Key insights:

• • • Agentic AI acts autonomously, creating new accountability challenges — Agentic AI acts and makes decisions with minimal human intervention, and this shift changes everything about responsibility and oversight.

• • • With intentional design, the risks can be addressed confidently — Silent failures, accountability diffusion, and confidentiality breaches can only be mitigated through governance, testing, and rigorous human oversight.

• • • AI is changing legal work, not eliminating it — When agentic AI handles routine tasks, legal professionals can move their attention onto higher-value work and increased responsibilities.

It is no longer useful to treat all AI as a single category or a tool for a single use case. Generative AI (GenAI) has already begun reshaping legal work by drafting documents, researching precedents, and answering questions with remarkable speed. At its core, however, GenAI remains a responsive tool. Agentic AI, on the other hand, represents a distinct evolution. Rather than waiting for a prompt, agentic AI systems can plan workflows, carry them out autonomously, and make decisions along the way.

As technology and the judicial system become increasingly intertwined, it is essential to examine where these more advanced tools intersect and what that convergence means for legal institutions. Ankita Upadhyay, Senior Director of AI Enablement at ¶¶ŇőłÉÄę, recently shared her perspective during a recent webinar,Ěý, presented by theĚýĚý— a joint effort by the National Center for State CourtsĚý(NCSC) and the Thomson Reuters Institute (TRI) —Ěýand offered valuable insight into the opportunities and responsibilities that accompany this shift.

One of the key notes to understand from the panel is that “generative AI gives you an answer. Agentic AI takes an action — and that distinction changes everything about the accountability,” Upadhyay said, adding that the distinction is not merely technical. It must reshape how we think about professional responsibility and the integration of AI into institutions that are built on trust and accuracy.

The promise of efficiency and transformation at scale

The potential of agentic AI is already visible in courts across the country. In Palm Beach County, Fla., for example, court officials are using agentic AI to process incoming documents at unprecedented scale. When an attorney files a document, the system autonomously identifies the document type, classifies it, extracts data, and routes it appropriately. The county already has processed up to 5 million documents using this process, operating 20 hours a day, every day of the year.

The most important part isn’t just the volume, however, it’s what happened to the people.

The staff who spent time on routine document processing were not laid off; instead, they were reassigned. Clerk 1 positions were transitioned to Clerk 3 and Clerk 4 roles, and that meant greater responsibility, more complex decision-making, and increased compensation for those making that transition.

“The staff that was doing all the processing of documents has been reallocated to customer experience and more complex tasks,” explained Parik Chokski, Director of IT for Palm Beach, on the webinar. This development reflects a broader truth: AI is not taking jobs in the legal sector; rather, it’s changing what those jobs entail.

You can explore the white paperĚýĚýhere

As more repetitive work moves to AI, legal professionals move their attention toward the kind of work that demands their judgment, expertise, and accountability.

Risks are real, but not insurmountable

Yet the promise of agentic AI comes with genuine risks that differ from those posed by generative AI. Because agentic AI acts autonomously, for instance, failures can occur silently and invisibly, and sometimes repeatedly before detection.

¶¶ŇőłÉÄę’ Upadhyay identified three predominant risks for legal professionals and their organizations with agentic AI use:

1. Accountability diffusion — When an agentic AI system produces a document through a chain of autonomous decisions, it becomes difficult to determine where human judgment ended, and machine decision-making began. This ambiguity directly challenges professional conduct rules, which assume lawyers make every material decision. The result is an unclear line of responsibility and potential legal exposure for the lawyer.

2. Confidentiality at scale — Agentic AI systems operate across entire databases and multiple use cases simultaneously. A single misconfiguration of permissions can allow an AI agent to access privileged information to which it shouldn’t have access, potentially sharing sensitive client data across unintended matters. The danger lies in the fact that this often happens silently and repeatedly until discovered.

3. Irreversibility — Unlike GenAI, where a flawed draft often gets caught during review, agentic AI can send client communications, file documents, or update records based on faulty reasoning even before human oversight intervenes. The speed of action outpaces the speed of review, and thus, it creates a gap that traditional legal processes weren’t designed to address.

“The risk isn’t that AI gets it wrong,” Upadhyay said. “The problem is agentic AI systems, when it gets things wrong, it happens silently in a black box until you monitor it, and that’s the biggest challenge.”

Guardrails for responsible implementation

Given this, how do courts and legal organizations implement agentic AI thoughtfully? The webinar panelists, drawing on real-world implementations and NCSC research, emphasized several critical actions, including:

Establish clear governance — Begin with centralized registration of all agentic AI agents, conduct rigorous risk classification based on task impact, and start with low-risk workflows before advancing to high-stakes tasks. “Having a proper agentic AI governance is really important,” Palm Beach’s Chokski said.

Commit to rigorous testing — Extensive stress-testing in development and Q&A environments must precede any production deployment. Palm Beach’s implementation required weeks, if not months, of testing before going live — but that investment paid dividends in reliability and organizational confidence.

Design for transparency — Build workflows with built-in checks, balances, and fail-safes. Establish comprehensive logging that tracks what the AI agent does, what permissions it has, and what decisions it makes at each step. Monitor continuously for behavioral drift.

Maintain human oversight —”Trust but verify,” Chokski noted. Agentic AI is powerful and here to stay; but so are human professionals, and they must always retain oversight, the ability to intervene, and ultimate accountability for outcomes.

The conversation continues

The choice legal organizations face today is not whether agentic AI will exist, but how to engage with it responsibly.

Organizations that approach agentic AI with intentionality, clear frameworks, and commitment to human judgment will unlock its potential to expand capability, improve efficiency, and free legal professionals to do work that requires their expertise and accountability. Those that rush forward without guardrails risk silent failures that could undermine trust in both the technology and in the overall institution.

The path forward demands partnership: AI handles scale and speed, while humans provide judgment, accountability, and ethical reasoning. When those work two parts work together intentionally and with clear guardrails, that’s where justice is served.

For more on the impact of AI in courts, visit theĚý

This webinar will take place on July 30 at 10:00 AM CT, bringing together experts across sectors to explore the evolving landscape of human trafficking and the critical role collaboration plays in addressing it.

Hosted by Heather Panton, ¶¶ŇőłÉÄę Senior Advisor of Social Impact and Human Rights, the session will feature Andrew Workman (TRSS), who will share insights from his forthcoming research on Missing and Murdered Indigenous Women and Girls (MMIWG)—highlighting the intersection of trafficking, vulnerability, and systemic risk. Additional panelists from federal law enforcement and investigative agencies are expected to join the discussion, offering perspectives from the front lines of prevention and enforcement.

Together, panelists will examine the complexities of trafficking today, including emerging trends, the impact on vulnerable communities, and the importance of coordinated efforts across the public, private, and nonprofit sectors.

We invite professionals, partners, and advocates committed to advancing justice and protecting communities to join this important conversation as we work toward a world free from exploitation.

Register today and play a role in raising awareness and driving action.

Key insights:

• • • AI augments judicial judgment without replacing it — Used thoughtfully it clarifies reasoning and improves access.

    • Strict guardrails are needed — These can include structured prompts, anonymized data, and rule-based outputs helps interrupt bias and maintain integrity.

    • Judges should lead — They can do this through peer learning and education, which fosters responsible use while preserving public trust.

The integration of AI in the judiciary is gaining momentum, offering a promising solution to the growing caseloads, access-to-justice gaps, and public trust challenges faced by courts across the United States. And as the judiciary explores the potential of AI, a crucial conversation is emerging — one that highlights the importance of responsible and thoughtful adoption.

A recent webinar, , presented by theĚý — a joint effort by the National Center for State CourtsĚý(NCSC) and the Thomson Reuters Institute (TRI) — shed light on the experiences of early adopters of generative AI (GenAI) in the judiciary. In the webinar, Prof. Amy Cyphert of West Virginia University and U.S. Magistrate Judge Maritza Dominguez Braswell of the District of Colorado shared their insights from their own use of AI, emphasizing the need for a deliberate and informed approach.

The role of AI in judicial decision-making

A common fear is that AI will somehow take over the position of final arbiter in court proceedings. However, judges are not interested in having AI displace their judgment; rather, they see AI as a tool that augments and helps advance justice, not a tool that replaces decision-making or human judgment.

Judges also are not rushing into AI use. Instead, they are approaching it with a deep commitment to responsible use and a desire to increase, not decrease, public trust. “Everybody on that spectrum — from ‘I’m just learning’ to ‘I want to be a power user’ — says, ‘But I want to do it right,’” says Judge Braswell.

AI can also help judges close communication gaps. By taking decisions that judges have already reasoned through and converting them into accessible explanations, AI can help all litigants clearly understand the relevant legal framework, rule, or process behind the decision. This is even more impactful in cases involving self-represented litigants.

Leveraging AI to enhance judicial communication

Judge Braswell understands this well. In every case with at least one self-represented litigant, she offers a plain language summary of her written decisions. Although she does not use AI to draft those, she does use AI to translate complex legal reasoning when delivering information from the bench.

“If I have 15 minutes for a hearing and want to explain to a self-represented litigant something complex, I use AI to help me translate legal jargon into plain and simple language,” she explains. “I want the self-represented litigant to understand what I’m doing and why I’m doing it — and AI helps me translate lawyer-speak into plain-speak, quickly.”

You can explore the white paperĚý here

This capability is particularly valuable for judges who often struggle to find the time to connect with litigants. By leveraging AI, they can provide more personalized and informative interactions, ultimately enhancing litigants’ judicial experiences. In addition, some judges are using AI to create engaging content, such as avatars and videos on YouTube, to make themselves more relatable and accessible to the public; while others are using AI to help litigants navigate court processes, helping to demystify the system and reduce anxiety.

Guardrails for responsible AI use

Of course, Judge Braswell doesn’t use AI casually. She has strict policies and protocols in place, including segregation of work and personal accounts, prompt anonymization, and prohibiting her clerks from uploading sensitive information or delegating core functions and judgment to any AI tool. She also trains her chambers on high-risk and low-risk cases and emphasizes the importance of proper AI use through structured prompts, appropriate settings, standing instructions, and deliberate guardrails.

For example, Judge Braswell describes a dedicated project in which she uploaded her district’s local rules, the Federal Rules of Civil Procedure, and standing orders. She queries that project any time she needs to refresh on an applicable rule or procedure. She gave the AI tool clear instructions, such as: Don’t answer unless grounded in a rule. Cite the rule with every response. If you don’t know, say so.

While these types of practices do not make the tools risk-free, Judge Braswell notes, they do offer guardrails to help support, rather than undermine, judicial integrity.

Addressing risks and challenges

While , the deeper risks in AI use in the courts are bias, cognitive deskilling, and erosion of public trust. Judge Braswell warns that bias is harder to detect than any made-up case citation. “If you ask for a legal framework in an employment discrimination case, the system may pull more from defense-side articles because larger firms publish more content,” she explains. “The result is a subtle tilt in perspective.”

To counter this, she prompts her AI tools deliberately asking for diverse perspectives, asking the tool to gather contrary views, or telling the tool to answer only after asking follow-up questions that could identify user bias. Without this intentionality, bias can go undetected.

For judges ready to engage, visitĚýĚýto join the conversation

On the webinar, Prof. Cyphert echoed concerns about the next generation. “I worry that younger lawyers may skip critical learning processes if they rely too heavily on AI for drafting or research,” Prof. Cyphert says. “Is there a cognitive benefit to writing that we’re losing?”

The path forward through education, experimentation & transparency

During the webinar, both speakers rejected mandatory disclosure rules as counterproductive.

“It creates a chilling effect,” Judge Braswell says. “And we need people to engage for learning purposes.” Instead, she notes that she advocates for voluntary transparency — judges explaining their use of AI in ways that build public understanding and confidence.

Prof. Cyphert agrees. “You can’t assess risks and benefits if you don’t understand the technology,” she says, adding that she encourages judges to attend webinars, read research, and talk to peers. Similarly, Judge Braswell co-founded the , a judge-only, peer-led forum for candid discussion that exists as a safe space to share challenges, test ideas, and learn together.

As the webinar notes, the future of justice isn’t just about whether courts and judges are using advanced AI technology, it’s about how that technology should be used — with care, purpose, and always with people at the center.

For more on the impact of AI in courts, visit theĚý

Key insights:

• • • AI’s greatest strength in criminal justice is pattern recognition— AI can process vast amounts of data quickly, helping law enforcement and legal professionals detect connections, reduce oversight gaps, and improve consistency across investigations and casework.

    • AI should strengthen justice, not substitute for human judgment— Legal professionals are integral to evaluating AI-generated outputs, especially when decisions affect evidence, warrants, and individuals’ constitutional rights.

    • The most effective model is human/AI collaboration— AI handles scale and speed, while judges, attorneys, and investigators provide context, accountability, and ethical reasoning needed to protect due process.

The law has always been about patterns — patterns of behavior, patterns of evidence, and patterns of justice. Now, courts and law enforcement can leverage a tool powerful enough to see those patterns at a scale at a speed no human mind could match: AI.

At its core, AI works by recognizing patterns. Rather than simply matching keywords, it learns from large amounts of existing text to understand meaning and context and uses that learning to make predictions about what comes next. In the context of law enforcement, that capability is nothing short of transformative.

These themes were front and center in a recent webinar, , from theĚý, a joint effort by the National Center for State CourtsĚý(NCSC) and the Thomson Reuters Institute (TRI). The webinar brought together voices from across the justice system, and what emerged was a clear and consistent message: AI is a powerful ally in the pursuit of justice, but only when paired with the judgment, accountability, and constitutional grounding that human professionals can provide.

AI’s pattern recognition is a gamechanger

“AI is excellent,” said Mark Cheatham, Chief of Police in Acworth, Georgia, during the webinar. “It is better than anyone else in your office at recognizing patterns. No doubt about it. It is the smartest, most capable employee that you have.”

That kind of capability, applied to the demands of modern policing, investigation, and prosecution, is a genuine gamechanger. However, the promise of AI extends far beyond the patrol car or the precinct. Indeed, it cascades through the entire arc of justice — from the moment a crime is detected all the way through prosecution and adjudication.

Each step in that chain represents not just an operational and efficiency upgrade, but an opportunity to make the system more fair, more consistent, and more protective of the rights of everyone involved.

Webinar participants considered the practical implications. For example, AI can identify and mitigate human error in decision-making, promoting greater consistency and fairness in outcomes across cases. And by automating labor-intensive tasks such as reviewing body camera footage, AI frees prosecutors and defense attorneys to focus on other aspects of their work that demand professional judgment and legal expertise.

In legal education, the potential of AI is similarly recognized. Hon. Eric DuBois of the 9th Judicial Circuit Court in Florida emphasizes its role as a tool rather than a substitute. “I encourage the law students to use AI as a starting point,” Judge DuBois explained. “But it’s not going to replace us. You’ve got to put the work in, you’ve got to put the effort in.”

AI can never replace the detective, the prosecutor, the judge, or the defense attorney; however, it can work alongside them, handling the volume and velocity of data that no human team could process alone.

Judge DuBois’ perspective aligns with broader judicial sentiment on the responsible integration of AI. In fact, one consistent theme across the webinar was the necessity of maintaining human oversight. The role of the legal professional remains central, participants stressed, because that ensures accuracy, accountability, and ethical judgment. The appropriate placement of human expertise within AI-assisted processes is essential to ensuring a fair and effective legal system.

That balance between leveraging AI and preserving human judgment is not just good practice, rather it’s a cornerstone of justice. While Chief Cheatham praises AI’s pattern recognition, he also cautions that it “will call in sick, frequently and unexpectedly.” In other words, AI is a powerful but imperfect tool, and those professionals who rely on it must always be prepared to intervene in those situations in which AI falls short. Moreover, the technology is improving extremely rapidly, and the models we are using today will likely be the worst models we ever use.

Naturally, that readiness is especially critical when individuals’ rights are on the line. “A human cannot just rely on that machine,” said Joyce King, Deputy State’s Attorney for Frederick County in Maryland. “You need a warrant to open that cyber tip separately, to get human eyes on that for confirmation, that we cannot rely on the machine.” Clearly, as the webinar explained, AI does not replace constitutional obligations; rather, it operates within them, and the professionals who use AI are still the guardians of due process.

The human/AI partnership is where justice is served

Bob Rhodes, Chief Technology Officer for ¶¶ŇőłÉÄę Special Services (TRSS) echoed that sentiment with a principle that cuts across every application of AI in the justice system. “The number one thing… is a human should always be in the loop to verify what the systems are giving them,” Rhodes said.

This is not a limitation of AI; instead, it’s the design of a system that works. AI identifies the patterns, and trained, experienced professionals evaluate them, act on them, and are accountable for them.

That partnership is where the real opportunity lives. AI can never replace the detective, the prosecutor, the judge, or the defense attorney. However, it can work alongside them, handling the volume and velocity of data that no human team could process alone. So that means the humans in the room can focus on what they do best: applying judgment, upholding the law, and protecting an individual’s rights.

For judicial and law enforcement professionals, this is the moment to lean in. The patterns are there, the technology to read them is here, and the opportunity to use both in service of rights — not against them — has never been greater.

You can find out more about the webinars from the AI Policy Consortium here

Key highlights:

• • • Risk varies by workflow and context — Practitioners should apply risk ratings based on workflow and context, such as low for productivity, moderate for research, moderate to high for drafting and public‑facing tools, and high for decision-support.

    • Courts need their own developed benchmarks — Courts should develop and regularly review their own independent benchmarks and evaluation datasets instead of relying solely on vendor claims, because vendors may optimize systems for known tests.

    • Need for benchmarking to detect drift, degradation, and bias — Continuous, rigorous benchmarking of AI models is essential for courts and legal professionals to maintain confidence in these systems, since both the law and AI models change over time.

AI is not monolithic technology, and a risk-based assessment process is needed when using it. Indeed, courts and legal professionals must scale their scrutiny to match risk levels.

This approach — which balances innovation with accountability, along with other essential best practices — is detailed in a recent publication, , created as part of .

In a recent webinar, , one of the co-authors of the document, explained the purpose of the document: “The central aim of what we were thinking about in these best practices is to give courts and legal professionals a principle-based architecture when you’re thinking about the adoption of GenAI tools.”

Risk and human judgement serve as central elements

What is unique about this framework is that it categorizes risk based on key workflow actions of lawyering, for example:

• • • Productivity tools carry minimal to moderate risk
    • Research tools are assigned moderate risk
    • Drafting tools range from moderate to high risk
    • Public-facing tools carry moderate to high risk
    • Decision-support tools pose high risk

The framework holds that risk is dynamic rather than static, and there can be shifts in risk levels based on use cases. For example, a scheduling tool typically poses minimal risk; however, the same tool becomes high risk when used for urgent national security cases. And translation tools can shift from lower risk research support to high-risk decision-support depending on their use.

Similarly, when tools range from moderate risk to high risk, users need to be especially discerning in order to understand the underlying risks — and if the task should be delegated to AI at all.

“You can’t just rely on categories,” explains from the IP High Court of Korea. “You need to understand the underlying risks and ask yourself: Would I delegate this task to another person? Am I comfortable delegating it publicly? If the answer is no, then you probably shouldn’t be delegating it to an AI either.”

In addition, clear red lines around when AI should never be used and classified as unacceptable risk exist for judicial use. “I believe the clear red line is automated final decisions or AI systems that assess a person’s credibility or determine fundamental rights involving incarceration, housing, family,” says Judge Kwon, adding that fundamental rights require human judgment.

“You can’t just rely on categories. You need to understand the underlying risks and ask yourself: Would I delegate this task to another person? Am I comfortable delegating it publicly? If the answer is no, then you probably shouldn’t be delegating it to an AI either.”

The extent of human judgment also has layers. , Shareholder at Greenberg Traurig, says he believes that AI for any legal use currently requires human oversight. “The human supervision piece… is utterly critical in the real world of practicing lawyers and law firms,” Greenberg says. “You have to supervise the lawyers in the firm that are using the technology, including young lawyers.”

To help distinguish which type of human oversight is appropriate, the framework in the Key Considerations document defines two forms of such oversight: i) human in the loop, which means active human involvement in decisions; and ii) human on the loop, which means monitoring automated processes and intervening when needed.

What the difference between what each concept could look like in a court setting shows that a human in the loop is, for example, a law clerk using AI to do research on relevant case law and checking to make sure that the references are legally sound; and a human on the loop is a clerk monitoring an established robotic process to extract data for the case management system and spot-checking for accuracy.

Practical guidance for courts

In addition to judges considering the risk level of AI tools, Judge Kwon, Greenberg, and Carpenter, noted the importance of technical AI competence as part of lawyers’ and judges’ ethical duty, especially around verification, transparency, and independent benchmarks as part of accountability, as well as the need for understandable documentation to maintain public trust. To reinforce the latter point, , Director in Government Practice for ¶¶ŇőłÉÄę Practical Law states: “It’s very vital, especially as we usher in the age of AI, that the public be informed as much as they can be about how that decision-making process is taking place.”

In addition, Judge Kwon, Greenberg, and Carpenter highlighted additional guidance on the criticality of benchmarking, including:

• • • Court-developed benchmarks prevent overreliance on vendor data — Courts should develop their own benchmarks and independent evaluation datasets rather than relying entirely on vendor claims and review evaluation scenarios regularly. Vendors may optimize their systems for known tests, which leads to overfitting, in which a model learns patterns specific to its training data so well that it performs poorly on new, unseen data. This gives a misleading impression of reliability.
    • Ongoing rigorous benchmarking to detect model drift & degradation — To build confidence in AI models, courts and legal professionals must approach AI model evaluation with rigor and ongoing vigilance. Continuous benchmarking is essential, and it cannot be a one-time process because the law evolves constantly and precedents shift. In addition, AI models themselves update regularly, and courts need to monitor performance over time to detect AI degradation or bias drift.

Adopting a thoughtful, risk-informed approach to GenAI in legal practice and courts will help realize its benefits for efficiency and access to justice while protecting ethical obligations, due process, and public trust in the legal system.

You can find out more about how AI and other advanced technologies are impacting best practices in courts and administration here

Our distinguished panel includes experts from the ¶¶ŇőłÉÄę Social Impact Institute, and nonprofit partners Spotlight, and New Friends New Life. Additionally, a representative from U.S. Homeland Security Investigations will provide insights into the collaborative efforts required to tackle this critical issue.

This training aims to educate participants on the complexities of human trafficking, the impact on victims, and effective strategies for prevention and intervention. Attendees will gain valuable knowledge on the roles of various stakeholders, including non-profit organizations, law enforcement, and the community, in addressing trafficking and supporting survivors.

We invite individuals and organizations committed to making a difference to join this informative session, as we work together to create a world free from exploitation.

Watch the full recording below!

This exclusive two-part webinar series, “Enhancing Metrics for the General Counsel’s Office,” is designed to equip General Counsel and legal leaders with the knowledge and practical tools to effectively demonstrate theĚýrealĚývalue of their legal departments. We’ll delve into how to move beyond simply tracking expenses and hours, and instead, focus on metrics that showcase the proactive, strategic, and business-enabling work of your legal team.

In this series, you will learn how to:

• Optimize existing metrics:ĚýMove beyond cost and time to showcase both efficiency and effectiveness.
• Transform your metrics:ĚýIncorporate “Protect and Enable” metrics, highlighting the proactive and strategic contributions of your legal team.
• Communicate your value:ĚýDistil complex data into a concise and compelling narrative for senior leadership, including a practical exercise on creating a powerful one-slide summary.

This exclusive two-part webinar series, “Enhancing Metrics for the General Counsel’s Office,” is designed to equip General Counsel and legal leaders with the knowledge and practical tools to effectively demonstrate theĚýrealĚývalue of their legal departments. We’ll delve into how to move beyond simply tracking expenses and hours, and instead, focus on metrics that showcase the proactive, strategic, and business-enabling work of your legal team.

In this series, you will learn how to:

• Optimize existing metrics:ĚýMove beyond cost and time to showcase both efficiency and effectiveness.
• Transform your metrics:ĚýIncorporate “Protect and Enable” metrics, highlighting the proactive and strategic contributions of your legal team.
• Communicate your value:ĚýDistil complex data into a concise and compelling narrative for senior leadership, including a practical exercise on creating a powerful one-slide summary.

During the recent virtual annual meeting of , I was part of a panel, that discussed how in-house counsel must ensure that their company is prepared to handle any emergency. Other panelists included Laura Stevens, Executive Vice President and General Counsel of Cengage Group; Michelle-Kim Cohen, Deputy General Counsel of Dassault Systèmes; and Sarah Gatti, Corporate Counsel at Drift.com.

Here are some of the questions discussed by the panel and panelists’ responses.

How broad should your emergency response plan be for addressing any type of emergency?

A one-size-fits-all-approach may not always be feasible for company-wide emergency response planning. When preparing or updating an emergency response plan, a company should account for reasonably foreseeable emergencies that may occur, rather than addressing every possible emergency regardless of actual likelihood. This assessment depends on various factors, including geography, the company’s industry, the company’s products and services, and the nature of the workforce and whether it includes remote employees.

Geography plays a significant role in the risk assessment process and may result in different types of risk depending on location. For example, one region may be prone to certain types of natural disasters (such as earthquakes) that are unlikely to occur in another region where the company operates. Using this example, the emergency response plan for a worksite in that region must account for the possibility of those natural disasters occurring, whereas a plan for a worksite in a different region may not.

A company should also survey its existing resources and determine whether a plan already exists for a particular emergency situation, even if the internal distribution or use of these resources was limited. Existing resources can help identify reasonably foreseeable emergencies and provide a starting point for developing more comprehensive emergency planning.

Even if a company tailors its emergency response planning, certain components may be universal regardless of the type of emergency. For example, a company may use the same communication systems for alerting its workforce of an emergency, even if the extent of notification varies by the type of emergency.

How accessible should your company’s emergency response plan be?

A company must account for whether an emergency could impede access to the emergency response plan itself. A company should have copies of the emergency response plan printed out in hard copy format and kept at the company’s offices or work sites. In addition to hard copies, a company should have the emergency response plan electronically accessible, such as a version securely stored on a shared drive. Obviously, the inability to access an emergency response plan should not create an emergency in itself. For example, if there is a foreseeable risk of an emergency rendering an office physically inaccessible (such as from civil unrest), the company should not have the emergency response plan only kept in hard copy format at that office.

A company must take the proper steps to ensure that the plan’s needs are accessible to stakeholders and the persons responsible for implementing the plan. The company should also consider whether and to what extent to share the emergency response plan with its outside counsel.

Should the emergency response plan be shared externally?

A company should carefully determine to whom it discloses its emergency response plan and, if required, how much of the plan to disclose. This issue periodically comes up when customers or vendors want to determine if a company has a plan before doing business with the company. Sometimes limited disclosure of a company’s emergency response plan may be unavoidable.

A company should hesitate to fully disclose its emergency response plan to third parties unless absolutely required. Instead, a company should consider other ways of satisfying the needs of third parties that want to confirm the existence and content of the company’s emergency response plan. For example, a company could inquire whether providing a copy of the plan’s table of contents satisfies a third party’s needs. Alternatively, a company could require a nondisclosure or confidentiality agreement before disclosing any part of its emergency response plan or limiting disclosure to answering a questionnaire about its emergency response plan.

What is in-house counsel’s role in emergency response planning?

In-house counsel plays a central role in a company’s emergency response planning. Aside from serving on the crisis management team, in-house counsel often acts as a project manager in emergency response planning. As a result, in-house counsel communicates with a company’s departments and external and internal stakeholders, such as the company’s IT and communications personnel. In-house counsel also ensures that training and assessments of the plan regularly occur. In-house counsel may need to determine if the plan is current and accurately reflects up-to-date operational practices, the company’s business, and legal requirements.

In addition, in-house counsel serves as a subject matter expert with issues related to a company’s emergency response. This includes asking “what if” questions when reviewing the plan, conducting a post-mortem response to any testing of the plan or actual emergency, determining who to notify about the company’s emergency response, and ensuring that any emergency response is legally compliant.

How should your company prepare for implementing its emergency response plan?

A key component of emergency planning involves testing and training employees on the components of the plan that are relevant to their respective roles. To test the plan, the company should perform tabletop exercises to simulate reasonably likely emergency scenarios to better ensure that key personnel know their role and can implement the plan. These exercises can also identify any necessary changes for updating the plan. For example, if key personnel are unreachable during a tabletop exercise, the company should consider updating its plan by replacing them with more accessible individuals.

The company should test its emergency response plan in real-time. This may involve testing the plan after-hours because a real-life emergency occurs at any time.

As part of the event, one particular panel, Out of Shadow: Combating the Evolving Illicit Finance Threat, will focus on how the danger of illicit finance, which covers everything from laundering money from illegal activity to funding terrorism, is becoming greatly a bigger danger due mainly to the rapid growth in the use of cryptocurrencies.

With the inclusion of a provision in the 2020 National Defense Authorization Act to examine the use of new financial technologies in terrorism financing, regulatory scrutiny of cryptocurrencies is poised to take another step forward under newly appointed US Treasury Secretary Janet Yellen. Of course, even before Secretary Yellen’s arrival, anti-money laundering and combating the financing of terrorism programs were a top priority for both the Internal Revenue Service and law enforcement officials alike.

Indeed, if recent developments — such as the seizure of millions of dollars’ worth of cryptocurrency from Al-Qaeda and ISIS in August 2020 — are any indication, the dark world of crypto-terror appears ever more pronounced and insidious.

You canĚý about the upcoming American Security conference here.

This podcast offers an important update on the elevated illicit finance threat environment. What regulatory actions are expected under a Biden administration? How comprehensive will a renewed multinational fight against terrorism financing be in today’s tenuous climate?

The US has shown differing approaches to the crypto-regulatory environment, including several individual states taking it upon themselves to become trailblazers in crypto-regulation and enforcement. Statutes in several states are being enacted to require licensing for money-services or transmitter businesses, for example.

, available on theĚý, Gina Jurva, attorney and manager of market insights and thought leadership content for corporate and government at the Thomson Reuters Institute, speaks with one of the upcoming conference panelists, Jose Caldera, Chief Product Officer at , an AI-powered identity platform that provides identity verification, regulatory compliance, and digital identity solutions

The pair discuss how virtual currencies are being used by bad actors to move illegal money and fund terrorism, the recent rise of ransomware attacks, and how enhanced identity verification tools are a key component of fighting financial crime.