The 2023 many conversations about artificial intelligence started with the name of a tool. It was understandable: the new capabilities could be seen and tested in minutes. But a license doesn’t explain what an organization must transform, what risks it accepts, or how it will know if it has improved.
Before choosing technology, we propose to make five decisions.
What business results we pursue
“Being more efficient” is too broad. It is necessary to specify whether we want to reduce preparation time, expand the coverage of an analysis, improve consistency, accelerate a response or create a capacity that does not exist today.
This result allows to compare options and avoids that the technical novelty becomes the main criterion.
What process we are willing to change
The AI does not work in the vacuum. Enter a sequence of people, documents, tools, and approvals. If we only add a new interface without redesigning the process, we can create more steps instead of reducing them.
The strategic decision is which flow we want to change and which parts must remain the same for reasons of quality, culture or responsibility.
What knowledge has authority
A general model can provide language and patterns. The company’s own criteria lives in other places: policies, projects, data, brand, team experience and previous decisions.
It is necessary to define which sources are valid, who updates them and how contradictions are resolved. This basis will condition the outcome more than many differences between models.
What autonomy is acceptable
It is not the same to suggest an answer than to send it; to identify an opportunity to approve an expense; to prepare a decision to make it. The strategy must establish permissions, Human Gates and prohibited actions before the interface makes them invisible.
It must also define how the actions will be recorded and how the system can be stopped or reversed.
What we want to keep under our own control
Companies must decide which knowledge, integrations and processes are strategic enough to avoid unnecessary dependency. It doesn’t require you to build everything. It forces you to understand what will happen if the supplier, price, model or conditions of use change.
A good architecture can combine external services with data and rules governed by the organization.
The tool comes later.
When these decisions are made, the technological assessment is much clearer. We can compare capacity, privacy, integration, cost, maintenance and performance on real cases.
The LLM Strategy It’s not about turning a technology brand into a destination. Strategy is the consistent choice of problems, capabilities, boundaries, and learning. Tools are important, but they must be at the service of this choice.