Decision Compression and Context

I have been teaching my team to use AI in our business. This graphic is my one-page attempt to show how people and AI can best be framed. Simply put, a person has to start the process with a prompt and then a person a has to choose the outcome based on experience. I used the phrase “Decision Compression” (AI Tools allowing for faster decision-making) to show how AI tolls impact the process and then to capture the human role I used the term “Context”. Context in this case is the sum of time and experience, in relevant industries, locations, functions and levels.

Decision Compression represents the integration of artificial intelligence (AI) with human context and experience is shown to be pivotal for achieving better business outcomes. While AI has the capacity to process vast amounts of data and generate insights quickly, it lacks the nuanced understanding that human decision-makers use in real life. This is where the synergy between human expertise and AI becomes most productive.

Human context and experience allow professionals to craft more relevant prompts for AI to process. These prompts are more than just data inputs but are shaped by years of industry knowledge and an understanding of business environments, providing the AI with the more relevant context and information required to generate useful outputs. Without this foundational context, the AI's responses risk being too generic or lacking in practical application.

Finally all Outputs require human expertise to provide critical validation. While AI can produce suggestions or solutions, it is the human professional who must assess whether these outputs are commercially viable or aligned with strategic goals. AI may propose multiple scenarios, but the judgment call on what is reasonable or actionable is a uniquely human role, requiring experience that AI alone cannot replicate.

Our firm’s focus is on leveraging this human-AI collaboration to drive success. By blending AI’s efficiency with the individually unique depth of each employee’s experience, we can enhance decision-making and ensure outcomes that are more relevant and useful to our work. This graphic seemed to resonate with the team and has helped us focus on how best to use our AI tools. I should also say that all outcomes also required careful editing to assure authenticity – does the user really agree with the results in their frame of reference. In the end the use of AI is professionally helpful, but he output still requires a personal touch to be useful.