In a world where artificial intelligence (AI) is evolving at breakneck speed, companies find themselves in a landscape filled with both opportunities and risks. In this scenario, it becomes clear that implementing AI is not merely a technological issue — it is, above all, a profound transformation that demands strategic intelligence, organizational vision, and, most importantly, a key figure who can bridge the gap between the business side and the technical world.
Large Models vs. Specific Agents
One of the most critical decisions in any AI strategy is choosing between large, general-purpose models — powerful but costly — and more specialized agents, which are more accessible and task-oriented: customer service, creative generation, data management, code development, or cybersecurity. The key lies in understanding where each fits within the organization.
The connector is a crucial figure in this process, offering guidance, education, scalable models, and the ability to adapt to a constantly changing reality — an expert capable of distinguishing what is truly essential from what is superficial or mere appearance.
Governance, Culture, and Talent: The Right Questions to Ask
To make generative AI work effectively within an organization, much more than technology is required. Strategic answers to key questions are needed, such as:
- What governance model ensures both value and security?
- Do we have the right policies in place?
- How do we integrate AI with other ongoing projects?
- Do we foster an organizational culture that is open, experimental, and ethical?
- Do we have the necessary talent? How will this impact career development?
- Because while AI may seem very intelligent, the real challenge is for us to be smart in how we use it.
The Connector Role: A Strategic Bridge Between Business and Technology
In this context of constant change, the traditional role of the developer is no longer purely technical — it becomes a key element in value creation. This is what we call the “connector,” someone who bridges technology and business — in both directions.
The connector is the one who understands the business problem and translates it into solutions through emerging technologies, often combining generative AI, classical AI, and automation as appropriate for each case.
Choosing the right technology is far from trivial: the market is saturated, options are almost infinite, and the confusion between classical AI, generative AI, and automation can lead to misguided investments. Deep, up-to-date knowledge of each technology’s capabilities is therefore essential, along with a solid methodology to clearly define the problem before choosing the tool.
Organizations need to have a connector — a person who speaks both the language of business and the language of technology fluently. The connector plays a key role in this process, providing guidance, education, scalable models, and adaptability to a changing environment — an expert who can filter out what truly matters from what is just noise.
The connector should help to:
- Identify the most impactful use cases.
- Build a solid, iterative methodology.
- Prepare teams to be agile and adaptable.
- Develop realistic strategies that combine “small transformations” with a long-term vision.
In Conclusion
Effective AI management is not a race toward the newest technology — it is a process of maturity and strategic clarity. The companies that will succeed are those able to best combine innovation with simplicity and continuous learning. And the first step is having a good connector!
