Understand
Learn the people, workflows, software, institutional knowledge, constraints, and actual problem.
About Amanda Wion
A hands-on AI strategist, trainer, and business advisor.
I founded AKW AI Consulting to help businesses make sense of a technology that is changing faster than most organizations can realistically absorb. My work sits between frontier AI capability and everyday business use: understanding what new systems can do, testing them against real problems, and translating what proves useful into training, workflows, systems, and strategy.
My background spans AI implementation, go-to-market strategy, business development, and early-stage operations across enterprise software, consumer startups, professional services, and small growing companies. That business context matters. AI is only useful when it fits the people, decisions, knowledge, and work already inside an organization.
I am a dual U.S.–Swiss citizen, fluent in French, and experienced in helping international companies position and expand in the U.S. market. I graduated from UCLA with a bachelor's degree in Global Studies.
Background
A business career that precedes the AI work.
Before consulting on AI, I spent years inside real businesses: building, selling, operating, and scaling. That experience is why the work never starts from the technology.
Cross-industry experience
Enterprise software, consumer startups, professional services, and small growing companies across AI implementation, go-to-market strategy, business development, and early-stage operations.
UCLA, Global Studies
Bachelor's degree from UCLA in Global Studies, grounding the work in international context, research, and cross-cultural understanding.
Dual U.S.–Swiss citizen
Fluent in French. Experienced in helping international companies position, operate, and expand in the U.S. market.
How I learned AI
Discovery, not doctrine.
My expertise in AI has been built through years of intensive, hands-on experimentation with rapidly evolving models and platforms. Rather than learning one system or following a fixed methodology, I continuously test, compare, challenge, and apply new capabilities to understand how these tools actually behave.
That discovery-based approach has developed into an ability to quickly recognize patterns across AI systems, determine which tools and approaches fit a problem, and translate emerging capabilities into practical business applications.
AI changes too quickly for expertise to remain static. My work is built around learning with the technology as it evolves, then turning that understanding into systems, strategies, and training that make sense to the people actually using it.
Explore → Test → Compare → Observe → Adjust → Retest → Apply
A power user, not an observer.
Background
An interdisciplinary path into AI.
My path into advanced AI did not begin in computer science or engineering.
I studied Global Studies at UCLA, an interdisciplinary field examining how governance and politics, markets and economics, and society and culture shape one another.
That foundation continues to influence how I approach emerging technology.
I am interested not only in what AI systems can accomplish, but in how their capabilities change the way people work, learn, make decisions, and participate in the organizations and institutions around them.
My technical fluency developed through sustained experimentation: testing models, building systems, comparing capabilities, identifying limitations, and translating what I learned into practical applications.
That combination of interdisciplinary thinking and hands-on implementation shapes my work today.
I approach AI as both a technological capability and a human and organizational transformation.
How I work
Understand. Experiment. Translate. Apply.
Experiment
Test capabilities across models and tools before assuming what the solution should be.
Translate
Turn technical possibility into something the organization can understand and use.
Apply
Build the workflow, system, training, or strategy that proves useful in real work.
Frontier AI capability↔Actual business need
Technical possibility↔Human understanding
AI experimentation↔Repeatable workflow
Recognition
Bring the challenge. We’ll determine the right next step.
The initial 30-minute discovery call is for understanding your goals, confirming fit, and identifying the most useful starting point. It is not a sales presentation, and you do not need to prepare a technical brief.