Using AI to Turn Workforce Data into Executive-Ready Presentations
Overview
HR leaders are regularly responsible for presenting workforce insights to executives and stakeholders. While the underlying data already existed in HRIS systems—covering retention, turnover, diversity, benchmarking, and demographics—the process of turning that data into a clear narrative was slow and highly manual.
Users had to analyze data, select relevant metrics, build charts, assemble slide decks, and write supporting commentary before they could communicate insights effectively.
As the sole Product Designer, working alongside two Product Owners and an engineering team, I helped design an AI-powered presentation builder that transformed workforce analytics into executive-ready slide decks in minutes.
The Problem
The platform already provided access to rich workforce data through HRIS integrations. The challenge wasn’t data availability—it was sensemaking and storytelling.
Users struggled to:
- Identify which metrics were most meaningful for executives
- Translate raw data into insights
- Build coherent presentation narratives
- Manually create slides and visualizations
- Maintain consistency across reports
This resulted in a workflow that was powerful but time-intensive, often requiring hours of manual effort per presentation. The opportunity was to reduce the time required to create presentations without reducing accuracy or control.
Discovery & Alignment
Before designing solutions, we began with a structured discovery and sensemaking phase with stakeholders and product owners.
Together, we worked through:
- Product vision and goals
- Core user groups and personas
- User needs statements
- Key Jobs to Be Done
This alignment work was critical in defining what “success” looked like—not just in terms of output, but in terms of user trust and control. We also clarified how this new AI capability would integrate into an existing platform, which already had established workflows and user expectations. A key constraint was ensuring the AI feature felt like a natural extension of the product rather than a separate tool.
Defining the Experience
Once we aligned on user needs and product direction, I mapped out the initial site map and user flows, focusing on how users would move from raw data to a finished presentation.
This helped define:
- Entry points into the AI workflow
- Required inputs for generation
- Points of user review and control
- How generated content would be structured and edited
At this stage, the focus was not UI—it was workflow clarity and system behavior.
Low-Fidelity Exploration & Iteration
I then translated the flows into low-fidelity wireframes, mapping key screens directly within the user journey.
These early concepts were intentionally simple and focused on structure:
- How users initiate a presentation
- What inputs are required for AI generation
- How generated slides are reviewed and edited
- Where users maintain control versus automation
Rather than moving directly into high fidelity design, I presented these early concepts to the client for feedback.
This became a collaborative working session where we:
- Identified gaps in the workflow
- Refined AI input requirements
- Adjusted the balance between automation and manual control
- Clarified expectations for editable outputs
This iteration step significantly reduced ambiguity early in the process and ensured we were aligned before investing in visual design.
High-Fidelity Design
After validating structure and flow, I moved into high-fidelity design.
The final experience supported two creation paths:
- AI-generated presentations
- Manual slide creation
For AI-generated decks, users could input:
- Presentation topic
- Date range
- Desired length
The system then generated:
- Key workforce insights
- Data visualizations and charts
- Structured slide content
- Speaker notes
A critical design principle throughout was maintaining user control.
Even though AI generated the content, every slide remained fully editable, allowing HR professionals to refine messaging before sharing with executives.
This helped balance:
- Efficiency (AI generation)
- Trust (human oversight)
- Accuracy (editable outputs)
Working Within Constraints
This project had a relatively short timeline and limited budget, with a high number of stakeholder requirements.
Because of the structured discovery process and early low-fidelity validation, we were able to:
- Reduce late-stage revisions
- Avoid unnecessary design exploration
- Keep development focused and efficient
- Stay within budget while still meeting all requirements
This upfront alignment work was critical in ensuring we could move quickly without sacrificing quality.
Outcome
The final experience enabled HR professionals to transform workforce data into executive-ready presentations significantly faster than before.
By combining AI-generated content with full user control, we reduced the effort required to build presentations while maintaining trust in the final output. The result was a streamlined workflow that turned a manual, multi-step process into a guided, AI-assisted experience.
Reflection
This project reinforced an important lesson in designing AI-powered tools:
The goal is not to replace domain expertise—it is to eliminate repetitive, time-consuming work that surrounds it.
The most critical design decision wasn’t how the AI generated content, but how users could understand, trust, and refine it.
By investing early in discovery, workflow mapping, and low-fidelity validation, we were able to deliver a solution that balanced speed, control, and usability within tight constraints.
Working Within Constraints
This project had a relatively short timeline and limited budget, with a high number of stakeholder requirements.
Because of the structured discovery process and early low-fidelity validation, we were able to:
- Reduce late-stage revisions
- Avoid unnecessary design exploration
- Keep development focused and efficient
- Stay within budget while still meeting all requirements
This upfront alignment work was critical in ensuring we could move quickly without sacrificing quality.
Outcome
The final experience enabled HR professionals to transform workforce data into executive-ready presentations significantly faster than before.
By combining AI-generated content with full user control, we reduced the effort required to build presentations while maintaining trust in the final output. The result was a streamlined workflow that turned a manual, multi-step process into a guided, AI-assisted experience.
Reflection
This project reinforced an important lesson in designing AI-powered tools:
The goal is not to replace domain expertise—it is to eliminate repetitive, time-consuming work that surrounds it.
The most critical design decision wasn’t how the AI generated content, but how users could understand, trust, and refine it.
By investing early in discovery, workflow mapping, and low-fidelity validation, we were able to deliver a solution that balanced speed, control, and usability within tight constraints.