Executive Summary Definition: AI agents are autonomous systems that perceive data, reason through complex goals, and execute multi-step workflows across enterprise software without human intervention. Market Momentum: The global AI agent market is projected to reach RM 31.2 billion by the end of 2025, driven by a 40% annual growth rate. Core Benefit: Organizations adopting agentic workflows report productivity gains of 26% to 55% by automating 15% to 50% of routine business tasks.Artificial Intelligence has rapidly evolved from simple automation tools into sophisticated systems capable of reasoning, decision-making, and independent action. One of the most important developments in this evolution is the emergence of AI agents. In 2026, AI agents are becoming central to how organisations automate operations, deliver customer experiences, and make data-driven decisions. Businesses are increasingly deploying AI agents to manage workflows, support customers, analyse information, and perform tasks that previously required human involvement. The growing interest in AI agents is supported by strong market data. According to industry research, the global AI agents market was valued at approximately RM 21.3 billion (USD 5.4 billion) in 2024 and is expected to reach around RM 31.2 billion (USD 7.9 billion) by 2025, with annual growth exceeding 40%. Market Scale and Impact (2025–2026) Metric Estimated Value (RM) Source / Reference Global AI Agent Market RM 31.2 Billion Precedence Research (2025 Forecast) AI Business Value Generation RM 10.3 to 17.4 Trillion McKinsey Global Institute Gartner Enterprise Adoption 40% of Applications Gartner Press Release (Aug 2025) Routine Task Automation 15% to 50% WeAreTenet (2026 Industry Report) Customer Support Market RM 59.2 Billion ChatMaxima (2026 Forecast) Note: Conversions based on 2026 exchange rates (1 USD = 3.95 MYR). What Is an AI Agent? An AI agent is an intelligent software system designed to perceive information, make decisions, and perform tasks autonomously in order to achieve specific goals. Unlike traditional automation tools that follow rigid instructions, AI agents are capable of understanding context, learning from data, and adapting to changing situations. This allows them to perform complex actions such as analysing large datasets, responding to customer enquiries, and coordinating multiple business systems. AI agents typically combine several artificial intelligence technologies: Natural language processing (NLP) Machine learning algorithms Decision-making engines Enterprise system integrations These technologies allow AI agents to operate independently while still working alongside human teams. For businesses looking to deploy these capabilities, REDtone’s AI Agent solutions provide the necessary framework to turn these technologies into production-ready assets. The Rapid Rise of AI Agents in Business AI adoption across organisations has accelerated significantly in recent years. According to the Stanford AI Index, 78 percent of organisations reported using AI in at least one business function in 2024, a significant increase compared to previous years. Within this broader AI landscape, AI agents are emerging as a major area of investment. For example, research indicates the following: Nearly 60 percent of business leaders plan to adopt AI agents within a year as part of their digital transformation strategies. The AI agents market is projected to grow rapidly, potentially reaching RM 722.5 billion (USD 182.9 billion) by 2033  Gartner predicts that 40 percent of enterprise applications will include task-specific AI agents by 2026, up from less than 5 percent in 2025. How AI Agents Work AI agents operate through a cycle of perception, decision, and action. This process allows them to interact with their environment and complete tasks effectively. 1. Data Perception AI agents begin by collecting information from various sources. These sources may include customer queries, enterprise databases, documents, sensors, or business applications. 2. Analysis and Decision Making Once information is collected, the AI agent processes the data using machine learning models and decision frameworks. This allows the system to determine the most appropriate action based on the available information. For instance, an AI agent responding to a customer enquiry might analyse the request, identify the relevant product information, and determine whether the issue requires escalation to a human support team. 3. Action and Automation After making a decision, the AI agent performs the appropriate task. This could include answering a customer question, updating records in a CRM system, generating reports, or triggering workflow automation. How Businesses Are Using AI Agents in 2026 Customer Support Automation Customer service is one of the most common applications of AI agents. The global AI customer service market is projected to reach over RM 59.2 billion (USD 15 billion) by 2026, reflecting strong demand for intelligent automation tools. Sales and Lead Management AI agents are increasingly being used to support sales teams by managing leads and guiding potential customers through the buying process. For example, REDtone’s AI Agent solutions can qualify leads automatically, provide product information, and schedule meetings with sales representatives. Workflow and Process Automation Beyond customer-facing roles, AI agents are also being deployed internally to automate business processes. Research suggests that companies adopting AI agents can automate 15 to 50 percent of routine business tasks by 2027, significantly improving productivity. The Benefits of AI Agents for Businesses Organisations adopting AI agents often report measurable operational improvements: Improved Efficiency: Studies suggest businesses using AI technologies may see productivity gains ranging from 26 to 55 percent. Faster Response Times: AI agents can instantly respond to customer enquiries, reducing delays and improving service quality. Better Scalability: AI agents can handle thousands of interactions simultaneously without additional staffing costs. Data-Driven Decision Making: Research suggests that AI technologies could generate between RM 10.3 trillion and RM 17.4 trillion in value annually across business use cases The Future of AI Agents As artificial intelligence technologies continue to advance, AI agents are expected to become even more capable and widely adopted. Future developments will likely focus on: deeper integration with enterprise systems improved reasoning and planning capabilities multi-agent collaboration enhanced security and governance frameworks Industry analysts predict that by 2028, agentic AI will be embedded in a large share of enterprise software, transforming how organisations operate and make decisions. For businesses, the question is no longer whether AI agents will become important, but how