AI Workflow Foundations
AI Workflow Foundations is a practical, team-based program for research, design, product, and CX teams who are already using AI but need to define shared processes, methods and standards in order to transform their work.
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Who it’s for:
- Research, design, product, and CX teams who want to use AI to both accelerate and deepen their work
- Teams who see a lot of individual AI experimentation, but lack shared processes and workflows
- Customer-centered organizations who want to be intentional about where and how to use AI to keep their work human-led and high quality
Your team will learn how to:
- Map your real future workflow and identify where and how AI will and will not be used
- Use automation to accelerate work and augmentation to scaffold and improve your own thought process
- Apply AI-supported methods to research ops and synthesis, concept generation and prototyping, and stakeholder storytelling without losing quality
- Run small, safe experiments on real work to test what adds value and decide what to implement
- Define team guardails and standards for accuracy, quality, and ethics
Program Design:
1. Pre work (individual + team)
- A short survey on current AI use, confidence, and goals
- A team workflow audit mapping the current process, pain points, and opportunities
2. Workshop 1: Current state analysis (2 hours)
- Review survey insights and align on shared goals and learning needs
- Walk through the current workflow and prioritize the problems to solve
- See case studies of real AI-enabled workflows and learn the core skill of thinking with AI (dialogue + evaluation)
- Define 3-4 focused experiments to run that apply AI methods and new processes to solve the team's top problems
3. Practice week: AI experiments in real work
- Apply selected methods to real project work
- Use experiment briefs to document what worked, what didn't, and what was missing
- Practice AI dialogue and evaluating AI outputs in guided individual exercises
4. Workshop 2: learning & alignment (2 hours)
- Align on what methods and steps improved quality, speed, or collaboration (and what didn’t)
- Define the team’s guardrails and enablers
- Refine a future-state AI-supported workflow
- Agree on next steps to address skill gaps and support adoption
👉🏽 Get in touch
THE DETAILS
Typical time to results:
3-4 weeks
Quick wins:
Immediately applicable AI methods to offload tedious tasks, reduce rework, and accelerate output delivery.
Scope:
What’s included
- Pre-work survey and workflow audit
- Two facilitated working sessions (2 hours each)
- A guided individual practice week to experiment with AI methods applied to real workflows
- The Methods Playbook (23 AI-supported research/design methods)
- AI Evaluation Toolkit (13 quality and evidence assessment methods)
- Thinking with AI exercise to practice iterative AI dialogue
- Future workflow documentation and next steps summary
Team impact:
- Clearer guidance on when and how AI should be used
- Faster synthesis without loss of rigor
- Fewer rework cycles and less duplicated effort
- More confidence sharing AI-supported outputs with stakeholders
- A shared language and set of standards, methods and norms across the team
Business impact
- More consistent insights and deliverables
- Faster, better-supported decisions
- Reduced operational bottlenecks
- Increased team capacity without burnout
- Safer, more responsible AI adoption
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