AI like ChatGPT is now creeping into the Organizational Augmentation world.
Organizational augmentation is like outsourcing a skillset or having an excellent assistant. They’re not totally autonomous, but they do a lot by themselves without you needing to get involved. You set the rules and expectations, and they do the work. Plus, you’ve empowered them to make some decisions on your behalf, but staying with the guidelines you’ve set up.
Organizations and teams start to feel some benefits here.
The Helpdesk is a great example. If you train an LLM on your stuff, it can effectively hold a conversation about it with humans. Even as that conversation twists and turns around an unknown number of curves. If the training data is sufficient, the chatbot can keep up.
The virtual graduate assistant is another example. You can offload a specific task, such as analyzing data to find trends, researching and summarizing prior art, or even interpreting legal briefs.
But organizational augmentation comes with a required expertise and a financial cost.
It requires programming your own application and incurs a dynamic cost across the interface to the LLM. To bring virtual bots into your workflow or team, you must use the LLM’s Application Programming Interfaces (APIs). Which means, “you have to write your own code to create the bot.” And you have to pay for every piece of information you send and receive to the LLM. More data == more cost.
Organizational automation is where it starts. Maybe you need less helpdesk people. Maybe you need two grad assistants instead of three. Maybe you don’t need to hire out some specific task.
But at the end of the day, the effect is minimal.
Next, we’ll look at the holy grail — Autonomous Automation.
