Making a complex national transformation challenge actionable
Client
IMF: Digital Transformation Across Scales
Year
2025
Content
Scope of Work
FROM A BROAD QUESTION TO A RESEARCH LENS
AI was changing how designers work. We wanted to understand what it was changing between them.
Most existing research we found focused on individual AI use and performance. Our question was broader:
“How is AI reshaping creativity and collaboration within design teams?”
We studied how AI was changing the design process, team dynamics, and the human judgment involved in creative work.
Literature Review · Trend Research · Diary Studies · Professional Interviews · Expert Interviews · Workflow Mapping · Qualitative Synthesis
VISUAL: Research Framework
THE EMERGING BEHAVIOR
AI is becoming the first collaborator.
Across the research, we observed an emerging “AI-first, human-react” pattern.
Designers increasingly used AI to frame problems, extract insights, generate ideas, and develop narratives before engaging their colleagues.
This increased speed, reduced operational burden, and made visualization and prototyping more accessible. It also changed when human collaboration happened.
VISUAL: Before / After AI Collaboration Workflow
FROM OBSERVATION TO SYNTHESIS
Mapping AI across the design process revealed a broader shift.
AI was accelerating work across Discover, Define, Develop, and Deliver.
As more exploration moved into individual human-AI interactions, teams increasingly came together around developed outputs.
VISUAL: AI Across the Double Diamond / Design Process Map
Collaboration was shifting from co-creation to co-evaluation.
Co-evaluation can make teams faster and help individuals develop ideas further before sharing them. Our research also showed that shared exploration, interpretation, and collective sensemaking can become compressed when more of the generative process happens individually with AI.
VISUAL: Co-Creation → Co-Evaluation Model
LOOKING BENEATH THE WORKFLOW
The workflow was only part of the story.
The effects of AI varied across designers and organizations.
Our systems analysis showed that AI adoption was interacting with existing assumptions around productivity, individualism, and speed.
Teams were already under pressure to produce more with fewer resources. AI fit naturally into that environment by making individual work faster and more autonomous.
VISUAL: Iceberg Analysis
FROM FINDINGS TO DESIGN PRINCIPLES
The research pointed to a different opportunity for AI.
As AI takes on more activities across the design process, our research surfaced four values that become increasingly important for collaborative creative work.
EXPLORE TOGETHER
Create space for teams to discover together.
IMAGINE “WHAT IF”
Support multiple interpretations and reframings.
BUILD ON EACH OTHER
Strengthen ideas through interaction.
OWN OUR STORY
Keep meaning-making and narrative construction in human hands.
VISUAL: Four Design Principles
These values gave us a way to evaluate where AI could support collaboration without optimizing only for individual speed.
PRIORITIZING WHERE TO INTERVENE
We couldn’t design for every part of collaboration.
We mapped 20 design activities against two dimensions:
Does this activity build shared understanding?
Does it strengthen ownership and trust?
This helped us identify Interpretation and Knowledge Competence as priority areas for intervention.
VISUAL: Activity Prioritization Matrix
PRIORITY AREAS
Interpretation
How teams make sense of information and develop meaning together.
Knowledge Competence
How individual perspectives, experience, and judgment become part of collective work.
THE OPPORTUNITY
How might we help teams feel they are discovering answers together, not separately through AI?
This became the starting point for explAIn, where we explored how individual reasoning from AI interactions could become useful to the team.
See how this research became explAIn →