In this phase, the team maps both the Current User Journey (CUJ) and the Target User Journey (TUJ) to visualize how users interact with the product today versus how AI can enhance their experience tomorrow.

The Current User Journey captures every major step of the existing workflow, including:

• Step/Action
• Actor (user or system)
• Pain Point / Emotion
• Data exchanged
• KPI or performance metric

Designers often use AI to generate a first draft of the CUJ by feeding it user research data (e.g., transcripts, personas, and insights). AI can quickly outline key stages, actors, and pain points (“Step 3: User waits for manual approval – Pain: long delays”), which the team then reviews and corrects. The finalized CUJ serves as a clear snapshot of the current experience and its bottlenecks.

The Target User Journey reimagines the same flow, now augmented with AI.

At this stage, the SDAA framework emphasizes explicit Human–AI role allocation:

• Steps the AI performs autonomously
• Steps where Human and AI collaborate
• Steps reserved for human judgment

Example: “AI analyzes the user’s input and drafts a recommendation; Human reviews and validates the final decision.”

This clarity prevents over-automation and ensures intentional human oversight, assigning repetitive or low-risk actions to AI and leaving nuanced or high-impact decisions to people.

Throughout journey mapping, AI remains a co-pilot for ideation and acceleration — suggesting improved flows or highlighting opportunities to streamline steps.

However, every AI-generated output is human-validated to ensure realism and alignment with user needs.

Teams also identify HITL checkpoints (Human-in-the-Loop), explicitly marking where users verify, adjust, or approve AI actions.

This guarantees safety, transparency, and accountability at the journey level.