We are often asked how we think about AI, not just in the programmes we deliver, but in how we run our own operations. If we advise clients on AI adoption, we ought to have some internal practice to point to.
We have been working with AI internally since late 2022. What began as conversations in our weekly Community of Practice meetings has gradually integrated into how different departments work. We are not aiming for automation for its own sake. We look for specific, repeatable tasks where AI reduces friction or improves consistency across our departments.
A Specific Example: Proposal Generator
The most developed internal application is the proposal generator for the sales team.
Before this system, proposals were stored as individual files on Google Drive. Each time a proposal was needed, a team member manually edited details like facilitator name, delivery mode, and dates. When something changed across all proposals, someone had to update each file manually. The process was slow and repetitive as pictured below.
We described the problem to ChatGPT, Claude, and Gemini. The response was to build a simple application inside PowerPoint using Visual Basic code. None of our team members knew how to write that code before the conversation. The AI also recommended updating the visual design.
Using AI generated code, we built a system with a dropdown menu on the first PowerPoint slide. A sales representative selects the programme details, and a customised proposal generates automatically. The system even attaches the proposal to an email draft. What once required multiple manual steps now happens in a few seconds as shown in the picture.
We mention this not because it is extraordinary, but because it is practical. It is a solution to a real inefficiency, built with tools available to anyone. Through innovative thinking and a proactive approach using AI, we transformed a tedious, time-consuming process into a streamlined and efficient system.
Daniel Lourdes
Marketing Executive