Author: Mike

The media industry is entering a new era of intelligent automation as Mediagenix has unveiled its Trusted Agentic AI Operating Model, designed to help media enterprises automate real-time operations while maintaining transparency, governance, and human oversight. The new operating model enables broadcasters, streaming platforms, and media organizations to leverage autonomous AI agents to streamline complex workflows, optimize scheduling, and improve operational efficiency across the content lifecycle. Bringing Agentic AI to Media Operations Media organizations manage an increasingly complex ecosystem of content creation, scheduling, rights management, advertising, and distribution. These processes often require rapid decision-making based on constantly changing audience behavior,…

The Rise of Autonomous AI Demands a New Approach to Identity Governance Artificial intelligence is rapidly evolving from a tool that assists employees to a workforce of autonomous agents capable of making decisions, accessing enterprise systems, and executing business processes independently. While organizations are racing to deploy agentic AI to improve productivity and automate complex workflows, a critical security challenge is emerging: AI agents are becoming some of the most privileged users in the enterprise. Unlike traditional chatbots, modern AI agents can retrieve sensitive information, interact with multiple applications, trigger financial transactions, approve workflows, and even collaborate with other AI…

As organizations accelerate the adoption of Agentic AI, a new cybersecurity challenge is rapidly emerging: managing and securing AI identities. While AI agents promise to automate workflows, improve productivity, and support employees, many enterprises are discovering that governance—not technology—is becoming the biggest obstacle to deploying autonomous AI at scale. According to industry experts, businesses are creating AI agents faster than they can establish the governance frameworks needed to manage them safely. As a result, many agentic AI initiatives remain stuck in pilot stages, unable to move into production due to concerns around security, compliance, and accountability. AI Governance Is Slowing…

Artificial Intelligence is entering a new phase. While Generative AI transformed how people create content and interact with information, Agentic AI is redefining how work gets done. Unlike traditional AI assistants, AI agents can reason, plan, make decisions, and execute multi-step tasks with minimal human intervention. This shift promises significant gains in productivity and operational efficiency, but it also introduces new risks. Autonomous AI agents are increasingly interacting with enterprise applications, financial systems, customer data, and business workflows. As a result, organizations must rethink how they govern AI. Industry experts argue that governance models designed for traditional AI are no…

India’s digital payments ecosystem could soon enter a new era as the National Payments Corporation of India (NPCI) is reportedly working on a protocol that would allow Agentic AI to initiate and complete Unified Payments Interface (UPI) transactions on behalf of users. If implemented, the initiative could transform how consumers interact with digital payments. Instead of manually searching for products, comparing prices, and approving every step, AI agents could handle much of the process autonomously while operating within user-defined rules and security controls. The proposed framework represents an important milestone in the evolution of AI-driven commerce, where intelligent software agents…

For decades, businesses have used technology to automate repetitive tasks. From robotic process automation (RPA) to intelligent chatbots and AI copilots, every wave of innovation has aimed to improve productivity and reduce manual effort. Today, enterprises are entering a new phase of digital transformation with Agentic AI. Unlike traditional AI assistants that answer questions or generate content, AI agents can understand goals, make decisions, interact with enterprise applications, coordinate with other agents, and complete multi-step workflows with minimal human intervention. This evolution raises an important question: Can AI agents become the enterprise’s next digital workforce? Increasingly, the answer appears to…

Agentic AI has rapidly become one of the most discussed technologies in enterprise artificial intelligence. Unlike traditional AI systems that generate content or answer questions, Agentic AI is designed to reason, make decisions, execute tasks, and collaborate with other systems with minimal human intervention. Organizations across industries—including banking, healthcare, manufacturing, retail, logistics, and customer service—are investing heavily in autonomous AI agents to improve productivity, automate workflows, and deliver better customer experiences. However, amid this growing enthusiasm comes a reality check. According to Gartner, more than 40% of Agentic AI projects are expected to be canceled by the end of 2027.…

What Is Context Engineering? Context Engineering is the practice of selecting, organizing, managing, and delivering the right information to an AI system at the right time so it can reason, plan, and complete tasks accurately. It combines memory, enterprise knowledge, user preferences, real-time data, business rules, and external tools to give AI agents the context they need to make intelligent decisions. For traditional AI chatbots, a prompt may be enough. For Agentic AI, which performs multi-step tasks and interacts with enterprise systems, context is the foundation of intelligence. Key Takeaways Why Context Engineering Is Becoming the Most Important AI Skill…

Enterprises Shift Beyond Traditional Automation Toward Intelligent, Self-Operating Business Processes For years, businesses have invested in automation to eliminate repetitive tasks, improve efficiency, and reduce operational costs. Robotic Process Automation (RPA), workflow engines, and AI-powered assistants have streamlined many business functions, but most still rely on human intervention for decision-making and exception handling. That is beginning to change. The rise of Agentic AI is enabling enterprises to move beyond automation toward autonomous operations, where intelligent AI agents can reason, make decisions, coordinate workflows, and execute complex business processes with minimal human involvement. This shift is laying the foundation for what…

Regulators Call for Stronger Guardrails as Autonomous AI Expands Across Banking and Financial Markets The rapid adoption of agentic AI in banking and financial services is prompting fresh warnings from central bankers and regulators, who say existing oversight frameworks may not be sufficient for increasingly autonomous AI systems. As financial institutions deploy AI agents to automate trading, payments, fraud detection, and customer service, policymakers are urging the industry to strengthen governance, resilience, and risk controls. Why Regulators Are Concerned Unlike traditional AI systems that generate recommendations, agentic AI can independently make decisions, execute transactions, and interact with multiple financial systems.…