AI agent deployment: Copilot, autopilot, or fully autonomous system
AI agents create value through a variety of levers. Agents may increase quality, reduce costs, increase throughput, or do all the above and more. The value that an AI agent creates is determined by the role the agent plays in your business. AI agents may serve as copilots, autopilots, or fully autonomous systems. In this article, I will cover the differences between these roles and factors to consider in deciding which role is best for your business.
Copilot is the advisory role of AI agents. Copilots provide input and guidance to human decision makers in real time. The copilot role carries the least risk because a human in the loop approves and finalizes all recommendations by the AI agent.
The copilot role is appropriate when the goal is to enhance human decision making. Copilots excel when the volume of operational data is high and experienced decision makers are in short supply.
An example use case for copilots is control of a complex manufacturing process. Manufacturing lines can require years for a new operator to learn and gain the necessary experience to control. An AI agent operating as a copilot can help new operators achieve results beyond their experience by providing expert guidance and serving as a real-time mentor to the human operator.
Another important role for AI agents is as an autopilot. Autopilots share the duties of decision making with human operators. Autopilots are highly effective in scenarios where human operators remain critical to good decision making but are not able to provide dedicated support.
An autopilot provides support when a human decision maker is unavailable. Consider the example of a rock hauling truck operating in a mine. The AI agent may extend the skills of the human driver when the driver is tired or needs to multitask. Autopilots are also effective in managing routine operations, allowing the human operator to focus on more challenging tasks.
Success of an autopilot depends on teamwork between the AI agent and the human operator. The agent extends the capabilities of the human operator. It is up to the human operator to manage their attention and select the best scenarios to leverage the AI agent.
Fully autonomous systems
The third role of AI agents is as fully autonomous systems. In a fully autonomous system, an AI agent manages all tactical decision making while the human operator adopts a supervisory role. This mode seeks to combine the speed of automated decision making with human experience and judgement.
Consider the example of a human customer service agent overseeing a collection of chat bots that automate routine customer service tasks. The human supervisor may deploy several AI agents and monitor their performance. The human supervisor monitors the agents through a dashboard.
In the case of a fully autonomous system, the human being is still a key team member. However, the role of the human supervisor shifts from active participant to architect. The human supervisor provides support and maintenance for the agents and looks to improve the system over time.
Fully autonomous systems require the most care in design of surrounding processes and machinery to ensure good operation. This is because the human operator now sits outside of the business process. The human operator requires a thoughtful user interface and system of warnings and alerts to enable quick intervention when required.
Extending capabilities of human operators
In summary, AI agents can offer support to human operators in many ways:
- Copilot support enhances the human operator’s decision-making capabilities by providing recommendations
- Autopilot support extends the human operator’s capabilities, shares decision-making duties
- Fully autonomous systems manage all tactical decision making while human operators take on the role of supervisor and architect
AI agents have shown enormous potential to create value in industry by extending the capabilities of human decision makers. Whether an AI agent should be used as a copilot, an autopilot, or a fully autonomous system depends on the business process and overall goals. For an in-depth discussion on your business needs and how AI can help, please contact Neal Analytics.