Author: Mike
Infobip’s CTO on Moving From Demo to Production Most enterprises have already deployed AI tools. Far fewer have built the systems, workflows, and governance needed to run them as part of daily operations. That gap — between adoption and real operational scale — is the focus of a recent Q&A with Izabel Jelenić, Chief Technology Officer at Infobip, on what it actually takes to move agentic AI from pilot to production. The Problem Isn’t Adoption — It’s Scale Enterprise investment in agentic AI keeps growing because the underlying business pressure hasn’t gone away: organisations still need to serve customers faster,…
Every enterprise technology wave produces a familiar pattern: excitement outruns infrastructure. Cloud computing had it. Big data had it. Now agentic AI is having its turn — and the gap this time is unusually wide. A recent CIO.com feature by senior writer Grant Gross captured the problem precisely: enterprises are busy deploying agents, but few understand the building blocks and blueprints necessary to engineer effective agent-enhanced business workflows. IDC predicts a tenfold increase in agent use by large enterprises by the end of this year. Yet many CIOs haven’t focused on the architecture needed to run a large fleet of…
That changed on June 16, 2026, when Databricks took the stage at its annual Data + AI Summit in San Francisco and unveiled Genie One — a new generation of general AI agents built specifically for business teams. It is not a chat assistant bolted onto a dashboard. It is an agentic coworker that understands finance, sales, marketing, and operations from the ground up, powered by a self-improving context layer called Genie Ontology. The Wall Street Journal was among the first to call it: Databricks is pushing further into AI applications for general work. This blog unpacks what Databricks actually…
The hospital room of 2026 looks very different from what it did five years ago — not just in its equipment, but in the invisible intelligence that surrounds every patient interaction. A patient sends a message at 2 a.m. worried about post-surgical symptoms. Within seconds, an AI agent has reviewed the clinical notes, cross-referenced discharge protocols, escalated a flag to the on-call nurse, and sent the patient a reassuring — and accurate — response. No human was woken up unnecessarily. No critical signal was missed. This is agentic AI in healthcare in action: not a chatbot that answers FAQ questions,…
The travel industry is taking a major step toward autonomous commerce with the launch of the world’s first End-to-End Agentic AI Travel Protocol by Travala. This innovative platform enables AI agents to search, book, and pay for travel services with minimal human involvement, signaling a new era of AI-powered travel experiences. What Makes This Launch Significant? Travala’s new Travel MCP (Model Context Protocol) allows autonomous AI agents to manage the entire travel booking process—from searching accommodations to completing payments—within a single conversational interface. The user only needs to authorize the final payment. Key Highlights ✔ AI agents can search, compare,…
Introduction As enterprises accelerate their adoption of Artificial Intelligence (AI), a new debate is emerging among technology leaders, AI architects, and data scientists: Context Engineering vs Prompt Engineering. For the past few years, prompt engineering has been considered the key to unlocking the potential of Large Language Models (LLMs). Organizations invested heavily in crafting effective prompts to improve AI outputs. However, as businesses move toward Agentic AI, autonomous AI agents, and enterprise-scale AI systems, prompt engineering alone is no longer enough. Today, successful AI deployments depend on providing AI systems with the right context, data, memory, tools, and business knowledge.…
The rise of Agentic AI is changing the way businesses operate, customers shop, and transactions are completed. While AI has already transformed recommendations, customer support, and personalization, a new era is emerging—Agentic Commerce. In this model, AI agents don’t just assist shoppers; they actively make purchasing decisions on behalf of users. Imagine an intelligent AI agent that understands your preferences, budget, goals, and constraints, then automatically researches products, compares prices, negotiates deals, and completes purchases. This shift represents one of the most significant transformations in the future of digital commerce. As organizations prepare for the next generation of AI-powered business…
The rise of Agentic AI is transforming how organizations operate, innovate, and compete. Unlike traditional AI systems that primarily generate content or provide recommendations, Agentic AI introduces autonomous agents capable of reasoning, planning, making decisions, and executing complex tasks with minimal human intervention. From intelligent customer service agents and autonomous financial advisors to self-healing IT infrastructure and AI-powered business operations, Agentic AI is rapidly becoming the next frontier of enterprise transformation. However, there is one critical challenge that many organizations overlook: Agentic AI is only as effective as the data foundation supporting it. Without modern, unified, and accessible data, even…
The rise of Agentic AI is transforming how organizations operate, innovate, and compete. Unlike traditional AI systems that primarily generate insights or respond to prompts, Agentic AI can autonomously plan, reason, make decisions, and execute tasks to achieve specific objectives. These intelligent AI agents are rapidly moving from experimental projects to mission-critical business applications across industries. From banking and healthcare to manufacturing and retail, enterprises are embracing Agentic AI to automate workflows, improve customer experiences, enhance productivity, and accelerate decision-making. However, as organizations deploy increasingly autonomous AI systems, a new challenge has emerged—AI governance. While most discussions around Agentic AI…
The Life Sciences industry is entering a new era of transformation driven by artificial intelligence. For years, pharmaceutical companies, biotechnology firms, medical device manufacturers, and healthcare organizations have leveraged AI to accelerate research, improve clinical trials, enhance patient outcomes, and streamline operations. However, the emergence of Agentic AI represents a far more significant shift—one that extends beyond operational efficiency and into the realm of regulatory compliance and governance. Unlike traditional AI systems that generate insights or recommendations, Agentic AI systems can autonomously plan, execute, monitor, and adapt actions to achieve specific goals. These intelligent agents have the potential to transform…