Jensen Huang says AI brokers are a ‘multi-trillion-dollar alternative’. Mark Benioff thinks brokers signify ‘what AI was meant to be’. And Satya Nadella thinks SaaS is lifeless. It’s 2025, and brokers are the one recreation on the town (or so it might appear). The tech business adores its buzzwords, and ‘AI brokers’ is likely to be the buzziest of all of them! Whereas just a few vendor platforms are genuinely constructing agentic options into their roadmaps, others are merely ‘agent washing’. I see a lot of confusion amongst Forrester purchasers – patrons of those applied sciences – who’re attempting to sift via all this frenzy to make sense of what brokers actually are, what they imply to the enterprise, and what their selections are.
I’ve ideas.
If it doesn’t have company, it isn’t an agent
We’re nonetheless early sufficient alongside the expertise maturity cycle that definitions and traits could be a bit fluid, however it’s typically accepted that AI brokers are LLM-based constructs that show particular design patterns: planning, reflection, collaboration with different brokers, and gear use. Underlying these patterns are two foundational constructing blocks of true ‘agentic’ functionality:
Company: A defining attribute of an agentic AI system is the ‘company’ to manage and direct its personal program circulation, making impartial selections concerning the particular pathways, sequence and nature of actions it should execute to realize its targets. After all, company could be slender or broad, however AI brokers are anticipated to have broad company throughout a wide range of targets inside a context-space.
Autonomy: This can be a product of an agent’s ‘company’ in addition to the generalized intelligence of in the present day’s basis fashions. Autonomy refers back to the breadth of contexts (exceptions, externalities and edge instances) inside which the AI can function successfully and ship desired outcomes, with out requiring express directions or intervention from a human.
You’ll be able to instantly see that company and autonomy feed off one another. Collectively, these traits distinguish true AI brokers from their lesser counterparts.
In the event you look fastidiously at most of the ‘agentic’ choices that SaaS merchandise provide, they arrive throughout as a combined bag. You’ll shortly understand that these ‘brokers’ have restricted autonomy, or restricted company, or are restricted to such a slender context-space that you just may as effectively have simply used a deterministic workflow or an everyday LLM immediate to supply the identical final result. Sadly, a number of of the purported agentic demos that I’ve seen from SaaS distributors are merely LLM prompts embedded right into a flowchart-y, deterministic course of circulation, inside which they’re deployed to carry out slender duties. Principally, these are LLM-wrappers round deterministic course of workflows.
These should not ‘agentic’. Most of the time, they’re merely ‘agent-ish’.
The autonomy spectrum
This isn’t to say that there’s little to no worth in these ‘agent-ish’ workflows. Agent-ish workflows have their place in an autonomous ecosystem, and the aptitude footprint of those ‘agent-ish’ workflows will get higher and higher over the following few months. However it’s nonetheless a stretch to name them AI brokers.
On this context, it’s useful to consider autonomy at totally different ranges. At Forrester we are likely to map AI methods alongside a spectrum of various company and autonomy, throughout the distinct dimensions of management, execution and monitoring. That is analogous to the idea of ranges of autonomy in self-driving automobiles, however as an alternative, as utilized to enterprise processes. Let’s define the important thing ranges:
Degree 0: Guide. People, sarcastically, embody the very best ranges of company and generalized functionality (or ‘widespread sense’). A human worker can often be tasked into a task with no need detailed directions or step-by-step flowcharts to navigate their job. However the level of autonomy is to cut back this reliance on human labor, and so this degree kinds a baseline from which to measure higher-level autonomy.
Degree 1: Software program-driven, or rules-based automation. This encompasses conventional software-driven automation, in addition to task-specific assistants that may be constructed utilizing conventional automation tech reminiscent of Robotic Course of Automation (RPA) or workflow automation. These methods execute predefined duties alongside preconfigured pathways effectively however lack any significant decision-making means past easy deterministic logical operations.
Degree 2: Probabilistic automation. This consists of methods that combine machine studying or giant language fashions (LLMs) to reinforce automation, but they continue to be tethered to static workflows. For instance, an RPA-like buyer outreach workflow could dip right into a machine studying (ML) mannequin to generate a listing of consumers who’re more likely to churn. We regularly hear distributors assert that their software program is ‘agentic’ as a result of it may possibly make non-deterministic selections… effectively, most machine studying fashions work with chances and are, due to this fact, non-deterministic. That doesn’t make them agentic, as they haven’t any company and are solely centered on a particular job.
Degree 3: AI operators, or agentic course of orchestration. These quasi-agents mimic company however function inside tightly outlined guardrails. Consider ‘LLM wrappers’ round deterministic workflows. A overwhelming majority of the present wave of so-called ‘brokers’ from SaaS distributors fall at this degree, as do instruments that Forrester phrases as ‘agentic course of automation’. These are ‘agent-ish’ as a result of they ship autonomy solely inside a narrowly outlined context house and have very restricted company inside these slender context-spaces. On this context, you will need to notice that for a lot of organizations, ‘agent-ish’ workflows and hybrid orchestration throughout Degree 2 and Degree 3 – wherever performed proper – will show extraordinarily helpful within the close to time period for organizations which might be dipping their toes into the house, however the alternative of use instances and finesse in technical execution can be essential to success.
Degree 4: AI brokers, or ‘agentic methods’. Programs at this degree exhibit each company and autonomy inside broad contexts. Like a extremely expert human colleague or supervisor, they don’t want a step-by-step flowchart; they’re goal-oriented, utilizing their information and contextual consciousness to find out the very best plan of action. AI brokers fee excessive on management and execution dimensions, with restricted monitoring capabilities. A number of examples of true AI brokers are coming into being. A couple of examples would come with Devin, a programming agent, or AI Scientist for analysis and scientific discovery. We’ve seen a number of enterprise use instances for these true AI brokers in areas reminiscent of drug discovery, complicated know-your-customer processes or superior insights technology (to call just a few of a number of). That stated, really agentic methods function at a degree of functionality that could be a step-function larger than ‘agent-ish’ methods in enterprise worth created.
Degree 5: AGI (Synthetic Normal Intelligence), or no matter comes subsequent. We don’t know the place AI may evolve within the subsequent 5 years. Whereas AGI is aspirational and poorly outlined in the present day, it does describe a future the place AI methods self-govern and handle not solely targets but in addition their evolving goal.
What it means
It’s not unrealistic to think about organizations designed within the type of hierarchies whereby agentic methods handle different types of autonomy throughout Degree 1, 2 and three ‘ (together with agent-ish’ methods), both changing or augmenting human labor in these roles.
Nevertheless, most organizations are at very early phases of this journey. So, it’s important that expertise patrons and resolution makers take a clear-eyed view to the hype and to grasp that these ‘agent-ish’ methods should not the Promised Land of enterprise autonomy, however simply an intermediate (however however necessary) step alongside the journey.
