Listen to the organization.
Understand employee use, confidence, concern, work realities, leadership expectations, and capacity for change.
Human-Centered AI
Design AI around the people doing the work.
We involve the people whose work will change, define where their judgment is needed, and examine how AI affects their workload, responsibilities, and access to support.
A practical philosophy
Start with human goals and organizational context.
People are accountable for outcomes.
AI can produce, recommend, classify, retrieve, or act. A named human owner remains responsible for its quality and consequences, with authority to pause it, correct errors, and respond to people affected.
Account for the judgment and relationships each job requires.
Jobs include judgment, relationships, context, tacit knowledge, learning, coordination, and accountability. Workflow redesign must account for the whole system.
Augmentation changes roles.
Even when AI does not replace a job, it can alter what people spend time on, which skills matter, how performance is evaluated, and where expertise lives.
Participation improves design.
The people closest to the work often see constraints, exceptions, risks, and opportunities that a top-down technology decision misses.
Help people question and evaluate AI output.
People need enough understanding and practical fluency to direct, question, evaluate, and sometimes reject what an AI system produces.
In practice
Human-centered questions at every stage.
01
Whose work, experience, or decision is changing?
02
What expertise or context must the person retain?
03
Where should human review, discretion, and accountability remain?
04
How could the change affect trust, access, workload, or dignity?
05
What does the person need to understand to use the system well?
06
What feedback will reveal whether the design is helping?
Across the continuum
Human-centered from readiness through implementation.
Define value broadly.
Evaluate time saved alongside quality, employee experience, access, risk, and the organization’s mission.
Build human capability.
Give people the understanding, practice, tools, support, and authority to work with AI thoughtfully.
Design oversight into work.
Make roles, decisions, review, exceptions, accountability, and feedback explicit in the operating process.
The RESPECT framework
Check how an AI workflow affects people.
Responsible ownership. Equitable access. Safety. Privacy. Efficient and effective work. Control. Transparency. These seven principles help a team decide how to use AI and what needs to change before a workflow runs.
Read: What is human-centered AI?Put people and work at the center of your AI decisions.
RUDI helps leadership teams translate human-centered principles into strategy, workflows, enablement, governance, and implementation.