Value-Focused Approach in AI Projects

The Gap Between Expectation and Reality

Zeynep Erdoğan, presenting on behalf of Architecht at the Webrazzi Fintech 2025 event, analyzed the main reasons behind the disappointment institutions experience in AI projects. The presentation, which referenced Gartner data, drew attention to the adoption times of technologies. ChatGPT reaching in just 2 months the audience that the automobile reached in 33 years and the telephone in 15 years created a level of expectation on the corporate side that is hard to manage.

Especially in the fintech sector, the inability to use public cloud solutions due to regulations is pushing institutions to build their own internal GPT structures. However, the tendency of technical teams to use technologies such as blockchain or AI just because they are popular negatively affects the sustainability of projects and value creation.

Three-Layer Strategy: Need, Impact, and Technology

For AI investments to succeed, value needs to be put at the center before technology. Erdoğan addresses this process in three basic layers:

• Business Need: First, clearly defining the targeted work and problem.
• Impact Analysis: Discussing the added value the defined work will create and its effects on the process.
• Technology Selection: At the final stage, determining the most suitable technology to meet the identified need.

Pilot and Scaling Processes

It is stated that massive AI models are not needed to solve every problem, and that sometimes a simple Robotic Process Automation’s (RPA) can produce more efficient results. When designing solutions, obtaining feedback from the end user and determining measurable metrics are of critical importance. Scaling pilot studies according to feasibility reports stands out as the main factor that prevents waste of resources and leads the project to success.