforce announced its intention to acquire Informatica for $8 billion. This strategic move is aimed at positioning Salesforce as a formidable competitor in the burgeoning agentic AI sector. The acquisition seekes to enhance Salesforce's data management capabilities, thereby providing a more robust platform for its AI solutions. Informatica's offerings, including its Intelligent Data Management Cloud, are expected to integrate seamlessly with Salesforce's existing services, thereby broadening their data handling across non-Salesforce systems. However, there exists a significant concern among IT leaders; a survey indicated about 48% believe that their company’s data infrastructure remains inadequate for effective AI deployment. Despite these challenges, Salesforce intends to leverage Informatica to strengthen its Agentforce strategy which focuses on simplifying the implementation of AI solutions in business processes.

  • 5-2. Microsoft-sponsored IDC report on GenAI ROI

  • A recent report by the International Data Corporation (IDC), sponsored by Microsoft, has highlighted that businesses integrating Generative AI (GenAI) across their operations are witnessing substantial returns on investment (ROI), estimated at 3.7 times the dollar spent. This report, released on June 4, 2025, articulates that businesses in various sectors are increasingly recognizing GenAI not merely as an experimental technology but as a vital component of their operations, with measurable business value being derived from its strategic implementation. In the financial services sector, GenAI shows the highest ROI; the findings indicate that firms using GenAI tools such as Microsoft Copilot are enhancing productivity and optimizing decision-making effectively.

  • 5-3. Tech executives championing Agentic AI deployments

  • Technology executives are at the forefront of accelerating the deployment of agentic AI within organizations. A survey conducted by Ernst & Young reveals that over half of the technology executives from various industries anticipate that their future AI systems will function autonomously, indicative of a significant evolution in AI’s role from mere assistive technologies to autonomous decision-making agents. This paradigm shift is not just a theoretical exercise but a strategic priority; the survey indicates that 92% of executives plan to increase their investment in AI systems, underscoring the urgent need for efficiency and innovation facilitated through AI. Despite promising perspectives, challenges remain as 81% of these executives express confidence in AI's potential to meet business objectives in 2025.

  • 5-4. Legal profession transformations with autonomous assistants

  • The legal industry is experiencing a transformative phase due to the integration of agentic AI. Recent developments have shifted agentic AI from experimental stages to practical applications used to streamline tasks in legal practice, such as contract analysis and legal research. This transition has become increasingly accessible to legal professionals across varying resource levels. The agility and promptness offered by agentic AI promise to redefine traditional roles in law, allowing practitioners to focus on high-value strategies while routine tasks are efficiently managed by AI tools. Reports indicate that as agentic AI grows more established, its implications for legal practice will necessitate skill adaptation and modification of workflows to incorporate these technologies effectively.

  • 5-5. Emerging M&A and partnership trends

  • The agentic AI landscape is witnessing a surge in mergers and acquisitions (M&A) as businesses aim to strengthen their capabilities and enhance competitive positions within this dynamic market. Recent trends indicate a significant increase in partnerships between technology firms focusing on AI, creating expansive ecosystems that support the development and deployment of agentic AI across business domains. Such strategic partnerships not only enhance technological capabilities but also crucially provide the necessary governance and compliance frameworks that are paramount as organizations navigate the complexities of integrating autonomous systems into existing workflows.

6. Sector-Specific Applications and Opportunities

  • 6-1. Intelligent agents transforming CX

  • In the evolving landscape of customer experience (CX), intelligent agents are at the forefront of transformation. As highlighted in a recent report by Tiger Analytics, organizations have increasingly shifted from traditional analytics to intelligent agent systems that not only interpret data but enable actionable insights in real time. This paradigm shift is crucial as it directly addresses the challenges related to organizational silos which slow down decision-making processes and overall customer satisfaction. The demand for personalized and responsive interactions drives companies to deploy AI-powered systems capable of analyzing a comprehensive view of customer journeys, allowing for immediate responses to changing needs and preferences.

  • Examples of successful implementations abound. A large apparel retailer has effectively integrated Agentic AI to revolutionize report generation and insight formulation. The system allows users to customize their reports using natural language prompts, streamlining the workflow and significantly enhancing operational efficiency. Similarly, a major quick-service restaurant chain employs AI to tailor marketing strategies, generating real-time insights for personalized campaigns that significantly elevate customer engagement. These use cases illustrate the potential of intelligent agents to elevate customer experience from being merely transactional to genuinely exceptional.

  • 6-2. AI-powered surveillance and planning in aerospace & defense

  • Artificial intelligence is rapidly transforming the aerospace and defense sectors, reflecting its increasing significance in operational efficiency and mission success. The market for AI in these sectors is projected to grow to $44.1 billion by 2030, demonstrating a compound annual growth rate (CAGR) of 8.8%. According to the 'Artificial Intelligence in Aerospace & Defense Strategic Research Report 2025', AI technologies are being integrated into various applications including surveillance, threat detection, and operational planning, significantly reshaping the conduct of missions.

  • AI-powered systems, such as autonomous drones and predictive maintenance tools, are enhancing real-time intelligence and operational readiness. By employing sophisticated algorithms, these systems can process and analyze colossal datasets sourced from satellites and reconnaissance missions, delivering critical insights to military commanders on the ground. This capacity for rapid data analysis and decision-making has become indispensable in modern defense operations, especially given the increasing complexity of geopolitical threats.

  • 6-3. OSINT integration for actionable intelligence

  • The Open Source Intelligence (OSINT) market is experiencing robust growth, projected to rise to $46.12 billion by 2034, with an 18.01% CAGR. A report by Exactitude Consultancy underscores this trend, attributing the growth to heightened demand for real-time data analytics amidst rising cyber threats. OSINT draws from publicly available sources, enhancing decision-making in various sectors such as national security and corporate risk management.

  • The strategic importance of OSINT is evident as government agencies adopt these tools to bolster security frameworks, counter cyber threats, and enhance proactive intelligence measures. The integration of OSINT into existing defense practices encapsulates a shift toward leveraging abundant public data for effective risk assessment and situational awareness, underscoring a progressive approach to intelligence gathering in the digital age.

  • 6-4. Vertical industry revolution through specialized GenAI

  • The rise of Generative AI (GenAI) is ushering in a new era of industry-specific applications, fundamentally altering how businesses operate. The transition from general-purpose AI capabilities to tailored, industry-specific applications signifies a strategic pivot that leverages GenAI's potential for significant operational efficiencies and market relevance. The concept of verticalization, as discussed in various recent studies, emphasizes that the true value of AI lies not in the technology itself, but in its contextual application across specific industries.

  • For instance, sectors such as finance, healthcare, and retail are increasingly deploying specialized GenAI solutions that prioritize context, enabling organizations to optimize processes and enhance decision-making. By harnessing the capabilities of GenAI within traditional business frameworks, firms can create bespoke solutions that meet unique industry challenges, ensuring that they not only integrate AI effectively but also capitalize on its transformative potential.

Conclusion

  • The current landscape of Agentic AI, as of June 4, 2025, illustrates a significant paradigm shift within enterprise operations, transitioning from experimental technologies to vital components of business strategy. Forecasts indicate that the demand for AI agents, particularly in predictive analytics and specialized applications, will witness exponential growth supported by promising CAGR rates. Noteworthy investments, such as Salesforce’s acquisition of Informatica, reveal both the heightened market interest and the imperative for organizations to innovate and integrate AI tools effectively.

  • Sector-specific applications underscore the tangible benefits Agentic AI brings, particularly in enhancing customer experience through intelligent agents and transforming aerospace and defense operations with advanced analytics. These developments not only improve efficiency but also establish a profound competitive advantage for organizations willing to adapt. Technology executives foresee an autonomous future for AI systems, with over half planning to intensify their investment in AI, confirming the relentless drive towards integrating these advanced capabilities.

  • As the industry progresses, organizations must prioritize the modernization of their data infrastructures and establish partnerships with key providers of AI chips and platforms to facilitate seamless implementation. Furthermore, developing robust governance frameworks will be essential to manage the evolving landscape of agent autonomy responsibly. Embracing Agentic AI as a core element of business strategies will not only enhance productivity but will also position enterprises favorably as leaders in the forthcoming digital revolution. The maturation of Agentic AI signifies that businesses leveraging these advanced technologies will be at the forefront of their industries, ready to capitalize on the unprecedented opportunities that lie ahead.

Glossary

  • Agentic AI: Agentic AI refers to autonomous decision-making software agents capable of interpreting data, making decisions, and taking actions independently without human intervention. As of June 4, 2025, it represents a significant evolution from traditional AI systems that primarily provided insights without actionable autonomy.
  • AI Agents: AI agents are software programs that use artificial intelligence to perform tasks autonomously. By June 4, 2025, they are expected to revolutionize various sectors, with a predicted 327% increase in their adoption by 2027, enhancing efficiency across business functions.
  • Market Forecast: Market forecasts involve predictions regarding the future growth and trends of specific sectors. The forecast for AI agents, particularly in predictive analytics, anticipates significant expansion, with the market expected to grow from USD 2.7 billion in 2024 to USD 50.8 billion by 2034.
  • CAGR: Compound Annual Growth Rate (CAGR) is a measure used to calculate the mean annual growth rate of an investment over a specified period of time longer than one year. The AI Agents for Predictive Analytics market is projected to experience a CAGR of 34.1% from 2025 to 2034.
  • AI Chips: AI chips are specialized hardware designed to accelerate artificial intelligence operations. By June 4, 2025, the market for AI chips is expected to reach approximately USD 501.97 billion by 2033, driven by growing demand for improved performance in AI applications.
  • OSINT: Open Source Intelligence (OSINT) refers to data collected from publicly available sources for intelligence purposes. By 2034, the OSINT market is projected to expand to USD 46.12 billion, driven by increasing cybersecurity concerns and the need for real-time data analytics.
  • Customer Experience (CX): Customer Experience (CX) encompasses all interactions a customer has with a company. Intelligent agents powered by Agentic AI are transforming CX by providing immediate, personalized responses to customer inquiries, indicating a shift towards a more refined customer interaction model as of June 4, 2025.
  • Generative AI ROI: Generative AI (GenAI) refers to artificial intelligence systems that can create new content. A Microsoft-sponsored IDC report released on June 4, 2025, claims organizations integrating GenAI are seeing an average return on investment (ROI) of 3.7 times their initial expenditure, highlighting the technology's growing importance.
  • Vertical Revolution: The Vertical Revolution refers to the shift towards industry-specific applications of technology. By June 4, 2025, Generative AI is leading this trend by providing tailored solutions to sectors like finance, healthcare, and retail, enhancing operational efficiency and decision-making.
  • Predictive Analytics: Predictive Analytics involves the use of statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. This sector is predicted to grow significantly, reflecting the increasing reliance on real-time insights in business decision-making.
  • Automation: Automation refers to technology that performs tasks with minimal human intervention. By June 4, 2025, the rising use of Agentic AI is set to significantly enhance automation in various business operations, allowing employees to focus on more complex tasks.
  • Digital Transformation: Digital Transformation is the integration of digital technology into all areas of a business, fundamentally changing how it operates. The adoption of Agentic AI represents a crucial aspect of digital transformation as organizations strive for operational efficiencies and competitive advantage.
  • Aerospace Defense: Aerospace Defense pertains to the sector focusing on protecting airspace and military operations using advanced technologies. By June 4, 2025, the use of AI in this field is expected to reach USD 44.1 billion by 2030, highlighting the importance of technology in enhancing mission effectiveness.
  • Salesforce Informatica: Salesforce Informatica refers to Salesforce's acquisition of Informatica, a significant investment aimed at enhancing its AI capabilities. Announced on May 27, 2025, this acquisition is expected to strengthen data management for AI solutions within Salesforce.

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