Microsoft- Applying AI
Strategy-Research-AI
AI is a rapidly emerging technology that revolutionizes the industries that adopt it, but despite this many companies are reluctant to adopt this versatile tool for various reasons. My team and I were sponsored by the Microsoft Experience Strategy and Design Studio to find ways to apply AI within the financial services industry, as well as exploring strategies to convince companies to adopt AI.
The problem
While the Financial services industry is a large and well established industry, many of the tools they use are quite antiquated. This is due to a few reasons:
-Hesitance to adopt new technology due to security risks that can come from change
-The precedent of current systems (if it's not broke don't Fix it).
While these are valid concerns, it hurts the industry a lot, as it negatively effects the customer experience, opens the door for competitors such as financial technology companies to fill the void they leave in the market, and reduces internal efficiency.
Our task
Our task within this problem space was to first determine an area we could integrate artificial intelligence into within the financial services industry, whether it was internal focusing on practices and efficiency, or customer facing focusing on user experience.
To achieve this our team would first have to analyze the problem space and understand what areas of opportunity there were, then to create a solution that solves one or multiple of the problems addressed, while considering the constraints that come with working within such a data sensitive field.
Embracing versatility to ensure success
Within this project I took on multiple roles to ensure the success of my team, operating both as a product manager as well as a researcher. As a product manager I created the project plan and sprint outlines within the beginning of the project, as well as designed and led a co-design workshop with multiple industry professionals and Microsoft UX designers. As a Researcher I led multiple research phases, conducting secondary research as well as leading interviews with industry professionals.
Project Planning
While the Financial services industry is a large and well established industry, many of the tools they use are quite antiquated. This is due to a few reasons:
- Hesitance to adopt new technology due to security risks that can come from change
- -The precedent of current systems (if it's not broke don't Fix it).
While these are valid concerns, it hurts the industry a lot, as it negatively effects the customer experience, opens the door for competitors such as financial technology companies to fill the void they leave in the market, and reduces internal efficiency.
My Approach
Due to the exploratory nature of this project I adopted and modified googles double diamond for our teams project plan. This method divides the design process into 2 main parts, with the first focusing on defining the problem space, and the second focusing on creating the solution. After creating the general outline I filled it in with activities and sprints. within the first diamond of our plan I planned a secondary research sprint as well as a primary research sprint, where we would first create a base of knowledge of the problem space to work off of, then move into ideation and design within this problem space .
Creating a solution that meets both the explicit and implicit goals.
The result of this project was handing off 2 main deliverables to Microsoft. The first was a comprehensive research doc to give to the UXD research them, giving an in depth dive on the perceptions of AI within the Financial services industry, the possible areas of opportunity for new products to be made, and the existing players within the industry that could either be possible partners for Microsoft or competition within the field. The second result of this project was the creation of a high fidelity prototype showcasing our solution, as well as addressing the drawbacks that stem from working with such a new technology in an established industry.
