Can Ai make us more competitive?
Through a Design Sprint process
Overview
Empowering Professional Competitiveness
In today’s fast-paced world, staying professionally competitive is a challenge that many individuals face. The constant evolution of industries, technologies, and job markets demands that people adapt and acquire new skills throughout their careers. However, the reality is that many resist change, believing it’s either too late to pivot or they lack the time and resources to upskill.
Our mission was to tackle this pervasive issue and create an innovative and creative solution that would enable individuals to stay updated, learn, and adapt to the ever-changing professional landscape. In essence, we sought to answer the question:
“How can we help people stay current and become more competitive?”
The Challenge
Our mission was to find a way for individuals to stay professionally competitive in a rapidly evolving world, regardless of their age or background, breaking the barriers of resistance to change and the misconception that it’s too late to learn new skills.
The Importance of Staying Updated
The significance of staying updated in today’s professional world cannot be overstated. It directly impacts the quality of work and the ability to meet the ever-increasing expectations of clients and employers. Staying current is not just a preference; it’s a necessity for long-term success.
The Design Sprint Approach
To tackle this challenge effectively, our team adopted the Design Sprint methodology — a five-day collaborative process developed by Google. It empowered us to rapidly prototype, test, and validate innovative solutions, initially working as a team and later transitioning to individual exploration to gain a comprehensive understanding of the problem and generate diverse ideas to address it.
Monday | Understand
On the first day of our Design Sprint journey, we dived deep into understanding the challenge at hand — how to help individuals maintain professional competitiveness.
We explored the various aspects of this issue, including the psychological barriers to change and the importance of continuous learning in today’s world. Through research, discussions, and brainstorming, we laid the foundation for a solution that would truly address the core of the problem.
We posted all our thoughts in a big plan, starting the week by asking a wide range of questions about how to keep people updated in the digital field. This phase, known as “Sprint Questions,” allowed us to gather various perspectives on the issue.
We then meticulously analyzed these questions, refining them by adding the phrase “How might we…?” at the beginning of each. This transformation sharpened our focus and set the stage for innovative problem-solving.
Additionally, we embarked on building journey maps to gain a more intimate understanding of our potential users. These maps provided valuable insights into the experiences and pain points of those we aimed to assist.
With all these insights and information on the table, the challenge became unmistakably clear: How can AI make us more competitive in our professional pursuits?
Tuesday | Ideate
As we moved into the second day, our focus shifted to generating creative ideas. We gathered as a team to brainstorm potential solutions, leaving no concept unexplored. The goal was to unleash our collective creativity and come up with a wide range of possibilities that could potentially transform the way people approach professional growth.
With the overarching goal of using AI to empower professional competitiveness, we sought inspiration from a variety of websites and applications, drawing insights and innovative concepts from the digital landscape. This visual exploration enabled us to gather a spectrum of ideas and diverse approaches.
As we followed the structured path of the Design Sprint process, we ventured into individual work to amplify our well of inspiration. Here, we embarked on the Crazy 8 exercise, allocating eight minutes to each participant to let their minds and creativity flow freely, generating a wealth of ideas and concepts.
This exercise allowed us to rapidly expand our pool of ideas and set the stage for further refinement and selection in the days to come.
Wednesday | Decide
With a multitude of ideas in hand, Day 3 was dedicated to the critical task of making decisions. Each team member meticulously crafted wireframes that condensed the insights gleaned from the preceding two days of intense brainstorming and ideation.
Pooling together all three distinct ideas, we embarked on a comprehensive evaluation process, taking into account crucial factors such as feasibility, potential impact, and alignment with our overarching mission. Through a structured decision-making procedure, we narrowed down our focus to the most promising solution: LISA.
LISA is an innovative AI-powered bot that amalgamates elements from our various ideas, incorporating features like:
➡️ A personalized learning platform, enhanced by a bot that establishes a genuine and individualized rapport with users.
➡️ Tailored to address specific learning preferences and time constraints.
➡️ Adapts the learning pace and support to meet the unique requirements of each user.
This winning concept emerged as the cornerstone of our project and formed the basis for the prototype development phase, which we tackled individually in the next stage of our Design Sprint.
Thursday | Prototype
With a well-defined vision in hand, Day 4 revolved around the transformation of the selected solution into a tangible prototype.
I embarked on the exciting journey of crafting a mockup that would serve as a visual representation of the final product, known as Albert — an AI-powered learning app, rooted in three core ideas:
➡️ An AI bot that establishes a close and personalized relationship with each user.
➡️ Learning Journey: Albert AI customizes users’ learning experiences, tailoring content to their unique preferences and the essential subjects required for specific career advancements. The system designs personalized learning paths, recommending specific topics, assignments, and adjusting difficulty levels based on the user’s progress.
➡️ Personalized Learning Paths: Leveraging the power of AI, this learning platform employs machine learning algorithms to assess a user’s unique learning style, track progress, and understand their interests.
Initiating the prototype development process, I began sketching wireflows that encapsulated the ideas we had meticulously explored.
This wireflow served as the foundation for constructing a medium-fidelity model, a pivotal step in preparation for testing in the next phase.
The video showcases the interactive journey of a user as they search for a personalized course within the Albert app, providing a glimpse into the user experience we aimed to create.
Friday | Test
The final day of the Design Sprint was dedicated to testing the prototype with real users. I sought feedback, conducted user trials, and gathered valuable insights to refine the solution further.
The primary objective of the test was to validate the concept of our AI-powered learning app:
- Would users embrace it?
- Was it user-friendly?
- Did it genuinely serve their needs?
To gain a comprehensive understanding, I selected four subjects from our target audience and initiated interactions with them.
Each participant was tasked with performing various actions within the app, providing us with firsthand insights into its usability.
We also solicited their evaluations and feedback on the concept.
This critical step ensured that Albert’s innovation would meet the needs of those striving to maintain their professional competitiveness.
The testing phase yielded valuable findings:
Findings
Strengths
✅ Easy and fluid navigation.
✅ Valuable for learning and discovering new knowledge.
✅ Adaptability is a significant advantage.
✅ Albert’s engaging personality was well-received.
Areas for Improvement
❌ Users found a speaking bot less appealing and somewhat unusual.
❌ A multitude of options did not necessarily enhance the experience.
❌ Some users found it challenging to navigate the interface in black and white.
Lessons Learned from Failing Fast and Failing Cheap:
🚀 AI holds great potential as a valuable learning tool.
🚀 Testing allows for a deeper understanding of user needs and uncovers previously unseen aspects of the product.
🚀 The iterative process is the bedrock of digital product development, guiding us toward continuous improvement.
