**AI** is creating new possibilities when it comes to using more intelligent systems in the enterprise.
But many companies don't even come close to the fully utilizing the potential of AI. This is mostly because employees are not allowed to use **generative AI** tools like **ChatGPT** because of privacy concerns, or because employees don't know what to do with it besides using it as a smarter Google search engine.
Chatbots are slowly finding their way in the enterprise but have strong limitations leading to limited adoption. A chatbot is good at answering questions, but most jobs require action. Technology providers like Microsoft tried to make an enterprise ready product with the introduction of **copilot**, but with all its limitations in functionality and the missing piece of actionable AI, copilot misses the mark in the context of contextualized actionable AI that can act on behalf of employees. The copilot concept has just been an assistant panel on the right side of the screen that requires explicit instruction, it's Clippy all over again. Because of the lack of action, especially in the enterprise, AI has not seen the adoption yet it deserves.
The gateway to value added AI in the enterprise is **actionable AI**; AI that performs actions on behalf of users as opposed to chatbots that would say "Sorry, I can't help with that" when you ask them to do something for you. **AI agents** are the embodiment of actionable AI. AI agents are able to access tools and perform actions within those tools without you having to explicitly instruct them what to do exactly. You give them a broadly defined goal, and the AI agent is able to figure out which tool they have to access and which functions to access within that tool. AI agents are digital entities with capabilities to act and collaborate to achieve broadly defined goals. Agents are different than for example a copilot or ChatGPT because they can execute actions and can do so within the context of your organization.
As a result of these new capabilities, agents behave more like humans do than tools. The easiest way to understand the potential of AI agents is seeing them as your digital colleagues who work alongside you and can access systems just like human workers do. Agents are able to plan, act, reflect and collaborate because they are capable of reasoning (understanding, calculating, problem-solving) and communication (understanding and generating language and other modalities like vision and sound).
Because AI agents possess a degree of **autonomy** that allows them to act, reflect, plan, and collaborate, they have a combination of capabilities that enables them to function as **digital colleagues** capable of taking on entire roles and responsibilities within an organization with a level of independence that mirrors human cognitive processes.
The **autonomous digital worker** and the **AI workforce** are not just another technological trend, but a fundamental reshaping of how organizations function, compete, and create value.
This fundamental shift from tool to autonomous actor cannot be overstated - it represents a transition from enhancing human productivity to creating an entirely new class of workforce.
The rapid advancement of AI agent capabilities is not a distant possibility but an imminent reality. The technology stack powering these agents - from the infrastructure layer to the models, middleware, and specialized agents themselves - is evolving at an exponential rate enabling rapid development of the capabilities of these agents. Processing units get faster exponentially, data gets more rich and synthetic data is generated, **LLM ops** gets more sophisticated, more and more smaller special purpose finetuned models get trained, orchestration and distribution expand in functionality and scale up, and specialized and general agents get out of proof of concept and deployed at customers as we speak, all compounding to an ever accelerating pace of improvement of AI agents with exponentials stacking up.
This compounding effect means that the capabilities of AI agents are not improving linearly but exponentially. What seems like science fiction today could be commonplace in a matter of years, not decades. Organizations that fail to recognize and prepare for this acceleration risk being left behind in a rapidly evolving business landscape.
The AI workforce: the new organizational transformation
The impact agents can make and their behavior point to a new paradigm in the workforce. The workforce will become **AI/Human hybrid**, consisting of both humans and AI's collaborating with each other.
Imagine having an entire team of several AIs and humans working together, having an AI financial support agent, an AI billing AI agent and a reporting agent in the finance team, with a human finance manager and one human finance operations specialist. Even managers of teams can be AIs, especially in smaller companies like in startups this is expected to be commonplace in the near future.
Consider the implications: organizations will no longer simply deploy software to assist human workers; they will onboard digital entities capable of operating with a level of independence previously reserved for human employees. From AI sales agents to AI lawyers, these digital workers will not merely support human staff but will increasingly operate as full-fledged members of the organizational ecosystem.
You can stop relentlessly adding headcount and start building an AI powerhouse.
Now extrapolate that to the entire organization, this is where things really get interesting. Once you have an AI/Human hybrid workforce, you can start scaling up the AI workforce to be covering an increasing part of productivity. When one AI agent can do the work that normally you would have to hire and onboard an employee for, then you can also imagine at some point it will make sense to scale this up to the entire organization. Eventually companies will even become fully autonomous.
To understand the urgency of preparing for the AI workforce, it's crucial to recognize the stages of transformation that organizations will undergo.
Companies will go through three stages driven by the introduction of AI workers:
AI enabled companies (now)
Currently, almost every company is using AI in their business. In this stage, AI is used to enhance existing processes and boost human productivity. Processes are improved, in most cases incrementally, by giving employees the right AI tools to do their existing work more efficiently and effectively. Generative AI is used by many companies at scale, mostly in the form of **Software as a Service (SaaS)** products. However, AI agents haven't fully entered the workforce yet. Some companies have started experimenting with agents, but agentification is still very limited.
AI/Human hybrid companies (transition)
In this stage, there will be large scale deployment of agents in the workforce. The 'AI workforce' arises, able to execute and manage a large part of business processes themselves. At some point, agents will be responsible for half of total workforce productivity across companies. This AI workforce will collaborate with the human workforce, forming a hybrid workforce. There will be a major shift of productivity from human labor to AIs, with agents executing processes and tasks and reporting back to humans and managing agents.
AI run companies (future)
In the not-so-far future, there will be companies that are completely operated and run by AI. Teams of AI agents will be responsible for (almost) all productivity. The humans still in the loop in AI run companies will have a relatively passive role, representing stakeholder interests but not interfering with business as usual and operations. Even though there will be companies fully operated and managed by AI, it's likely that humans will still be involved because they will have an interest in the business, expressed in money and status (power).
The **fully autonomous enterprise** is still a dream today, but reality sooner than most people would think. The autonomous enterprise is an organization run and managed entirely by AI, where the involvement of humans is merely stakeholders (people with financial or other interest in the company) and outside stakeholders (like regulators doing audits). Not every business will choose to be an autonomous enterprise, in the near-term most will be AI/Human hybrid companies, but at some point it will be hard to compete as an AI/human hybrid company with autonomous enterprises, which will strengthen the incentive to scale up AI in the organization.
Some people think that at some point they will just use one super intelligent AI that can do everything all at once and that it's not necessary to have teams of AIs since that one super AI can do everything. But in the context of an organization, one super AI is both extremely risky and inefficient. That's why this transformation is about the increasing level of autonomy of the enterprise through AI agents rather than deploying one intelligent model.
Making AI agents a reality in your organization
Within the context of an organization, there's a lot more to it than just wildly executing tools. An organization has its own unique mission, ways of working, hierarchical structure, role based access system, compliance, guidelines and guardrails.
The challenge for many larger organizations trying to implement actionable AI is to deploy AI in a way serves the organization within the current organizational structure and guardrails.
Since agents behave more like humans do than tools, they also have to be managed differently. Getting an agent up and running is more like onboarding an employee than acquiring a new SaaS tool. They need to be aware of company mission, guidelines, where to access information, roles within the teams, standard operating procedure and how to communicate and collaborate in the organization internally and outside of that.
You can read further here on how to manage AI agents in your organization.
The road to becoming an AI/Human hybrid company is one that requires changes, but luckily this new technology is guided by technology itself which makes it a lot more manageable to deploy and get started with agents. For a quick start with AI agents, use an AI agent workforce management platform to build, manage and monitor agents in the context of your organization.