Category: Blogs

This week I’m back in the United Kingdom—wall-to-wall engagements, packed rooms, and board-level urgency. Two themes are dominating every corridor conversation and every executive session:

1. Digital risk & resilience management (cyber risk, IT risk, information security), this is not your father’s information security program—and the market has noticed, and
2. UK Corporate Governance Code Provision 29—the looming attestation requirement that pulls risk and controls from the boiler room to the bridge.

They’re not separate stories. They’re the same plotline: governance must now prove risk, control, and resilience.

Next week I head to Denmark and Sweden with an overbooked schedule and an active waiting list. It’s so busy I’ve booked four business meetings on Sunday in Copenhagen because the workweek is full. Demand is surging because the operating reality has changed.

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The UK Context: Incidents That Forced the Issue

Yesterday in London, over 90 professionals registered for my Digital Risk & Resilience Management by Design workshop. We opened with what the UK has actually experienced this year—real events that disrupted operations, damaged trust, and elevated the conversation to the board:

• Harrods disclosed a new incident after hackers compromised a third-party, stealing 430,000 e-commerce customer records—a second major event this year (see the latest from GRC Report: Harrods Suffers New Data Breach Exposing 430,000 Customer Records. This wasn’t “just” a data problem; it was a digital supply-chain failure with reputational consequences.
• Marks & Spencer acknowledged a significant cyber incident in the spring, with official updates noting personal data exposure. Independent analyses estimate substantial disruption costs.
• Co-op faced an attack that affected operations and supply, with press reporting on material revenue impact.
• Jaguar Land Rover (JLR) suffered a major cyberattack that halted production and cascaded across suppliers, leading to government action to stabilize the supply chain and a phased restart. This is cyber risk turning into industrial and financial risk overnight.
• Airports across Europe (including the UK) experienced disruptions tied to a third-party check-in provider—collateral damage when an ecosystem vendor falters.
• Looking back to 2024, the Synnovis ransomware event reminded everyone that cyber incidents can spill into clinical operations—in this case, impacting NHS pathology services across London.

Add to that the UK’s Cyber Security Breaches Survey 2025 and public warnings from officials about rising hostile activity; the trendline is clear: frequency, materiality, and interdependence are all up.

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Provision 29: When Governance Must Prove Resilience

The updated UK Corporate Governance Code 2024 applies from 1 January 2025, with Provision 29 (the board’s declaration over the effectiveness of material internal controls, including those over reporting) applying to financial years beginning on or after 1 January 2026. Translation: boards must step beyond narrative disclosure to assert control effectiveness—and evidence it.

Practical guidance circulating in the market rightly pushes companies to identify risks to objectives, define material controls, stand up testing and monitoring cycles, and remediate weaknesses well ahead of the first reporting year. If you wait until year-end, you won’t have the audit trail, telemetry, or confidence to sign. I am teaching a full-day workshop on this on November 6th, UK Corporate Governance Code by Design, LONDON.

Provision 29 makes cyber and digital resilience a governance obligation as it is part of broader risk and internal control management. It’s no longer sufficient for security leaders to say “we’re doing our best.” Boards must demonstrate that controls over risk, operations, and reporting are effective—continuously, not sporadically.

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“Not Your Father’s Information Security Program”: What Keeps Leaders Up at Night

In yesterday’s workshop opening breakouts, attendees shared the nightmares that wake them at 2 a.m. Below I expand on each—because every one is valid, and together they define the new scope of digital resilience.

1. Digital dependence. When every process is digitized, digital is business risk. Capture business-service twins (see below) that tie technology to outcomes so investment and trade-off decisions are made in business units, not technical silos.
2. Ransomware (mentioned repeatedly). Assume data theft + encryption + extortion. Emphasize identity (MFA, phishing-resistant auth), immutable backups, segmentation, EDR containment, and exfil detection. Align with cyber insurance obligations before an event.
3. Data breaches. Move beyond perimeter thinking to data-centric controls: classification, encryption, retention/rationalization, and continuous DLP tuned to business context. Reduce toxic data stores—what you don’t keep can’t be stolen.
4. Third-party & digital supply chain. Most incidents now arrive through someone else’s API, SSO, or managed service. Build tiered criticality, continuous assurance (evidence feeds, attack-surface monitoring), and kill-switch playbooks (token revocation, traffic shaping, failover).
5. Complexity of environment. Hybrid/Multi-cloud, SaaS sprawl, legacy on-prem, OT/ICS—complexity is the attack surface. Rationalize platforms, impose architectural guardrails (identity first, least privilege, service isolation), and automate hardening at the pipeline.
6. Pace of technology, business, risk, & regulatory change. Static frameworks fail in dynamic environments. Shift from annual cycles to continuous risk assessment, streaming indicators (threat intel, misconfig drift), and regulatory horizon scanning tied to policy updates and training.
7. Real-time insight into digital risk & resilience. Dashboards must reflect material risk now, not last quarter. Integrate attack surface, identity risk, vuln posture, and control status into one place, with drill-downs that show evidence, not just colors.
8. Social engineering. Human-centric attacks (phishing, pretexting, MFA fatigue) bypass hardened perimeters. Resilience demands behavioral control design, adaptive training, and active monitoring of anomalous requests—especially in finance, HR, and privileged IT channels.
9. Behavior. Policies don’t move mice; people do. Incentives, consequences, nudges, and leadership example-setting are necessary to turn rules into reflexes. Measure cultural indicators (reporting rates, near-misses, phishing test performance) as rigorously as technical KPIs.
10. AI risk. AI expands both attack surface (prompt injection, data leakage, model theft) and attacker capabilities (automation, deepfakes). Establish an AI risk register, model validation, and guardrails (content filters, retrieval hardening, data minimization), and treat AI vendors as high-risk third parties.
11. Employee practices on social media. Oversharing enables social engineering, doxxing, and physical risk. Provide clear, practical guidance, red-team your own open-source footprint, and monitor for impersonation and brand misuse.
12. Silos of oversight. Security, risk, audit, privacy, and compliance often operate on parallel tracks. Converge on a common risk ontology, unified control library, and shared telemetry to eliminate duplicative testing and blind spots.
13. Lack of assurance. Assurance is not a PDF; it’s a signal backed by evidence. Operationalize continuous control monitoring (CCM), link tests to controls, and maintain an immutable evidence ledger for internal audit and Provision 29 support.
14. Critical system availability. “Data protected” is not “business up.” Map business services to dependencies (apps, data, vendors, facilities), define impact tolerances, test recovery to realistic RTO/RPO, and engineer graceful degradation.
15. Corporate culture. A culture of speed and shadow IT without guardrails breeds loss events. Bake controls into the developer and product experience (policy-as-code, paved roads) so doing the right thing is the fastest path.
16. Interconnected nature of digital risk on other risks. Cyber incidents cascade to operational, financial, legal, and reputational risk. Quantify causal chains: “one auth outage ⇒ order backlog ⇒ revenue dip ⇒ covenant risk.” This is the language of the board.
17. Cyber incidents. Treat incident response as business continuity with forensics. Pre-negotiate counsel, crisis comms, and law enforcement engagement. Rehearse board-level tabletop exercises to align decisions under pressure.
18. Extended enterprise. Partners, affiliates, franchisees, integrators—risk propagates through contracts. Expand scope beyond “vendors” to all external relationships; standardize onboarding, evidence exchange, and offboarding data destruction.
19. Constant data breaches. Frequency has normalized, but tolerance hasn’t. Move toward event-ready posture: pre-built comms templates, regulator playbooks, customer remediation workflows, and materiality decision criteria.
20. Cyber insurance. Policies are tighter; exclusions matter. Map controls to underwriting requirements (MFA, backups, EDR, patching SLAs), maintain attestable evidence, and simulate loss scenarios to set economically rational limits.
21. PCN attacks on refineries (OT/ICS). Process Control Networks in energy and petrochemicals raise safety, environmental, and macro-economic stakes. The UK energy sector remains a prime target; bring OT and IT risk under a single governance model, with strict network isolation, asset discovery, and incident drills that include safety.
22. Access control. Identity is the perimeter. Enforce least privilege, JIT/JEA for admins, continuous access review, and session recording for high-risk functions. Kill standing privileges.
23. Out-of-date systems. Technical debt is breach bait. Build a decommission cadence, isolate what you can’t patch, and make “end-of-life” a board metric with remediation funding.
24. Lack of segmentation. Flat networks turn local issues into enterprise outages. Segment by trust zone, blast radius, and business service; verify with purple-team exercises.
25. Regulations. Requirements are multiplying (DORA, NIS2, CER, UK Code, UK Operational Resilience). Normalize obligations to controls and tests; avoid duplicate evidence generation by centralizing control mapping across frameworks.
26. Support streams such as power. Cyber resilience depends on physical resilience (power, cooling, connectivity). Model these dependencies explicitly and test alternative sites, UPS run-times, and failover contracts.

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Why Provision 29 and Digital Resilience Are the Same Conversation

Provision 29 isn’t a paperwork exercise; it’s a capability: governance that can see material risk, control it, and prove it. Yes, Provision 29 is much broader than digital risk and resilience, but it certainly is a critical part of it. The declaration forces boards to ask:

• Which controls are material to our business services and reporting?
• Do we have evidence, not assertions?
• Can we detect control failure quickly and respond before outcomes degrade?
• Are third-party and AI-driven risks within the same scope of control and testing?

The new standard of care is continuous, assurable, and board-readable.

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Digital Risk & Resilience in the Age of GRC 7.0 – GRC Orchestrate

This is where the next evolution—what I call GRC 7.0 – GRC Orchestrate—earns its keep. Think of it as a business-integrated command center underpinned by digital twins, agentic AI, and continuous assurance:

1. Digital twins of business services. Map each critical service (e.g., “E-commerce checkout”, “Claims adjudication”) to its applications, data, identities, vendors, facilities, and support streams (power, network). Now you can analyze materiality, simulate impact, and target investment where it moves the needle.
2. Unified risk ontology & control library. Collapse silos by adopting one language for risk, control, and obligation across security, resilience, privacy, and compliance. Provision 29 depends on a single source of control truth feeding testing, evidence, and reporting.
3. Continuous control monitoring (CCM) & evidence ledger. Automate tests (config drift, MFA coverage, backup immutability, EDR health, segmentation rules), bind the results to the control, and store signed evidence with lineage. Assurance moves from “annual binders” to streaming signals.
4. Agentic AI for detection, triage, and mapping. Use AI to reconcile findings to controls and obligations, summarize deviations for executives, draft remediation plans, and keep policies aligned to changing regs (DORA, NIS2, UK Code) without manual re-keying. Humans decide; AI does the grunt work.
5. Third-party & AI vendor orchestration. Ingest SOC2/ISO attestations, penetration reports, SBOMs, and attack-surface telemetry. Maintain live risk tiers, enforce contractual controls, and keep “pull-to-revoke” playbooks (SSO tokens, API keys) ready.
6. Identity-first architecture. Make identity and authorization the enforcement plane: phishing-resistant MFA, least privilege, continuous verification, high-risk session recording, and automated removal of stale access.
7. OT/ICS governance alongside IT. Treat PCN assets with their own twin, zoning, and procedure sets. Drill scenarios that integrate cyber response with safety and environmental controls.
8. Resilience analytics & impact tolerances. Tie recovery objectives to business outcomes (orders processed, beds filled, flights dispatched). Visualize tolerances and variance in real time; rehearse failovers using your twins, not guesswork.
9. Board-ready reporting. Replace red/amber/green with narratives grounded in evidence: “3 of 3 material access-controls for E-commerce are in tolerance; segmentation test #142 failed in Zone C; compensating control is active; remediation ETA 72 hours.” That’s a Provision 29-grade update.
10. Assured compliance. Map control signals to obligations and make audit a bystander effect: when evidence is baked into operations, audits consume it—not create it.

This is not a tool swap. It’s an operating model that treats digital risk as a system-of-systems problem, orchestrated across people, process, technology, and partners—with verifiable assurance as the output.

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Closing the Loop

The UK incidents of 2025 — Harrods, M&S, Co-op, JLR, airport disruptions — show how quickly “IT issues” become business crises and governance tests. The only durable answer is a modern resilience architecture with continuous assurance that a board can attest to with confidence.

Now, I’m off to a string of meetings today and tomorrow in London—then wheels up for Denmark and Sweden. If you’re in Copenhagen this Sunday, you already know my schedule is spilling into the weekend. The message from every boardroom is the same: orchestrate resilience, or risk orchestrating your own headlines.

The week began with two very different conversations that echoed the same theme. One was with a major U.S. healthcare organization grappling with how to stay ahead of regulatory change. The other was with a European financial services firm confronting the tsunami of new regulations washing over their business. Both organizations wanted to understand how regulatory change management integrates with policy management and the broader GRC architecture.

Those discussions flowed directly into my Policy Management by Design Workshop in New York City yesterday (hosted by COMPLY), where 42 participants from financial services joined me for a half-day of interactive discussion. The workshop confirmed what those initial calls signaled: policies are the nervous system of governance, risk management, and compliance, but too often they are fragmented, outdated, and ill-equipped to keep up with regulatory and business change.

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What Keeps Risk and Compliance Leaders Awake at Night

Financial services attendees were candid about the challenges they face in policy governance amid regulatory volatility. Among the most pressing concerns raised:

• Mapping policies directly to regulations and keeping them synchronized.
• Sheer volume and velocity of regulatory change.
• Ensuring stakeholders and employees actually see and understand policies.
• Conflicting or duplicative policies across different regions and business units.
• The frequency of updates required to keep policies relevant.
• Documentation that satisfies both board oversight and regulatory examiners.
• Multinational conflicts in language, jurisdiction, and enforcement.
• Enforcement across the extended enterprise — including third parties.
• Horizon scanning to anticipate change and prepare policies in advance.
• Policy fatigue, apathy, and the danger of checkbox attestations.
• Inconsistent governance and scattered ownership across silos.
• Quality control, clarity, and conciseness in policy drafting.
• Training, awareness, and testing of policy effectiveness.
• The operational implications and implementation of policies — moving from words on paper to behaviors in practice.
• Version control, access management, and audit trails to demonstrate accountability.
• The looming question of how AI will reshape policy management itself — from drafting to monitoring compliance.

These are not isolated pain points; they are systemic fractures that demand a federated, structured, and technology-enabled approach.

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The Blueprint for Policy Management by Design

At the workshop, I shared my Blueprint for an Effective, Efficient, and Agile Policy Management Program. The premise is simple but urgent: policy mismanagement is no longer a back-office nuisance — it is a GRC failure waiting to happen.

The blueprint calls for a structured, strategic, and scalable approach to policy governance:

• Define a complete lifecycle for policy creation, approval, communication, training, monitoring, and retirement.
• Establish governance, ownership, and accountability for policies, supported by a Policy Committee and a “meta-policy” (the policy on policies).
• Standardize policy format, language, and metadata to eliminate confusion and inconsistency.
• Communicate and embed policies across business units and third parties, supported by targeted training and attestations.
• Link policies to objectives, risks, controls, obligations, and incidents within the broader GRC information architecture.
• Measure effectiveness and compliance with clear KPIs/KRIs and test policies in practice.
• Leverage technology for automation, distribution, and traceability, including integration with regulatory change management and horizon scanning tools.

The objective is not more policies. It is better policies: concise, relevant, realistic, and enforceable. Policies should guide decisions, reduce liability, and build trust — not gather dust on a shelf or clutter intranet pages.

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RegTech: The Engine of Policy Agility

This is where RegTech enters the stage. Organizations cannot manually keep pace with the scale and speed of today’s regulatory change. Automated regulatory change management and horizon scanning feed into structured policy management so that:

• New regulations are quickly mapped to affected policies.
• Impact analyses identify gaps and conflicts.
• Updates and attestations are triggered across the enterprise.
• Boards and regulators see a clear, defensible audit trail.
• Multinational organizations can harmonize global frameworks while respecting local nuances.

The convergence of RegTech with policy management is not optional. It is the only way organizations can remain agile in the face of regulatory velocity, while embedding integrity into their culture and operations.

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From New York Workshops to the Global RegTech Summit

This week’s conversations and workshop set the stage for my role today at the Global RegTech Summit USA 2025 in New York, where I am moderating two panels.

• In Stream B, we will explore RegTech and the Regulators: Striking the Balance Between Innovation and Risk, featuring voices from compliance leadership, investment management, and technology providers.
• In Stream A, I’ll moderate Reg Change in the Financial Sector: Navigating the Evolving Regulatory Landscape, where we will dive into shifting compliance strategies, risk management frameworks, and how RegTech and AI are shaping the future.

The message I will carry into both discussions is the same: policy management is where regulatory change becomes real. Without effective policies — clear, current, and enforced — all the investment in regulatory intelligence and RegTech falls short.

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Closing Reflections

Policy management is at the crossroads of governance and RegTech. It is where regulatory complexity meets organizational behavior. The organizations that succeed will be those that design policy governance as a strategic capability: federated across silos, automated with technology, and aligned to values and objectives.

In this era of constant change, policies are no longer static documents. They are living instruments of governance. And when managed by design, they empower organizations to achieve objectives, navigate uncertainty, and act with integrity.

Policies are more than documents on a shelf. They are the DNA of organizational integrity, the framework that defines culture, directs behavior, and provides accountability in times of scrutiny. When done well, policies guide decisions, reduce liability, and build trust across the enterprise. When they are fragmented, inconsistent, or outdated, they create exposure rather than protection. 

Unfortunately, many organizations still operate in that fragmented state. Policies live across file shares, emails, intranet sites, and even printed binders. Multiple versions circulate at the same time, and employees are never quite sure which is the right one. New policies are sometimes authored without legal review, creating unintended liabilities. Attestations are tracked poorly, if at all, leaving leadership uncertain whether employees even know what standards apply. In this environment, policy management is not a back-office nuisance — it is a governance, risk, and compliance failure waiting to happen. 

This confusion undermines culture as well as compliance. Every policy is, at its heart, a risk document. It exists because a risk was identified and needed to be addressed. Policies . . .

[The rest of this blog can be read on the Comply blog, where GRC 20/20’s Michael Rasmussen is a Guest Blogger]

Inevitability of Failure: the Digital EcoSystem of Business

Every organization today is defined by the digital fabric and architecture in which its operations relies upon. This fabric is sprawling, complex, and interdependent. The systems, processes, and relationships that sustain modern business are increasingly digital, and increasingly fragile. Reminds me of the U.S. National Security Agency (NSA) paper from the 1990’s The Inevitability of Failure: The Flawed Assumption of Security in Modern Computing Environments, which was foundational in my early career. The reality is that this is no longer just about the IT department, the data center, or even the historic CISO role. The digital architecture of the enterprise is now the architecture of the business itself.

We have seen in stark terms how this fabric can unravel . . .

• CrowdStrike. In 2024, a CrowdStrike update spiraled into global disruption. This was not a hacker, virus, or worm — it was a trusted vendor’s software failure, rippling across industries and bringing down organizations worldwide.
• U.K. Retail Attacks. Earlier this year, the United Kingdom retail giants Marks and Spencer, Harrods, and the Co-Op faced devastating cyberattacks and ransomware that crippled operations and shook customer trust.
• Ascension Ransomeware. In healthcare, Ascension Hospital’s ransomware crisis last year was a chilling reminder that digital failure does not just stop business; it can endanger lives.
• Southwest Airlines Digital Meltdown. Southwest Airlines’ holiday meltdown was driven by outdated crew scheduling and IT systems that failed to track and reassign staff during winter storms, turning a weather disruption into a full-scale operational collapse.

Each of these events underscores a reality we can no longer ignore: digital risk is systemic, enterprise-wide, and existential.

What makes digital risk so challenging is not just the sophistication of threats but the convergence of multiple risk factors. Human error continues to cause outages and breaches through simple missteps. Malicious behavior — whether from insiders or external adversaries — adapts constantly. The relentless pace of change across infrastructure, applications, and cloud transformation adds new exposures by the day. And perhaps most precariously, organizations now operate in vast digital supply chains where one weak link can send shockwaves across thousands of entities. In practice, disruption often emerges from a combination of these elements, such as:

• A misconfiguration in a cloud environment paired with a rushed change window.
• A ransomware attack on a supplier that cascades into dependent operations.
• An insider error or action that intersects with a system update or third-party service.

This intricate web means digital risk management cannot be siloed into compliance checklists or narrowly scoped security controls. It must be orchestrated, decision-driven, and tied directly to business objectives.

Rearchitecting to Digital Risk & Resilience for Digital Trust

Too many organizations still treat digital risk as a matter of regulatory compliance or a set of prescribed controls. But compliance alone is not resilience, and certainly is not risk management. Controls alone cannot deliver digital trust. True resilience begins with clarity of objectives — understanding what the business is trying to achieve and how digital capabilities support those goals.

From there, organizations must build foresight into their approach: anticipating disruption, simulating scenarios, and preparing adaptive responses. And it requires integration — weaving governance, risk management, and compliance into the very design of digital business operations rather than layering them on afterward. This is digital risk and resilience management to deliver digital trust.

The digital supply chain highlights why this is so urgent. Organizations depend on ecosystems of cloud providers, SaaS vendors, outsourcers, and digital partners. These relationships provide value but also amplify fragility. A single failed software update, as with CrowdStrike, can cause cascading outages. A ransomware-hit partner can expose data far beyond their own network. Even a brief supplier outage can paralyze entire business units. Managing this requires more than vendor scorecards or compliance attestations. It requires the ability to map dependencies, monitor signals, simulate breakdowns, and design resilience into interconnected digital ecosystems.

GRC 7.0 – GRC Orchestration of Digital Trust

This is where the future of GRC comes into play. GRC 7.0 — GRC Orchestrate provides the architecture to meet this challenge (as long as strategy and process are in place). It is not about defense alone but about foresight and trust. This does not eliminate risk to objectives but enables resilience so they can be achieved:

• Agentic AI. With agentic AI, organizations can sense risk in real time, analyze context, and support decision-making at scale.
• Digital Twins. With digital twins, they can model supply chains, business processes, and systems, simulate disruptions, and evaluate recovery strategies before crises strike.
• Orchestration. With orchestration, resilience becomes embedded into governance, objectives, performance, and compliance, ensuring trust is designed into digital operations rather than left to chance.

The organizations that will thrive are those that embed resilience into their DNA. This is not a technical initiative but a business imperative. Digital trust is earned not through slogans but through deliberate strategy, careful design, and continuous execution.

On October 1st in London, I will be leading the Digital Risk & Resilience Management by Design workshop — a full-day session delivering a blueprint for building agile, integrated, and context-aware digital resilience programs. We will explore how to align digital risk with enterprise objectives, shift from reactive continuity to proactive resilience, and use emerging technologies like agentic AI and digital twins to orchestrate trust across complex ecosystems.

Digital risk is the business risk of our time. The question is no longer whether disruption will occur, but how ready your organization will be to anticipate, absorb, and adapt. The future belongs to those who design resilience into their digital architecture — and orchestrate digital trust.

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There comes a point in every organization’s journey when it must choose whether it is going to lead or follow — whether it will proactively shape its future or continually react to disruption.

For organizations with ambition — those seeking to scale responsibly, innovate with confidence, and uphold their commitments to stakeholders — that moment is now. Governance, Risk Management, and Compliance (GRC) has become the fulcrum on which that decision rests. 

The GRC conversation is no longer about avoiding penalties or surviving audits. It is about enabling the organization to reliably achieve objectives (governance), address uncertainty (risk management), and act with integrity (compliance). This is not a compliance slogan; it is the operational imperative of our time. And for aspirational organizations, it is a now-or-never decision. The complexity, speed, and interconnectedness of today’s risk and regulatory environment will not wait; and those who hesitate risk losing both control and credibility. 

Risk Is Moving Faster Than You Can Track with Spreadsheets 

The pace of risk has changed. Yesterday’s risk landscape was linear and episodic; today’s is complex, systemic, and real-time. The very nature of risk has evolved from being internal and controllable to external, interconnected, and constantly shifting. And nowhere is this more evident than in . . .

[The rest of this blog can be read on the GRCxperts blog, where GRC 20/20’s Michael Rasmussen is a Guest Blogger]

Command and Control on the Bridge of the Enterprise with GRC 7.0 – GRC Orchestrate

“Captain, sensors are detecting increased fluctuations in the warp field. I recommend we adjust our alignment.” — Commander Spock

In the expansive landscape of modern business, the ability to manage risk and performance across an extended enterprise of third parties and suppliers is not simply important, it is mission-critical. Just as the bridge of the USS Enterprise coordinates navigation, operations, security, and engineering to sustain its mission, organizations today require a unified command center to orchestrate third-party governance, risk management, and compliance (GRC) that adds in performance (GPRC).

In this first article of our series exploring G[P]RC, we examine how organizations must move beyond fragmented checklists, static workflows, and reactive monitoring. Instead, the new paradigm — powered by GRC 7.0 – GRC Orchestrate — emphasizes enterprise architecture, business process modeling, digital twins, agentic AI, analytics, and intelligent systems that align governance and performance with proactive risk management and compliance.

Because the extended enterprise is no longer simply managed—it must be orchestrated.

The Legacy Problem: Navigating Without Sensors

Traditional third-party and supply chain risk management often looks like a . . .

[The rest of this blog can be read on the Corporater blog, where GRC 20/20’s Michael Rasmussen is a Guest Blogger]

Featuring my collected insights combined with thoughts from the most recent Risk Is Our Business Podcast with Ayoub Fandi, Security Assurance Automation Team Lead at GitLab and founder of the GRC Engineer Podcast & Newsletter

In the most recent transmission of the Risk Is Our Business Podcast, I beam aboard Ayoub Fandi — Security Assurance Automation Team Lead at GitLab and the founder of the GRC Engineer Podcast and newsletter — to explore what is a next frontier for governance, risk management, and compliance: GRC engineering and how it related to GRC 7.0 – GRC Orchestrate. Our conversation ranged from first principles to hard-won lessons in automation and architecture, and from the current cyber-heavy use of the term to a broader, enterprise-wide discipline that touches objectives, risk, integrity, and assurance across the business.

Ayoub’s professional arc mirrors the transformation underway in the field. He moved from Big Four consulting in France to roles in high-growth technology environments at Salesforce and GitLab, where the cadence of change is measured not in quarters but in deployments per hour. That pace renders traditional GRC practices — annual control checks, screenshots, manual evidence packs, after-the-fact testing — increasingly unfit for purpose. As Ayoub put it, the gap between how fast the business operates and how slowly GRC verifies has become untenable. The solution, he argues, is not more checklists; it’s a structural shift: treat risk, compliance, and assurance as engineered capabilities built directly into systems, processes, and workflows.

Ayoub Fandi: “Some companies push a hundred thousand deployments a year. You can’t meet that speed with yearly tests and screenshots. GRC has to move earlier into design and become machine-readable in how we test, monitor, and gather evidence.”

What follows is a detailed exploration — narrative and pragmatic — of what GRC engineering is, why it matters, and how to make it real.

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First Principles: Defining GRC Engineering against OCEG’s Core

We ground this in the OCEG definition of GRC as a capability to reliably achieve objectives (governance), address uncertainty (risk), and act with integrity (compliance). Against that backdrop, GRC engineering is not a new “flavor” of risk, compliance, or control; it is the technical discipline that embeds those principles into the fabric of the organization.

Here’s the definition we refined together:

Michael Rasmussen (validated by Ayoub): “GRC engineering is the discipline of embedding governance, risk management, and compliance into the technical fabric of the organization through systems architecture, automation, and data engineering — so that GRC is not just a policy function, but an operationalized, engineered capability.”
Ayoub’s verdict: “9.999 out of 10 — the data engineering part is critical. Get the data wrong and everything else collapses.”

That last sentence is a constant refrain in our discussion. The most sophisticated automation fails without coherent data models, clean pipelines, and consistent semantics. In other words, data engineering is table stakes.

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The Manifesto Mindset: Shift-Left, Treat GRC as a Product, and Be Practitioner-Led

Ayoub has articulated a simple, powerful set of principles in what he calls the GRC Engineer Manifesto. Three ideas stand out:

• Shift Left: Move risk management and compliance considerations into the design phase so that GRC influences how systems are built, not just how they’re verified.Ayoub: “We want GRC present when the product manager makes trade-offs, not arriving at the end asking for screenshots.”
• Treat GRC as a Product: Manage GRC iteratively, with a roadmap, telemetry, and a user experience orientation toward control owners and contributors. Reduce toil by sourcing data from native systems rather than forcing duplicate entry into GRC tools.
• Practitioner-Led: Ensure those who live the problems shape the solutions. Partner with vendors, yes, but be clear-eyed about what good looks like, and build lightweight internal capabilities where necessary to bridge gaps.

Together, these principles convert GRC from a project (checklist, deadline, binder) into a product (ongoing capability, measured outcomes, engineered UX).

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Architect vs. Engineer: Two Sides of the Capability

We also distinguished GRC architects from GRC engineers. The engineer writes the scripts, wires the webhooks, builds the workflows, and automates the evidence gathering. The architect designs the overarching decision and data architecture: how risk, control, obligation, and assurance flows traverse systems; where the source of truth sits; how to align GRC telemetry with business objectives and reporting.

Ayoub: “Software engineering skills may increasingly be commoditized with AI, but architecture endures— orchestrating systems, data, and stakeholders so the whole actually works.”

I shared an example of a Nordic telecom whose first GRC implementation faltered; their second succeeded only after they restarted with data models and enterprise architecture first. Ayoub agreed: many failures stem from starting with vendor feature lists instead of a clear picture of inputs, outputs, and flows (e.g., how a third-party risk assessment creates obligations, exceptions, and control tests downstream).

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Beyond Cyber: Expanding the Scope to Enterprise GRC

Today, most visible “GRC engineering” examples sit inside digital and cyber programs — policy-as-code, cloud configuration monitoring, continuous compliance for SOC 2 / ISO 27001 / PCI / FedRAMP. That’s understandable; the technical acumen and tooling maturity in security are ahead of many business functions. But both of us argue that the same engineering principles must extend beyond IT to the full enterprise:

• Performance & Objectives: connecting KPIs/KRIs/KCIs to objectives so that performance is always viewed with its uncertainty and control posture.
• Enterprise & Operational Risk: scenario modeling, risk quantification, and control telemetry tied to processes, people, and assets.
• Compliance & Ethics: obligation parsing and mapping, policy lifecycle automation, training triggers, and case management that integrates HR, Legal, and Compliance.
• Internal Control & Audit: continuous controls testing, automated evidence pipelines, exception governance, and analytics-driven assurance.

Ayoub: “We started in tech because that’s where the engineers were, but the benefits are even greater as you move into functions with legacy process debt. The evangelism and some pre-built patterns just need to catch up.”

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What GRC Engineering Looks Like in Practice (Across GRC 7.0 – GRC Orchestrate)

To make this concrete, here is a cross-section of engineered capabilities aligned to the GRC 7.0 – Orchestrate domains. Note how they move from workflow lists to data-centric, automation-ready architectures.

Strategy & Decision Management

• Problem: Strategy reviews lack risk-adjusted intelligence.
• Build: A decision architecture that links objectives to risk and control telemetry; simulation models surface trade-offs (“If we accelerate Region X, supply risk and ESG non-compliance increase by Y”).
• Result: Decisions show the path to target and the cost of uncertainty.

Performance & Objective Management

• Problem: KPIs are blind to risk and control efficacy.
• Build: Data models that bind KPIs ↔ KRIs ↔ KCIs with lineage back to source systems (ERP, CRM, HRIS, cloud).
• Result: Performance dashboards that surface early warning signals and control degradation.

Enterprise & Operational Risk & Resilience

• Problem: Paper scenarios and tabletop exercises don’t translate into action.
• Build: Digital twins of critical processes and assets; stress-test scenarios (workforce, vendor, facility, cyber, regulatory).
• Result: Playbooks driven by telemetry, not static documents; alignment to DORA, CPS 230, UK Operational Resilience.

Digital Risk & Resilience

• Problem: Cyber posture is siloed from business risk.
• Build: Continuous configuration and vulnerability telemetry mapped to business services and obligations (NIST CSF, PCI, GDPR).
• Result: Cyber metrics contextualized by business impact and regulatory exposure.

Compliance, Ethics & Obligation Management

• Problem: Obligations live in PDFs and spreadsheets.
• Build: Obligation parsing (human + AI), normalized into a graph that links to processes, policies, controls, owners, and evidence sources.
• Result: Machine-actionable compliance with automated attestations and evidence collection.

Third-Party GRC

• Problem: Onboarding is front-loaded; monitoring and offboarding are weak.
• Build: End-to-end orchestration — intake → segmentation → KYC/AML/sanctions → ESG → contract → performance/risk telemetry → offboarding controls.
• Result: Governance of the entire third-party lifecycle, not just initial risk scoring.

Policy & Training

• Problem: Policies aren’t adopted or understood at the point of work.
• Build: Version-controlled policies linked to obligations and roles; contextual policy guidance APIs and Q&A assistants embedded where employees work.
• Result: Reduced policy-toil and higher adherence.

Internal Control Management

• Problem: Point-in-time testing misses drift.
• Build: Continuous control monitoring (CCM) via APIs, event streams, and rules engines; exception management with risk-based SLAs.
• Result: Early detection, lower audit fatigue, clearer lines of accountability.

Issue & Case Management

• Problem: Fragmented hotlines and incident trackers.
• Build: A unified case platform with routing, confidentiality tiers, evidence management, and disclosure workflows.
• Result: Integrity becomes operationalized and reportable.

Audit & Assurance

• Problem: Audits recreate the past instead of validating the present.
• Build: Evidence pipelines and data lineage, enabling continuous auditing; risk-based sampling and automated test scripts.
• Result: Assurance at the speed of change.

ESG & Sustainability

• Problem: CSRD/ESG data is manually wrangled and error-prone.
• Build: Instrumentation and vendor data feeds (energy, scope data, workforce) normalized to reporting taxonomies with provable lineage.
• Result: Timely, defensible disclosures tied to objectives and risk.

Integrated Reporting & Analytics

• Problem: Reports are static and backward-looking.
• Build: A GRC command center that unifies objectives, risks, controls, obligations, third-party and ESG metrics; layered with digital twins and agentic AI to surface weak signals and recommend actions.
• Result: A living system of governance, not a stack of PDFs.

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Agentic AI: Promise, Pragmatism, and the Data Imperative

Both of us see agentic AI as a transformative accelerant — but only when the data substrate is ready.

Ayoub: “A lot of ‘agentic’ workflows today are still step-by-step automations. Without coherent, consistent data, the agent will just go faster in the wrong direction. Fix the data, and even a modest tool delivers outsized value.”

The horizon he sketches is compelling: AI that becomes technology-agnostic, generating custom integrations and workflows to meet business objectives regardless of the underlying cloud or tool stack. In that world, engineering gives way to architecture as the enduring discipline — because the agent writes scripts, but humans still design the goals, constraints, and governance.

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Pathways into GRC Engineering (From Both Sides of the Aisle)

One of the most practical sections of our conversation was Ayoub’s guidance on how to enter and grow in the discipline:

• If you’re a GRC practitioner:
  • Learn the basics of Python or similar.
  • Pick a single, painful, repetitive task — e.g., quarterly evidence collection from a handful of systems — and automate it end-to-end (even with AI-assisted coding).
  • Measure toil reduction and error rate improvements; socialize the win and repeat.
• If you’re a software engineer:
  • Study GRC objectives and frameworks (OCEG, ISO 31000, internal control principles, sector regulations).
  • Shadow a control owner or an auditor for a sprint.
  • Apply your skills to build reliable evidence pipelines, clean data models, and simple but robust automations that survive audits.

For ongoing learning, Ayoub points to the GRC Engineer Manifesto and his newsletter and podcast — where he features practitioners from Netflix, Zoom, IKEA, and beyond. The pattern across episodes is the same: start where the data already lives, automate one real bottleneck, and focus on fit-for-purpose outcomes rather than flashy demos.

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From Workflow to Architecture: The Operating Model Changes

A recurring theme in our exchange is that GRC engineering is not merely “doing workflows in a tool.” It is adopting an architectural operating model:

• From forms to pipelines: Inputs flow from source systems; validations and transformations are explicit.
• From controls to telemetry: Tests run continuously; drift is detected early.
• From evidence packs to lineage: Data is traceable from report back to system of record.
• From one-off projects to product roadmaps: Backlogs, usage metrics, SLAs, and success criteria exist.
• From isolated teams to orchestration: Risk, compliance, audit, security, and the business share a common data model and glossary.

This is precisely where GRC architects and engineers collaborate: decide what must be true in the data and the flows, then implement it with the right blend of vendor capabilities and custom glue.

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Why Now: Regulation, Complexity, and Tooling Maturity

The timing is not accidental. Three forces converge:

• Regulatory pressure (e.g., UK Corporate Governance Code Provision 29, EU DORA, CSRD, NIS2) demands not just policies but evidence of effectiveness and ongoing assurance.
• Business complexity — global supply chains, hybrid work, digitized operations — creates a volume and velocity of change that manual GRC cannot handle.
• Technology maturity — APIs everywhere, event streams, cloud data platforms, rules engines, LLMs, and early digital twin practices — makes engineering the practical path to sustainable GRC.

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Making It Real: A Practical Starter Blueprint

If you’re ready to move from concept to capability, here’s a pragmatic starter plan that works in organizations large and small:

1. Choose one value stream (e.g., third-party onboarding, change management, or financial close).
2. Map the GRC flows: objectives → risks → obligations/policies → controls → telemetry/evidence → exceptions → attestations → reporting.
3. Define the minimum data model (entities, relationships, owners, sources of truth, lineage requirements).
4. Automate one control test end-to-end (trigger → gather → evaluate → log → notify → escalate).
5. Stand up a tiny “command center” view for that stream — objectives, risk indicators, control status, exceptions — in a single page.
6. Measure toil removed and assurance gained; capture lessons; expand by one adjacent control or obligation each sprint.
7. Institutionalize the operating model: backlog, product ownership, SLAs, data standards, change management, and documentation that auditors can love.

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The Road Ahead: GRC 7.0 – Orchestrate

We closed by situating GRC engineering inside the broader evolution I call GRC 7.0 – GRC Orchestrate. This next era blends agentic AI with digital twins and business-integrated architectures so organizations can reliably achieve objectives, address uncertainty, and act with integrity — continuously, and at scale. GRC engineering is how we get there: by making assurance native to the way the enterprise plans, builds, buys, changes, and learns.

Ayoub: “Fix the data, build the flows, and the rest follows. Start small, automate what hurts, and keep the human judgment where it matters.”

Risk isn’t the enemy; it’s the mission. GRC engineering gives us the instrumentation, the telemetry, and the control surfaces to navigate that mission with speed and integrity — not just in cyber, but across the entire enterprise. If you want to dive deeper into practitioner stories and the manifesto, check out Ayoub’s GRC Engineer newsletter and podcast — and expect to hear more from both of us as this discipline matures from pockets of automation into a coherent, engineered operating model for GRC.

In today’s interconnected and fast-moving environment, organizations face an array of disruptions that threaten their ability to deliver critical products and services. Cyberattacks, technology failures, supply chain breakdowns, and geopolitical upheavals are no longer rare events; they are persistent realities. The expectation from regulators, investors, and customers alike is clear: organizations must not only withstand disruption but also demonstrate their capacity to recover and adapt.

Operational resilience has therefore moved from a back-office consideration to a board-level responsibility. It is no longer optional or supplemental; it is central to business strategy, trust, and survival. The question organizations must answer is not if disruption will occur, but when — and whether the business is prepared to adapt with agility and confidence.

This is where GRC — governance, risk management, and compliance — provides the foundation. With the advancements of GRC 7.0 – GRC Orchestrate, organizations can align governance with resilience objectives, integrate risk and resilience processes across silos, and embed compliance within the very fabric of operations.

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The Expanding Regulatory Galaxy

Around the globe, regulatory bodies are converging on the same message: resilience is mandatory. While the details differ, the core expectations align across jurisdictions.

For example:

• United Kingdom – The FCA, PRA, and Bank of England require firms to identify important business services, set impact tolerances, and test severe but plausible scenarios.
• European Union DORA – The Digital Operational Resilience Act mandates ICT risk management, resilience testing, incident reporting, and third-party oversight across the financial sector.
• Australia CPS 230 – Embeds operational risk and resilience into governance, controls, and third-party arrangements.
• EU NIS2 & CER – Extend resilience obligations beyond finance to digital infrastructure and critical entities.
• United States Fed/OCC/FDIC – Joint guidance highlights governance, incident response, and interconnections across critical operations.
• Singapore MAS, Hong Kong HKMA OR-2, and Canada OSFI B-13 – All emphasize resilience testing, governance, communication, and assurance in critical operations.

Though diverse in scope, these frameworks orbit a shared center: resilience is an enterprise-wide obligation, spanning governance, risk management, testing, third-party oversight, and accountability.

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From Fragmentation to Orchestration

Despite these clear demands, many organizations still manage resilience in silos. Technology teams may focus on digital continuity, risk managers on business continuity, compliance teams on regulations, and procurement on third-party oversight. Each unit acts with the best intentions, yet without integration the result is duplication, inefficiency, and blind spots.

Such fragmentation undermines resilience. Disruptions rarely respect organizational boundaries. A cyberattack can ripple through suppliers, customer service, and compliance reporting simultaneously. Without orchestration, organizations remain vulnerable to risks that span multiple domains.

The future requires a unified approach. GRC 7.0 – GRC Orchestrate provides the architecture to integrate governance, risk management, and compliance into a single operational command center. This is not just about efficiency; it is about ensuring that resilience is measurable, actionable, and embedded across the enterprise.

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Digital Twins: A Living Map of Resilience

Among the most powerful tools enabling this orchestration is the digital twin. Unlike traditional static repositories such as a CMDB, a digital twin is a living, dynamic model that reflects the interconnected nature of an organization’s assets, people, processes, and third parties.

By unifying data from across the enterprise — IT systems, operational dependencies, vendor relationships, and external intelligence — a digital twin becomes a resilience encyclopedia, translating complexity into actionable insight.

With digital twins, organizations can:

• Map dependencies across critical services and suppliers.
• Simulate disruptions such as outages, cyber incidents, or supplier failures.
• Test impact tolerances against regulatory expectations (e.g., DORA or CPS 230).
• Visualize cascading effects, showing how a single point of failure impacts the wider organization.
• Provide intuitive reporting that bridges technical detail with executive decision-making.

This continuous, scenario-driven view allows organizations to anticipate problems, adjust strategies, and strengthen resilience long before disruption occurs.

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Agentic AI: Augmenting Human Oversight

While digital twins provide the model, agentic AI enhances the ability to act upon it. By continuously scanning intelligence feeds, identifying anomalies, and recommending mitigation strategies, AI acts as a constant monitor for resilience.

Key roles of agentic AI include:

• Scanning for new threats or emerging risks.
• Suggesting remediation actions or escalation paths when tolerances are breached.
• Coordinating workflows across risk, compliance, and operational teams.
• Learning from past disruptions to refine resilience strategies.

AI is not a replacement for human decision-making but a force multiplier, ensuring resilience oversight is proactive, adaptive, and data-driven.

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Embedding Resilience in the DNA of the Enterprise

True resilience cannot be bolted on after the fact. It must be woven into the enterprise architecture — embedded in business processes, risk frameworks, and compliance obligations. GRC 7.0 makes this possible by:

• Aligning regulatory obligations with internal controls and operations.
• Linking risks, policies, and continuity plans directly to business services.
• Integrating systems, data, and third-party relationships into a unified resilience fabric.

The result is an organization where resilience is not a separate program but part of everyday decision-making — built into the very DNA of how the business operates.

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A Call to Action: Resilience as the Prime Directive

Resilience is not simply about survival. It is about enabling the organization to fulfill its mission, no matter what disruptions arise. The regulatory landscape is intensifying, but the core expectation remains the same: organizations must demonstrate operational resilience.

By embracing GRC 7.0 – GRC Orchestrate, with digital twins as the living map and agentic AI as a supporting watch officer, organizations can build an integrated, forward-looking approach to resilience.

The call to action is clear: resilience cannot remain fragmented or reactive. It must be orchestrated, embedded, and continuously assured. Only then can organizations confidently navigate uncertainty and move forward with agility and integrity.

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In the ever-expanding GRC Technology Galaxy, organizations are not cruising through empty space. They are dodging regulatory meteors, navigating gravitational pulls of risk, and occasionally sucked into black holes of failed audits and compliance findings. Governance, Risk Management, and Compliance isn’t a single planet you can set your phasers to — it’s a galaxy you must navigate.

Now, as with any proper galactic journey, it’s worth remembering that some will tell you the answer to GRC is simply “42.” They’re wrong (though Douglas Adams would approve). The real answer is architecture: not just software architecture, but capability architecture. GRC 7.0 – GRC Orchestrate is about transforming the silos of the past into an intelligent, integrated command center — one that spans strategy, objectives, risk, compliance, and assurance.

And to chart your course through this galaxy, you need two sets of coordinates:

1. The Enterprise GRC constellation — the twelve domains that form the high-level star chart.
2. The Specialized GRC domains — the deep-space explorers, each patrolling a critical sector with precision.

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The Enterprise GRC Constellation: 12 Stars in Orbit

Just a recap on Enterprise GRC which is the bridge of the starship, guiding direction and coordinating purpose as detailed in Don’t Panic: A Hitchhiker’s Guide to the GRC Technology Galaxy. Its 12 domains provide the navigation chart:

• Strategy & Decision Management
• Performance & Objective Management
• Enterprise & Operational Risk & Resilience Management
• Digital Risk & Resilience Management
• Compliance, Ethics & Obligation Management
• Third-Party GRC Management
• Policy & Training Management
• Internal Control Management, Monitoring & Automation
• Issue Reporting & Event/Case Management
• ESG & Sustainability Management
• Audit Management, Analytics & Assurance
• AI GRC (AI Governance, Risk Management & Compliance)

Together, these domains form the gravitational framework of integrity and resilience. But no starship survives on navigational charts alone. Specialized missions require specialized vessels. Enter the 10 Specialized GRC domains.

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10 Specialized GRC Domains in the Galaxy of GRC

Now, if Enterprise GRC gives us the star chart, Specialized GRC is where individual departments and functions strap themselves into their own ships and plot courses through their unique risk nebulae. Each of these ten domains takes the OCEG definition of GRC — the capability to reliably achieve objectives (governance), address uncertainty (risk management), and act with integrity (compliance) — and adapts it to the day-to-day reality of their mission. Finance must navigate the asteroid fields of reporting and controls, Legal keeps the enterprise from being sucked into the black holes of litigation, and Quality ensures the engines hum without defect.

Together, these specialized domains turn abstract principles into operational practice — giving every function its own compass, thrusters, and shields in the wider constellation of GRC Orchestrate. These 10 Specialized GRC Domains (with links for more detail) are:

• Data GRC. The lifeblood of the enterprise, data fuels innovation and strategy — but also creates privacy, compliance, and ethical hazards. Data GRC governs classification, lineage, mapping, retention, and regulatory alignment, while digital twins simulate entire data ecosystems. Agentic AI continuously monitors for misuse or drift.
• Financial Crime GRC. Fraud, money laundering, sanctions evasion, bribery — the rogues’ gallery of financial crime is vast. Financial Crime GRC unifies AML, ABAC, KYC/KYB, sanctions screening, fraud detection, and suspicious activity reporting into orchestrated defense. AI agents prioritize alerts and generate contextual reports, while digital twins simulate regulatory change scenarios.
• Finance GRC. Beyond quarterly reporting, Finance GRC embeds oversight into daily operations — from SOX/ICFR to treasury risk and capital management. It connects financial governance, fraud detection, and disclosure integrity. AI highlights anomalies before they hit the balance sheet; digital twins simulate risks in close and consolidation cycles.
• Environmental GRC. Air, water, carbon, chemicals, biodiversity — Environmental GRC orchestrates compliance and stewardship across them all. It manages permits, PFAS tracking, waste, and GHG reporting, while AI monitors IoT sensors and digital twins forecast emission impacts of operational changes.
• Health & Safety GRC. People are the first line of resilience. Health & Safety GRC ensures worker protection through incident management, inspections, PPE oversight, emergency drills, and compliance with OSHA/ISO 45001. AI mines safety data for leading indicators; digital twins simulate crisis scenarios to strengthen preparedness.
• Human Resources GRC. The workforce is not just talent — it’s risk, performance, and culture. HR GRC spans policy delivery, disclosures, case management, DEI metrics, misconduct oversight, and workforce risk analytics. AI identifies attrition risks and cultural red flags, while digital twins model workforce restructuring scenarios.
• Identity GRC. Who has access to what — and why — is one of the most fundamental questions of governance. Identity GRC ensures access lifecycle management, SoD monitoring, privileged access oversight, and continuous risk evaluation. Agentic AI evaluates access requests in real time; digital twins simulate SoD risks before rollout.
• Legal GRC. The legal department is more than dispute defense — it’s a proactive line of assurance. Legal GRC spans matter management, eDiscovery, retention, contract governance, and spend control. AI reviews contracts for risk exposure, while digital twins simulate litigation scenarios across jurisdictions.
• Privacy GRC. Privacy is trust in action. Privacy GRC operationalizes PIAs/DPIAs, DSAR automation, consent management, breach response, and cross-border transfer tracking. AI monitors unauthorized data use and regulatory updates, while digital twins simulate breach impact and compliance changes.
• Quality GRC. Quality is not just checked at the end — it’s designed, governed, and continuously improved. Quality GRC embeds ISO 9000, FDA, GMP, and industry frameworks into CAPA, supplier quality, complaint handling, and product safety oversight. AI detects early signals of quality drift; digital twins simulate supply chain disruptions or production line adjustments.

So there you have it — the ten specialized domains orbiting alongside the twelve enterprise domains, each with its own gravitational pull on governance, risk, and compliance. Together they form the constellations of GRC Orchestrate, guiding organizations through the galaxy of uncertainty with agility and integrity.

Final Transmission: Hitchhiking Forward

Specialized GRC domains are the starships of assurance, each with its own mission — data, finance, safety, people, privacy, and more. They don’t replace Enterprise GRC, but extend it, embedding governance, risk, and compliance into the very structure of specialized business functions.

Together, Enterprise and Specialized GRC form a fleet — interconnected, orchestrated, and empowered by AI and digital twins. This is how GRC 7.0 moves from reactive compliance to an intelligent command center for trust and resilience.

So, grab your towel. Insert your digital Babel Fish. And prepare for the next leg of the journey. Because this week, I’m launching the Hitchhiker’s Guide to the GRC Technology Galaxy podcast — where we’ll boldly seek the ultimate answer to the ultimate question of GRC technology.

Stay tuned. And remember: in the GRC Galaxy, architecture is everything — and trust is your universal translator.

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The OCEG GRC Illustrations are visual, educational resources designed to clearly communicate complex governance, risk management, and compliance concepts in an accessible and engaging way.

Within this library, the GRC Technology Illustrated Series focuses specifically on technology-enabled capabilities that support integrated GRC practices across the enterprise that are mapped to GRC 20/20’s framework of GRC technology categories. Each illustration distills best practices, critical capabilities, and lifecycle processes into a single, intuitive visual.

We are excited to announce the release of the latest illustration in this series — Third-Party GRC Management Solutions Illustrated — which examines how organizations can govern, manage risk, and ensure compliance across their extended enterprise relationships. This blog explores the concepts behind the illustration and why Third-Party GRC is essential in today’s hyperconnected world.

In the modern economy, no organization truly operates alone. Business today is conducted within an extended enterprise, a vast, interconnected web of suppliers, vendors, contractors, service providers, partners, distributors, agents, and other third parties that deliver products, services, data, and capabilities essential to operations.

This extended enterprise fuels innovation, enables speed to market, and drives competitive advantage. But it also multiplies risk. A failure, breach, or compliance lapse by one entity in this network can reverberate across the ecosystem, disrupting operations, damaging brand reputation, and triggering regulatory scrutiny.

Many in the market label this discipline as third-party risk management (TPRM), vendor risk management, or supplier risk management. While these terms are common, they are often too narrow, focusing primarily on risk mitigation rather than the full spectrum of what is required to manage third-party relationships effectively. I use the term Third-Party GRC because it begins with governance — defining the purpose and objectives of each relationship — before addressing risk and compliance.

Following the OCEG definition, GRC is the capability to reliably achieve objectives (governance), address uncertainty (risk management), and act with integrity (compliance). This holistic framework must extend across all third-party relationships. Every relationship exists for a purpose, with objectives to be achieved, risks that introduce uncertainty, and integrity requirements that ensure ethical, lawful, and sustainable operations. Third-party risk, performance, and compliance cannot be managed in silos—they must be integrated within a unified governance framework.

Now let’s explore this illustration in words below, but you can download the visual here: Third-Party GRC Management Solutions Illustrated to go along with this commentary . . .

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The Reality: Growing Complexity and Shrinking Margins for Error

In nearly every sector, third-party ecosystems are growing larger, more global, and more complex. This complexity brings real challenges:

• Siloed oversight and disconnected processes mean that no one has a complete, real-time picture of third-party performance, risk, and compliance.
• Manual, redundant tasks slow onboarding, create bottlenecks, and increase the likelihood of errors or omissions.
• Fragmented technology stacks—a patchwork of spreadsheets, email threads, and point solutions—make it difficult to integrate data, detect emerging risks, or demonstrate compliance.
• Lack of timely insights leads to reactive firefighting rather than proactive risk management.
• Difficulty scaling oversight as the number and diversity of third-party relationships multiply.
• Weak change management hinders adaptation to shifting regulatory landscapes and market expectations.

In short, organizations often struggle to govern their extended enterprise with the efficiency, effectiveness, resilience, and agility that today’s risk environment demands.

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Why This Matters Now

The stakes are rising. Regulatory regimes are imposing explicit operational resilience, due diligence, and accountability requirements for third-party relationships. Investors and consumers are pressing for greater ESG transparency. Cyberattacks increasingly target the weakest link in the supply chain. Disruptions — from pandemics to geopolitical conflicts — are exposing the fragility of global sourcing.

The message is clear: Without mature third-party governance, risk management, and compliance (GRC) capabilities, organizations risk being blindsided by issues originating outside their four walls.

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From Fragmentation to Integration: The Role of Third-Party GRC Solutions

This is where integrated Third-Party GRC management solutions come into play. These platforms facilitate and automate the governance, risk management, and compliance of an organization’s third-party relationships across their entire lifecycle: from onboarding to offboarding.

They deliver:

• Unified visibility into third-party objectives, risks, and performance
• Streamlined workflows and automation to replace inefficient manual processes
• Integrated risk intelligence to continuously monitor for sanctions, negative news, security ratings, financial viability, ESG metrics, and more
• Clear accountability through centralized audit trails and performance metrics
• Alignment between third-party engagements and organizational strategy, performance, and compliance obligations

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The Lifecycle Approach to Third-Party Governance

Managing third-party relationships effectively requires structured lifecycle oversight that technology automates:

1. Onboarding – Identification, qualification, and integration of third parties, supported by automated due diligence and verification that they meet required standards.
2. Ongoing Monitoring & Assessment – Continuous evaluation of performance, risk, and compliance against agreed KPIs and regulatory expectations.
3. Audits & Inspections – Periodic, evidence-based reviews to ensure third parties are meeting contractual, legal, and policy requirements.
4. Offboarding – Secure disengagement when relationships end, including fulfillment of obligations, termination of data access, and mitigation of residual risks.

When done well, this lifecycle approach ensures that organizations have no surprises in their third-party ecosystem and can act swiftly when intervention is needed.

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Critical Capabilities That Drive Value

A mature Third-Party GRC technology platform should integrate capabilities that directly address the challenges of today’s extended enterprise, including:

• Real-time monitoring and automated risk alerts
• Integrated third-party risk assessment across multiple domains
• Automated due diligence during onboarding and renewal cycles
• Compliance tracking and audit trails to meet regulatory and contractual demands
• Performance metrics and dynamic reporting for continuous improvement
• Third-party portals for secure information exchange and collaboration
• Contract and issue management for full lifecycle oversight
• Scalability and integration with risk intelligence providers for continuous data enrichment

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The Business Case: Efficiency, Effectiveness, Resilience, Agility

When building the case for Third-Party GRC investment, the benefits align with four measurable outcomes:

1. Efficiency – Reduce cost and time by automating processes and centralizing oversight.
2. Effectiveness – Identify and mitigate risks before they escalate into costly incidents.
3. Resilience – Maintain operational continuity despite disruptions in the third-party network.
4. Agility – Quickly adapt to new risks, regulations, and market shifts.

These value drivers not only support compliance but also position third-party governance as a strategic enabler of organizational performance.

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From Risk to Readiness in the Extended Enterprise

Third-Party GRC solutions transform extended enterprise oversight from reactive problem-solving to proactive orchestration. They allow organizations to govern relationships with transparency, manage uncertainty with precision, and ensure that third parties contribute to—not compromise—strategic objectives.

In a world where a supplier’s mistake, a vendor’s security lapse, or a partner’s compliance failure can impact your bottom line within hours, the ability to monitor, manage, and align third-party relationships in real time is no longer optional—it is essential.

If your organization is still relying on siloed oversight, spreadsheets, or disconnected tools, it may be time to rethink your approach. Integrated Third-Party GRC management solutions provide the clarity, confidence, and control needed to thrive in the complex, high-stakes reality of today’s extended enterprise.

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