Key highlights:

• • • Three emerging business models, one unresolved tension��— AI is compressing time, which directly threatens the logic of billing by the hour, but the smartest law firms are not waiting for a winner to emerge before building their strategic foundation.

    • Technology strategy and talent strategy are the same conversation — The talent model must be designed in tandem with the business model, even amid uncertainty, because many of the structural conditions of legal work are changing all at once.

    • The next great lawyer will lead with human skills, not tool proficiency��— Forward-thinking firms are doubling down on their lawyers’ curiosity, judgment, client skills, and relationship-building as these capabilities are those that AI cannot replicate.

Every law firm is asking how AI will change the way legal work gets done; but , Chief Legal Operations Officer at , is asking a more consequential question: How will AI change the way legal work gets��paid for?

Planning around 3 law firm business models in the AI era

AI is making law firms more efficient, of course, but efficiency alone does not answer the harder question of how to capture value and how AI-enabled legal services get priced. Olson Bluvshtein sees three paths emerging in law firms:

1. 1. 1. Billable-hour (still) — The first is the path of least resistance. Firms stay anchored to the billable hour, raise rates, and use AI to move faster and handle more volume, with the idea that more volume will make up the revenue losses of faster work. With this model, however, the client-firm incentive misalignment remains intact, and the fundamental tension between billing for time and AI compressing that time never gets resolved.
      2. Value-based pricing — The fixed fee pathway also is likely to gain further traction, as it’s one that many AI-native law firms are pursuing. In this model, value-based pricing creates a natural meeting point between firm and client interests because when incentives align, everyone wins, Olson Bluvshtein explains.
      3. Frontier models rule — The third scenario is more speculative but worth watching. As foundational models improve, the need for expensive legal-specific tools may diminish. “I could see a scenario in the future in which we don’t necessarily need all the legal-specific tools that are out there,” she says. Even though technology costs historically come down, cheaper tools do not make the business model question disappear, Olson Bluvshtein notes.

Candidly, Olson Bluvshtein admits that “the truth is probably somewhere in the middle,” and the firms best positioned for any of these futures are the ones building the strategic and operational foundation now rather than waiting for the answer to become obvious.

Indeed, the most thoughtfully designed business model will fall short without the right talent foundation to support it. “Technology strategy and people strategy are not separate conversations,” Olson Bluvshtein says, adding that they are key parts of the same strategy.

Legal innovation consultant reinforces this point in , noting that many aspects of the structural foundation under which the legal profession has operated are changing all at once. This means that addressing the technology strategy separately from the human side, slice by slice, does not make sense.

Boyko says she encourages law firms to take a step back and approach the problem by identifying what the firm will need first in the future and then plan the talent and tech part for that reality.

Aligning the talent model to the future business model

Not surprisingly, a key challenge for law firms right now is that the future is uncertain. Therefore, it is difficult to design a talent model for an uncertain future and an unknown business model. At the same time, there are some known facts, but the unknown aspect is when these certainties will occur.

More specifically, what is known is that there is mounting pressure on the three possible law firm business models because AI is automating the tasks of past junior associates, clients do not want to pay for tasks completed by junior associates, and clients are bringing more legal work in-house, often until the time when the almost final deliverable is handed over to outside counsel for final review.

To explore the right talent model, one experiment that Boyko suggests is to expand the junior associate experience to include rotations through back-office functions, such as knowledge management, professional development, and technology functions.

At law firm Fredrikson & Byron, Olson Bluvshtein says its associate development program is evolving to prepare for the uncertain future based on three current tactics:

• • • Building AI fluency — This is a near-term imperative that will soon become table stakes. The goal is to move past basic adoption into something more sophisticated and durable. To enable this, the litigation and M&A practices at Fredrikson are actively working with a variety of tools to test prompts that they can then share more broadly with other teams, while also identifying how AI policy guidance will evolve.
    • Accelerating the development of legal judgment — Shortening the learning curve for developing legal judgment, which includes the ability to supervise and efficiently validate AI-produced work, is the second essential part of the firm’s talent development framework. Olson Bluvshtein is candid about where things stand. “It has not fully happened yet,” she says. “But building the training infrastructure to operationalize this is a stated goal for the year ahead, including formalized curriculum around effectively and efficiently supervising AI output.”
    • Being hyper-focused on the development and recruiting of human skills — Doubling down on the human skills — including client development, negotiation, relationship-building, and sound judgment — that technology cannot replicate are the capabilities that will define the next generation of great lawyers, regardless of which law firm business model ultimately prevails.

This same philosophy is shaping how Fredrikson recruits. Rather than screening candidates for a checklist of AI tools, the firm is prioritizing curiosity, openness, and the ability to demonstrate human skills. Indeed, the firm is looking for lawyers “who are really good at those human skills” and who bring the kind of judgment and adaptability that compounds over time, explains Olson Bluvshtein.

Boyko underscores a similar approach to skills. “Right now, the skills needed to be a good lawyer are no longer those rote skills that AI can automate,” she explains. “Instead, they are the people skills, the operational skills, and the client skills.”

Of course, moving from broad experimentation to disciplined, firm-wide maturity takes time, and the gap between early movers and late adopters is already widening. Those firms that will define the next era of legal services already are asking how AI changes the way it delivers value and what skills its lawyers will most need — and not just looking for the next tool to buy.

You can learn more about the challenges facing legal talent here

Key highlights:

• • • Universities face pressure over pedagogy— Academic institutions are adopting AI as a reputational marker that’s driven by market pressure rather than educational need, creating a risk for students who can work with AI but not independently of it.

    • Entry-level roles under threat— AI is being deployed most heavily to automate the grunt work of entry-level positions in which foundational professional skills are traditionally built through struggle and feedback.

    • K-shaped cognitive economy emerging— Experienced professionals with existing expertise are gaining efficiency from AI, while entry-level workers are losing access to skill-building experiences.

According to Harvard University’s Professional & Executive Development division, innovation is defined as a “process that guides businesses through developing products or services that deliver value to customers in new and novel ways.” Along this journey, professional judgement in decision-making is used numerous times to determine next steps at key stages.

Notably, the word technology is nowhere to be found in this definition — an absence , Assistant Professor of Learning Technologies at the University of Minnesota, has long found revealing. Instead, innovation is framed as creative problem-solving, contextual intelligence, and the ability to work across perspectives. Interestingly, Dr. Heinsfeld adds, none of these require constant automation. In fact, many of them are undermined by it.

However, AI adoption has the real potential to automate away the very experiences that build these capabilities from university lecture halls to corporate offices. With notable data already suggesting that , the risk that the current approaches to AI use in universities and companies are engineering away innovation and professional judgement skills is real, notes , Group Leader in AI Research at Harvard and NTT Research.

Indeed, some observers view AI as the largest unregulated cognitive engineering experiment in human history. Yet, unlike medical drugs that require years of approval and testing, AI systems are reshaping how millions of students think, learn, and make decisions without a comparable approval process or a shared framework for discussing any potential “side effects,” as Dr. Heinsfeld pointed out.

Most worrisome is that AI is being deployed most heavily to automate precisely the entry-level roles where foundational professional skills are built.

So, what happens when an entire generation of future employees learn to delegate judgment before they develop it? And what actions do universities and companies need to take now to avoid this reality?

Risks of universities adopting AI under pressure

For universities, AI “has become a reputational marker, and not adopting AI is framed as institutional risk, regardless of whether an educational case has been made or not,” says Dr. Heinsfeld, adding that this is being driven, in part, by market pressure rather than pedagogical need.

Already, companies can greatly influence universities as employers of new graduates; and as such, AI systems are currently being optimized for speed, agreeability, and accessibility to stimulate ongoing use. However, as Dr. Heinsfeld contends, as universities race to earn the label AI ready without a careful, cautious and detailed understanding of how it may impact students’ cognitive processes, they run the risk of damage to their reputations of pedagogical integrity.

In addition, the “data as truth” paradigm is a complicating factor, she says. Drawing on her research, Dr. Heinsfeld explains how data “is often framed as the idea of being a single source of truth based on the assumption that when collected and analyzed, it can reveal objective, indisputable facts about the world.” Indeed, this ubiquitous mindset across universities and corporations treats data — such as that used to train large and small language models — as objective and indisputable.

Yet this obscures critical decisions about what gets measured, whose perspectives are included, and what forms of knowledge are systematically excluded from AI systems. As Dr. Heinsfeld warns, when data becomes synonymous with truth, “knowledge is what is measurable and optimizable.” This narrows professional judgment to efficiency metrics rather than the interpretive depth, ethical reasoning, and cultural context that are essential for sound decision-making.

Judgment gap widens in workforce downstream

Under the current AI adoption approach, students could leave universities able to work��with��AI but not independently��of��it, a distinction emphasized by Dr. Heinsfeld. Like calculators, AI works as a tool only when foundational skills for its use exist first. Without this, graduates enter the workforce with a critical judgment gap that compounds from their lives as students at college campuses to becoming employees working in corporations.

AI adoption has the real potential to automate away the very experiences that build these capabilities from university lecture halls to corporate offices.

Most worrisome is that AI is being deployed most heavily to automate precisely the entry-level roles where foundational professional skills are built, warns Dr. Tanaka. Indeed, this is exactly the type of grunt work that teaches judgment through struggle and feedback. Over time, overuse of AI will result in quality being sacrificed because critical evaluation skills have atrophied.

Looking into the future, Dr. Tanaka foresees a K-shaped economy of cognitive capacity. Experienced professionals with existing expertise and contextual judgment built through years of experience will gain increasing efficiency from AI. Entry-level workers, however, will lose access to the valuable experiences that build professional judgement. This gap widens between professionals who can independently accelerate their workflows using AI and those whose traditional tasks are merely displaced by it.

Intervention may be able to break the cycle

The pattern is not inevitable, as both Dr. Tanaka and Dr. Heinsfeld explain. Drawing on Dr. Heinsfeld’s emphasis on institutional agency, meaningful intervention will depend on conscious, intentional choices made at every level. Both experts share their guidance for how different organizations can manage this:

Academic institutions — Universities must first recognize that AI adoption is a decision rather than an inevitability and make educational need the North Star for decision-making around AI. In her analysis, Dr. Heinsfeld emphasizes that when vendors set defaults, they quietly redefine academic practice. Defaults shape what is made visible or invisible and what becomes normalized. In AI-driven environments, universities often lose control over how models are trained and updated, what data shapes outputs, how knowledge is filtered and ranked, and how student and faculty data circulate beyond institutional boundaries — especially if decision-making is left to vendors. As a result, the intellectual byproducts of teaching and learning increasingly become inputs into external systems that universities do not govern.

Private entities — For organizations, Dr. Tanaka calls for feedback loops and other mechanisms that will promote more open discussion about AI use without stigma. In addition, companies need to proactively redesign entry-level roles��to ensure these positions continue to cultivate judgment and foundational skills in an AI-driven environment. Likewise, Dr. Tanaka suggests that companies explicitly provide feedback about cognitive trade-offs to employees, fostering an understanding of possible skill entrophy.

Employees — Similarly, individuals working for organizations bear much of the responsibility for making sure critical thinking is enhanced by AI. Indeed, strategic decisions about when to use AI while seeking to preserve cognitive capacity and professional judgement are key.

Looking ahead

In today’s increasingly AI-driven environment, a new paradigm is needed to combat the current operating assumption that optimization from AI is the sole path to progress. And because the current trajectory sacrifices human development for efficiency, the need for universities and companies to choose a different path is urgent — while they still have the judgment capacity to do so.

You can find out more about how organizations are managing their talent and training issues here

You can read TRI’s latest “Inside the Shift” feature,��The human side of AI: The growing risks of ubiquitous use of AI on talent here

It’s no exaggeration to say that AI is everywhere in our workplaces right now. It writes our emails, summarizes our meetings, generates slides, and even helps us think through problems. On the surface, this may sound like progress — and in many ways, it is.

However, our latest��Inside the Shift��feature, The human side of AI: The growing risks of ubiquitous use of AI on talent by Natalie Runyon, Content Strategist for Sustainability and Human Rights Crimes for the Thomson Reuters Institute, makes a clear and timely point: When AI use becomes excessive and unchecked, it can quietly undermine the very people it’s meant to help.

One major consequence of cognitive decay is the weakening of the brain’s capacity to engage deeply, question systematically, and — somewhat ironically — resist the potential manipulation of AI.

As the article goes into in much greater detail, these harms caused by AI overuse can include a slow erosion of human connections, a loss of a professional’s sense of purpose, and a general sense of feeling overwhelmed in the workplace.

Of course, the solution isn’t to reject AI, it’s to use it better. To this end, the article makes a strong case for organizations to foster hybrid intelligence, a process by which human judgment and creativity work alongside AI capabilities.

In today’s workplace, AI can be a powerful advantage; however, that is only if organizational leaders can remember that technology should enhance the human experience, not replaces the parts of professional life that workers value.

To examine this and many more situations, the Thomson Reuters Institute (TRI) has launched a new feature segment,��Inside the Shift, that leverages our expert analysis and supporting data to tell some of the most compelling stories professional services today

Key insights:

• • • AI literacy is role-specific and essential — Courts need to move beyond general AI conversations and focus on concrete, role-based strategies that support AI readiness.

    • Balanced AI adoption is crucial — The goal for courts is not to automate blindly but rather should adopt a balanced AI-forward mindset.

    • Ongoing education and adaptability are vital — AI literacy requires continuous learning and upskilling that focus on building managers’ comfort and capability to lead their teams.

For today’s court system, AI literacy is quickly becoming a core professional skill, not just a technical curiosity. In the recent webinar AI Literacy for Courts: A New Framework for Role-Specific Education, panelists emphasized that courts need to move from holding abstract conversations around AI to enacting concrete, role-based strategies that support judicial officers and court professionals throughout their AI journey.

The webinar is part of a series from the��, a joint effort by the National Center for State Courts (NCSC) and the Thomson Reuters Institute (TRI).

The need for AI literacy is great

Courts are being urged to treat AI literacy as a foundational pillar of AI readiness, not as an optional add-on training. AI literacy is “the knowledge, attitudes, and skills needed to effectively interact with, critically evaluate, and responsibly use AI systems,” said the NCSC’s , adding that it cannot be one-size-fits-all. “The important thing to know about the definition of AI literacy is it’s going to be different for every single personnel role.”

Building a serious AI literacy strategy therefore begins with defining what success looks like for each role, and then aligning recruitment, training, and evaluation practices around those expectations.

You can find out more about here

To support this, policy and security concerns must come before (and alongside) AI use. Webinar panelist , Chief Human Resources Officer at Los Angeles County Superior Court, described how the court started by clarifying the sandbox for safe AI use. First, the court’s generative AI (GenAI) policy sets parameters, such as prohibiting staff from using court usernames or passwords to create accounts on external AI tools. Only then, after those guardrails were in place, did the training really lean into the technical how-to of writing prompts and experimenting with tools. Policy development and skills development happened in tandem, Griffin explained.

To make space for learning in an already overloaded environment, her team lit a creativity spark with managers first, she said, giving them concrete use cases — such as drafting performance evaluations, coaching documents, and job aids. As a result, these managers, in turn, feel motivated to create room for their teams to experiment.

This, Griffin added, is all anchored in a clear, people-centered message from leadership: “We have a lot of work to do, and not enough people to do our work — and so AI is going to help us serve the court users and help us provide access to justice.”

You can register for here

How to make AI “work”

On the webinar, the conversation repeatedly returns to what lawyers and court professionals are actually doing with AI tools today and where they’re getting stuck. , Founder of Creative Lawyers, noted that despite AI’s rapid advance, many professionals are still at a surprisingly basic stage in how they use it. For example, Leonard said that users tend to treat AI as a one-way question-and-answer box instead of using it as an expertise extractor that asks them targeted questions. To combat this, she suggested that users ask AI to ask them questions to extract from their expertise.

When thinking about how to interact with AI generally, users should treat it like a smart colleague and ask themselves (and implicitly the AI) these questions:

• • • What information would this colleague need from me to do the assignment well?

    • What questions would I want them to ask me?

    • What specific task do I actually want them to execute?

    • What feedback would I give them to make the work product better?

As the webinar examined, leadership messaging needs to be explicit. AI is being adopted to augment human work, reduce burnout, and expand access to justice — not to eliminate jobs, particularly in courts that are already understaffed. For example, LA Superior Court has been meeting with unions around their GenAI policy, repeatedly affirming that they are not using AI to replace court staff, Griffin said. Instead, they show how AI can be used to demonstrate use cases, and offload repetitive tasks that will make remaining work more meaningful.

At the same time, managers themselves often feel unprepared to talk about AI, which is why building their comfort and capability — especially around explaining where the court is going — is becoming a critical managerial competency, panelists noted.

Supporting the journey

To support all of this, the TRI/NCSC AI Policy Consortium has built practical training resources that courts can plug into their own strategies. For example, the offers curated materials mapped to specific roles such as judges, court administrators, court reporters, clerks, and interpreters. Courts can use these resources as targeted supplements when rolling out AI projects to better prepare staff members who are just starting their AI journey.

Complementing this is the , an environment in which staff can safely experiment with GenAI tools without sending data back to the open internet. This gives judges and staff a place to practice prompt-writing, ask follow-up questions, and give feedback, all while staying inside a controlled environment and within the bounds of most court AI policies.

Looking ahead, the panelists argued that the most durable “future skills” may not be specific technical proficiencies but human capabilities, such as adaptability, creativity, critical thinking, and change leadership. In fact, HR leaders across industries largely agree they cannot predict exactly which tools or skill sets will dominate in a few years, Griffin said, and instead, courts should focus on helping managers to craft better prompts, interpret outputs critically, and lead their teams through repeated waves of technological change.

Leonard similarly urged legal organizations to move beyond basic, adoption use cases — such as document summarization and email refinement — and start exploring more creative, transformative uses that could redesign legal services and court systems to be more responsive to the public.

Finally, the webinar stressed that AI literacy cannot be a one-and-done initiative. The , published by NCSC, encourages courts to treat AI projects as catalysts for revisiting their overall literacy strategy and HR practices.

You can find out more about the work that NCSC is doing to improve courts here

Key insights:

• • • Continuous AI upskilling is critical for a competitive advantage — Organizations must mandate and incentivize diverse learning approaches. Indeed, professionals with good AI knowledge are 2.8-times as likely to see organizational benefits.
    • Culture of experimentation drives AI success — Organizations that foster experimentation and adaptability see significantly better results. Professionals who feel encouraged to try new ways of working are nearly twice as likely to see tangible benefits from adoption of AI.
    • Generational differences require tailored approaches — The research uncovers important generational nuances with Gen Z-aged professionals twice as likely to identify digital literacy gaps among their colleagues while Baby Boomers report lower AI proficiency.

It is not just the rise of AI that is reshaping the future direction of business. Instead, it is how professionals within organizations adapt and thrive alongside this transformative technology. As Steve Hasker, President & CEO of ��������, recently stated in the 2025 Future of Professionals report: “AI will not replace professionals, but AI-powered professionals will.”

Indeed, while AI offers immense potential, it is the human element — including the willingness to learn, adapt, and collaborate — that will determine whether organizations and their professionals realize AI’s full value.

The survey research underpinning this year’s Future of Professionals report reveals insights on the people-related barriers and skill gaps that must be addressed to allow professional services organizations to unlock sustainable innovation and competitive advantage. The report also contains several recommended actions for companies that wish to future-proof their AI-enabled operations.

Here are two of those actions:

Action 1: Mandate and incentivize continuous AI upskilling

Widespread skill gaps in technology and data proficiency have emerged as a critical barrier to realizing the full benefits of AI across professional services, the report showed. In fact, 46% of professionals surveyed report skills gaps within their teams, which include power skills, such as responsiveness and interpersonal communications. In addition, 31% specifically cite deficits in technology and data skills.

These gaps pose significant risks for professionals. As organizations race to adopt AI, those professionals who do not prioritize upskilling risk not only losing their competitive edge but also diminishing the value that they can deliver to clients and stakeholders. Further, while an impressive 96% of professionals say they now have at least a basic awareness of AI capabilities, the majority (71%) still feel unprepared for practical implementation.

In addition, generational differences add further complexity to the upskilling challenge. Gen Z professionals are twice as likely as Baby Boomers to identify insufficient digital literacy among their colleagues, sometimes expressing frustration at their teams’ ability to leverage technology for greater efficiency, the research shows. Interestingly, Gen X-aged individuals, who now comprise nearly half the workforce, demonstrates stronger technological engagement than commonly assumed and participate in AI training at rates that often exceed those of their younger colleagues.

In contrast, Baby Boomers self-report lower AI proficiency and engage less in AI-focused learning, which may be understandable given their advanced career stage, However, that still leaves a gap that organizations cannot afford to ignore. Addressing these generational nuances through tailored upskilling initiatives will be essential for organizations seeking to build truly AI-ready teams and ensure sustainable, long-term growth.

The report underscores that the biggest predictor of AI proficiency is engaging in a variety of learning methods, both on an organizational and individual level. This is why companies need to adopt a variety of learning modalities — including formal training, hands-on experimentation, peer collaboration, and active involvement in AI development — to enable their professionals to learn and adapt in order for the organization to obtain the full return on its investments.

All of these efforts contribute to greater skill acquisition. Indeed, professionals with good or expert AI knowledge are 2.8-times as likely to see organizational benefits from AI than their less proficient peers.

Action 2: Foster a culture of experimentation and permanent mindset shift

Fostering a culture of experimentation and adaptability, along with an accompanying mindset shift is essential for organizations if they seek to unlock the full potential of AI. Despite rapid technological advancements, resistance to change and outdated professional mindsets remain persistent barriers to progress.

The report research reveals that even though a small percentage of respondents specifically cite mindset gaps — such as reluctance to adapt and resistance to change — as major obstacles on their teams, such a disconnect can become a problem. Moreover, there is a growing concern about overreliance on technology with 24% of professionals saying they worry that excessive dependence on AI could limit the development of core professional skills.

The good news is that most professionals are open to new approaches. In fact, 80% report feeling encouraged to try new ways of working; however, this encouragement is not evenly felt across all generations. Gen Z, for example, is less likely than their older counterparts to feel empowered or supported in experimenting with AI and innovative workflows. This highlights the importance of leadership and organizational culture in bridging these generational divides.

Our research also illustrates that fostering a culture that values experimentation and adaptability is proven to deliver results. According to the report, professionals who feel encouraged to explore new ways of working are nearly twice as likely (1.9-times) to see tangible benefits from adoption of AI. This finding underscores the need for organizations to actively promote a growth mindset and provide safe environments for testing new ideas, learning from mistakes, and sharing insights.

In the view of ��������: “This new mindset also requires professionals be willing to experiment, learn from their (and others’) mistakes, and continuously adapt to the rapidly evolving AI landscape.” By prioritizing adaptability and an experimental approach, organizations can ensure their workforce not only keeps pace with technological change but also thrives in an AI-enabled future.

The future of work belongs to those organizations that prioritize people as much as technology and to those professionals who aim to improve their tech prowess. By actively closing skill gaps, nurturing a culture of experimentation, and addressing generational needs, businesses can unlock AI’s full potential.

As the 2025 Future of Professionals report emphasizes, AI-enabled professionals will gain a competitive edge by boosting both their personal impact and their organization’s long-term value.

You can download your copy of the��2025 Future of Professionals Report here

However, as global trade continues to grow — both in volume and complexity — there are growing concerns whether existing skills and training are keeping pace with today’s needed requirements of the profession.

The double-edged sword of technology

Technology is helping organizations deal with the growing complexity — automating numerous tasks that are otherwise laborious and time-consuming, and handling everything from the voluminous paperwork involved in shipping, logistics, and customs to drafting contracts and translating documents. And this has enabled businesses and organizations to greatly improve their efficiency, even as global trade complexity increases.

However, Rowden says she is worried that the growing use of technology could be eroding some core skills needed by global trade professionals. Many senior trade professionals gained their experience over recent decades during which global trade grew tremendously, providing them with critical grounding and foundational knowledge of how the current trade systems and policies evolved into their current state.

Citing customs as one example, Rowden explains that while specific details and policies may differ between countries, the primary building blocks are generally similar. This is largely because many of the key attributes — such as place of origin, classification, valuation, bills of lading, intellectual property ownership, etc. — have been defined, measured, and tracked literally since the dawn of cross-border trade centuries ago by caravan and sea. While processes have grown more sophisticated over time, the fundamental concepts remain largely the same.

“It’s like playing 3D or even 4D chess in order to balance and manage the multiple factors, issues and scenarios that are involved every day.”

There have been significant shifts in recent decades in how global trade professionals are trained, however, Rowden says. One catalyst was the aftermath of the events of the 9/11 terrorist attacks, which prompted a renewed emphasis on security. “While both understandable and necessary, given the circumstances, the increased orientation around security oftentimes came at the expense of core training on many of the basics,” she adds.

Another growing trend has been the emergence into the profession of digital natives — people born after the birth of Internet — a transition that is still taking place. Rowden says she is concerned that the new generation of global trade professionals may be overly reliant on technology and are not as accustom as previous generations to thoroughly validating everything from record-keeping to decision-making. She says she believes it’s critical for today’s trading professionals to understand and question the underlying data, calculations, assumptions, and scenarios rather than simply relying on the outputs contained in a spreadsheet or other application.

“Trade is a highly data-intensive field,” explains Rowden. “I teach global trade as an adjunct professor, and I’ve increasingly noticed that many students can’t discern between different sources of information and have difficulty validating information.

“You may have heard the phrase ‘there is but one truth,’” she adds. “For trade, you want there to be one truth: the system of record. Validation is a critical part of the process for ensuring the integrity of data within the system of record. And not having the necessary expertise for carrying out that validation could pose serious problems. I see this as a growing exposure for both government agencies and private sector companies.”

Need for global trade education

Academia can play a key role in bridging these skills gaps, she says, noting that academic programs may be best equipped to develop the multi-disciplinary curriculum that will be needed. Indeed, today’s global trade environment requires that professionals possess a comprehensive range of skills to tackle the growing complexity of the field.

“There’s an incredible number of moving parts in global trade,” says Rowden. “It requires sophisticated understanding of economic, tax, and trade policies and how they interact, as well as technical skills such as data analytics and management. Developing curriculum to cover all of these fields and integrate them into a global trade discipline will be challenging.” Further, Rowden says she believes that certification programs will be essential to improving and expanding global standardization of trade practices. Currently, however, the industry generally lacks certification programs that are dedicated specifically to global trade.

Looking ahead, the continued adoption of generative AI into trade operations will change how global trade work is conducted, what skills trade professionals will need, and what educational tools will be available and most effective. For Rowden, that is all the more reason why improved education and certification are essential ways to ensure that global trade professionals are in a position to successfully manage global trade as it continues to grow in complexity.

You can download a full copy of the Thomson Reuters Institute’s����here

If you want to see the impact of organizational resilience in your company by 2025, acting now is critical.

After attending numerous conferences and meetings over the past three months, I’ve noticed one thing repeatedly missing — the How. Many corporate leaders understand the importance of organizational resilience and its urgency, but few are taking strategic action. Why is that? I’ve narrowed it down to three possible reasons: i) it’s not a priority; ii) it doesn’t fit in the budget; and iii) the company doesn’t know how.

In this second installment of our three-part blog series on organizational resilience, we’ll discuss these setbacks that are preventing action and a process for managing them while building resilience in your company.

Making organizational resilience a priority

Organizational resilience isn’t a priority for many companies because its cost is not fully appreciated. Companies often dismiss it as a well-being initiative or a nice-to-have without calculating the actual costs of non-implementation, a running expense that’s accumulating daily.

Organizational leaders should start by asking: “What are the outcomes we want from an organizational resilience initiative?” Most companies will mention retention, engagement, productivity, and margins — and while these are valid goals, they are short-sighted if they don’t consider what employees also need in order to achieve them.

Think of a sick goldfish in a bowl of dirty water. The fish is dying, so what do you do — give it medicine or change the water? If we compare this to a burned-out employee in a toxic work culture, we see that both actions are needed. A toxic work culture (dirty water) only worsens over time, and one burned-out employee (sick fish) can bring down a whole team.

“As leaders, we need to proactively anticipate challenges before they actually occur. I do this with my teams,” says Kristi Eckert, Global Consulting Partner at EY, adding that programs that overlook employee needs usually result in failure.

Often, employees don’t care about engagement or retention — they want real work-life balance, less stress, and the ability to cope with daily pressures. To make transformational progress, you need to address both sides of the equation. “Every employee has their own unique needs, and we need to be very mindful in the way we engage,” Eckert says.

Leaders should identify their companies’ goals, and then determine what their employees need to achieve those goals. Once leaders understand the full cost, they’ll want to prioritize organizational resilience immediately.

Finding a budget for organizational resilience

In the first installment of this series, you were challenged to identify a budget. While it sounds simple, I know finding money can be difficult, but here’s a key insight: Most companies have hiring budgets, but few have retention budgets. This demonstrates that many companies’ focus is on replacing lost talent rather than retaining existing talent.

The Society for Human Resource Management (SHRM) and other sources report that replacing a highly educated employee can cost 50% to 200% of their annual salary. Higher-level employees can cost even more. These expenses include advertising, recruiting, hiring, on-boarding, and training a new employee to full productivity.

If you’re looking for a resilience budget, then start with your hiring budget. What if you reallocated 10% of your hiring budget to retention? Let’s consider a hypothetical scenario: If you invested $100,000 in organizational resilience programs for all employees, that’s likely less than the cost of replacing even one employee. Therefore, a successful program might only need to retain one person to breakeven, and two to be a success.

Many company leaders think of wellness initiatives as a waste of money because they aren’t implemented with a return on investment (ROI) in mind. Yet even simple programs can significantly improve employee well-being and resilience when planned thoughtfully.

A process to kick-start organizational resilience

Now that you’ve committed to prioritizing and budgeting for organizational resilience, it’s time to determine the right approach. While no single method is inherently better than another, there are key decisions you must make when shaping your company’s resilience framework:

Go wide vs. Go deep

• • • Go wide — Implement broad solutions for the entire workforce, potentially including company-wide strategies that address common stressors.
    • Go deep — Target specific groups within the organization. For example, you may focus on improving retention at the manager level or helping entry-level employees set boundaries.

Top-down vs. Bottom-up

• • • Top-down — Start with leadership. Equip leaders with the tools to manage their stress, then teach them how to recognize and support burned-out employees.
    • Bottom-up — Start with employees. Provide resources, channels, and support that can be accessed throughout the company. Encourage employees to ask for help when needed.

Tactics vs. Mindset

• • • Tactics — Teach employees practical skills such as time management and stress reduction. While these are essential, these skills alone are usually not enough to drive lasting change.
    • Mindset — Help employees develop a resilient mindset that can handle change, challenges, and uncertainties. A strong mindset is key to fostering long-term resilience.

Regardless of the decisions you make, it’s crucial that company leadership sets the tone and that employees are fully engaged and understand that the company is genuinely committed to these efforts. Ultimately, it’s the organization’s responsibility to implement the plan and ensure its success. Indeed, there are four key steps that can help make that happen:

1. 1. 1. Implement the plan
      2. Regularly evaluate progress
      3. Make necessary adjustments, and
      4. Repeat

“You aren’t going to get it right 100% of the time,” explains EY’s Eckert. “But if a company has built the infrastructure and can demonstrate the ability to be agile and adaptable then it can start to create resiliency that leads to success.”

Solving for organizational resilience isn’t a quick fix, but there are tangible actions you can take to create lasting change. By following these four steps with consistent effort and commitment, you can help your company and its employees reach their long-term goals with greater odds of success.

Next steps

Building a resilient organization requires a thoughtful and sustainable approach — and we no longer can rely on old solutions to fix new problems. And now that we’ve addressed the problem, the solution, and the process, here’s what to do next:

1. 1. 1. Identify your goals — Consider both the company’s and its employees’ needs.
      2. Finalize your budget — Begin re-allocating from your hiring budget if necessary.
      3. Take action today — Now, is one of the best times to start.

In the final installment of our 3-part��Organizational Resilience series, we will examine the results you can expect once your organization achieves its resilience goals.

An economist opened the panel by describing a still-tight labor market, particularly for skilled workers, despite a slight rise in overall unemployment. While inflation has generally cooled, wage-based inflation persists, making the search for talent as competitive as ever since the end of 2020.

Compensation: Rewarding excellence

One of the key topics discussed was, not surprisingly, lawyer compensation. The era of double-digit compensation increases may be over but retaining standout talent remains crucial in a competitive market. The focus is now on ensuring that overachievers are properly rewarded and retained.

One panelist highlighted their organization’s dual focus on the what and how as part of their review process and the resulting emphasis on those factors that should be used to enhance compensation. The panelist described their firm’s approach as one that’s anchored in clear financial metrics and three broad parameters: i) resilience in the face of challenges; ii) proficiency in training and adaptability; and iii) confidence in leadership.

In the ongoing competition for top talent, if a law firm fails to grow and accelerate their overperforming lawyers early, there is a tendency to lose them.

These metrics are crucial for evaluating performance and driving the firm’s success, the panelist explained, adding however, that one of the growing challenges they were tackling involved those lawyers who are just starting to grow and overachieve. In the ongoing competition for top talent, if an organization fails to grow and accelerate these overperformers early, there was a tendency to lose them. As such, the panelist said their firm now spend a great deal of time at this point to identify these emerging talents and seek to retain them.

Another panelist discussed the significance of rewarding innovation. They pointed out that support for people who use tools like Alteryx, which empower frequent users to automate repetitive tasks and reduce the time spent on monthly processes, is crucial. This, in turn, enhances employee morale and productivity, and thus firms should promote greater compensation for the people who make it possible.

The shift towards automation and efficiency is particularly relevant in the legal sector, where increased use of artificial intelligence and automation tools is becoming a defining feature in the legal industry. By incentivizing innovation, law firms can not only improve operational efficiency but also create a more dynamic and motivated workforce. Indeed, offering the right incentives to the people who make this happen is thus all the more important, especially in a labor market in which poaching top talent remains a constant threat due to competitors’ ability to offer hybrid and flexible work options.

Flexible work arrangements

As the conversation moved away from compensation and towards other employee benefits, one potential perk in particular came to dominate the discussion: flexible work arrangements.

One panelist noted that while there is a clear need for lawyers to be present in the office on specific days, there is also considerable flexibility available regarding which days these are. The general expectation at their firm was for a minimum of two days in the office, with a goal of three days to facilitate collaboration and teamwork.

Another panelist pointed out that dedicated spaces for teams can really help make in-office days productive. However, they acknowledged that a fully remote culture is not feasible for law firms, which thrive on in-person interactions and spontaneous exchanges of ideas. That panelist said their organization succeeded by merging their offices into a new location, hosting regular lunch events, and cultivating an atmosphere where FOMO (fear of missing out) about office events was a major motivator for attendance.

The still-ongoing “war for talent” is pushing many law firms to seek talent in unconventional locations, leading to cross-geographic teams and frequent teleconferencing.

Yet according to another panelist, the still-ongoing “war for talent” is pushing firms to seek talent in unconventional locations, leading to cross-geographic teams and frequent teleconferencing. This reality raises questions about the necessity of in-office presence, as virtual collaboration becomes increasingly effective and the norm. By having these types of teams in which someone is always remote, it means that even those members in the office spend their days on virtual meetings, raising the question of why they have to take these meetings in the office in the first place.

The panel determined that the hybrid work dilemma remains unresolved in the legal industry and elsewhere, and that the current new normal has legal organizations maintaining a balancing act between luring people into the office and trying to make online work as effective and collaborative as possible.

The pandemic hangover

Prior to the panel’s discussion, Institute, offered a comprehensive view on how the pandemic has affected the labor economy. He noted that the pandemic has fundamentally altered how organizations function and engage with their employees. Issues like quiet quitting, talent retention, and cultural development have become central topics as firms navigate the post-pandemic environment.

Yet, significant progress has been made in tackling these challenges over the past 12 to 24 months, Abbott explained, adding that still more effort is needed to fully comprehend and adjust to the new conditions of the labor market.

While the panel didn’t venture into this territory explicitly, it was difficult to escape the impression that a solution had been found to the hybrid work issue, that the 2 to 3 days in the office with additional work to make sure those who were in the office benefitted from it, had become the solution de jour for law firms. Much like major banks and companies that continue to grumble about this new status quo, many legal organizations merely do not like the answer as much as they may wish they did. However, they are increasingly spending time smoothing down the pain points rather than seeking to overturn the entire paradigm.

For now, the panel’s conversation seemed to cement that this new reality may be here to stay.

For more on what you might have missed at the Thomson Reuters Institute’s 23rd Annual Law Firm COO & CFO Forum, click here.

Looking into 2024 and beyond, the future appears to be just as turbulent. To make sense of these dynamic changes, the BANI model provides a spot-on description of these realities:

• • • Brittle refers to the fabricated narratives that individuals share among themselves to foster a sense of comfort and security.
    • Anxiety is characterized by feelings of powerlessness and being overwhelmed by one’s circumstances and is a subjective feeling caused by a gap between what one expects and what one experiences. To combat anxiety, people need a sense of control.
    • Non-linearity is a concept connecting two or more variables that does not follow a linear pattern, and the chaos of the world follows a nonlinear pattern as a foundational trait of any intricate system.
    • Incomprehensible describes a situation in which individuals struggle to understand unfolding events that they find themselves unable to comprehend, interpret, or make sense of as to what is happening and why.

BANI primarily reflects our perception of the situation rather than the world itself. However, it is just that — a sense. With 24/7 information flow, unrest, economic uncertainty, and dramatic technological change, control becomes an illusion.

At the end of the day, however, we can only control how we respond to these simultaneous, destabilizing shifts. As Gordon Moore, co-founder of Intel once stated: “Change has never been this fast and will never be this slow again.” That means that BANI circumstances brought about by change and increasingly fast-paced change is telling a person’s brain, Oh no. I am under threat. What do I do now? I need to find safety.

If safety is not found, panic in humans is hardwired as a natural response, and the threat response driven by fear can start to lead to stress. This acute stress, which was useful when humans needed to run away from beasts during the Paleolithic age, is triggered by the flight. flight, or freeze response, but it is not so useful when dealing with chronic stress.

Power skills development to cope with change

One of the ways employees and organizations can effectively respond in the wake of chronic uneasiness is through skills development; and power skills, formerly known as soft skills, are a critical element to creating thriving workplaces. Power skills include developing capabilities for leaders, individual contributors, teams, and functions. These leader capabilities include managing talent, strategic execution and direction, coaching, and leading through change, according to a

Key power skills for individuals include adaptability, resilience, change ability, decision-making and problem solving, and being planful. Among teams, collaboration, communication, influencing, emotional intelligence, and networking are the primary power skills; and at the organizational level, power skills include business acumen, organizational awareness, and risk management.

The swift pace of change and the sense of destabilization are altering the landscape of workplace skills, making the development of power skills essential to human, employee, and workplace well-being during chaotic times. The time is now for employers and employees together to invest in power skills. However, it is important to remember that the more enduring and adaptable skills and competencies becomes more complex when considering the varied experiences of employees and economic conditions.

Power skills include developing capabilities for leaders, individual contributors, teams, and functions.

To maintain high employee productivity, skills development across employees most often focuses on tasks and functional skills. These naturally are easier to teach and train, and it’s often easier to determine their impact in terms of return of investment (ROI) because of the straightforward nature of their impact on efficiency.

Power skills, however, are more difficult to master because in many cases, they require experiential experimentation and intentionality. In addition, the ROI can be nebulous because of the nonlinear nature of seeing the impact. Moreover, when forced to choose between one or the other, task and functional skills will usually win. For example, only 32% of respondents reported that their office workers were highly proficient at leadership skills and competencies, according to the McLean report, which also noted that across office and non-office workers, task and functional skills are being prioritized disproportionately, while power skills are more closely associated with organizational success.

When all employees are highly proficient at power skills at the individual, team, organizational, and leadership levels, however, a flywheel effect occurs for the organization. More specifically, organizations cultivating power skills, according to the same report, are:

• • • 1-times more likely to be high performing at the ability to change at scale to capitalize on new opportunities at the individual level;
    • 1-times more likely to be high performing at diversity, equity, and inclusion among teams;
    • 1-times more likely to be high performing at generating and implementing new ideas at the organization level; and
    • 8-times more likely to be high performing at shaping a strong organizational culture by leadership.

While task and functional skills are important for productivity, underinvesting in power skills in the long run does a disservice to the organization and its employees multi-dimensionally. Organizations should be preparing their workforce with resilient skills and competencies to successfully navigate the circumstances of the BANI model and the ongoing changes and disruptions occurring in 2024 and beyond.