Productivity blocked by manual workflows
Teams were drowning in time-consuming, repetitive tasks, leading to delays, rising costs, and missed revenue opportunities. Scaling these inefficient workflows would only make things worse.
Teams were drowning in time-consuming, repetitive tasks, leading to delays, rising costs, and missed revenue opportunities. Scaling these inefficient workflows would only make things worse.
By designing AI as a supportive tool rather than a disruptive force, we transformed skepticism into efficiency—proving that when done right, AI is not just a productivity booster, but a key driver of business success.
Adoption
Manual overhead
Task completion time
Product Strategy, Vision, Research, IXD, Visual Design
3 months
1 PM, 4 Engs, 2 PDs
The challenge is that users didn’t trust AI to handle critical tasks and feared losing control over decision-making.
Through user research, iterative design, and cross-functional collaboration, I transformed AI from an abstract concept into a trusted, time-saving assistant, driving a 75% increase in efficiency and enabling teams to focus on revenue-generating work.
I led the design of an AI-driven task management platform that automated manual workflows, enabling teams to focus on high-value work instead of administrative overhead.
Design enhancements
• Automated task assignment – AI intelligently assigned tasks to the best-suited team members.
• Real-time progress tracking – A dashboard provided instant visibility into workload distribution.
• Smart prioritization – AI dynamically adjusted priorities based on urgency and deadlines.
• Predictive insights – Actionable analytics helped teams optimize workflow efficiency.
I led stakeholder interviews, user research, and process audits to pinpoint key challenges:
• Users feared losing control – They wanted visibility into AI-driven task decisions.
• Confusion around AI’s role – They weren’t sure where automation would help versus hinder.
• Resistance to workflow changes – Existing habits made AI adoption feel like a disruption.
• Need for clear ROI – Teams needed proof that AI would actually save them time and drive measurable business value.
I focused on designing an AI experience that enhanced, rather than replaced, human decision-making:
• Transparent AI Decisions – Clear justifications for why AI recommended or automated certain tasks.
• User Override & Control – Users could modify, reprioritize, or reject AI-suggested tasks.
• Seamless Workflow Integration – AI worked within existing task management tools, rather than requiring users to adapt to a completely new system.
• Small Wins First – AI started with low-risk automations (e.g., task prioritization), then expanded based on user trust and adoption.
This initiative reinforced a key lesson:
AI adoption isn’t just about automation—it’s about trust, control, and measurable business impact.
• Users need to feel in control – Transparency and flexibility drive AI adoption.
• Seamless integration matters – AI should enhance workflows, not disrupt them.
• Efficiency unlocks business growth – Freeing teams from repetitive tasks allows them to focus on higher-value initiatives.