Enable AI
Enable AI
Responsibility
Responsibility
Designer
Designer
Product Designer
Duration
Duration
3 months (ongoing)
3 months (ongoing)
3 months (ongoing)
Team
Team
2 UXDs, 2PMs, 2 Data scientists, 8 Devs
2 UXDs, 2PMs, 2 Data scientists, 8 Devs
1 UXR, 2 PMs, 1 DA, 8 Devs
End deliverables:
3 phases of releases (1 released, 2 ongoing)
One modular AI component library
End deliverables:
3 phases of releases (1 released, 2 ongoing)
One modular AI component library
What's Wrong?
What's Wrong?
What's Wrong?
The current rebate process requires heavy manual effort, which makes the process time-consuming and error-prone.
The current rebate process requires heavy manual effort, which makes the process time-consuming and error-prone.
The current rebate process requires heavy manual effort, which makes the process time-consuming and error-prone.
User quotes
User quotes
User quotes
"Initial setup is very manual and annoying. Everything is very repetitive and takes a lot of careful eye work".
"You guys have some fairly flexible reports, but I find myself needing to often run multiple reports and combine them together."
"My estimate was it takes a week if I want to feed data regularly into Enable the data that comes into us from our vendors in the existing format."
"Initial setup is very manual and annoying. Everything is very repetitive and takes a lot of careful eye work".
"You guys have some fairly flexible reports, but I find myself needing to often run multiple reports and combine them together."
"My estimate was it takes a week if I want to feed data regularly into Enable the data that comes into us from our vendors in the existing format."
"Initial setup is very manual and annoying. Everything is very repetitive and takes a lot of careful eye work".
"You guys have some fairly flexible reports, but I find myself needing to often run multiple reports and combine them together."
"My estimate was it takes a week if I want to feed data regularly into Enable the data that comes into us from our vendors in the existing format."
Affinity mapping board
Affinity mapping board
Affinity mapping board
The Goal
The Goal
Integrating GenAI into our product should both improve the current pain point and drive business value
Integrating GenAI into our product should both improve the current pain point and drive business value
User value
User value
Leveraging AI's natural language processing ability can reduce a lot of manual work and relevant errors.
Leveraging AI's natural language processing ability can reduce a lot of manual work and relevant errors.
Business objective
Business objective
Bringing AI into our product is a big value driver that gives us an edge in the market.
Bringing AI into our product is a big value driver that gives us an edge in the market.
Competitor Analysis
Competitor Analysis
Competitor Analysis
Looked into top industry examples of AI usage and shared back referable learnings
Looked into top industry examples of AI usage and shared back referable learnings
Looked into top industry examples of AI usage and shared back referable learnings
Raw competitor experience
Raw competitor experience
Raw competitor experience
Learning shareback: two pillars of a great AI product
Right use cases & functionalities
Right interactions and presentation of AI functions
Right use cases & functionalities
Right interactions and presentation of AI functions
Right use cases & functionalities
Right interactions and presentation of AI functions
Ideations
Ideations
Ideations
With 3 workshops we landed on 2 main use cases and their workflows.
With 3 workshops we landed on 2 main use cases and their workflows.
With 3 workshops we landed on 2 main use cases and their workflows.
Workshop 01: Goals and distractors setting
Workshop 01: Goals and distractors setting
Workshop 01: Goals and distractors setting
This allows the team to work towards a shared vision.
This allows the team to work towards a shared vision.
This allows the team to work towards a shared vision.
Workshop 02: Brainstorm ideas
Workshop 02: Brainstorm ideas
Workshop 02: Brainstorm ideas
We collected each individual's ideas for our problems and created themes of solutions
We collected each individual's ideas for our problems and created themes of solutions
We collected each individual's ideas for our problems and created themes of solutions
Workshop 03: Creating workflows
Workshop 03: Creating workflows
Workshop 03: Creating workflows
Narrowing down to two main use cases, the team worked out key steps in each of the use case's workflow.
Narrowing down to two main use cases, the team worked out key steps in each of the use case's workflow.
Narrowing down to two main use cases, the team worked out key steps in each of the use case's workflow.
Bringing solutions to life
Bringing solutions to life
11 customer validation calls, monitored beta testing, 3 phases of releases for MVP
11 customer validation calls, monitored beta testing, 3 phases of releases for MVP
Running design validation with customers
Running design validation with customers
We conducted structured interviews with 11 customers to test out our prototypes, and also further prioritized our use cases for each release.
3 phases of implementation
3 phases of implementation
Phase 1: Conversational AI chatbot integrated within Enable platform
With the AI chatbot, users can retrieve data across the platform without excessive navigation and repetitively running reports.
Phase 2+3: Redesigned agreement creation flow with AI assistant
AI can create agreements for users by reading and parsing users' uploaded files, and offer contextual assistance to fix anomalies. We also redesigned the end-to-end flows and UI of the entire creation experience for better usability.
AI component design library
AI component design library
Along with the end-to-end design process, I also created an AI design pattern library, integrated into our company's design system, including detailed documentations.
What's next?
What's next?
As this project is still a work in progress, we don't have conclusive data about the project's success yet. But here's what we're doing:
Continuously building feedback log via the AI chatbot
Controlled Beta testing with a smaller user group
Conducting more conversations with users to guide iteration
Learnings
Learnings
Bringing solutions to life
11 customer validation calls, monitored beta tesing, 3 phases of releases for MVP
Clear prioritization reduces project risks during constant change
Clear prioritization reduces project risks during constant change
Projects often face unpredictable changes in timelines and resources. In these moments, having a clear prioritization and alignment on what truly matters enable the team to adapt quickly and make thoughtful tradeoffs while staying focused on the most impactful work.
Projects often face unpredictable changes in timelines and resources. In these moments, having a clear prioritization and alignment on what truly matters enable the team to adapt quickly and make thoughtful tradeoffs while staying focused on the most impactful work.
Running design validation with customers
We conducted structured interviews with 11 customers to test out our prototypes, and also further prioritized our use cases for each release.
3 phases of implementation
Phase 1: Conversational AI chatbot integrated within Enable platform
With the AI chatbot, users can retrieve data across the platform without excessive navigation and repetitively running reports.
Phase 2+3: Redesigned agreement creation flow with AI assistant
AI can create agreements for users by reading and parsing users' uploaded files, and offer contextual assistance to fix anomalies. We also redesigned the end-to-end flows and UI of the entire creation experience for better usability.
AI component design library
Along with the end-to-end design process, I also created an AI design pattern library, integrated into our company's design system, including detailed documentations.
What's next?
As this project is still a work in progress, we don't have conclusive data about the project's success yet. But here's what we're doing:
Continuously building feedback log via the AI chatbot
Controlled Beta testing with a smaller user group
Conducting more conversations with users to guide iteration
Learnings
Clear prioritization reduces project risks during constant change
Projects often face unpredictable changes in timelines and resources. In these moments, having a clear prioritization and alignment on what truly matters enable the team to adapt quickly and make thoughtful tradeoffs while staying focused on the most impactful work.
Website design owned by © Danshi Chen
Website design owned by © Danshi Chen
Website owned by © Danshi Chen
Website owned by © Danshi Chen