SELECTED PROJECT:
Democratizing Data
@ AT&T | 2021-22
Helping AT&T design the future of AI across the organization.
The Need
AT&T tasked us with creating their vision to make AI available across the organization. We developed Data Stories, an AI collaboration hub that provided all AT&T business people with simple-to-use yet highly sophisticated AI and machine learning tools, empowering no-experience AT&T users to find relevant, trustworthy AI-powered insights to better serve their customers.
The Work.
Over the course of four months, AT&T engaged TheoremOne to research what it would take to level up Non-Data Scientists to confidently consume or collaborate on AI.
We engaged people with diverse roles across BUs within AT&T to answer the following questions around AI and data.
How might we democratize AI creation?
How might we reduce friction to engage CDO (ATT’s Chief Data Office)?
How might we drive AI usage within AT&T development teams?
Our solution was driven by an expansive discovery and design process built on primary and secondary research.
TheoremOne engaged directly with AT&T stakeholders and users through interviews, cognitive walkthroughs, and prototype testing, as well as developed insights from deep dives into third-party tools and industry best practices.
Discovery & Design Process
In order to create impactful solutions, the team followed design thinking and UX research best practices. Our approach required close collaboration with stakeholders, SMEs, and potential users throughout the project.
TheoremOne conducted in-depth interviews with project stakeholders to surface key program goals and data & AI best practices. Following stakeholder interviews, we engaged potential users to understand their current needs and pain points.
This approach informed decisions around product strategy, design, and prototyping, with the intent of informing AT&T’s CDS product roadmap
Methods & Activities
Facilitated a 5 day intensive Design Sprint to identify the highest-value areas of focus
Designed and tested 10 interactive prototypes and rapidly iterated, based on user feedback
Collaborated with AIaaS program leaders to ensure we took their needs into account and could leverage existing systems.
Conducted 1:1 & group interviews to surface key user insights and needs
Audited 3rd party tools to better understand user and systems integrations opportunities
The Outcome.
Increased overall accessibility to AI methods and capabilities for non-professional data scientists
Developed solutions that make data & AI more consumable to a broader audience
Created opportunities for employees to become evangelists of CDS projects and programs
Identified and defined opportunities for technical integrations and engineering feasibility
Designed and prototyped a product that is validated by potential users and targets their specific workflow needs
Provided a Strategic Roadmap to launch a path to building fully functional software