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Design Researcher

Present research findings to stakeholders and influence product decisions

Enhances✓ Available Now

What You Do Today

Frame findings as a story, connect to business goals, make clear recommendations, handle pushback from skeptics

AI That Applies

AI helps build presentation decks from research data, generates compelling data visualizations

Technologies

What Changes

Presentation creation is faster. More time for the political work of building research influence

What Stays

Storytelling, reading stakeholder reactions, knowing when to push and when to plant a seed

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for present research findings to stakeholders and influence product decisions, understand your current state.

Map your current process: Document how present research findings to stakeholders and influence product decisions works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Storytelling, reading stakeholder reactions, knowing when to push and when to plant a seed. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Presentation AI tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long present research findings to stakeholders and influence product decisions takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.