Systems for scale
Built GTM operating mechanisms supporting more than $600M in annual pipeline creation, integrating executive planning, governance, and business intelligence.
Exploring the economics of AI-enabled work, enterprise transformation, and the operating systems that turn technological capability into measurable business performance.
Where AI investment meets financial accountability, organizational design, and the reality of getting work done.
Eliminating labor expense isn't the same as creating economic value. Why enterprise AI needs a better measure of success than hours saved or positions removed.
Read the perspective ↗Estimate the complete cost of an AI-enabled workflow, with a worked ledger that connects directly to the Value Realization Lab.
Read the cost guide ↗Why renewed human-service staffing didn’t mean abandoning AI—and what automation savings reveal about operating model decisions.
Read the case file ↗The UPS ORION case traces how route optimization became measurable operating benefit through changes to deployment, management, and field practice.
Read the UPS case file ↗Where does an AI productivity improvement stop becoming business value? Examine the diagnostic and its contrasting Klarna and UPS case files, using the same seven dimensions and evidence standards.
Interactive decision models that turn complex strategic questions into measurable scenarios.
Hours saved are an operational measure. Economic value depends on what the organization actually realizes.
Illustrative assumptions only. Released labor capacity is not automatically cash savings or incremental revenue. Validate attribution, costs, and outcomes before using results for investment decisions.
Model the full cost of an AI-enabled workflow, separate capacity from cash savings, and compare scenarios. Learn how to estimate the costs ↗
Experience designing operating mechanisms, aligning stakeholders, and connecting technology to measurable enterprise outcomes.
Built GTM operating mechanisms supporting more than $600M in annual pipeline creation, integrating executive planning, governance, and business intelligence.
Developed production AI-powered seller tools including account planning, prospecting, and opportunity monitoring.
Aligned cross-functional leaders around shared operating mechanisms and redesigned outcome-based performance measures across six roles.
Selected achievements reflect prior professional experience; descriptions are intentionally high-level and do not disclose proprietary systems.
I'm Drew Peneton, a strategy and operations leader working at the intersection of enterprise technology, financial accountability, and organizational performance.
My career spans financial services, marketplace operations, and enterprise cloud—building systems that help organizations prioritize, execute, and measure business outcomes. Today, I'm exploring how those same disciplines can help enterprises realize sustainable value from AI.
My background includes a Master of Accounting and Financial Management and experience designing production AI tools, operating models, and executive performance mechanisms.