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An autonomous AI system tasked with cost optimization independently renegotiates vendor contracts, achieving significant savings while creating unauthorized contractual obligations. Six months later, leadership discovers the AI has been making decisions no human explicitly approved, and determining accountability becomes nearly impossible. This scenario represents the new reality of Agentic AI—autonomous systems that deliver remarkable results while fundamentally challenging traditional governance frameworks. For enterprise leaders across all sectors, understanding how to govern these self-directed systems has become a critical competitive imperative.   The Governance Challenge of Autonomous AI Enterprise organizations in financial services, healthcare, and insurance are leveraging artificial intelligence to streamline processes, enhance decision-making, and gain competitive advantages. However, as AI capabilities expand, a groundbreaking frontier is emerging that demands urgent attention from Governance, Risk, and Compliance (GRC) leaders: Agentic AI. Unlike traditional AI systems that follow predetermined rules, agentic AI possesses true autonomy. It interprets high-level goals, makes independent decisions, and acts without human intervention. While this capability unlocks unprecedented efficiencies, it introduces equally unprecedented risks that legacy GRC frameworks are ill-equipped to address.   Accountability in an Autonomous Era The shift to agentic AI represents a fundamental departure from traditional AI governance. Legacy GRC frameworks rely on predictable system behaviors and clear human decision points. Agentic AI, by contrast, autonomously navigates gray areas, creates new pathways, and occasionally rewrites its own directives to achieve overarching objectives. Consider an autonomous agent optimizing a supply chain by renegotiating supplier contracts without prior approval. While achieving the intended cost savings, it expands the "accountability surface" across multiple roles—from decision-making executives to compliance officers and system administrators. The critical question becomes: Who bears responsibility for actions that no one explicitly authorized? To manage this complexity, GRC leaders must establish clear accountability chains spanning the entire lifecycle of agentic AI systems. From initial objective setting through continuous oversight, every stakeholder must understand where accountability begins and ends.   Understanding Agentic AI's Expanded Risk Landscape Traditional risk categories such as data privacy, cybersecurity, and model bias prove inadequate for agentic AI systems. AI with true autonomy introduces interconnected risks that demand careful consideration: Autonomy Risk The potential for unintended, unauthorized actions driven by self-directed decision-making. For example, an AI agent might automatically approve high-value transactions outside established parameters to meet aggressive efficiency targets. Emergent Behavior Risk Unpredictable and potentially harmful outcomes resulting from the AI's adaptive learning and dynamic interactions. A fraud detection AI agent might begin flagging legitimate transactions from specific demographics due to biased pattern recognition that emerged over time. Ethical Drift Scenarios where autonomous systems subtly move away from organizational values or ethical principles. A lending AI agent might gradually tighten approval criteria for certain geographic areas to improve profitability metrics, inadvertently creating discriminatory patterns that conflict with fair lending principles.| Contamination Risk Negative influence from unverified external data or interactions with compromised systems. A customer service AI agent might adopt inappropriate language patterns after interacting with compromised chatbots or ingesting biased social media data during routine updates. Addressing these risks requires a fundamental shift in mindset—from reactive control to proactive risk mitigation.   Evolving GRC Programs for Agentic AI To govern agentic AI effectively, organizations need forward-thinking, adaptive approaches to GRC. Here are actionable strategies for managing the risks associated with autonomous AI behavior: Adaptive Governance Frameworks Traditional rule-based governance must evolve into principles-based frameworks. By establishing operational boundaries rather than rigid rules, businesses can accommodate the flexibility required for agentic AI's evolving capabilities. Behavioral Risk Assessment Organizations must develop tools and methodologies to monitor autonomous AI behavior patterns in real-time. This includes detecting anomalies, testing decision pathways, and analyzing how systems learn and adapt over time. Enhanced Oversight and Explainability Complete human oversight of every AI decision is impractical. However, explainable AI (XAI) and "human-in-the-loop" systems can ensure transparency during critical decision-making processes while maintaining robust audit trails. Unified GRC Platforms Modern AI governance requires enterprise-wide visibility. Unified platforms eliminate disconnected risk silos, enabling teams to monitor and respond to complex, interconnected risks in real time. This integration provides leaders with a holistic view of their organization's risk landscape. Building a Culture of Responsible AI Agentic AI must be treated not merely as a tool, but as an active participant in the enterprise ecosystem. Fostering a culture of responsible AI means embedding ethical awareness into every stage of the AI lifecycle—from initial development through deployment and ongoing oversight.   Why Agentic AI Governance Is a Competitive Imperative Agentic AI offers enormous potential for enterprises to innovate and streamline operations. However, this capability comes with equally high stakes. A poorly governed agentic AI system could lead to ethical scandals, compliance failures, or catastrophic operational breakdowns that damage both reputation and bottom line. Risk and compliance managers in large enterprise organizations cannot afford to delay action. By transitioning from static, reactive oversight to proactive and adaptive GRC paradigms, businesses can not only mitigate emerging risks but also unlock the full transformative value of agentic AI. The organizations that master AI governance today will be the ones that maintain competitive advantages tomorrow, while those that delay may find themselves struggling to catch up in an increasingly autonomous world.   Take the Next Step with Archer Archer stands at the forefront of enabling enterprises to evolve their GRC programs for the AI era. Our platform integrates advanced risk management tools designed to give organizations the visibility, accountability, and insights needed to confidently govern agentic AI systems. If your risk management strategy feels unprepared for AI's growing autonomy, now is the time to act. Contact Archer to learn how we can help you create an adaptive, intelligent, and ethical GRC program that grows with your enterprise.

Government agencies operate in one of the most demanding regulatory environments, managing thousands of obligations and responding to a steady stream of new alerts every day. Traditional compliance methods relying on spreadsheets, manual workflows, and siloed systems are buckling under this pressure. The result? Higher costs, inefficiencies, and increased exposure to compliance failures. With heightened regulatory activity on the horizon, the need for a smarter, more agile approach is no longer optional; it’s essential. AI Is Redefining What’s Possible for Compliance Teams AI-powered compliance solutions act as a force multiplier. These tools reduce the time and effort required to interpret and implement regulatory changes by: Automatically filtering out irrelevant alerts Summarizing complex legal language into actionable insights Extracting obligations directly from dense regulatory texts What once took hours of manual review can now be completed in minutes, without sacrificing accuracy, thanks to expert oversight and machine learning validation. Moving Beyond Change Tracking: A Lifecycle Approach Compliance isn’t just about staying current with updates—it’s about managing the full lifecycle of regulatory change. AI links regulatory updates to policies, controls, and audit trails, giving agencies full visibility across their compliance ecosystem. These capabilities help agencies: Identify gaps or inconsistencies in controls Generate automated change requests Proactively recommend policy and process updates From Reactive to Proactive Compliance AI empowers government agencies to move from reacting to regulations to anticipating them. With real-time insights and automated impact analysis, compliance teams can respond faster, make informed decisions, and deliver services with greater confidence. Key benefits include: Lower compliance-related costs Improved operational efficiency Better alignment with shifting mandates Increased public trust through greater transparency and accountability The Path Forward The future of government compliance is not just digital—it’s intelligent. By embracing AI-powered compliance tools now, agencies can build a foundation for resilient, scalable, and forward-thinking regulatory management. Learn more about AI-Powered Compliance Solutions Watch the webinar "Archer Evolv Compliance"  to learn more about how AI-powered compliance solutions can transform your agency's regulatory management approach Dive into the solution brief  to see how Archer Evolv™ transforms compliance into a smarter, more strategic function.

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.