Finance AI strategy hub

This hub ties together notes on how finance organizations adopt AI—from CFO survey signals and unit economics to COSO controls, agent audit trails, orchestration standards, and capability signals. Start anywhere; each piece links sideways to peers and back to this map.

Controls and compliance

• COSO GenAI controls and the AI risk register — February 2026 COSO roadmap, capability taxonomy, and ICFR implications for finance.
• Agent audit trails for close and financial reporting — minimum log fields, SOC 1 gaps, and human approval gates auditors expect.
• AI governance for finance teams: model audits, controls, and trust — AICPA-aligned angles before you scale past a pilot.

Economics and unit economics

• Inference economics and AI COGS — cost per successful output, agent loop multipliers, and driver-based forecasting.
• Compute capacity as a CFO supply chain — GPU commitments, lead times, and stacked contract portfolio risk.
• AI FinOps in corporate finance: ROI, unit economics, and the 2026 reality check — BCG-style ROI benchmarks, inference spend per workflow, and KPIs CFOs add to dashboards.

Operating model and efficiency

• Agentic FP&A: long context, scenario planning, and close automation — million-token Q&A, scenario agents, AP automation, and metrics that matter.
• The future of finance and AI: agentic systems, efficiency, and augmented analysis — macro view on where work moves next.
• AI in finance 2026: scaling where the productivity gap hurts most — workloads, budgets, and where adoption is real.
• What CFOs are prioritizing in 2026 — Deloitte CFO Signals numbers on digital finance and agents.

Agents, automation, and orchestration

• Multi-agent orchestration in finance: MCP, A2A, and intent-based workflows — beyond single chatbots; interoperability standards and finance controls.
• AI agents in finance: from experiments to transformation priorities — how agentic workflows differ from chat-only GenAI, and what to log.

Capabilities and careers

• Finance skills the AI economy is pricing — capability map from LLM labs, hyperscalers, and enterprise finance hiring signals.
• Learning AI in finance: a practitioner’s 90-day map — one measurable workflow at a time, aligned with 2026 CFO priorities.

Stack and procurement

• Model-agnostic AI stacks for finance: swap models without rebuilding workflows — portability layer, open vs closed APIs, governance on model change.
• When ERP and CRM become agentic: what finance leaders should watch — procurement, pipeline, and GL impact; oversight design for ops agents.
• Embedded AI vs. point solutions — L.E.K. OCFO survey on how CFOs buy and deploy.
• Five AI tools for financial analysis by use case — named platforms by use case, with limits and governance caveats.
• Building an AI-powered financial dashboard with Python — build lens and narrative automation.

Profession and accounting

• The future of accounting and AI — close automation vs advisory work, with controls and metrics to track.

For collaboration or briefings, use the contact page. Full reverse-chronological list: blog .