AEGIS is how regulated enterprises turn governance from compliance overhead into production velocity: evidence you can defend, controls that scale, oversight boards trust, and cost discipline that survives token economics.
Unified Enterprise AI Governance · 2026
The operating system for governed agentic AI
Each pillar addresses a distinct governance domain: accountability, inventory, assessment, agentic controls, transparency, monitoring, and evolution, interconnected through a shared evidence layer and common risk language. Two cross-cutting layers thread through the stack: cost governance and supply-chain & access resilience. One architecture satisfies cross-regulatory and G7 2026 voluntary-signal expectations simultaneously, so governance accelerates production instead of delaying it.
Work email unlocks the full Agentic Enterprise Governance & Intelligence Standard PDF on this page: 7 pillars, G7 2026 signal map, cross-regulatory matrix, agentic controls, cost governance, access resilience, and 90-day roadmap.
We're launching a new series on AEGIS, starting with the executive case: why governance is not the brake on AI, but the architecture that lets regulated enterprises move from pilot to production with evidence, controls, oversight, and cost discipline.
Then we go practical: how AEGIS maps across Microsoft, Salesforce, ServiceNow, Snowflake, Databricks, frontier models, open-source AI, MCP, agent-to-agent systems, and token-cost optimization.
The most publicly documented enterprise Claude deployment in banking: 250,000 employees on LLM Suite, ten named financial-services agents, and a connector layer built on Model Context Protocol over legacy JADE and OmniAI infrastructure. JPMorgan's own executives say the constraint is no longer model capability — it's organizational absorption and governance clarity. AEGIS maps that gap to deployable controls.
Each deadline maps to AEGIS pillars and governance outputs, not one-off projects. See what passing looks like before examiners or regulators ask.
Pass: consequential-decision impact assessments, public risk statement, algorithmic-discrimination duty of care. Federal court stayed SB 24-205 AG enforcement (Apr 27, 2026); replacement SB 26-189 signed May 14 - confirm posture with counsel.
See AEGIS mapping →Pass: disclose AI interactions, label synthetic / deepfake content, traceable system documentation. Art. 50(2) marking grace to 2 Dec 2026 for systems on market before 2 Aug 2026 (Digital Omnibus). Most Art. 50 duties apply 2 Aug 2026 — Omnibus does not delay chatbot/deepfake disclosure.
See AEGIS mapping →Pass: agent inventory, model-risk file per GenAI use, human oversight + logging, board attestation.
See AEGIS mapping →Pass: pre-use notice, opt-out for significant decisions (employment, credit, housing, health, education), access to ADMT logic + appeal rights.
See AEGIS mapping →Pass: FRIA, risk mgmt system, human oversight, logging, conformity assessment, post-market monitoring. EP approved Digital Omnibus 16 Jun 2026; Council adoption pending. Until OJ publication, Aug 2026 high-risk date remains on the books.
See AEGIS mapping →Start with readiness, staff the bench, or fix context and experience, then scale under AEGIS.
Seven dimensions. Twenty-eight questions. Under five minutes. Built on the AI readiness frameworks published by PwC, McKinsey, Deloitte, BCG, and Gartner in 2025-2026 — get a scored breakdown and priority actions you can fund this quarter.
ROI: Know which governance gap is blocking scale before you spend on pilots.
Take the diagnostic →Nine specialist roles for regulated work that ships in production: diagnostic leads, context engineers, agentic UX, MRM, and more. Remote-first, transparent day rates, vetted through talent.myndQ.ai.
ROI: Deploy governed agentic systems without a 12-month hiring cycle.
View open roles →S&P Global's 2025 Voice of the Enterprise survey found that 42% of companies abandoned most of their AI initiatives in 2025 — up from 17% the year prior. RAND, MIT NANDA, and McKinsey research converges on a consistent set of root causes: weak data foundations, misaligned success metrics, and broken workflow integration. Two AI Success Pack programs address the operational layers that determine whether AI delivers ROI in production: the context layer (knowledge infrastructure) and the experience layer (interaction design).
ROI: Turn governance from overhead into measurable adoption and production value.
Explore programs →Each card specifies the exact governance activities, the regulations it satisfies, agentic AI-specific controls, and the roles accountable.
Build the organizational structure that makes AI governance real and defensible
You cannot govern what you cannot see - complete visibility is non-negotiable
Gate deployment on evidence of safety - not assumptions
The technical implementation of governance - where policy becomes code
Legal obligations to disclose, explain, and empower - meeting the person affected by AI
Governance doesn't end at deployment - it intensifies. Every system needs a heartbeat.
AI regulation is evolving faster than any other tech domain - the framework must evolve with it or become a liability rather than a shield
Implement AEGIS once. Each pillar carries compliance weight across multiple regulations simultaneously.
Regulation → pillar coverage
| Regulation | P1 Govern |
P2 Inventory |
P3 Assess |
P4 Controls |
P5 Transpar. |
P6 Monitor |
P7 Evolve |
|---|---|---|---|---|---|---|---|
| EU regulations | |||||||
| EU AI Act - Prohibited Practices (Art. 5) | ● | ● | ◐ | ● | ◐ | ◐ | - |
| EU AI Act - High-Risk AI (Art. 9-17) | ● | ● | ● | ● | ● | ● | ◐ |
| EU AI Act - GPAI Model Obligations | ◐ | ● | ● | ◐ | ● | ● | - |
| GDPR - Automated Decision-Making (Art. 22) | ◐ | ◐ | ● | ◐ | ● | ◐ | - |
| US federal | |||||||
| NIST AI RMF 1.0 (GOVERN / MAP / MEASURE / MANAGE) | ● | ● | ● | ● | ◐ | ● | ● |
| ISO/IEC 42001 AI Management System | ● | ● | ● | ● | ◐ | ● | ● |
| OMB M-25-22 Federal AI Procurement | ● | ◐ | ◐ | ● | - | ◐ | - |
| FTC Section 5 - AI Deception & Unfairness | ● | - | ◐ | ◐ | ● | ◐ | - |
| SEC AI Risk Disclosure (10-K / 8-K) | ● | ◐ | ◐ | - | ● | ● | - |
| US state laws | |||||||
| Colorado AI Act (SB 24-205 / SB 26-189) | ● | ● | ● | ◐ | ● | ● | ● |
| California CPPA ADMT Regulations | ◐ | ● | ● | ◐ | ● | ◐ | ● |
| California AI Transparency Act (SB 942) | ◐ | - | - | ◐ | ● | ◐ | - |
| Illinois AI in Employment (AIVII) | ◐ | ● | ● | - | ● | ◐ | - |
| NYC Local Law 144 (Hiring Bias Audits) | - | ◐ | ● | - | ● | ◐ | - |
| Texas TRAIGA (Prohibited AI Practices) | ● | ◐ | - | ● | - | - | - |
| G7 France 2026 · voluntary signals | |||||||
| HAIP Reporting Framework 2.0 (OECD, May 2026) | ● | ● | ● | ◐ | ● | ● | ● |
| G7 Évian · Safer digital space for minors | ◐ | ◐ | ● | ● | ● | ◐ | ● |
| G7 Évian · Frontier AI (finance & cyber) | ◐ | ◐ | ● | ◐ | - | ● | ● |
| Model access & jurisdiction resilience (operational) | ● | ● | ◐ | ◐ | - | ◐ | ● |
Autonomous agents that perceive, reason, decide, and act across multi-step workflows introduce governance dimensions traditional ML does not address. These controls layer onto all seven AEGIS pillars.
Fixed-fee packages that turn G7 2026 voluntary signals into evidence you can run, disclose, and defend, add in the engagement planner.
Gap review for youth-facing conversational AI: default safety settings, age assurance, parental controls, restricted interaction modes, and Évian-aligned evaluation evidence.
Add G11 in planner →C2PA provenance, synthetic labeling, deepfake detection integration, and takedown workflows, satisfies EU Art. 50 and G7 provenance expectations. Existing governance SKU.
Add G09 in planner →Live exercise for Legal, Risk, Treasury, and Engineering on frontier-model systemic risk, vendor access loss, and cyber misuse, aligned to G7 Évian finance and cyber tasking.
Add G12 in planner →Ungoverned AI spend is a board-level risk hiding in plain sight. Cost governance threads through Pillars 1, 2, 4, and 6 - making compliance the financially optimized choice.
G7 Évian elevated frontier-model access and vendor jurisdiction as operational continuity risks, not compliance checkboxes. This layer threads through Pillars 1, 2, 4, and 7 alongside cost governance.
Microsoft
Adobe
NVIDIAInception
Fixed-fee offerings mapped to AEGIS pillars, G7 2026 signals, and binding regimes (AI Act, Colorado, TRAIGA, ISO 42001, SR 11-7). Sized to fit one budget cycle. Outputs you can hand to the board or a regulator.
Before you spend another dollar. Fixed-fee, 2 - 4 week engagements. Most clients start here.
Scoped, outcome-linked engagements. Complexity slider adjusts where in the range you land.
Pick one tier. Monthly retainer, 6 - 12 month minimum.
Fixed package, 4 - 8 weeks to launch. Priced for speed.
Hourly billing rewards slowness. We agree on scope and price upfront, then deliver.
The range you see is the range we quote. Where you land depends on scope, complexity, and data quality.
Month-to-month after the minimum term. If we stop delivering value, you should be able to stop paying.
Full transfer on Build. Your team pairs with ours. Nothing leaves as a black box.
AEGIS (Agentic Enterprise Governance & Intelligence Standard) is Ariana.Digital's unified framework for enterprise AI governance, seven interconnected pillars, a cross-regulatory evidence layer, and agentic controls that let regulated organizations move from pilot to production with defensible oversight and cost discipline.
When treated as operating infrastructure, not a late-stage compliance checkbox, governance becomes the architecture that unlocks production: inventory, assessment, human oversight, logging, and cost governance built into how agents run.
EU AI Act, Colorado AI, SR 11-7 and OCC expectations, CCPA ADMT, ISO 42001, NIST AI RMF, G7 HAIP Reporting Framework 2.0 voluntary deployer transparency, and sector-specific examiner requirements, mapped through a single cross-regulatory matrix rather than one-off compliance projects.
G7 Évian 2026 did not create binding law. It sharpened voluntary expectations: child-safe conversational AI, synthetic-content provenance, frontier AI financial and cyber preparedness, and allied model-access resilience. AEGIS produces the operational evidence behind those signals, through seven pillars plus cost governance and supply-chain access resilience, without duplicating ISO, NIST, or EU AI Act programs.
A new Ariana.Digital series starting June 22: the executive case for governance as operating infrastructure, then practical implementation across Microsoft, Salesforce, ServiceNow, Snowflake, Databricks, frontier and open-source models, MCP, agent-to-agent systems, and token-cost optimization.
Fixed-fee Diagnose, Build, Run, and Governance offerings, scoped after a 30-minute call. Use the engagement planner on this page to explore fit.
Fixed fee, not hourly. Ranges in the engagement planner are the same ones we quote in contracts, finalized after a scoping call. Full IP transfer on Build. Run is month-to-month after the minimum term. Diagnose fees credit toward Build within 90 days.