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ISO 27001: The Security Foundation ISO/IEC 27001 is the global standard for establishing, implementing, and maintaining an Information Security Management System (ISMS). It focuses on protecting the confidentiality, integrity, and availability of information through risk-based security controls. For most organizations, this is the bedrock—governing infrastructure security, access control, incident response, vendor risk, and operational resilience. It answers the question: Are we managing information security risks in a systematic and auditable way?
ISO 27701: Extending Security into Privacy ISO/IEC 27701 builds directly on ISO 27001 by extending the ISMS into a Privacy Information Management System (PIMS). It introduces structured controls for handling personally identifiable information (PII), clarifying roles such as data controllers and processors, and aligning security practices with privacy obligations. Where ISO 27001 protects data broadly, ISO 27701 adds explicit guardrails around how personal data is collected, processed, retained, and shared—bridging security operations with privacy compliance.
ISO 42001: Governing AI Systems ISO/IEC 42001 is the emerging standard for AI management systems. Unlike traditional IT or privacy standards, it governs the entire AI lifecycle—from design and training to deployment, monitoring, and retirement. It addresses AI-specific risks such as bias, explainability, model drift, misuse, and unintended impact. Importantly, ISO 42001 is not a bolt-on framework; it assumes security and privacy controls already exist and focuses on how AI systems amplify risk if governance is weak.
Integrating the Three into a Unified Governance, Risk, and Compliance Model When combined, ISO 27001, ISO 27701, and ISO 42001 form an integrated governance and risk management structure—the “ISO Trifecta.” ISO 27001 provides the secure operational foundation, ISO 27701 ensures privacy and data protection are embedded into processes, and ISO 42001 acts as the governance engine for AI-driven decision-making. Together, they create mutually reinforcing controls: security protects AI infrastructure, privacy constrains data use, and AI governance ensures accountability, transparency, and continuous risk oversight. Instead of managing three separate compliance efforts, organizations can align policies, risk assessments, controls, and audits under a single, coherent management system.
Perspective: Why Integrated Governance Matters Integrated governance is no longer optional—especially in an AI-driven world. Treating security, privacy, and AI risk as separate silos creates gaps precisely where regulators, customers, and attackers are looking. The real value of the ISO Trifecta is not certification; it’s coherence. When governance is integrated, risk decisions are consistent, controls scale across technologies, and AI systems are held to the same rigor as legacy systems. Organizations that adopt this mindset early won’t just be compliant—they’ll be trusted.
At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec.
The threat landscape is entering a new phase with the rise of AI-assisted malware. What once required well-funded teams and months of development can now be created by a single individual in days using AI. This dramatically lowers the barrier to entry for advanced cyberattacks.
This shift means attackers can scale faster, adapt quicker, and deliver higher-quality attacks with fewer resources. As a result, smaller and mid-sized organizations are no longer “too small to matter” and are increasingly attractive targets.
Emerging malware frameworks are more modular, stealthy, and cloud-aware, designed to persist, evade detection, and blend into modern IT environments. Traditional signature-based defenses and slow response models are struggling to keep pace with this speed and sophistication.
Critically, this is no longer just a technical problem — it is a business risk. AI-enabled attacks increase the likelihood of operational disruption, regulatory exposure, financial loss, and reputational damage, often faster than organizations can react.
Organizations that will remain resilient are not those chasing the latest tools, but those making strategic security decisions. This includes treating cybersecurity as a core element of business resilience, not an IT afterthought.
Key priorities include moving toward Zero Trust and behavior-based detection, maintaining strong asset visibility and patch hygiene, investing in practical security awareness, and establishing clear governance around internal AI usage.
The cybersecurity landscape is undergoing a fundamental shift with the emergence of a new class of malware that is largely created using artificial intelligence (AI) rather than traditional development teams. Recent reporting shows that advanced malware frameworks once requiring months of collaborative effort can now be developed in days with AI’s help.
The most prominent example prompting this concern is the discovery of the VoidLink malware framework — an AI-driven, cloud-native Linux malware platform uncovered by security researchers. Rather than being a simple script or proof-of-concept, VoidLink appears to be a full, modular framework with sophisticated stealth and persistence capabilities.
What makes this remarkable isn’t just the malware itself, but how it was developed: evidence points to a single individual using AI tools to generate and assemble most of the code, something that previously would have required a well-coordinated team of experts.
This capability accelerates threat development dramatically. Where malware used to take months to design, code, test, iterate, and refine, AI assistance can collapse that timeline to days or weeks, enabling adversaries with limited personnel and resources to produce highly capable threats.
The practical implications are significant. Advanced malware frameworks like VoidLink are being engineered to operate stealthily within cloud and container environments, adapt to target systems, evade detection, and maintain long-term footholds. They’re not throwaway tools — they’re designed for persistent, strategic compromise.
This isn’t an abstract future problem. Already, there are real examples of AI-assisted malware research showing how AI can be used to create more evasive and adaptable malicious code — from polymorphic ransomware that sidesteps detection to automated worms that spread faster than defenders can respond.
The rise of AI-generated malware fundamentally challenges traditional defenses. Signature-based detection, static analysis, and manual response processes struggle when threats are both novel and rapidly evolving. The attack surface expands when bad actors leverage the same AI innovation that defenders use.
For security leaders, this means rethinking strategies: investing in behavior-based detection, threat hunting, cloud-native security controls, and real-time monitoring rather than relying solely on legacy defenses. Organizations must assume that future threats may be authored as much by machines as by humans.
In my view, this transition marks one of the first true inflection points in cyber risk: AI has joined the attacker team not just as a helper, but as a core part of the offensive playbook. This amplifies both the pace and quality of attacks and underscores the urgency of evolving our defensive posture from reactive to anticipatory. We’re not just defending against more attacks — we’re defending against self-evolving, machine-assisted adversaries.
Perspective: AI has permanently altered the economics of cybercrime. The question for leadership is no longer “Are we secure today?” but “Are we adapting fast enough for what’s already here?” Organizations that fail to evolve their security strategy at the speed of AI will find themselves defending yesterday’s risks against tomorrow’s attackers.
At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec.
Zero Trust Security is a security model that assumes no user, device, workload, application, or network is inherently trusted, whether inside or outside the traditional perimeter.
The core principles reflected in the image are:
Never trust, always verify – every access request must be authenticated, authorized, and continuously evaluated.
Least privilege access – users and systems only get the minimum access required.
Assume breach – design controls as if attackers are already present.
Continuous monitoring and enforcement – security decisions are dynamic, not one-time.
Instead of relying on perimeter defenses, Zero Trust distributes controls across endpoints, identities, APIs, networks, data, applications, and cloud environments—exactly the seven domains shown in the diagram.
2. The Seven Components of Zero Trust
1. Endpoint Security
Purpose: Ensure only trusted, compliant devices can access resources.
Key controls shown:
Antivirus / Anti-Malware
Endpoint Detection & Response (EDR)
Patch Management
Device Control
Data Loss Prevention (DLP)
Mobile Device Management (MDM)
Encryption
Threat Intelligence Integration
Zero Trust intent: Access decisions depend on device posture, not just identity.
2. API Security
Purpose: Protect machine-to-machine and application integrations.
Key controls shown:
Authentication & Authorization
API Gateways
Rate Limiting
Encryption (at rest & in transit)
Threat Detection & Monitoring
Input Validation
API Keys & Tokens
Secure Development Practices
Zero Trust intent: Every API call is explicitly authenticated, authorized, and inspected.
3. Network Security
Purpose: Eliminate implicit trust within networks.
Key controls shown:
IDS / IPS
Network Access Control (NAC)
Network Segmentation / Micro-segmentation
SSL / TLS
VPN
Firewalls
Traffic Analysis & Anomaly Detection
Zero Trust intent: The network is treated as hostile, even internally.
4. Data Security
Purpose: Protect data regardless of location.
Key controls shown:
Encryption (at rest & in transit)
Data Masking
Data Loss Prevention (DLP)
Access Controls
Backup & Recovery
Data Integrity Verification
Tokenization
Zero Trust intent: Security follows the data, not the infrastructure.
5. Cloud Security
Purpose: Enforce Zero Trust in shared-responsibility environments.
Key controls shown:
Cloud Access Security Broker (CASB)
Data Encryption
Identity & Access Management (IAM)
Security Posture Management
Continuous Compliance Monitoring
Cloud Identity Federation
Cloud Security Audits
Zero Trust intent: No cloud service is trusted by default—visibility and control are mandatory.
6. Application Security
Purpose: Prevent application-layer exploitation.
Key controls shown:
Secure Code Review
Web Application Firewall (WAF)
API Security
Runtime Application Self-Protection (RASP)
Software Composition Analysis (SCA)
Secure SDLC
SAST / DAST
Zero Trust intent: Applications must continuously prove they are secure and uncompromised.
7. IoT Security
Purpose: Secure non-traditional and unmanaged devices.
Key controls shown:
Device Authentication
Network Segmentation
Secure Firmware Updates
Encryption for IoT Data
Anomaly Detection
Vulnerability Management
Device Lifecycle Management
Secure Boot
Zero Trust intent: IoT devices are high-risk by default and strictly controlled.
3. Mapping Zero Trust Controls to ISO/IEC 27001
Below is a practical mapping to ISO/IEC 27001:2022 (Annex A). (Zero Trust is not a standard, but it maps very cleanly to ISO controls.)
Identity, Authentication & Access (Core Zero Trust)
Zero Trust domains: API, Cloud, Network, Application ISO 27001 controls:
A.5.15 – Access control
A.5.16 – Identity management
A.5.17 – Authentication information
A.5.18 – Access rights
Endpoint & Device Security
Zero Trust domain: Endpoint, IoT ISO 27001 controls:
A.8.1 – User endpoint devices
A.8.7 – Protection against malware
A.8.8 – Management of technical vulnerabilities
A.5.9 – Inventory of information and assets
Network Security & Segmentation
Zero Trust domain: Network ISO 27001 controls:
A.8.20 – Network security
A.8.21 – Security of network services
A.8.22 – Segregation of networks
A.5.14 – Information transfer
Application & API Security
Zero Trust domain: Application, API ISO 27001 controls:
A.8.25 – Secure development lifecycle
A.8.26 – Application security requirements
A.8.27 – Secure system architecture
A.8.28 – Secure coding
A.8.29 – Security testing in development
Data Protection & Cryptography
Zero Trust domain: Data ISO 27001 controls:
A.8.10 – Information deletion
A.8.11 – Data masking
A.8.12 – Data leakage prevention
A.8.13 – Backup
A.8.24 – Use of cryptography
Monitoring, Detection & Response
Zero Trust domain: Endpoint, Network, Cloud ISO 27001 controls:
A.8.15 – Logging
A.8.16 – Monitoring activities
A.5.24 – Incident management planning
A.5.25 – Assessment and decision on incidents
A.5.26 – Response to information security incidents
Cloud & Third-Party Security
Zero Trust domain: Cloud ISO 27001 controls:
A.5.19 – Information security in supplier relationships
A.5.20 – Addressing security in supplier agreements
A.5.21 – ICT supply chain security
A.5.22 – Monitoring supplier services
4. Key Takeaway (Executive Summary)
Zero Trust is an architecture and mindset
ISO 27001 is a management system and control framework
Zero Trust implements ISO 27001 controls in a continuous, adaptive, and identity-centric way
In short:
ISO 27001 defines what controls you need. Zero Trust defines how to enforce them effectively.
Zero Trust → ISO/IEC 27001 Crosswalk
Zero Trust Domain
Primary Security Controls
Zero Trust Objective
ISO/IEC 27001:2022 Annex A Controls
Identity & Access (Core ZT Layer)
IAM, MFA, RBAC, API auth, token-based access, least privilege
Ensure every access request is explicitly verified
A.5.15 Access control A.5.16 Identity management A.5.17 Authentication information A.5.18 Access rights
Endpoint Security
EDR, AV, MDM, patching, device posture checks, disk encryption
Allow access only from trusted and compliant devices
A.8.1 User endpoint devices A.8.7 Protection against malware A.8.8 Technical vulnerability management A.5.9 Inventory of information and assets
At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec.
The report highlights that defining AI remains challenging due to evolving technology and inconsistent usage of the term. To stay practical, ENISA focuses mainly on machine learning (ML), as it dominates current AI deployments and introduces unique security vulnerabilities. AI is considered across its entire lifecycle, from data collection and model training to deployment and operation, recognizing that risks can emerge at any stage.
Cybersecurity of AI is framed in two ways. The narrow view focuses on protecting confidentiality, integrity, and availability (CIA) of AI systems, data, and processes. The broader view expands this to include trustworthiness attributes such as robustness, explainability, transparency, and data quality. ENISA adopts the narrow definition but acknowledges that trustworthiness and cybersecurity are tightly interconnected and cannot be treated independently.
3. Standardisation Supporting AI Cybersecurity
Standardisation bodies are actively adapting existing frameworks and developing new ones to address AI-related risks. The report emphasizes ISO/IEC, CEN-CENELEC, and ETSI as the most relevant organisations due to their role in harmonised standards. A key assumption is that AI is fundamentally software, meaning traditional information security and quality standards can often be extended to AI with proper guidance.
CEN-CENELEC separates responsibilities between cybersecurity-focused committees and AI-focused ones, while ETSI takes a more technical, threat-driven approach through its Security of AI (SAI) group. ISO/IEC SC 42 plays a central role globally by developing AI-specific standards for terminology, lifecycle management, risk management, and governance. Despite this activity, the landscape remains fragmented and difficult to navigate.
4. Analysis of Coverage – Narrow Cybersecurity Sense
When viewed through the CIA lens, AI systems face distinct threats such as model theft, data poisoning, adversarial inputs, and denial-of-service via computational abuse. The report argues that existing standards like ISO/IEC 27001, ISO/IEC 27002, ISO 42001, and ISO 9001 can mitigate many of these risks if adapted correctly to AI contexts.
However, limitations exist. Most standards operate at an organisational level, while AI risks are often system-specific. Challenges such as opaque ML models, evolving attack techniques, continuous learning, and immature defensive research reduce the effectiveness of static standards. Major gaps remain around data and model traceability, metrics for robustness, and runtime monitoring, all of which are critical for AI security.
4.2 Coverage – Trustworthiness Perspective
The report explains that cybersecurity both enables and depends on AI trustworthiness. Requirements from the draft AI Act—such as data governance, logging, transparency, human oversight, risk management, and robustness—are all supported by cybersecurity controls. Standards like ISO 9001 and ISO/IEC 31000 indirectly strengthen trustworthiness by enforcing disciplined governance and quality practices.
Yet, ENISA warns of a growing risk: parallel standardisation tracks for cybersecurity and AI trustworthiness may lead to duplication, inconsistency, and confusion—especially in areas like conformity assessment and robustness evaluation. A coordinated, unified approach is strongly recommended to ensure coherence and regulatory usability.
5. Conclusions and Recommendations (5.1–5.2)
The report concludes that while many relevant standards already exist, AI-specific guidance, integration, and maturity are still lacking. Organisations should not wait for perfect AI standards but instead adapt current cybersecurity, quality, and risk frameworks to AI use cases. Standards bodies are encouraged to close gaps around lifecycle traceability, continuous learning, and AI-specific metrics.
In preparation for the AI Act, ENISA recommends better alignment between AI governance and cybersecurity governance frameworks to avoid overlapping compliance efforts. The report stresses that some gaps will only become visible as AI technologies and attack methods continue to evolve.
My Opinion
This report gets one critical thing right: AI security is not a brand-new problem—it is a complex extension of existing cybersecurity and governance challenges. Treating AI as “just another system” under ISO 27001 without AI-specific interpretation is dangerous, but reinventing security from scratch for AI is equally inefficient.
From a practical vCISO and governance perspective, the real gap is not standards—it is operationalisation. Organisations struggle to translate abstract AI trustworthiness principles into enforceable controls, metrics, and assurance evidence. Until standards converge into a clear, unified control model (especially aligned with ISO 27001, ISO 42001, and the NIST AI RMF), AI security will remain fragmented and audit-driven rather than risk-driven.
In short: AI cybersecurity maturity will lag unless governance, security, and trustworthiness are treated as one integrated discipline—not three separate conversations.
At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec.
In developing organizational risk documentation—such as enterprise risk registers, cyber risk assessments, and business continuity plans—it is increasingly important to consider the World Economic Forum’s Global Risks Report. The report provides a forward-looking view of global threats and helps leaders balance immediate pressures with longer-term strategic risks.
The analysis is based on the Global Risks Perception Survey (GRPS), which gathered insights from more than 1,300 experts across government, business, academia, and civil society. These perspectives allow the report to examine risks across three time horizons: the immediate term (2026), the short-to-medium term (up to 2028), and the long term (to 2036).
One of the most pressing short-term threats identified is geopolitical instability. Rising geopolitical tensions, regional conflicts, and fragmentation of global cooperation are increasing uncertainty for businesses. These risks can disrupt supply chains, trigger sanctions, and increase regulatory and operational complexity across borders.
Economic risks remain central across all timeframes. Inflation volatility, debt distress, slow economic growth, and potential financial system shocks pose ongoing threats to organizational stability. In the medium term, widening inequality and reduced economic opportunity could further amplify social and political instability.
Cyber and technological risks continue to grow in scale and impact. Cybercrime, ransomware, data breaches, and misuse of emerging technologies—particularly artificial intelligence—are seen as major short- and long-term risks. As digital dependency increases, failures in technology governance or third-party ecosystems can cascade quickly across industries.
The report also highlights misinformation and disinformation as a critical threat. The erosion of trust in institutions, fueled by false or manipulated information, can destabilize societies, influence elections, and undermine crisis response efforts. This risk is amplified by AI-driven content generation and social media scale.
Climate and environmental risks dominate the long-term outlook but are already having immediate effects. Extreme weather events, resource scarcity, and biodiversity loss threaten infrastructure, supply chains, and food security. Organizations face increasing exposure to physical risks as well as regulatory and reputational pressures related to sustainability.
Public health risks remain relevant, even as the world moves beyond recent pandemics. Future outbreaks, combined with strained healthcare systems and global inequities in access to care, could create significant economic and operational disruptions, particularly in densely connected global markets.
Another growing concern is social fragmentation, including polarization, declining social cohesion, and erosion of trust. These factors can lead to civil unrest, labor disruptions, and increased pressure on organizations to navigate complex social and ethical expectations.
Overall, the report emphasizes that global risks are deeply interconnected. Cyber incidents can amplify economic instability, climate events can worsen geopolitical tensions, and misinformation can undermine responses to every other risk category. For organizations, the key takeaway is clear: risk management must be integrated, forward-looking, and resilience-focused—not siloed or purely compliance-driven.
Source: The report can be downloaded here: https://reports.weforum.org/docs/WEF_Global_Risks_Report_2026.pdf
Below is a clear, practitioner-level mapping of the World Economic Forum (WEF) global threats to ISO/IEC 27001, written for CISOs, vCISOs, risk owners, and auditors. I’ve mapped each threat to key ISO 27001 clauses and Annex A control themes (aligned to ISO/IEC 27001:2022).
WEF Global Threats → ISO/IEC 27001 Mapping
1. Geopolitical Instability & Conflict
Risk impact: Sanctions, supply-chain disruption, regulatory uncertainty, cross-border data issues
ISO 27001 Mapping
Clause 4.1 – Understanding the organization and its context
Clause 6.1 – Actions to address risks and opportunities
Annex A
A.5.31 – Legal, statutory, regulatory, and contractual requirements
Risk impact: Compound failures across cyber, economic, and operational domains
ISO 27001 Mapping
Clause 6.1 – Risk-based thinking
Clause 9.1 – Monitoring, measurement, analysis, and evaluation
Clause 10.1 – Continual improvement
Annex A
A.5.7 – Threat intelligence
A.5.35 – Independent review of information security
A.8.16 – Continuous monitoring
Key Takeaway (vCISO / Board-Level)
ISO 27001 is not just a cybersecurity standard — it is a resilience framework. When properly implemented, it directly addresses the systemic, interconnected risks highlighted by the World Economic Forum, provided organizations treat it as a living risk management system, not a compliance checkbox.
Here’s a practical mapping of WEF global risks to ISO 27001 risk register entries, designed for use by vCISOs, risk managers, or security teams. I’ve structured it in a way that you could directly drop into a risk register template.
At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec.
The CISO role is evolving rapidly between now and 2035. Traditional security responsibilities—like managing firewalls and monitoring networks—are only part of the picture. CISOs must increasingly operate as strategic business leaders, integrating security into enterprise-wide decision-making and aligning risk management with business objectives.
Boards and CEOs will have higher expectations for security leaders in the next decade. They will look for CISOs who can clearly communicate risks in business terms, drive organizational resilience, and contribute to strategic initiatives rather than just react to incidents. Leadership influence will matter as much as technical expertise.
Technical excellence alone is no longer enough. While deep security knowledge remains critical, modern CISOs must combine it with business acumen, emotional intelligence, and the ability to navigate complex organizational dynamics. The most successful security leaders bridge the gap between technology and business impact.
World-class CISOs are building leadership capabilities today that go beyond technology management. This includes shaping corporate culture around security, influencing cross-functional decisions, mentoring teams, and advocating for proactive risk governance. These skills ensure they remain central to enterprise success.
Common traps quietly derail otherwise strong CISOs. Focusing too narrowly on technical issues, failing to communicate effectively with executives, or neglecting stakeholder relationships can limit influence and career growth. Awareness of these pitfalls allows security leaders to avoid them and maintain credibility.
Future-proofing your role and influence is now essential. AI is transforming the security landscape. For CISOs, AI means automated threat detection, predictive risk analytics, and new ethical and regulatory considerations. Responsibilities like routine monitoring may fade, while oversight of AI-driven systems, data governance, and strategic security leadership will intensify. The question is no longer whether CISOs understand AI—it’s whether they are prepared to lead in an AI-driven organization, ensuring security remains a core enabler of business objectives.
At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec.
A CISO must design and operate a security governance model that aligns with corporate governance, regulatory requirements, and the organization’s risk appetite. This ensures security controls are consistent, auditable, and defensible. Without strong governance, organizations face regulatory penalties, audit failures, and fragmented or overlapping controls that create risk instead of reducing it.
2. Cybersecurity Maturity Management
The CISO should continuously assess the organization’s security posture using recognized maturity models such as NIST CSF or ISO 27001, and define a clear target state. This capability enables prioritization of investments and long-term improvement. Lacking maturity management leads to reactive, ad-hoc spending and an inability to justify or sequence security initiatives.
3. Incident Response (Response Readiness)
A core responsibility of the CISO is ensuring the organization is prepared for incidents through tested playbooks, simulations, and war-gaming. Effective response readiness minimizes impact when breaches occur. Without it, detection is slow, downtime is extended, and financial and reputational damage escalates rapidly.
The CISO must ensure the organization can rapidly detect threats, alert the right teams, and automate responses where possible. Strong SOC and SOAR capabilities reduce mean time to detect (MTTD) and mean time to respond (MTTR). Weakness here results in undetected breaches, slow manual responses, and delayed forensic investigations.
5. Business & Financial Acumen
A modern CISO must connect cyber risk to business outcomes—revenue, margins, valuation, and enterprise risk. This includes articulating ROI, payback, and value creation. Without this skill, security is viewed purely as a cost center, and investments fail to align with business strategy.
6. Risk Communication
The CISO must translate complex technical risks into clear, business-impact narratives that boards and executives can act on. Effective risk communication enables informed decision-making. When this capability is weak, risks remain misunderstood or hidden until a major incident forces attention.
7. Culture & Cross-Functional Leadership
A successful CISO builds strong security teams, fosters a security-aware culture, and collaborates across IT, legal, finance, product, and operations. Security cannot succeed in silos. Poor leadership here leads to misaligned priorities, weak adoption of controls, and ineffective onboarding of new staff into security practices.
My Opinion: The Three Most Important Capabilities
If forced to prioritize, the top three are:
Risk Communication If the board does not understand risk, no other capability matters. Funding, priorities, and executive decisions all depend on how well the CISO communicates risk in business terms.
Governance Oversight Governance is the foundation. Without it, security efforts are fragmented, compliance fails, and accountability is unclear. Strong governance enables everything else to function coherently.
Incident Response (Response Readiness) Breaches are inevitable. What separates resilient organizations from failed ones is how well they respond. Preparation directly limits financial, operational, and reputational damage.
Bottom line: Technology matters, but leadership, governance, and communication are what boards ultimately expect from a CISO. Tools support these capabilities—they don’t replace them.
At DISC InfoSec, we help organizations navigate this landscape by aligning AI risk management, governance, security, and compliance into a single, practical roadmap. Whether you are experimenting with AI or deploying it at scale, we help you choose and operationalize the right frameworks to reduce risk and build trust. Learn more at DISC InfoSec.
GRC Solutions offers a collection of self-assessment and gap analysis tools designed to help organisations evaluate their current compliance and risk posture across a variety of standards and regulations. These tools let you measure how well your existing policies, controls, and processes match expectations before you start a full compliance project.
Several tools focus on ISO standards, such as ISO 27001:2022 and ISO 27002 (information security controls), which help you identify where your security management system aligns or falls short of the standard’s requirements. Similar gap analysis tools are available for ISO 27701 (privacy information management) and ISO 9001 (quality management).
For data protection and privacy, there are GDPR-related assessment tools to gauge readiness against the EU General Data Protection Regulation. These help you see where your data handling and privacy measures require improvement or documentation before progressing with compliance work.
The Cyber Essentials Gap Analysis Tool is geared toward organisations preparing for this basic but influential UK cybersecurity certification. It offers a simple way to assess the maturity of your cyber controls relative to the Cyber Essentials criteria.
Tools also cover specialised areas such as PCI DSS (Payment Card Industry Data Security Standard), including a self-assessment questionnaire tool to help identify how your card-payment practices align with PCI requirements.
There are industry-specific and sector-tailored assessment tools too, such as versions of the GDPR gap assessment tailored for legal sector organisations and schools, recognising that different environments have different compliance nuances.
Broader compliance topics like the EU Cloud Code of Conduct and UK privacy regulations (e.g., PECR) are supported with gap assessment or self-assessment tools. These allow you to review relevant controls and practices in line with the respective frameworks.
A NIST Gap Assessment Tool helps organisations benchmark against the National Institute of Standards and Technology framework, while a DORA Gap Analysis Tool addresses preparedness for digital operational resilience regulations impacting financial institutions.
Beyond regulatory compliance, the catalogue includes items like a Business Continuity Risk Management Pack and standards-related gap tools (e.g., BS 31111), offering flexibility for organisations to diagnose gaps in broader risk and continuity planning areas as well.
🚨 If you’re ISO 27001 certified and using AI, you have 47 control gaps.
And auditors are starting to notice.
Here’s what’s happening right now:
→ SOC 2 auditors asking “How do you manage AI model risk?” (no documented answer = finding)
→ Enterprise customers adding AI governance sections to vendor questionnaires
→ EU AI Act enforcement starting in 2025 → Cyber insurance excluding AI incidents without documented controls
ISO 27001 covers information security. But if you’re using:
Customer-facing chatbots
Predictive analytics
Automated decision-making
Even GitHub Copilot
You need 47 additional AI-specific controls that ISO 27001 doesn’t address.
I’ve mapped all 47 controls across 7 critical areas: âś“ AI System Lifecycle Management âś“ Data Governance for AI âś“ Model Risk & Testing âś“ Transparency & Explainability âś“ Human Oversight & Accountability âś“ Third-Party AI Management âś“ AI Incident Response
🔥 Truth bomb from a experience: You can’t make companies care about security.
Most don’t—until they get burned.
Security isn’t important… until it suddenly is. And by then, it’s often too late. Just ask the businesses that disappeared after a cyberattack.
Trying to convince someone it matters? Like telling your friend to eat healthy—they won’t care until a personal wake-up call hits.
Here’s the smarter play: focus on the people who already value security. Show them why you’re the one who can solve their problems. That’s where your time actually pays off.
Your energy shouldn’t go into preaching; it should go into actionable impact for those ready to act.
⏳ Remember: people only take security seriously when they decide it’s worth it. Your job is to be ready when that moment comes.
Opinion: This perspective is spot-on. Security adoption isn’t about persuasion; it’s about timing and alignment. The most effective consultants succeed not by preaching to the uninterested, but by identifying those who already recognize risk and helping them act decisively.
ISO 27001 assessment → Gap analysis → Prioritized remediation → See your risks immediately with a clear path from gaps to remediation.
Start your assessment today — simply click the image on above to complete your payment and get instant access – Evaluate your organization’s compliance with mandatory ISMS clauses through our 5-Level Maturity Model — until the end of this month.
Let’s review your assessment results— Contact us for actionable instructions for resolving each gap.
The Help Net Security video titled “The CISO’s guide to stronger board communication” features Alisdair Faulkner, CEO of Darwinium, who discusses how the role of the Chief Information Security Officer (CISO) has evolved significantly in recent years. The piece frames the challenge: CISOs now must bridge the gap between deep technical knowledge and strategic business conversations.
Faulkner argues that many CISOs fall into the trap of using overly technical language when speaking with board members. This can lead to misunderstanding, disengagement, or even resistance. He highlights that clarity and relevance are vital: CISOs should aim to translate complex security concepts into business-oriented terms.
One key shift he advocates is positioning cybersecurity not as a cost center, but as a business enabler. In other words, security initiatives should be tied to business value—supporting goals like growth, innovation, resilience, and risk mitigation—rather than being framed purely as expense or compliance.
Faulkner also delves into the effects of artificial intelligence on board-level discussions. He points out that AI is both a tool and a threat: it can enhance security operations, but it also introduces new vulnerabilities and risk vectors. As such, it shifts the nature of what boards must understand about cybersecurity.
To build trust and alignment with executives, the video offers practical strategies. These include focusing on metrics that matter to business leaders, storytelling to make risks tangible, and avoiding the temptation to “drown” stakeholders in technical detail. The goal is to foster informed decision-making, not just to show knowledge.
Faulkner emphasizes resilience and innovation as hallmarks of modern security leadership. Rather than passively reacting to threats, the CISO should help the organization anticipate, adapt, and evolve. This helps ensure that security is integrated into the business’s strategic journey.
Another insight is that board communications should be ongoing and evolving, not limited to annual reviews or audits. As risks, technologies, and business priorities shift, the CISO needs to keep the board apprised, engaged, and confident in the security posture.
In sum, Faulkner’s guidance reframes the CISO’s role—from a highly technical operator to a strategic bridge to the board. He urges CISOs to communicate in business terms, emphasize value and resilience, and adapt to emerging challenges like AI. The video is a call for security leaders to become fluent in “the language of the board.”
My opinion I think this is a very timely and valuable perspective. In many organizations, there’s still a disconnect between cybersecurity teams and executive governance. Framing security in business value rather than technical jargon is essential to elevate the conversation and gain real support. The emphasis on AI is also apt—boards increasingly need to understand both the opportunities and risks it brings. Overall, Faulkner’s approach is pragmatic and strategic, and I believe CISOs who adopt these practices will be more effective and influential.
Here’s a concise cheat sheet based on the article and video:
📝 CISO–Board Communication Cheat Sheet
1. Speak the Board’s Language
Avoid deep technical jargon.
Translate risks into business impact (financial, reputational, operational).
2. Frame Security as a Business Enabler
Position cybersecurity as value-adding, not just a cost or compliance checkbox.
Show how security supports growth, innovation, and resilience.
3. Use Metrics That Matter
Present KPIs that executives care about (risk reduction, downtime avoided, compliance readiness).
Keep dashboards simple and aligned to strategic goals.
4. Leverage Storytelling
Use real scenarios, case studies, or analogies to make risks tangible.
1. Framing a Risk-Aware AI Strategy The book begins by laying out the need for organizations to approach AI not just as a source of opportunity (innovation, efficiency, etc.) but also as a domain rife with risk: ethical risks (bias, fairness), safety, transparency, privacy, regulatory exposure, reputational risk, and so on. It argues that a risk-aware strategy must be integrated into the whole AI lifecycle—from design to deployment and maintenance. Key in its framing is that risk management shouldn’t be an afterthought or a compliance exercise; it should be embedded in strategy, culture, governance structures. The idea is to shift from reactive to proactive: anticipating what could go wrong, and building in mitigations early.
2. How the book leverages ISO 42001 and related standards A core feature of the book is that it aligns its framework heavily with ISO IEC 42001:2023, which is the first international standard to define requirements for establishing, implementing, maintaining, and continuously improving an Artificial Intelligence Management System (AIMS). The book draws connections between 42001 and adjacent or overlapping standards—such as ISO 27001 (information security), ISO 31000 (risk management in general), as well as NIST’s AI Risk Management Framework (AI RMF 1.0). The treatment helps the reader see how these standards can interoperate—where one handles confidentiality, security, access controls (ISO 27001), another handles overall risk governance, etc.—and how 42001 fills gaps specific to AI: lifecycle governance, transparency, ethics, stakeholder traceability.
3. The Artificial Intelligence Management System (AIMS) as central tool The concept of an AI Management System (AIMS) is at the heart of the book. An AIMS per ISO 42001 is a set of interrelated or interacting elements of an organization (policies, controls, processes, roles, tools) intended to ensure responsible development and use of AI systems. The author Andrew Pattison walks through what components are essential: leadership commitment; roles and responsibilities; risk identification, impact assessment; operational controls; monitoring, performance evaluation; continual improvement. One strength is the practical guidance: not just “you should do these”, but how to embed them in organizations that don’t have deep AI maturity yet. The book emphasizes that an AIMS is more than a set of policies—it’s a living system that must adapt, learn, and respond as AI systems evolve, as new risks emerge, and as external demands (laws, regulations, public expectations) shift.
4. Comparison and contrasts: ISO 42001, ISO 27001, and NIST In comparing standards, the book does a good job of pointing out both overlaps and distinct value: for example, ISO 27001 is strong on information security, confidentiality, integrity, availability; it has proven structures for risk assessment and for ensuring controls. But AI systems pose additional, unique risks (bias, accountability of decision-making, transparency, possible harms in deployment) that are not fully covered by a pure security standard. NIST’s AI Risk Management Framework provides flexible guidance especially for U.S. organisations or those aligning with U.S. governmental expectations: mapping, measuring, managing risks in a more domain-agnostic way. Meanwhile, ISO 42001 brings in the notion of an AI-specific management system, lifecycle oversight, and explicit ethical / governance obligations. The book argues that a robust strategy often uses multiple standards: e.g. ISO 27001 for information security, ISO 42001 for overall AI governance, NIST AI RMF for risk measurement & tools.
5. Practical tools, governance, and processes The author does more than theory. There are discussions of impact assessments, risk matrices, audit / assurance, third-party oversight, monitoring for model drift / unanticipated behavior, documentation, and transparency. Some of the more compelling content is about how to do risk assessments early (before deployment), how to engage stakeholders, how to map out potential harms (both known risks and emergent/unknown ones), how governance bodies (steering committees, ethics boards) can play a role, how responsibility should be assigned, how controls should be tested. The book does point out real challenges: culture change, resource constraints, measurement difficulties, especially for ethical or fairness concerns. But it provides guidance on how to surmount or mitigate those.
6. What might be less strong / gaps While the book is very useful, there are areas where some readers might want more. For instance, in scaling these practices in organizations with very little AI maturity: the resource costs, how to bootstrap without overengineering. Also, while it references standards and regulations broadly, there may be less depth on certain jurisdictional regulatory regimes (e.g. EU AI Act in detail, or sector-specific requirements). Another area that is always hard—and the book is no exception—is anticipating novel risks: what about very advanced AI systems (e.g. generative models, large language models) or AI in uncontrolled environments? Some of the guidance is still high-level when it comes to edge-cases or worst-case scenarios. But this is a natural trade-off given the speed of AI advancement.
7. Future of AI & risk management: trends and implications Looking ahead, the book suggests that risk management in AI will become increasingly central as both regulatory pressure and societal expectations grow. Standards like ISO 42001 will be adopted more widely, possibly even made mandatory or incorporated into regulation. The idea of “certification” or attestation of compliance will gain traction. Also, the monitoring, auditing, and accountability functions will become more technically and institutionally mature: better tools for algorithmic transparency, bias measurement, model explainability, data provenance, and impact assessments. There’ll also be more demand for cross-organizational cooperation (e.g. supply chains and third-party models), for oversight of external models, for AI governance in ecosystems rather than isolated systems. Finally, there is an implication that organizations that don’t get serious about risk will pay—through regulation, loss of trust, or harm. So the future is of AI risk management moving from “nice-to-have” to “mission-critical.”
Overall, Managing AI Risk is a strong, timely guide. It bridges theory (standards, frameworks) and practice (governance, processes, tools) well. It makes the case that ISO 42001 is a useful centerpiece for any AI risk strategy, especially when combined with other standards. If you are planning or refining an AI strategy, building or implementing an AIMS, or anticipating future regulatory change, this book gives a solid and actionable foundation.
The role of the modern CISO has evolved far beyond technical oversight. While many entered the field expecting to focus solely on firewalls, frameworks, and fighting cyber threats, the reality is that today’s CISOs must operate as business leaders as much as security experts. Increasingly, the role demands skills that look surprisingly similar to sales.
This shift is driven by business dynamics. Buyers and partners are highly sensitive to security posture. A single breach or regulatory fine can derail deals and destroy trust. As a result, security is no longer just a cost center—it directly influences revenue, customer acquisition, and long-term business resilience.
CISOs now face a dual responsibility: maintaining deep technical credibility while also translating security into a business advantage. Boards and executives are asking not only, “Are we protected?” but also, “How does our security posture help us win business?” This requires CISOs to communicate clearly and persuasively about the commercial value of trust and compliance.
At the same time, budgets are tight and CISO compensation is under scrutiny. Justifying investment in security requires framing it in business terms—showing how it prevents losses, enables sales, and differentiates the company in a competitive market. Security is no longer seen as background infrastructure but as a factor that can make or break deals.
Despite this, many security professionals still resist the sales aspect of the job, seeing it as outside their domain. This resistance risks leaving them behind as the role changes. The reality is that security leadership now includes revenue protection and revenue generation, not just technical defense.
The future CISO will be defined by their ability to translate security into customer confidence and measurable business outcomes. Those who embrace this evolution will shape the next generation of leadership, while those who cling only to the technical side risk becoming sidelined.
Advice on AI’s impact on the CISO role: AI will accelerate this transformation. On the technical side, AI tools will automate many detection, response, and compliance tasks that once required hands-on oversight, reducing the weight of purely operational responsibilities. On the business side, AI will raise customer expectations for security, privacy, and ethical use of data. This means CISOs must increasingly act as “trust architects,” communicating how AI is governed and secured. The CISO who can blend technical authority with persuasive storytelling about AI risk and trust will not only safeguard the enterprise but also directly influence growth. In short, AI will make the CISO less of a firewall operator and more of a business strategist who sells trust.
This book positions itself not just as a technical guide but as a strategic roadmap for the future of cybersecurity leadership. It emphasizes that in today’s complex threat environment, CISOs must evolve beyond technical mastery and step into the role of business leaders who weave cybersecurity into the very fabric of organizational strategy.
The core message challenges the outdated view of CISOs as purely technical experts. Instead, it calls for a strategic shift toward business alignment, measurable risk management, and adoption of emerging technologies like AI and machine learning. This evolution reflects growing expectations from boards, executives, and regulators—expectations that CISOs must now meet with business fluency, not just technical insight.
The book goes further by offering actionable guidance, case studies, and real-world examples drawn from extensive experience across hundreds of security programs. It explores practical topics such as risk quantification, cyber insurance, and defining materiality, filling the gap left by more theory-heavy resources.
For aspiring CISOs, the book provides a clear path to transition from technical expertise to strategic leadership. For current CISOs, it delivers fresh insight into strengthening business acumen and boardroom credibility, enabling them to better drive value while protecting organizational assets.
My thought: This book’s strength lies in recognizing that the modern CISO role is no longer just about defending networks but about enabling business resilience and trust. By blending strategy with technical depth, it seems to prepare security leaders for the boardroom-level influence they now require. In an era where cybersecurity is a business risk, not just an IT issue, this perspective feels both timely and necessary.
AI isn’t just another tool—it’s a paradigm shift. CISOs must now integrate AI-driven analytics into real-time threat detection and incident response. These systems analyze massive volumes of data faster and surface patterns humans might miss.
2. New vulnerabilities from AI use
Deploying AI creates unique risks: biased outputs, prompt injection, data leakage, and compliance challenges across global jurisdictions. CISOs must treat models themselves as attack surfaces, ensuring robust governance.
3. AI amplifies offensive threats
Adversaries now weaponize AI to automate reconnaissance, craft tailored phishing lures or deepfakes, generate malicious code, and launch fast-moving credential‑stuffing campaigns.
4. Building an AI‑enabled cyber team
Moving beyond tool adoption, CISOs need to develop core data capabilities: quality pipelines, labeled datasets, and AI‑savvy talent. This includes threat‑hunting teams that grasp both AI defense and AI‑driven offense.
5. Core capabilities & controls
The playbook highlights foundational strategies:
Data governance (automated discovery and metadata tagging).
Zero trust and adaptive access controls down to file-system and AI pipelines.
AI-powered XDR and automated IR workflows to reduce dwell time.
6. Continuous testing & offensive security
CISOs must adopt offensive measures—AI pen testing, red‑teaming models, adversarial input testing, and ongoing bias audits. This mirrors traditional vulnerability management, now adapted for AI-specific threats.
7. Human + machine synergy
Ultimately, AI acts as a force multiplier—not a surrogate. Humans must oversee, interpret, understand model limitations, and apply context. A successful cyber‑AI strategy relies on continuous training and board engagement .
🧩 Feedback
Comprehensive: Excellent balance of offense, defense, data governance, and human oversight.
Actionable: Strong emphasis on building capabilities—not just buying tools—is a key differentiator.
Enhance with priorities: Highlighting fast-moving threats like prompt‑injection or autonomous AI agents could sharpen urgency.
Communications matter: Reminding CISOs to engage leadership with justifiable ROI and scenario planning ensures support and budget.
AI transforms the cybersecurity role—especially for CISOs—in several fundamental ways:
1. From Reactive to Predictive
Traditionally, security teams react to alerts and known threats. AI shifts this model by enabling predictive analytics. AI can detect anomalies, forecast potential attacks, and recommend actions before damage is done.
2. Augmented Decision-Making
AI enhances the CISO’s ability to make high-stakes decisions under pressure. With tools that summarize incidents, prioritize risks, and assess business impact, CISOs move from gut instinct to data-informed leadership.
3. Automation of Repetitive Tasks
AI automates tasks like log analysis, malware triage, alert correlation, and even generating incident reports. This allows security teams to focus on strategic, higher-value work, such as threat modeling or security architecture.
4. Expansion of Threat Surface Oversight
With AI deployed in business functions (e.g., chatbots, LLMs, automation platforms), the CISO must now secure AI models and pipelines themselves—treating them as critical assets subject to attack and misuse.
5. Offensive AI Readiness
Adversaries are using AI too—to craft phishing campaigns, generate polymorphic malware, or automate social engineering. The CISO’s role expands to understanding offensive AI tactics and defending against them in real time.
6. AI Governance Leadership
CISOs are being pulled into AI governance: setting policies around responsible AI use, bias detection, explainability, and model auditing. Security leadership now intersects with ethical AI oversight and compliance.
7. Cross-Functional Influence
Because AI touches every function—HR, legal, marketing, product—the CISO must collaborate across departments, ensuring security is baked into AI initiatives from the ground up.
Summary: AI transforms the CISO from a control enforcer into a strategic enabler who drives predictive defense, leads governance, secures machine intelligence, and shapes enterprise-wide digital resilience. It’s a shift from gatekeeping to guiding responsible, secure innovation.
1. Evolving Role of Cybersecurity Services Traditional cybersecurity engagements—such as vulnerability patching, audits, or one-off assessments—tend to be short-term and reactive, addressing immediate concerns without long-term risk reduction. In contrast, end-to-end cybersecurity programs offer sustained value by embedding security into an organization’s core operations and strategic planning. This shift transforms cybersecurity from a technical task into a vital business enabler.
2. Strategic Provider-Client Relationship Delivering lasting cybersecurity outcomes requires service providers to move beyond technical support and establish strong partnerships with organizational leadership. Providers that engage at the executive level evolve from being IT vendors to trusted advisors. This elevated role allows them to align security with business objectives, providing continuous support rather than piecemeal fixes.
3. Core Components of a Strategic Cybersecurity Program A comprehensive end-to-end program must address several key domains: risk assessment and management, strategic planning, compliance and governance, business continuity, security awareness, incident response, third-party risk management, and executive reporting. Each area works in concert to strengthen the organization’s overall security posture and resilience.
4. Risk Assessment & Management A strategic cybersecurity initiative begins with a thorough risk assessment, providing visibility into vulnerabilities and their business impact. A complete asset inventory is essential, and follow-up includes risk prioritization, mitigation planning, and adapting defenses to evolving threats like ransomware. Ongoing risk management ensures that controls remain effective as business conditions change.
5. Strategic Planning & Roadmaps Once risks are understood, the next step is strategic planning. Providers collaborate with clients to create a cybersecurity roadmap that aligns with business goals and compliance obligations. This roadmap includes near-, mid-, and long-term goals, backed by security policies and metrics that guide decision-making and keep efforts aligned with the company’s direction.
6. Compliance & Governance With rising regulatory scrutiny, organizations must align with standards such as NIST, ISO 27001, HIPAA, SOC 2, PCI-DSS, and GDPR. Security providers help identify which regulations apply, assess current compliance gaps, and implement sustainable practices to meet ongoing obligations. This area remains underserved and represents an opportunity for significant impact.
7. Business Continuity & Disaster Recovery Effective security programs not only prevent breaches but also ensure operational continuity. Business Continuity Planning (BCP) and Disaster Recovery (DR) encompass infrastructure backups, alternate operations, and crisis communication strategies. Providers play a key role in building and testing these capabilities, reinforcing their value as strategic advisors.
8. Human-Centric Security & Response Preparedness People remain a major risk vector, so training and awareness are critical. Providers offer education programs, phishing simulations, and workshops to cultivate a security-aware culture. Incident response readiness is also essential—providers develop playbooks, assign roles, and simulate breaches to ensure rapid and coordinated responses to real threats.
9. Executive-Level Communication & Reporting A hallmark of high-value cybersecurity services is the ability to translate technical risks into business language. Clear executive reporting connects cybersecurity activities to business outcomes, supporting board-level decision-making and budget justification. This capability is key for client retention and helps providers secure long-term engagements.
Feedback
This clearly outlines how cybersecurity must evolve from reactive technical support into a strategic business function. The focus on continuous oversight, executive engagement, and alignment with organizational priorities is especially relevant in today’s complex threat landscape. The structure is logical and well-grounded in vCISO best practices. However, it could benefit from sharper differentiation between foundational services (like asset inventories) and advanced advisory (like executive communication). Emphasizing measurable outcomes—such as reduced incidents, improved audit results, or enhanced resilience—would also strengthen the business case. Overall, it’s a strong framework for any provider building or refining an end-to-end security program.
Aaron McCray, Field CISO at CDW, discusses the evolving role of the Chief Information Security Officer (CISO) in the age of artificial intelligence (AI). He emphasizes that CISOs are transitioning from traditional cybersecurity roles to strategic advisors who guide enterprise-wide AI governance and risk management. This shift, termed “CISO 3.0,” involves aligning AI initiatives with business objectives and compliance requirements.
McCray highlights the challenges of integrating AI-driven security tools, particularly regarding visibility, explainability, and false positives. He notes that while AI can enhance security operations, it also introduces complexities, such as the need for transparency in AI decision-making processes and the risk of overwhelming security teams with irrelevant alerts. Ensuring that AI tools integrate seamlessly with existing infrastructure is also a significant concern.
The article underscores the necessity for CISOs and their teams to develop new skill sets, including proficiency in data science and machine learning. McCray points out that understanding how AI models are trained and the data they rely on is crucial for managing associated risks. Adaptive learning platforms that simulate real-world scenarios are mentioned as effective tools for closing the skills gap.
When evaluating third-party AI tools, McCray advises CISOs to prioritize accountability and transparency. He warns against tools that lack clear documentation or fail to provide insights into their decision-making processes. Red flags include opaque algorithms and vendors unwilling to disclose their AI models’ inner workings.
In conclusion, McCray emphasizes that as AI becomes increasingly embedded across business functions, CISOs must lead the charge in establishing robust governance frameworks. This involves not only implementing effective security measures but also fostering a culture of continuous learning and adaptability within their organizations.
Feedback
The article effectively captures the transformative impact of AI on the CISO role, highlighting the shift from technical oversight to strategic leadership. This perspective aligns with the broader industry trend of integrating cybersecurity considerations into overall business strategy.
By addressing the practical challenges of AI integration, such as explainability and infrastructure compatibility, the article provides valuable insights for organizations navigating the complexities of modern cybersecurity landscapes. These considerations are critical for maintaining trust in AI systems and ensuring their effective deployment.
The emphasis on developing new skill sets underscores the dynamic nature of cybersecurity roles in the AI era. Encouraging continuous learning and adaptability is essential for organizations to stay ahead of evolving threats and technological advancements.
The cautionary advice regarding third-party AI tools serves as a timely reminder of the importance of due diligence in vendor selection. Transparency and accountability are paramount in building secure and trustworthy AI systems.
The article could further benefit from exploring specific case studies or examples of organizations successfully implementing AI governance frameworks. Such insights would provide practical guidance and illustrate the real-world application of the concepts discussed.
Overall, the article offers a comprehensive overview of the evolving responsibilities of CISOs in the context of AI integration. It serves as a valuable resource for cybersecurity professionals seeking to navigate the challenges and opportunities presented by AI technologies.
AI is rapidly transforming systems, workflows, and even adversary tactics, regardless of whether our frameworks are ready. It isn’t bound by tradition and won’t wait for governance to catch up…When AI evaluates risks, it may enhance the speed and depth of risk management but only when combined with human oversight, governance frameworks, and ethical safeguards.
A new ISO standard, ISO 42005 provides organizations a structured, actionable pathway to assess and document AI risks, benefits, and alignment with global compliance frameworks.
As cyber threats become more frequent and complex, many small and medium-sized businesses (SMBs) find themselves unable to afford a full-time Chief Information Security Officer (CISO). Enter the Virtual CISO (vCISO)—a flexible, cost-effective solution that’s rapidly gaining traction. For Managed Service Providers (MSPs) and Managed Security Service Providers (MSSPs), offering vCISO services isn’t just a smart move—it’s a major business opportunity.
Why vCISO Services Are Gaining Ground
With cybersecurity becoming a top priority across industries, demand for expert guidance is soaring. Many MSPs have started offering partial vCISO services—helping with compliance or risk assessments. But those who provide comprehensive vCISO offerings, including security strategy, policy development, board-level reporting, and incident management, are reaping higher revenues and deeper client trust.
The CISO’s Critical Role
A traditional CISO wears many hats: managing cyber risk, setting security strategies, ensuring compliance, and overseeing incident response and vendor risk. They also liaise with leadership, align IT with business goals, and handle regulatory requirements like GDPR and HIPAA. With experienced CISOs in short supply and expensive to hire, vCISOs are filling the gap—especially for SMBs.
Why MSPs Are Perfectly Positioned
Most SMBs don’t have a dedicated internal cybersecurity leader. That’s where MSPs and MSSPs come in. Offering vCISO services allows them to tap into recurring revenue streams, enter new markets, and deepen client relationships. By going beyond reactive services and offering proactive, executive-level security guidance, MSPs can differentiate themselves in a crowded field.
Delivering Full vCISO Services: What It Takes
To truly deliver on the vCISO promise, providers must cover end-to-end services—from risk assessments and strategy setting to business continuity planning and compliance. A solid starting point is a thorough risk assessment that informs a strategic cybersecurity roadmap aligned with business priorities and budget constraints.
It’s About Action, Not Just Advice
A vCISO isn’t just a strategist—they’re also responsible for guiding implementation. This includes deploying controls like MFA and EDR tools, conducting vulnerability scans, and ensuring backups and disaster recovery plans are robust. Data protection, archiving, and secure disposal are also critical to safeguarding digital assets.
Educating and Enabling Everyone
Cybersecurity is a team sport. That’s why training and awareness programs are key vCISO responsibilities. From employee phishing simulations to executive-level briefings, vCISOs ensure everyone understands their role in protecting the business. Meanwhile, increasing compliance demands—from clients and regulators alike—make vCISO support in this area invaluable.
Planning for the Worst: Incident & Vendor Risk Management
Every business will face a cyber incident eventually. A strong incident response plan is essential, as is regular practice via tabletop exercises. Additionally, third-party vendors represent growing attack vectors. vCISOs are tasked with managing this risk, ensuring vendors follow strict access and authentication protocols.
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With the rise of automation and the widespread emergence of agentic AI, are you prepared to navigate this disruption responsibly? Providing all these services can be daunting—especially for smaller providers. That’s where platforms like Cynomi come in. By automating time-consuming tasks like assessments, policy creation, and compliance mapping, Cynomi enables MSPs and MSSPs to scale their vCISO services without hiring more staff. It’s a game-changer for those ready to go all-in on vCISO.
Conclusion: Delivering full vCISO services isn’t easy—but the payoff is big. With the right approach and tools, MSPs and MSSPs can offer high-value, scalable cybersecurity leadership to clients who desperately need it. For those ready to lead the charge, the time to act is now.
​The RSA Conference Executive Security Action Forum (ESAF) report, How Top CISOs Are Transforming Third-Party Risk Management, presents insights from Fortune 1000 Chief Information Security Officers (CISOs) on evolving strategies to manage third-party cyber risks. The report underscores the inadequacy of traditional risk management approaches and highlights innovative practices adopted by leading organizations.​
1. Escalating Third-Party Risks
The report begins by emphasizing the increasing threat posed by third-party relationships. A survey revealed that 87% of Fortune 1000 companies experienced significant cyber incidents originating from third parties within a year. This statistic underscores the urgency for organizations to reassess their third-party risk management strategies.​
2. Limitations of Traditional Approaches
Traditional methods, such as self-assessment questionnaires and cybersecurity ratings, are criticized for their ineffectiveness. These approaches often lack context, fail to reduce actual risk, and do not foster resilience against cyber threats. The report advocates for a shift towards more proactive and context-aware strategies.​
3. Innovative Strategies by Leading CISOs
In response to these challenges, top CISOs are implementing bold new approaches. These include establishing prioritized security requirements, setting clear deadlines for control implementations, incorporating enforcement clauses in contracts, and assisting third parties in acquiring necessary security technologies and services. Such measures aim to enhance the overall security posture of both the organization and its partners.​
4. Emphasizing Business Leadership and Resilience
The report highlights the importance of involving business leaders in managing cyber risks. By integrating cybersecurity considerations into business decisions and fostering a culture of resilience, organizations can better prepare for and respond to third-party incidents. This holistic approach ensures that cybersecurity is not siloed but is a shared responsibility across the enterprise.​
5. Case Studies Demonstrating Effective Practices
Six cross-sector case studies are presented, showcasing how organizations in industries like defense, healthcare, insurance, manufacturing, and technology are successfully transforming their third-party risk management. These real-world examples provide valuable insights into the practical application of the recommended strategies and their positive outcomes.​
6. The Role of Technology and Security Vendors
The report calls upon technology and security vendors to play a pivotal role in minimizing complexities and reducing costs associated with third-party risk management. By collaborating with organizations, vendors can develop solutions that are more aligned with the evolving cybersecurity landscape and the specific needs of businesses.​
7. Industry Collaboration for Systemic Change
Recognizing that third-party risk is a widespread issue, the report advocates for industry-wide collaboration. Establishing common standards, sharing best practices, and engaging in joint initiatives can lead to systemic changes that enhance the security of the broader ecosystem. Such collective efforts are essential for addressing the complexities of modern cyber threats.​
8. Moving Forward with Proactive Measures
The ESAF report concludes by encouraging organizations to adopt proactive measures in managing third-party risks. By moving beyond traditional methods and embracing innovative, collaborative, and resilient strategies, businesses can better safeguard themselves against the evolving threat landscape. The insights provided serve as a roadmap for organizations aiming to strengthen their cybersecurity frameworks in partnership with their third parties.​
Small business owners often prioritize growth and customer service, inadvertently overlooking cybersecurity. However, cyber threats are indifferent to company size, frequently targeting smaller enterprises due to their comparatively weaker security measures. Engaging a Virtual Chief Information Security Officer (vCISO) can provide the necessary expertise to bolster defenses and protect critical assets. ​
While many small businesses view cybersecurity merely as a compliance requirement, this perspective is limited. A vCISO offers more than just ensuring adherence to regulations; they proactively work to prevent breaches that could disrupt operations, erode customer trust, and incur substantial recovery costs. ​
Contrary to the belief that cybercriminals focus solely on large corporations, small businesses are often prime targets due to their perceived vulnerabilities. Attackers employ automated tools to identify and exploit weaknesses, making robust security measures essential for businesses of all sizes.
The financial burden of hiring a full-time Chief Information Security Officer can be prohibitive for many small businesses. A vCISO provides executive-level cybersecurity guidance at a fraction of the cost, granting access to seasoned professionals without the expense of a full-time position.
Relying solely on IT generalists or managed service providers for security may not suffice. A vCISO brings dedicated strategic insight, aligning security initiatives with business objectives and facilitating informed decision-making. For instance, during a cloud migration, a vCISO would address critical security considerations such as access control, data residency, vendor risks, and breach response plans.
In the event of a cybersecurity incident, having a well-practiced response plan is crucial. A vCISO ensures preparedness, enabling swift and effective action to mitigate damage, control costs, and preserve the company’s reputation. Their tailored approach considers the unique needs and risk tolerance of the business, ensuring appropriate investment in necessary protections without overspending on superfluous tools.
Why Small Businesses may Need vCISO Services
1. Targeted by Cybercriminals Small businesses often believe they fly under the radar, but cybercriminals see them as easy prey. With limited security budgets and lack of specialized personnel, they are prime targets for ransomware, phishing, and other attacks. A vCISO helps shore up defenses before attackers strike.
2. Cost-Effective Expertise Hiring a full-time Chief Information Security Officer (CISO) is often financially out of reach for small businesses. A vCISO offers the same strategic insight and leadership on a part-time or fractional basis—delivering enterprise-level expertise without the enterprise-level price tag.
3. Regulatory Compliance From HIPAA and PCI-DSS to GDPR and state-level data protection laws, compliance is critical. A vCISO ensures the organization meets necessary regulatory requirements, helping avoid fines, legal trouble, and loss of customer trust.
4. Risk-Based Security Strategy Not every threat deserves the same level of attention. A vCISO helps identify and prioritize risks based on the business’s unique environment, making sure resources are directed toward the most impactful protections.
5. Preparedness for Incidents Cyber incidents are not a matter of “if” but “when.” A vCISO creates and tests incident response plans so the business is ready to react swiftly. This minimizes damage, downtime, and potential losses.
6. Third-Party & Cloud Security Oversight With growing reliance on SaaS applications and third-party vendors, managing external risk is crucial. A vCISO provides guidance on secure vendor selection, cloud architecture, and ongoing monitoring to ensure strong data protection.
For small and mid-sized businesses, the stakes are even higher. Without a structured and operational security program in place, they may stand little chance of effectively managing their risks.
DISC InfoSec offer free initial high level assessment – Based on your needs DISC InfoSec offer ongoing compliance management or vCISO retainer.
