About Liz Linares.
I’m a learning strategist working at the frontier of AI adoption. My foundation is L&D — learning strategy, enablement, behavior change, readiness, and capability building. The frontier is helping organizations redesign workflows, adopt AI responsibly, and keep human judgment at the center of work.
My work is about helping people use AI well: not as a replacement for human expertise, but as a support system for clearer decisions, faster workflows, better practice, and more sustainable performance.
I'm not an AI engineer. I design the systems, workflows, and capability architecture that make AI usable, governable, and durable inside real organizations.
From frontline facilitation to enablement systems.
- 01FacilitationFrontline
- 02Instructional DesignPurdue M.S.
- 03ConsultingEnterprise
- 04Global Sales EnablementSaaS
- 05AI-supported workflowNow
Started in live facilitation and customer service training across hospitality and frontline teams. Learned how behavior actually changes when people are doing the real work.
Moved in-house to run service programs, support operational leaders, and connect training directly to guest and customer experience.
Built formal learning design expertise through Purdue and consulting work — simulations, onboarding, systems training, and enterprise learning programs.
Now designs onboarding, sales readiness, and AI-supported practice systems for global SaaS enablement teams.
Proof, scannable.
- 10+ years building readiness, enablement, and capability systems across enterprise environments
- 15-year foundation in hospitality, service operations, and frontline customer experience
- Purdue University — M.S. Education, Learning Design and Technology
- Southern New Hampshire University — B.A. Psychology
- Customer service program: guest satisfaction lifted from 70% to 90%
- Mentors senior IDs and leads multi-designer projects
- AI, accessibility, change management, and learning design credentials
Enterprise experience spans SaaS, healthcare, diagnostics, cybersecurity, retail, financial services, manufacturing, utilities, agriculture, and enterprise operations.
Where this practice operates.
Strategic capabilities at the intersection of learning systems, AI enablement, and workflow transformation — built to scale inside real organizational ecosystems.
Designing AI adoption around judgment, expertise, and trust — not around the tool.
Connecting signals, practice, reinforcement, and measurement into one operating system.
Redesigning the work itself so AI removes friction inside the day, not on top of it.
Sparring partners, rubrics, and feedback loops that build capability through real reps.
A layered view of outcomes, workflows, roles, and supports — built to scale and adapt.
Diagnosing where teams, workflows, and governance are ready to absorb change.
Onboarding, coaching, and reinforcement that flex with role, context, and pace.
Seeing the whole field — workflows, signals, behaviors, incentives — before designing the response.
A talented designer who homes in on the client's needs — and the learner's.
Raised our design standards while delivering eight courses on time — and made it fun.
Where AI adoption needs human strategy.
The hardest parts of AI adoption are not the models. They are the human decisions around the work — when to use AI, how to redesign workflows, and how to keep judgment, care, and expertise at the center.
Three principles.
Look at workflow, signals, and reinforcement before designing courses or assets.
Design for behavior change, feedback, and real application — not for seat time or completion checkmarks.
Use AI where it speeds up analysis, supports practice, sharpens feedback, and helps with decisions — with humans in the loop.
I design learning and enablement systems that connect signals, practice, feedback, and performance — so teams build real skill while the work is happening.
Also open to advisory and fractional strategy conversations around AI enablement, sales readiness, learning systems, and workflow optimization — see advisory focus areas.
Continue exploring
A few next steps. Each one opens another part of the work.