Contexts

Consumer AI Approach

When Birmingham City Council failed to replace its old system to update the city's digital services, the failure was not technical, although many read it that way. The story still serves as a lesson in digital transformation, but the lesson is not about technical failure; rather, the roots of failure extend far into the organization's failure to understand its own operations.

As we move into a new phase of digital transformation with artificial intelligence, we must reread the stories of success and failure anew. The problem relates to the organization's ability to grow without exceeding its capabilities. It requires the organization to know its shortcomings and identify the most impactful ones before deciding on transformation.

If the organization adopts a transformation plan to adopt AI, it must identify the shortcomings that prevent it from benefiting from this technology before adoption. What we see today is AI entering the organization as a tool—a tool that writes memos, classifies documents, and searches records. These uses are real and often necessary, but does the organization actually suffer from a shortcoming in automation or weakness in speed of completion, or is the benefit from the technology based on its capabilities rather than the organization's need?

If we learn from stories of organizational failure in transformation, we will seek a way to bridge the gap between what we understand about our organizations' operations and what technology implements to accomplish these tasks. The depth of the gap depends on the organization's culture: does the organization have sufficient transparency to reveal this gap?

If the answer is yes, then it must seek technologies that close this gap. If the answer is no, then these technologies will pass without realizing their role in solving root problems. If we look at AI, it can be used as a tool like other tools that increase productivity and quality, but the organization will lose a lot if its use is limited to that only.

If an ERP system executes a predefined workflow, AI can execute the same or add a simple addition. But what AI can do and what the organization needs to change in its culture if needed is to grant the freedom of criticism and thinking.

We do not claim that AI thinks like us; the philosophical side of this discussion is important, but practical application does not require it. Criticism and thinking in organizations for specific purposes, such as questioning assumptions, analyzing problems and returning them to their roots, and linking explanations to evidence—all are tasks that organizations vary in practicing, and AI can perform them.

What we clearly assume here is that optimal utilization of AI is conditional on its ability for self-criticism. The higher the level of freedom of self-criticism in the organization, the higher its ability to benefit from AI, and vice versa. We can describe the use of AI as consumerist if it is a primary or auxiliary executive tool, and strategic if it is a critical analyst of business and problems. The difference between the two uses depends on the organization's culture.