Introduction
There are multiple ingredients to a successful AI strategy. Starting with the people and ending with the output, we have nothing but data, technology, and systems in between. Similar to the components and mechanics of a racecar, the engine is the technology enabling speed, data represents the suspension, chassis, tires, and handling, often dictating agility, flexibility, and handling, and the systems are in between orchestrating it all.
As a by-product of systems knowledge, we understand data trends and analytics applied at the source of truth. We begin to further peel back the layers of our understanding into data hygiene, accessibility, and transformation. We often compare this to “Sherlock Holmes” searching for the sequence of clues from the exact source of the data in the warehouse up to the final clue – the crime scene where that data ultimately lands. This sequential process is incredibly important for employees to learn about how data is processed and managed front to end.
Within the systems, we see various milestones of data across data icebergs, each with its own personal function, sometimes isolated from other icebergs. Each data system, warehouse, or storage container may be very different than the last one, so each should be understood as it relates to organizational remit. Within these milestones, there may be various opportunities for optimization, which is where AI plays a large part in potential efficiencies. The next factor for unlocking value is the level and stage of AI literacy organizationally, more specifically those who would be using AI across internal systems. By understanding the data as it flows through the pipes, workers across all levels will start to generate a “learn-and-fail” curiosity enabling the usage of internally securely approved GenAI tools to optimize and enhance these processes from a bottom-up perspective.
This skill of systems engineering will integrate a pro-active data mindset for your team and will allow a more advanced opportunity of anomaly detection, pattern recognition, and autonomous optimization over time. To learn more about how AI Prophets can help build your team’s AI literacy around data systems and warehouses, reach out today and book a free consultatioproactiven.
Conclusion
Whether it be an AI agent for a CEO or a series of exceptional advisors to help detect modeling deviations, the most important thing for businesses and teams today is to understand the fundamentals needed to maximize AI value at an organizational level. As we seek to continue growing as humans and teams, we are presented with a tremendous opportunity to upskill and refine nearly everything we do. AI Prophets, we personalize AI literacy programs for organizations and teams of all sizes, enabling competitive data agility at scale. Contact us today to speak to an expert about how we can help.
