AI Literacy for the Modern Workplace
97% CSAT
bilingual course + quiz program with ADKAR in the design · CSAT measures satisfaction, not adoption
AI Adoption Strategy
Before commissioning training, technology, or metrics, this engagement organizes the decisions: where to start, which pilot fits the context, who is accountable for it, and what needs to happen next. The scope ends with an approved design; execution, integrations, and operations are later workstreams.
Enterprise experience
Since 2020
corporate facilitation and transformation for global brands · transferable experience, not direct proof of AI adoption
Service at a glance
Duration
2-6 weeks
Audience
Leadership, HR/L&D, and transformation sponsors
Outcome
Priorities, a bounded pilot, accountable owners, and an adoption roadmap
Format
Strategic consulting
Who it's for
- Sponsors who need to decide where to invest before commissioning a larger solution.
- HR, L&D, innovation, and technology teams that need to divide program responsibilities.
- Business areas with many possible use cases and little clarity about priority, risk, and dependencies.
How it works
- Milestone 1 — assess maturity, routines, constraints, and decisions already made.
- Milestone 2 — prioritize use cases by value, feasibility, risk, and data readiness.
- Milestone 3 — design the pilot with audience, hypothesis, boundaries, success criteria, and stop criteria.
- Milestone 4 — define the sponsor, accountable owners, decision forums, and minimum governance.
- Milestone 5 — build a roadmap with dependencies and the next training, asset, technology, and measurement workstreams.
What you get
- Executive assessment documenting decisions, gaps, and assumptions
- Prioritized backlog with visible criteria and rationale
- Pilot canvas with scope, exclusions, milestones, and acceptance criteria
- Accountability and governance map for decisions and escalation
- Approved roadmap, conditional on the identified dependencies
Related case studies
Frequently asked questions
What is included — and excluded — from this engagement?
Assessment, prioritization, pilot design, accountable owners, governance, and roadmap are included. Cohort facilitation, full asset production, integration development, and ongoing operations are not assumed; they can become separate scopes after the upstream decisions.
Who needs to participate in the purchase and the work?
The engagement needs a sponsor who can make decisions, representatives of affected areas, and access to people who understand processes, data, security, and technology. Without those inputs, the roadmap records assumptions and dependencies instead of treating them as facts.
What are the acceptance criteria for the strategy?
The work is accepted when priorities and exclusions are justified, the pilot has a clear hypothesis and boundaries, accountable owners are named, and the roadmap states milestones, pending decisions, and dependencies. It does not guarantee future adoption or impact without execution and data.
Contact
To talk about this service, write to oi@dorly.com.br.
Other services
Learning Paths & Workshops
Purchasable formats for a synchronous decision-making and practice experience: executive session, hands-on workshop, or modular path. Each format combines facilitation, real tasks, and feedback during the activity; it is not a generic lecture or a promise of behavior change without follow-through.
AI Prototypes & Demos
MVPs, automations, and demos to test an idea's value before scaling — using tools like ChatGPT, OpenAI API, n8n, TypeScript, and AWS to prove what works with a tight scope.
Enablement Playbooks & Assets
Enablement means giving a team practical conditions to use AI without always depending on outside help. The package turns recurring decisions and tasks into editable playbooks, templates, rubrics, and guides with a defined audience, validation path, owner, and maintenance rule.
Metrics & Continuous Improvement
I design the model connecting reaction, learning, behavior, and impact without treating correlation as causation. The work defines what to measure, where the data comes from, and how to read the signals; business outcomes and integrated dashboards depend on data quality and later implementation.