Companies and organizations: Becoming intelligible before becoming intelligent

For several years now, organizations have been investing in artificial intelligence. They are experimenting with conversational assistants, deploying intelligent agents, automating processes, and seeking to leverage their data to improve their performance. This evolution is natural. Artificial intelligence is gradually becoming a major lever of competitiveness.

One essential question remains underestimated: Is the organization truly ready to be understood by an artificial intelligence?

The first generations of AI mainly learned to recognize words, produce text, generate images, or analyze data. Increasingly capable, the next generations will seek more to understand their environment, establish relationships between pieces of information, anticipate the consequences of their actions, and reason in an ever more complex context. For an artificial intelligence to truly create value, it will have to understand how the organization in which it operates works. Yet that understanding cannot be improvised.

A company is made up of thousands of pieces of information, procedures, rules, decisions, responsibilities, bodies of knowledge, processes, and interactions that have often been built up over the years. Part of this knowledge is documented. Another part remains implicit, passed on through experience or held by a few key people. Some information appears in several systems, sometimes in different versions, while other information is not preserved anywhere. For a human being, these inconsistencies are often offset by experience, exchanges with colleagues, and knowledge of the context. For an artificial intelligence, they quickly become obstacles to understanding.

An organization whose knowledge is scattered, whose responsibilities are poorly defined, whose processes are barely documented, or whose rules are contradictory risks obtaining equally inconsistent results from its intelligent systems. The more coherent, structured, and well governed an organization is, the better artificial intelligence will be able to understand how it works, produce relevant recommendations, and effectively support its teams.

Preparing for artificial intelligence means choosing the right tools, but above all making the organization intelligible. This effort goes beyond technological considerations. It touches governance, information quality, the structuring of knowledge, the clarification of processes, the definition of responsibilities, risk management, and the organization's ability to share a common understanding of how it operates.

An intelligible organization also performs better for its own teams. New employees get up to speed more quickly, decisions become more consistent, knowledge is passed on more effectively, and organizational transformations become smoother.

Artificial intelligence then acts as a powerful catalyst. It accelerates the capabilities of an organization that already knows how it works. Conversely, it also amplifies inconsistencies wherever they remain.

For Quantum Beyond, the coming years will be marked by a significant evolution in the relationship between organizations and artificial intelligence. The companies that get the most out of these technologies will not necessarily be those that deploy the greatest number of intelligent agents. They will be those that have taken the time to structure their knowledge, clarify their governance, strengthen their processes, and prepare their teams so that artificial intelligence can genuinely understand their environment.

Before seeking to make an organization more intelligent through artificial intelligence, it becomes essential to make it intelligible. It is this understanding that will then allow artificial intelligence to sustainably amplify the value created by people, knowledge, and technologies.