What Agentic AI Is, and What It Isn't: Jacob Andra and Dr. Alexandra Pasi #agenticAI #aiagents #ai

Description

What is agentic AI? (And what it isn't) Most discussions about agentic AI start from flawed assumptions. The term gets tossed around as if everyone agrees on what it means, but scratch the surface and you'll find wildly different definitions, each with its own problems. In this episode, Talbot West CEO Jacob Andra interviews Dr. Alexandra Pasi, CEO of Lucidity Sciences and machine learning researcher, to cut through the confusion around agentic AI. Together, they examine three common but problematic ways people define agentic AI, and why each falls short when you're trying to build practical AI systems for your organization. The three flawed definitions we tackle: 1. The "digital employee" definition Some vendors pitch agentic AI as a complete replacement for human workers—hire the AI, fire the person. This framing misses the mark entirely. Current AI capabilities can't replicate the full scope of human expertise and judgment that real roles require. It's a marketing angle, not a functional definition. When vendors talk about digital employees, they're setting unrealistic expectations that lead to failed implementations and damaged trust in AI initiatives. 2. The "full autonomy" definition Another common take: agentic AI means the system completes tasks with zero human involvement. Book a flight, conduct market research, handle it end to end. But autonomy alone doesn't require AI at all. Zapier workflows and similar automation platforms have been handling autonomous tasks for years without any LLM involvement. If the definition applies equally well to pre-AI automation, it's not a useful way to think about agentic AI. This definition conflates automation with intelligence, missing what makes AI capabilities distinct and valuable. 3. The definition that actually works An AI function that completes tasks as part of a larger ensemble or system. This framing recognizes that agentic AI doesn't exist in isolation. It operates within broader workflows, coordinates with other AI components and human oversight, and contributes specific capabilities to compound intelligence rather than trying to replicate entire job functions. This modular approach aligns with how successful organizations actually build and deploy AI—not as replacement workers, but as specialized capabilities that enhance human decision-making and organizational intelligence. Why this matters for your organization If you're building or buying AI systems, the definition you use shapes your entire approach. Think agentic AI means replacing employees? You'll chase unrealistic outcomes and create change management nightmares. Think it just means automation? You'll miss the actual intelligence layer that AI brings. But frame it as component capabilities within larger systems? Now you can build modular, explainable architectures that actually deliver value. This conversation between Jacob and Dr. Pasi strips away the hype and gives you a clear framework for thinking about agentic AI in practical terms. No buzzwords, no vendor spin—just the functional understanding you need to make smart decisions about AI implementation. The discussion explores why the term "agentic" has stuck around despite its baggage, and what this means for building toward true organizational intelligence. Dr. Pasi brings her research background to bear on practical implementation questions, while Jacob connects these concepts to the real-world challenges executives face when trying to move from pilot projects to production systems. What you'll learn: The fundamental difference between automation and intelligent agency, and why confusing the two leads to poor AI strategy. How to think about AI as modular components rather than monolithic replacements. The path from isolated AI tools to compound intelligence through ensemble architectures. Why vendor definitions often obscure what agentic AI can actually do for your organization. If you're a decision-maker trying to separate signal from noise in the AI space, this conversation will save you from expensive mistakes. Whether you're just starting to explore AI capabilities or working to expand existing implementations, understanding what agentic AI actually means is foundational to making smart strategic choices. About Dr. Alexandra Pasi Dr. Alexandra Pasi is CEO of Lucidity Sciences and a machine learning researcher bringing academic rigor and practical experience to AI implementation challenges. About Talbot West Talbot West is a boutique AI consultancy helping mid-market companies navigate digital transformation without the technical debt or strategic dead ends. We focus on what actually works when building organizational intelligence in real companies with real constraints. Hosted by Jacob Andra, CEO of Talbot West. Connect with Talbot West Website: talbotwest.com LinkedIn: linkedin.com/company/talbot-west Schedule a consultation: talbotwest.com/contact