I am an AI economist focused on helping organisations make better decisions about Artificial Intelligence. My work sits at the intersection of economic analysis, human judgement and responsible AI practice.
The V17 approach
V17 helps organisations evaluate, design and govern AI in ways that create durable value. The approach combines economic thinking, data analysis and human expertise to align AI initiatives with clear business, policy and research objectives.
Technology alone does not create competitive advantage. Organisations succeed when AI is tightly connected to strategy, domain knowledge and responsible governance, with clear incentives and feedback loops.
Human-in-the-Loop (HITL) consulting
V17 uses a Human-in-the-Loop (HITL) consulting model. AI systems are treated as tools that extend expert judgement, not replace it. Quantitative models surface options, trade-offs and risks; human decision-makers interpret these outputs, apply contextual knowledge and make the final calls.
This HITL approach is critical for three reasons: it improves decision quality by combining statistical and experiential insight, it reduces the risk or biased automation, and it builds trust among stakeholders who must ultimately own and implement AI-enabled decisions.
Who V17 serves
V17 works with organisations that need clear, defensible reasoning behind their AI choices:
- Academic institutions designing research programmes, curricula and governance frameworks for AI and data-intensive economics.
- Technology companies seeking to evaluate AI product strategies, pricing, incentives and market design through an economic lens.
- Policy makers and government agencies developing regulation, public sector AI use-cases and impact assessments grounded in evidence and economic reasoning.
Across these contexts, V17 focuses on practical, analytically grounded recommendations that help leaders make transparent, accountable and economically sound decisions about AI.
V17 