FinOps · TBM · AI economics
Technology economics grounded in governance.
I am Eric Driscoll, a senior FinOps consultant at Apptio, an IBM company. My work helps technology, finance, and business leaders turn complex consumption data into accountable decisions, practical operating models, and measurable value.
Client-facing experience
From cost visibility to operating-model change.
My client-facing work spans FinOps strategy, operating-model design, governance, cloud economics, optimization, forecasting, reporting, organizational adoption, and training. The common objective is to connect technology consumption with ownership, decision rights, and business outcomes.
A TBM foundation strengthens that work by linking technology costs and services to the organizations and outcomes they support. FinOps adds the collaborative practices needed to manage variable consumption and improve decisions continuously.
Current direction
Extending FinOps discipline to AI.
I am applying established FinOps, TBM, governance, and optimization methods to AI economics: understanding token consumption, attributing cost, selecting appropriate models for a task, forecasting demand, and evaluating value and return on investment.
Here, token economics refers to AI consumption and value—not cryptocurrency. The focus is how model usage, tokens, quality, latency, risk, and business outcomes inform responsible technology choices.
This direction includes task-to-model governance, practical unit economics, policy-driven model access, and governed automation. The goal is not automation for its own sake; it is to encode sound decisions into repeatable, auditable workflows that reduce effort and improve control.
Working principles
Build for decisions, accountability, and learning.
- Begin with a defined business decision, owner, and value measure.
- Connect financial, technical, operational, and risk perspectives.
- Use clear policies, transparent exceptions, and measurable controls.
- Set materiality thresholds, review cadences, and explicit stopping rules.
- Prefer focused tools and workflows over unnecessary platform complexity.
- Measure adoption and outcomes, then use evidence to refine the policy.
Portfolio purpose
A record of work and an active laboratory.
This site documents selected professional themes, independently developed frameworks, and projects that demonstrate how I approach technology economics, governance, optimization, and focused software delivery.
Project pages identify their context and maturity where relevant. Some work is exploratory or in development and should not be read as a claim of completed client deployment or realized results. Confidential employer and client information is intentionally excluded or generalized.
Review selected work