Listen to the organization.
Understand employee use, confidence, concern, work realities, leadership expectations, and capacity for change.
Human-Centered AI
Design AI around people, judgment, and the work that matters.
Human-centered AI asks more than whether a system can perform a task. It asks how technology should change work, where human judgment belongs, who benefits, and what capability people need to remain effective.
A practical philosophy
Start with human goals and organizational context.
People are accountable for outcomes.
AI can produce, recommend, classify, retrieve, or act. The organization still needs clear human responsibility for the quality and consequences of the work.
Work is more than a list of tasks.
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.
Capability protects agency.
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.
Consider quality, capacity, experience, judgment, learning, equity, risk, and mission—not only efficiency.
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.
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.