4CRisk.ai’s playbook for AI governance and compliance

4CRisk.ai has published a guide on deploying a robust AI governance programme in 2026, with Supradeep Appikonda, COO and co-founder, setting out the core steps organisations need to stay aligned with AI regulations, rules and standards.

The guide frames governance as a practical programme that goes beyond defining AI strategy and principles, extending into AI model governance and technical monitoring—especially where vendors are involved—to evidence compliance with internal policies.

It says organisations are moving past simply showing their frameworks align with regulation (such as the EU AI Act), rules (including federal or state requirements) and standards (including NIST or ISO). Instead, programmes are being expanded to include impact assessments and technical monitoring so firms can demonstrate that both in-house and third-party AI products comply with internal procedures and controls.

Appikonda describes this as “third-party or vendor risk management on steroids”, focused on AI compliance. A “truly robust AI Governance program”, the guide argues, depends on risk tiering and assessments, regular monitoring of AI models, and the ability to close gaps with defensible evidence.

It notes many organisations have already built accountability through steering committees, working groups, training teams and sometimes an AI centre of excellence, but execution remains challenging when key documentation is “buried” across RFPs, contracts, vendor disclosures, attestations and pilot results.

The guide highlights foundational work across principles (trustworthiness, transparency, fairness, bias and accountability), human oversight, risk categorisation and Algorithmic Impact Assessments, plus security risks such as spoofing and data poisoning.

It also points to ongoing needs around data lineage, privacy compliance (GDPR, CCPA), model quality control, explainability, tracking “model drift,” and structured reporting. For scaling, it outlines steps including automated regulatory change management and horizon scanning, harmonised controls, vendor assessments using “test once, comply many, report across,” continuous monitoring, and faster stakeholder reporting with humans finalising outputs.