Situation
Franco wanted to explore how AI could make day-to-day work more efficient for integrated communications coordinators and specialists. Our initial focus was on tasks that took the most time and included repetitive or tedious steps, which would allow more time for strategy and creativity.
We aimed to reduce the time spent on those parts of the work while preserving the creativity, judgment and discernment that effective communications work requires.
Approach
We started by asking coordinators and specialists which responsibilities took the most time. Their feedback was paired with utilization data to identify patterns and create an initial list of potential use cases.
A prioritization matrix helped us evaluate those opportunities based on factors such as time, frequency, effort and how well AI could support the task. That process narrowed our focus to a select group of use cases.
Before introducing AI, we asked each person to walk us through the current workflow step by step. Seeing how the work was completed provided the context we needed to understand where time was being spent, which decisions required experience and where AI could fit naturally.
From there, we developed and tested workflows that used AI for the most time-consuming and repetitive portions of each task. Coordinators and specialists continued to shape the work, check accuracy, apply context and make the final communications decisions.
Working sessions gave us opportunities to test each process using real examples. Feedback from those sessions informed refinements to the steps, prompts and review points.
Results
The project produced five AI-supported workflows for recurring integrated communications tasks. Each one gave coordinators and specialists a clear process to follow, including how to prepare the inputs, where to use AI and how to review and improve the output.
The final workflows document gave the team a tangible reference that could be used during day-to-day work. It helped make the selected tasks faster and more consistent while keeping creativity and judgment with the people responsible for the work.
We also established a repeatable approach for future AI use cases. Start with the existing process, understand where the time goes, identify the right role for AI and always keep people responsible for the final result.
