AI has been replete with false claims since its inception, fueled in part by a widespread knowledge gap. Those without a technical background may struggle to distinguish between terms like generative AI, symbolic AI, or Agentic AI, and we’ve seen technology companies take advantage of this by claiming to offer capabilities they don’t actually provide. To make things more complicated, as AI becomes increasingly ubiquitous, companies performing even the most perfunctory statistical analysis are suddenly rebranding themselves as “machine learning companies.” This growing trend has left potential customers uncertain what different “AI” solutions can actually do.
As Agentic AI emerges, we are already seeing businesses use the term in similarly inaccurate ways—in fact, many companies that use simple “chat bots” are branding themselves as Agentic AI providers. Agentic AI represents a significant step forward for AI technology, but it’s important to understand exactly what it means. True Agentic AI is a delicate, four-way dance that balances elements of generative AI, symbolic AI, and explanatory maths and non-linear optimization engines within an agent-based presentation, upleveling human users by democratizing access to advanced technology.
Sorting through modern AI misconceptions
The definition of “artificial intelligence” is broad—but when you consider what is needed to make it both useful and robust, an ensemble of technology is required. A chat bot may be able to search the internet and summarize and regurgitate its findings, but it cannot validate data contained in Large Language Models (LLMs), nor can it reason with the subtle, human-like judgment needed to generate trusted insights. Creating an AI solution with transformative business impact requires a range of components that come together to form a larger whole. This intricate balance supports reasoning in a human-like fashion while synthesizing, analyzing, and optimizing trusted data for the end user at a scale beyond human capability. A basic tool may technically meet the minimal definition of “artificial intelligence,” but today’s businesses need solutions that can accomplish more.
Think of it like a mass-market car company trying to mimic the look of a luxury brand. They may be able to mirror surface-level aesthetics at a distance, but examining the details and material quality (let alone what’s under the hood) will reveal the truth. Those that use “Agentic AI” as a marketing term without the functionality to back it up should be similarly easy to spot—but customers don’t always have the technical expertise to identify what level of AI maturity they are being offered. A business may claim to be an “optimization company,” but can it actually perform constraint-based nonlinear optimization? Or does it use a linear regression model to perform basic forecasting? Worse still, does it use a program that can only handle four of the 40 constraints needed to model a given problem? Anyone can claim to provide “AI-based” solutions, but the gap in results is significant.
This is important to understand as we move into the next phase of AI development and deployment. Agentic AI promises to be a revolutionary technology—one that will effectively democratize access to powerful, AI-based analytics and advanced optimization capabilities.
How Agentic AI works and why it matters
There are four critical elements of Agentic AI: symbolic AI, explanatory maths and optimization engines, generative AI, and the “agent” itself:
- Symbolic AI is the “Deep Reasoning” part of the brain responsible for things like logical inference in the form of abductive and deductive reasoning. It uses logic-based programming and theorem-proving techniques to solve problems in a way that simulates the human brain.
- Powerful high-dimensional, explanatory maths and optimization engines are used to engage in the heavy-lift mathematical computation needed to process vast amounts of data and generate penetrating insights.
- Generative AI performs the “Thin-Slicing” functions needed to identify patterns across large data sets and extrapolate from them.
- Agentic AI is the conversational component that allows the machine to engage with people in a human-like fashion, easing engagement and democratizing access to advanced analytics and insights. It is the “quarterback” of the team, orchestrating actions across the system.
Agentic AI is like a delicate, four-way dance—and the agent is the leader. Without an agent to synthesize and optimize the data coming from the analytic engines underneath it, users would have access to vast amounts of information, but little idea how to organize or utilize it. Agentic AI translates complex analytics and optimization data into a democratically accessible user interface to provide business users with access to useful and actionable insights without the need for an advanced data analysis background. Generative AI, symbolic AI, and maths and optimization engines all have individual uses, but the agent is the critical fourth piece that enables all four elements to operate in a unique and harmonious manner.
Before Agentic AI, the role of the agent was played by a human operator—and it simply isn’t possible for a human being to process anything close to this volume of information. Today, an AI agent supported by the other three parts of the “brain” can analyze vast data sets impacted by dozens of constraints. These agents also have a thorough understanding of how each component impacts the others, generating the optimization insights needed to drive today’s businesses forward. And because they are presented by an AI agent capable of human-like reasoning and conversation, these critical business insights are increasingly available even to users without a high degree of technical expertise.
True Agentic AI is revolutionizing business optimization
At this year’s Consumer Electronics Show (CES), NVIDIA (NVDA +5.47%) CEO Jensen Huang predicted that 30% of companies will have “digital employees” making meaningful contributions to the business by the end of 2025. That may sound like a bold prediction, but for those who have spent significant time working with Agentic AI, it’s simply the acknowledgement of a long-held truth. The confluence of symbolic AI, generative AI, and modern explanatory maths and optimization engines, dancing together with the helpful guidance of an AI agent, is making critical business optimization insights more accessible than ever. True Agentic AI is a revolutionary technology, and those that fail to adopt it risk being left behind.
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