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Last week, Sentia attended IBM Think 2026, where leaders from across industries came together to explore how AI is reshaping the enterprise. This year’s event made one thing abundantly clear: the conversation has moved beyond experimentation - organizations are now focused on scaling AI to deliver measurable business outcomes.

As artificial intelligence (AI) continues to make waves in 2025 and beyond, other, newer, techologies are emerging. Agent AI is a rapidly evolving field within the realm of AI that focuses on creating autonomous systems capable of independent goal-directed behavior.

Unlike traditional AI models that primarily excel at specific tasks, Agent AI systems can:

Proactively pursue goals: Agents are designed to not just react to input but to actively seek out information and opportunities to achieve their objectives.

Plan and execute actions: They can formulate plans, make decisions, and take actions in the real world or within simulated environments.

Adapt and learn: Agent AI systems can learn from their experiences, adapt to changing conditions, and improve their performance over time.

These agents are capable of learning from their environment, making decisions, and executing actions to achieve specific goals. They can be found in various forms, from virtual assistants like Siri and Alexa to more complex systems used in industries such as finance, healthcare, and customer service.on, and innovation.

Undoubtedly, technology has evolved at a rapid pace over the past several decades and continues to do so. But some legacy machines that may be unfairly viewed as obsolete still hold tremendous value in today’s marketplace.

Enter IBM i – a family of mid-range computers that has gone through many name changes during the course of its lifetime.

As the image below illustrates: The evolution of IBM i began in the late 1970’s with the AS/400 (Application System/400) being introduced in 1988 as the successor of the previous two models.