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There are several key questions to ask in evaluating how well the content and associated documentation is managed for your use cases (like policy management). Is your change management program well designed? How would you demonstrate that to a stakeholder or outside party? Is the program applied earnestly / in good faith? How do you report on the results of the work done? The Archer Document Governance solution provides tools to manage your policy management’s critical documentation and help strengthen your program around these questions. 1: Key elements to a well-designed program: control and collaboration Policy programs are dynamic, with ongoing updates needed to keep policies and procedures current. A well-designed program will have both the agility and the control needed for ongoing change management. Archer Document Governance can help provide the agility and control you need through: Enabling simultaneous collaboration on documentation changes – no need to lose time emailing versions back and forth or risking lock-out of a collaborator from a shared network file Making teams aware of changes in the approval chain for the documentation they manage Providing a real-time view to where a document may be delayed in the change management process Documenting redlined changes for every published version Enabling quick response to audit inquiries 2. Enabling a strong culture of discipline: reinforcing the positive, removing the barriers In tandem with your leadership communications and targeted performance indicators, the right tool can help simplify and demonstrate diligent application of your policy management program. Archer Document Governance can support your culture of execution through how you manage the creation, governance, and publication of your program’s mission-critical documentation. Document Governance helps by: Simplifying through standardizing the creation, management, and distribution of policies and procedures Configuring your governance workflows and providing transparency into the process Accelerating the review and sign-off of documentation changes Serving as a single system of record for your documentation 3. Demonstrating program results Monitoring and reporting on the results of your policy management program takes both quantitative and qualitative measurements. Archer Document Governance can help you track and demonstrate program results through: Facilitating internal and external audits, providing detailed change logs, and redline comparisons for evidence across published versions Detailed management reporting, showing everything from change management cycle times to analysis where approvals get delayed by document type and team Contact us to speak to an Archer expert about how Archer Document Governance can support your program goals.

Organizations across the world continue to deal with the significant impacts of a global financial crisis, a pandemic, supply chain disruptions, increasing cyberattacks and more. While many have relied on traditional business recovery to withstand these and other factors, this confluence of threats has shown that disruption can be prolonged and evolving. The paradigm for has shifted from ‘if’ disruption will occur to ‘when’ it will occur. Traditional approaches to recovering after disruption are vital -- but they are no longer enough. Organizations need to ask: Are we proactively dealing with threats and risks? What do we need to do to build resilience? How do we know when we’re resilient enough? There are no quick or easy answers, but there are important steps your organization must take. Focus on your highest priorities. The organization should be building resilience into what enables them to achieve their strategic and operating objectives. This includes producing and offering their products and services to end customers, complying with regulations, satisfying investors, etc. The business impact analyses (BIA) is the best way to do that. However, traditional BIA approaches are often focused on the organization’s internal business processes, which is only part of the dependencies or value chain that produces the end product or service. A question to ask is, will this traditional approach help build resilience into all that is needed to produce that that product and achieve our strategic and operating objectives? A better focus for the BIA might be to identify the organization’s most important product and services offered to customers, and to make that supporting value chain, including internal business processes, systems, people, facilities, and third parties resilient. Identify risks and threats that could impact your organization and the right mix of mitigation and response to reduce the impacts. Half of the equation to building a resilient organization is being prepared for what may come. The first half is identifying the threats (known and unknown) and mitigating the risks they pose to your organization. This is done by identifying likely and plausible threats and scenarios that could impact your organization, assessing their risk, then implementing the best mix of preventive and reactive measures to mitigate the risk to within your organization’s risk tolerance. Once your measures are in place a vital step is to test them to determine how well they actually work to reduce the residual impacts to your organization. Measure and monitor your progress in building resilience. The question mentioned at the beginning of this blog - How do we know when we’re resilient enough – is an important one. I’m not sure an organization can be “too resilient” but I do know an organization can be not resilient enough. The answer only comes once you have set goals appropriate for your organization relative to its resilience and have metrics in place that allow you to measure and monitor status and progress. Examples include quantitative and qualitative impact tolerances, recovery time objectives, recovery point objectives, and residual risk compared to your risk appetite. These goals must also be aligned to your business goals. Once these resilience goals are set, it’s vital to test your capabilities, evaluate your responses in real situations, address gaps identified along the way, and continue to measure and improve. Interested in learning more? Register for our March 1 at 2:00pm Eastern webinar, How to Build Business Resilience Beyond Recovery , and check out Archer Business Resiliency .

Can your organization respond to a major disruption without incurring losses or other negative impacts? Unfortunately, Gartner reports that only 12% of organizations are able to do so. With today’s evolving threats of geopolitical events, economic downturns, supply chain disruptions, pandemics, and complex technology-related issues, it is crucial for organizations to become resilient. A resilient business is one that is able to quickly respond to, and recover from, these types of events while minimizing the impact on the business and its stakeholders. Some key components of business resiliency include: Risk management: Identifying potential risks and taking proactive steps to reduce their impact on the business. Business prioritization: Focusing efforts to make the most important business services and supporting processes, people, and technologies resilient. Continuity planning: Developing plans and processes to ensure that critical business functions can continue in the event of a disruption. Crisis management: Having a clear and structured approach to managing crises, including communication plans and decision-making frameworks. Flexibility and adaptability: Being able to quickly adapt to changing circumstances and make decisions based on new information. A resilient business is one that is able to quickly respond to and recover from disruptive events while minimizing impact on the business and its stakeholders. But building business resilience goes beyond responding to risks and disruptions. You need to create a sustainable organization that can withstand unforeseen challenges and emerge stronger and more prepared. Archer invites you to register for our upcoming webinar on June 22, 2:00 pm EDT, Best Practices for Reducing Risk and Building Business Resilience , to: Discover the top risks your organization should be planning for in today's complex business landscape. Learn about best practices for building business resiliency, from risk identification and evaluation to implementing resilience measures. Gain insights into creating a resilient organization that can withstand unforeseen challenges and emerge stronger and more prepared. For more information about how Archer can help your organization become resilient, check out Archer Business Resiliency .

There is much conjecture, guidance, and varied views about what most executives’ role should be related to the approach and direction of risk management in their organization. Executives play a critical role in risk management and need a comprehensive understanding of various aspects of risk management so they can make informed decisions that protect the company's interests and ensure its long-term sustainability. Here are some key things they should know: Risk Types: Executives should be familiar with the types of risks their organization faces. These can include financial risks, operational risks, strategic risks, compliance risks, and reputational risks. This is important so the executive has the context or risks the organization has to deal with. Recognize that external factors, such as economic conditions, geopolitical events, and natural disasters, can pose significant risks to the organization. Stay informed about these external risks. Risk Appetite and Tolerance : They need to define and communicate the organization's risk appetite and tolerance. This sets the boundaries for risk-taking and guides decision-making at all levels of the company. Risk Mitigation Strategies : Be aware of the various strategies for mitigating risks, such as risk avoidance, risk reduction, risk transfer (e.g., insurance), and risk acceptance. Executives should be involved in setting risk mitigation strategies and ensuring they align with organizational and strategic objectives. Crisis Management : Have a clear understanding of the organization's crisis management plan and their role in it. This includes knowing when to activate the plan and how to communicate during a crisis. Cybersecurity Risks : In this digital age, cybersecurity is a significant concern – one of the highest. Executives should be knowledgeable about potential cybersecurity threats and measures the organization has in place to protect sensitive data. Insurance and Risk Transfer : Understand the organization's insurance coverage, what it covers, and what it doesn't. Know when to transfer risk to insurers and when to self-insure. Monitoring and Reporting : Be aware of the key risk indicators (KRIs) that help track and manage risks and how they relate to key performance indicators (KPIs). Regularly review these metrics to stay informed. Risk Culture : Promote a risk-aware culture within the organization. This includes encouraging employees at all levels to identify and report risks, as well as ensuring that risk management is integrated into decision-making processes. Be involved in resource allocation decisions to ensure that adequate resources are dedicated to risk management efforts. Stakeholder Communication : Effectively communicate with stakeholders, including shareholders, employees, customers, and the board of directors, about the organization's approach to risk management and the steps taken to address risks. Continuous Improvement : Emphasize the importance of continuous improvement in the risk management process. Regularly review and update risk management policies and procedures to adapt to changing circumstances. Executives must work closely with risk management teams and the board of directors to ensure that risk management is an integral part of the organization's strategic planning and decision-making processes. It is essential for safeguarding the organization's long-term success and reputation.

Where were you during the unprecedented global IT outage of July 2024? If you were traveling by air — or planning to — you experienced firsthand the far-reaching impacts of the outage felt across the globe. Sectors like healthcare and banking were also significantly affected, leading to a halt in non-critical operations. Insurers are currently calculating the financial ramifications, estimating around $5 billion in direct losses for Fortune 500 companies alone. This outage serves as a stark reminder of the critical importance of robust enterprise risk management and offers valuable lessons to fortify your organization’s defenses against future disruptions. Recognize your reliance on external providers The outage underscored how heavily businesses depend on external providers for vital services, particularly in cybersecurity. Many organizations found themselves exposed to potential cyber threats, highlighting the critical need for comprehensive contingency plans and redundant systems to mitigate the impacts of service disruptions. This incident emphasized the risks associated with outsourcing essential functions to third-party vendors, which necessitates thorough assessments of vendor reliability, security practices, and their contingency plans.   Understand the potential impact of disruptions on your operations During the outage, many businesses faced significant challenges, including disrupted operations and compromised security postures. This illustrated why organizations must anticipate operational impacts and develop strategic alternatives to ensure business continuity during such disruptions.   Effective business continuity planning should encompass comprehensive strategies that maintain operations amid unforeseen challenges — from identifying critical business functions to establishing clear communication channels and maintaining escalation protocols for prompt and efficient issue resolution. Integrating third-party risk considerations into these plans is equally essential, which involves identifying backup vendors and ensuring seamless communication.   Ensure continuity with proactive planning Organizations that had well-prepared contingency plans, including alternative solutions or backup measures, fared significantly better during the outage. This experience emphasizes the value of proactive risk assessment and resilience planning for maintaining operational stability in the face of unexpected service interruptions. Resilience planning should involve clearly identifying critical business functions, establishing effective communication channels, and implementing robust escalation protocols to address issues promptly.   Undoubtedly, this outage exemplifies the interconnected nature of modern business operations and the vital role of risk management in ensuring resilience. Risk management professionals must take proactive steps to manage third-party risks, develop comprehensive business continuity plans, and foster resilience strategies that minimize the impact of service disruptions. By doing so, you can better protect and sustain your operations in the face of unforeseen challenges. Learn how Archer can assist you in building operational resilience and optimizing vendor risk management for your organization. Contact us or request a demo today.

AI will most likely win the buzzword award for 2023. ChatGPT and Google Bard have opened the eyes of millions to the potential benefits of AI. Additionally, AI introduces opportunities for organizations to exponentially increase efficiency and cut costs; unfortunately, AI also introduces new risks to these same organizations. In March 2023, over 30,000 individuals, including well known technology leaders, signed an open letter asking organizations to pause their work on advancing AI beyond the capabilities of ChatGPT-4 for at least six months. In their letter, they called for policy makers and AI developers to work together to accelerate the development of strong AI governance. They claimed governance should include the oversight and tracking of high-risk AI systems, research of watermarking technologies to distinguish reality from fiction, robust auditing systems in place, and to enforce risk management of AI-specific risks. While generative AI has caused quite a stir today, regulations around AI have been in the works for quite some time. The European Union (EU), per usual, arrived first at the scene with their wide-sweeping AI Act. Penalties under this law could cost organizations up to 30M euros or 6% of their revenue for non-compliance. Regulators over the financial sectors in the US and the UK have also declared that AI models need the same level of attention and rigor as any other model undergoing model risk management. In addition, the White House has released an AI Bill of Rights, specifically intended to help policy makers draft effective AI regulations, hinting that more regulations are coming to the AI space. Why AI Governance is Needed In short, the purpose of AI governance is to avoid and mitigate harm by building trustworthy AI. Organizations serious about AI governance should consider taking a “do no harm” oath regarding AI. When AI is used to make decisions that affect humans, harm may befall your customers, employees, community, or society. AI governance needs to address the potential impacts and harm to groups during the entire lifecycle of AI. Trustworthy AI has different definitions based on who you ask, but most have the same general premise. The EU AI Act defines trustworthy AI as “legally compliant, technically robust, and ethically sound.” The National Institute of Technology and Standards (NIST) outlines characteristics of trustworthy AI in the AI Risk Management Framework (AI RMF), such as valid and reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy-enhanced, and fair – with harmful bias managed. While we’re speaking of NIST, Archer customers should check out the Archer NIST AI Risk Management Framework app-pack on the Archer Exchange. It enables you to utilize the NIST AI Risk Management Framework to assess your AI implementations and determine the posture of your current AI implementation through a comprehensive risk assessment. It helps you design and implement effective risk mitigation strategies to address the gaps from the current implementation to the target implementation. The idea is that building and using trustworthy AI reduces harm. That’s what we are striving for when instituting AI Governance. How to Govern AI at Your Organization If you have been in risk management for a while, you can guess what general steps are required. At a high level, a general framework of AI governance would include identification and documentation of your AI systems, risk analysis and evaluation, implementation and testing of controls, and ongoing monitoring. Let’s break these down. #1 Identification To start managing AI systems, you have to know what AI systems you are using. NIST and EU AI Act provide good definitions of AI. Basically, any system using machine learning, logic-based, knowledge-based, or statistical approaches are considered to be AI. That covers a lot. And that is much more than just ChatGPT. When you document your AI systems, it’s critical you collect and document specific information. Important details include: Context – the intended purpose, benefits, norms and expectations, people involved, settings in which it’s deployed, goals, instructions on use, etc. Development details – methods and steps used to develop the AI system, key design choices, system architecture, data requirements, validation and testing information, etc. Monitoring information – the incident management process, key performance indicators, review cycles, etc. Risks and impacts – identified risks, how risks are managed, potential impacts to consumers, employees, society, communities, organizations, etc. Change management – historical log of changes to the AI system For more information, review the “map” categories in the NIST AI RMF, as well as the EU AI Act section on technical documentation and summary data sheet. #2 Risk Assessment The purpose of assessing the risk of your AI systems is to understand the potential harm it could cause and to know the level of controls you should apply. Typical information system risk assessments prioritize systems based on the data classification housed and processed within the system, as well as the functional importance of the system to the organization. This same thought process applies for AI systems, but organizations should also take into consideration the usage of the system as well. The EU AI Act for example outright bans certain uses of AI, or AI systems that cause specific impacts. Any systems that might exploit vulnerable groups or violates rights in any way are prohibited in the market. Using AI to socially score an individual or perform real-time biometric identification in public spaces is also prohibited. High risk AI systems might include systems that assist with education, like determining which students to admit to your school, which ones get into certain programs, etc. Any system used for hiring or firing would be considered high risk. Systems that determine who gets access to essential services, like determining your future credit score, would be considered high risk. AI systems that don’t make predictions or decisions are generally less risky. For more information, review the NIST AI RMF “Measure” categories, the EU AI Act on risk levels, the NIST Risk Management Framework, or regulations on Model Risk. #3 Implement and Assess Controls It is recommended to put in place strong controls at every stage of the AI lifecycle. This includes stages like design, development, evaluation and testing, deployment, operation, and eventual retirement. Generally, controls should be put in place to respond to and manage identified risks during your risk assessments. The objective is to maximize the benefits of AI, while minimizing the negative impacts. Examples of controls include, but are not limited to: Drafting policies that cover AI values and governance Conducting ethical assessments Keeping up-to-date technical documentation Enforcing data governance Continuously identifying and managing risks and impacts Conducting model reviews, validation, and performance monitoring Creating clear deployment strategies Implementing strong change management Setting clear decommission strategies for AI systems NIST recommends implementing and testing these types of controls based on the risk level of your AI systems. Under the EU AI Act, high-risk AI systems must undergo a conformity assessment to prove that their system has conformed to the highest standard of controls. This conformity assessment covers topics as shown above and more. Without a conformity assessment, you cannot deploy your AI system in the EU market. It’s expected that the US will have similar requirements in future legislation. #4 Ongoing Monitoring Once the risk analysis, evaluation, and control selection has been completed, organizations should continuously monitor their AI systems in production. Ongoing monitoring includes activities like control reassessment, regular reviews, incident tracking and management, and risk identification. Organizations should be proactive in reporting incidents to the proper stakeholders, as there has been greater emphasis on incident disclosure requirements. Trust that it’s better to be ahead of the curve in this space than behind. Organizations should be tracking their own incidents and managing them in an effective way. When logging and reporting incidents, organizations should track things such as the incident summary, reporter, source system, dates of occurrence, impacts of the incident, and the affected stakeholders. These incidents will need to be shared both internally and externally in many cases, so organizations should plan now on their communication strategy. Conclusion Risk managers can leverage current frameworks in place to help govern AI, but will need to adapt to the unique challenges presented by AI. By identifying AI systems, prioritizing them based on risk, applying controls, and monitoring their systems, organizations can build and use more trustworthy AI and avoid negative impacts and harm. Teams working to manage risks posed from AI will also need to be very agile in the rapidly developing regulatory space. For example, the current version of the NIST AI Framework, most model-related regulations, and even the EU AI Act were written to help mitigate risks from traditional AI, not generative AI (GAI). GAI presents its own unique challenges and risks. While these regulations and frameworks have lots of overlap, organizations that don’t adapt to these new AI technologies expose themselves to very large risks. Risk teams need to be looking ahead at what is to come and start their efforts now to institute proper AI governance.

The Archer Summit 2025 agenda is live—and it’s filled with opportunities to learn from industry leaders, connect with peers, and strengthen your organization’s approach to risk and resilience. Taking place September 15–18 in Chicago, Archer Summit brings together hundreds of professionals from around the world who are driving innovation in risk management, compliance, and resilience. Whether you're new to Archer® or looking to push the boundaries of what’s possible, the agenda offers something for every attendee. Designed Around Real-World Impact More than half of this year’s sessions are led by Archer customers. These are practical, experience-driven conversations from organizations navigating the same challenges you’re facing — and finding success. Speakers include: ·  Amazon , sharing how they developed a resilient, enterprise-wide response strategy across their global sites. · ZS Associates and EY , offering an outline for operationalizing ESG goals with Archer. ·  Nationwide , diving into how they built a flexible, enterprise-wide issues management process. · Risk and compliance leaders from BECU, TD Bank, Mass General Brigham, Corebridge, Quest Diagnostics, CVS, and many more. Sessions You Won’t Want to Miss This year’s program offers more than 60 breakout sessions, learning labs, and product showcases. Every session is designed to deliver real, applicable value you can bring back to your organization: Product innovation sessions featuring new Archer products and upcoming AI capabilities. Customer success stories that span third-party risk, business continuity, information security, ESG, audit, and beyond. Technical deep dives into topics like access control, dashboard design, API integrations, and cloud migration. Hands-on labs and workshops, including a complimentary Archer Associate Certification exam session (pre-registration required) and a Blueprint Workshop for implementing Archer Evolv™ within your organization (add-on to your registration). Peer panels focused on regulatory shifts, GRC challenges, and how teams are adapting to rising board expectations. Beyond the Breakouts Beyond the sessions, Archer Summit is your chance to connect with peers, talk strategy with Archer experts, and enjoy all the energy of downtown Chicago. From morning wellness sessions to evening networking events, we’ve built space into the agenda to recharge and build relationships. Highlights include: The Archer Summit Welcome Reception on opening night Our “Taste of Chicago” dine around at some of Chicago’s best restaurants The high-energy Archer After-Hours party A closing keynote and customer appreciation celebration Explore the full agenda, build your schedule, and get ready to experience Archer Summit 2025 in Chicago. View the Agenda Register now

Despite rapid technological advancements across nearly every sector, risk management information systems (RMIS) have seen little to no meaningful innovation in over a decade. Many organizations still rely on outdated systems, manual processes, and fragmented data to navigate increasingly complex risk challenges. That needs to change. Risk is more complex than ever Today, businesses face a growing web of risks that are more unpredictable and interconnected than ever before. The challenges are relentless, from a surge in claims and geopolitical instability to cyber threats, regulatory shifts, supply chain disruptions, climate-related disasters, and economic volatility. Traditional RMIS tools, designed for simpler times, are ill-equipped to handle evolving risks. Relying on outdated technology is like navigating a storm with a broken compass — it leaves your organization exposed and unable to respond effectively. RMIS solutions are stale—and in dire need of change For years, companies have been locked into legacy systems that fail to harness modern technological capabilities. Many RMIS platforms lack real-time data processing, predictive analytics, and seamless integration with other enterprise systems. This results in data silos, slow decision-making, and missed opportunities to mitigate risk. Furthermore, manual processes often dominate risk management workflows. Risk teams spend valuable time compiling reports, tracking incidents, and analyzing fragmented data rather than focusing on strategic decision-making. Without innovation, businesses remain vulnerable and reactive. It’s time for a shift. Fresh thinking and the adoption of modern, AI-powered solutions can bring RMIS into the digital age. AI and data-driven analytics: the future of RMIS Artificial intelligence (AI) and advanced data analytics are revolutionizing industries worldwide. In risk management, these technologies provide organizations with the tools to anticipate threats, respond swiftly, and make data-backed decisions. Next-generation RMIS platforms leverage AI to transform the way businesses manage risk by enabling: Real-time risk monitoring:  AI continuously scans global events, regulatory updates, and emerging threats, delivering instant alerts so organizations can respond proactively. Predictive analytics:  By analyzing historical data and identifying patterns, AI-driven systems can forecast potential financial, operational, or reputational risks. Automated compliance management: Regulatory tracking becomes streamlined with automated updates and compliance checks, reducing human error and ensuring adherence to evolving regulations. Unified risk visibility:  Advanced RMIS platforms break down data silos, offering a comprehensive view of risks across the enterprise, supporting better collaboration and informed decision-making. Imagine a system that not only flags a developing supply chain disruption but also models its potential financial impact and suggests mitigation strategies. That’s the power of AI-driven RMIS. Embracing the future of risk management The future of risk management is not just about keeping pace with emerging threats—it’s about gaining a strategic advantage. Organizations that adopt AI-powered RMIS solutions can reduce costs, enhance operational efficiency, and protect their reputation. It’s time to break free from outdated systems and embrace a data-driven, proactive approach to managing risk. Interested in learning more? Download our whitepaper, "Next-Generation RMIS: Revolutionizing Risk Management" ,  to explore how modern RMIS solutions can transform your organization’s approach to risk management. Want to see Archer RMIS AI in action? Visit us in Booth #1375 at RISKWORLD, May 3-5 in Chicago to discover how next-generation RMIS can strengthen your risk management strategy. Register now!

Many companies still treat sustainability as a reporting exercise. Metrics are collected, frameworks are checked, and disclosures are filed. But if your organization stops there, it's missing the point. Sustainability is no longer a side initiative. It's a strategic capability. Environmental, Social, and Governance (ESG) efforts are now directly tied to business resilience, brand reputation, investor confidence, and risk exposure. In IDC’s 2025 MarketScape for Worldwide Sustainability Management Platforms , nearly 30% of organizations identified "strategic advantage" as a top driver behind their ESG technology investments. These priorities send a clear message: organizations want more than dashboards - they want tools that support action.   Action starts with better decision-making. That requires data you can trust and systems that turn risk indicators into meaningful outcomes. IDC’s report highlights that many sustainability platforms still fall short. Some can't aggregate data across the organization. Others stop at reporting, without helping leaders take action when something goes wrong.   What Today’s ESG Platforms Need Top-performing platforms differentiate themselves by incorporating ESG considerations within their comprehensive risk management strategies. For example, Archer was recognized in the IDC MarketScape  for helping organizations detect issues early and connect ESG metrics to concrete responses. If a carbon emissions target is exceeded, the platform can raise an alert, assign responsibility, and launch a resolution workflow. This kind of functionality turns ESG from a static scorecard into a dynamic tool for managing risk in real time.   Another critical capability is tying ESG performance to financial materiality. Archer’s ESG Management solution helps teams evaluate the business impact of ESG risks and opportunities, considering timelines and probability. This approach supports evolving regulatory demands like the Corporate Sustainability Reporting Directive (CSRD) and ensures efforts focus where they deliver the most value.   Bringing ESG Into the Risk Conversation The evolution from reporting to proactive management is a sign of ESG maturity. Integrating ESG factors into the broader governance and risk framework drives increased business value. Organizations can identify root causes, strengthen resilience, and align sustainability with core strategic goals.   ESG should never be siloed. It belongs alongside operational risk, third-party risk, and business continuity in the conversation, and IDC’s findings show more organizations are making that connection.   Want to learn more? If your ESG reporting still depends on manual collection and delayed response, now is the time to rethink your approach. Contact Archer today  to learn how Archer ESG Management  can help you build a more connected, accountable ESG reporting process.

Many ESG teams spend most of their time gathering data. They chase spreadsheets, emails, and disconnected systems to meet disclosure deadlines. That process might satisfy minimum reporting requirements, but it’s not enough to build trust or meet the growing expectations from regulators and stakeholders.   According to the recently published 2025 IDC MarketScape for ESG Reporting and Compliance Management Applications , the most advanced platforms do more than collect ESG metrics. They support traceability, automate tasks, and trigger action when thresholds are breached. These capabilities help shift ESG reporting from a static activity to a live management function.   Compliance Isn’t the Finish Line One of the key trends highlighted in IDC’s report is the pressure on companies to meet requirements such as the Corporate Sustainability Reporting Directive (CSRD). This includes collecting auditable and verifiable ESG data and connecting it to clear, transparent disclosures. But meeting a disclosure framework isn’t the end goal. The real value lies in using ESG data to inform decisions and manage risk.   Auditability and Traceability Matter The IDC report emphasizes the growing focus on assurance. As regulations mature, external audits of ESG data will become more common, which means that teams need to do more than simply publish numbers. They will need to prove how the numbers were calculated, which systems they originated from, and whether the data was altered along the way.   Systems that offer automated tracking, evidence logs, and AI-assisted review of disclosure responses are better equipped to handle this level of scrutiny. They help ESG and sustainability leaders respond to regulator questions, investor concerns, and internal reviews with speed and clarity.   ESG Reporting Is Becoming a Team Sport The IDC report makes it clear that ESG reporting no longer belongs to a single department. Finance, legal, risk, compliance, HR, and procurement all play a role. Platforms that support cross-functional workflows and shared visibility are better equipped to reflect how ESG risks and opportunities show up across the business.   If your ESG reporting still depends on manual collection and delayed response, now is the time to rethink your approach. Contact Archer today  to learn how Archer ESG Management  can help you build a more connected, accountable ESG reporting process.

Businesses are increasingly turning to artificial intelligence (AI) as a tool for innovation and growth. A recent Gartner survey found that 44% of companies are now using AI in some capacity, up from 37% last year. But with this growth comes responsibility. Without proper oversight, businesses risk mismanaging the use of AI tools, potentially leading to ethical concerns and regulatory issues. Strong AI governance is no longer optional but an essential consideration for any business looking to thrive in the AI era. The use of AI brings new challenges for risk managers Risk managers face numerous challenges in managing and governing AI technologies. One of the biggest hurdles is the absence of centralized AI oversight. With AI systems deployed across various departments, the task of tracking AI assets and ensuring cohesive management becomes a formidable obstacle. This fragmentation can lead to unmanaged deployments, escalating the risk of ethical lapses and regulatory non-compliance, fines, and penalties. New AI regulations will have a substantial impact on how organizations use AI. Navigating the intricate requirements of the European Union (EU) AI Act and other regulatory frameworks can be daunting. Risk managers must continuously update policies and controls to adhere to evolving standards, which can be resource intensive and prone to errors.  Identifying, assessing, and mitigating risks, including biases in AI models, is critical to avoid legal and reputational damage. However, risk management programs tend to lack the necessary tools and expertise to conduct thorough risk assessments and audits, leaving them vulnerable to unintended consequences of AI usage.  Transparency and explainability of AI processes are crucial yet challenging to achieve. Stakeholders often struggle to understand and trust AI decision making due to the opaque nature of many AI models. Without clear explanations, gaining stakeholder buy in and ensuring accountability becomes difficult.  Furthermore, data governance is a critical area where many organizations falter. Ensuring data quality, integrity, and security throughout the AI lifecycle is essential. Maintaining high standards and complying with data protection regulations requires robust governance practices that many organizations find challenging to implement effectively.  What is AI Governance? The purpose of AI governance is to avoid and mitigate potential harm and build trustworthy AI systems that serve the interests of your customers, employees, community, and society. AI governance is a framework of policies, processes, and controls designed to ensure that AI systems are developed, deployed, and used ethically, responsibly, and in compliance with legal and societal norms.   When AI systems are employed to make decisions affecting individuals, there is a risk of unintended harm to customers, employees, communities, or broader society. AI governance must consider the potential risks and impacts at every stage of the AI lifecycle.   Trustworthy AI has varied definitions based on perspective, yet most converge on a set of core principles:   The European Union (EU) AI Act defines trustworthy AI as being "legally compliant, technically robust, and ethically sound." The National Institute of Standards and Technology (NIST) outlines characteristics of trustworthy AI in its AI Risk Management Framework (AI RMF), including valid and reliable, safe and secure, accountable, transparent, explainable, privacy-enhanced, and fair with regard to managing harmful bias. Five questions to ask your risk management team to evaluate your AI readiness How do you manage and track all AI assets across your business? What steps have you taken to ensure compliance with the EU AI Act? How do you assess and mitigate risk and biases in your AI models? How transparent are your AI decision-making processes to stakeholders, and what tools do you use to ensure explainability?  How scalable are your AI Governance practices to ensure compliance with new and changing AI Governance regulations? The answer to these questions is not a simple yes or no.  They require a thoughtful and thorough evaluation of the AI initiatives in use and the policies and processes in place to govern them. This evaluation should involve collaboration between risk managers, IT leaders, data scientists, and other key stakeholders to ensure a holistic understanding of AI usage across the organization. 83% of business leaders believe they need to adopt AI governance frameworks to ensure ethical AI usage and reduce bias. World Economic Forum May 2024 By regularly evaluating and adapting AI governance practices, the risk management function can anticipate potential risks and stay ahead of regulatory changes. Employing a robust AI Governance program also demonstrates a commitment to stakeholders and promotes trust in the organization's use of AI technologies. Introducing Archer AI Governance Archer AI Governance  empowers risk managers to tackle these challenges and ensure responsible AI use throughout the organization. Aligned with the stringent requirements of the EU AI Act, Archer AI Governance provides a robust suite of features that help to manage AI risks effectively, maintain compliance, and promote ethical AI practices.  Interested in learning how Archer AI Governance can help your organization effectively manage AI usage risks?  Archer clients and partners are invited to join us on October 4 for a Free Friday Tech Huddle .

For many organizations, third-party risk management remains a compliance-driven function—an exercise in checking boxes to satisfy regulatory requirements. While compliance is crucial, this narrow focus can leave significant value untapped, making third-party risk management reactive rather than proactive in anticipating and mitigating risks. This reactive stance can lead to blind spots in supply chain vulnerabilities, emerging risks, and missed opportunities for competitive advantage. When third-party risk management is limited to compliance, valuable insights that could enhance decision-making and operational resilience are overlooked. For example, supplier assessments that focus solely on financial stability and cybersecurity may miss broader risks, such as geopolitical instability, climate-related disruptions, or ethical sourcing concerns. These hidden risks can escalate quickly, affecting business continuity, brand reputation, and regulatory standing.  Leveraging third-party risk management for strategic growth   To unlock the full potential of third-party risk management, organizations must shift from a compliance-first mindset to a holistic approach that integrates third-party risk management into broader enterprise risk management (ERM). This means viewing third-party relationships as more than just potential liabilities but also as sources of innovation, efficiency, and competitive differentiation.  By integrating third-party risk management data with business strategy, organizations can make informed decisions about supplier partnerships, expand into new markets, and prioritize investments. For example, an organization tracking ESG performance across its supply chain can identify partners aligned with its sustainability goals, reducing long-term regulatory and reputational risks.  Transforming third-party risk management data into actionable insights   The key to maximizing third-party risk management’s value lies in turning risk data into strategic intelligence. Most organizations already collect vast amounts of data on their vendors, but few leverage it beyond risk scoring and compliance reporting. Advanced analytics and AI-driven tools can help transform this data into actionable insights that drive resilience and growth.  Proactively using third-party risk management intelligence not only mitigates risk but also creates opportunities, whether by identifying emerging markets, streamlining operations, or fostering innovation through stronger third-party collaborations.  To move from a compliance function to a strategic enabler, organizations can take several key steps:  Integrate third-party risk management with ERM  by establishing direct links between third-party risk management insights and broader enterprise risk discussions to ensure alignment with business objectives.  Leverage technology , such as AI and automation, to enhance risk assessments, monitor real-time third-party risks, and generate predictive insights.  Expand risk metrics  to include financial, cybersecurity, operational resilience, reputational, and climate risks.  Strengthen cross-functional collaboration  by engaging stakeholders across finance, procurement, IT, and legal teams to ensure a comprehensive risk management approach.  A well-executed third-party risk management strategy does more than mitigate risk—it becomes a driver of long-term business resilience and competitive advantage. By expanding beyond compliance, organizations can transform third-party relationships into a powerful asset for sustainable growth.  Watch the webcast " From Compliance to Confidence: Elevating the Strategic Impact of Third-Party Risk Management "  with Shared Assessments to discover how you can go beyond reporting and compliance to unlock the full strategic value of your TPRM program.