Key insights:

• • • Non-compliance is significantly more expensive than compliance — Data consistently shows the cost of non-compliance can be greater than proactive compliance investments.

    • Reputational damage and hidden costs often outweigh direct fines — Beyond financial penalties, the damage from legal fees, loss of customer trust, and operational disruptions from non-compliance can inflict long-term harm.

    • Strategic investment in compliance yields a competitive advantage — A robust compliance program builds trust, attracts investors, and demonstrates greater operational resilience in a complex regulatory landscape.

There’s a persistent myth in the business world that compliance programs are a necessary burden, a line item to be minimized and managed rather than invested in strategically. The data tells a very different story, however, and it has for quite some time. For organizations still treating compliance as an overhead expense, it’s time to reconsider the math and view the broader strategic picture.

The numbers don’t lie: Non-compliance costs more

Non-compliance costs are 2.65-times the cost of compliance itself, a finding that dates back to the of multinational organizations. While the average cost of compliance for the organizations in that study was $3.5 million, the cost of non-compliance was much greater. That means simply by investing in compliance activities, organizations can help avoid problems such as business disruption, reduced productivity, fees, penalties, and other legal and non-legal settlement costs.

According to a later report from from 2017 (the most recent set of analytical data on the subject), the numbers have only grown more striking. The study showed that average cost of compliance increased 43% from 2011 to 2017, totaling $5.47 million annually. However, the average cost of non-compliance increased 45% during the same time frame, adding up to $14.82 million annually. The costs associated with business disruption, productivity losses, lost revenue, fines, penalties, and settlement costs add up to 2.71-times the cost of compliance.

And these non-compliance costs from business disruption, productivity losses, fines, penalties, and settlement costs, among others aren’t simply abstract risks. They’re real, recurring, and measurable, and they don’t stop with the fine itself.

Beyond the fines themselves, legal costs are a significant and often underestimated component of non-compliance.

This gap between compliance and non-compliance provides evidence that organizations do not spend enough of their resources on core compliance activities. If companies spent more on compliance in areas such as audits, enabling technologies, training, expert staffing, and more, they would recoup those expenditures and possibly more through a reduction in non-compliance cost.

While the math here is straightforward, the strategic case is even clearer. Compliance isn’t overhead; rather, it’s an investment with a measurable, proven return.

The hidden costs: Legal fees, fines & reputational fallout

Regulatory fines get the headlines, but they represent only part of what non-compliance actually costs an organization — a cost that has only risen over time. As of February, a total of 2,394 fines of around €5.65 billion have been recorded in the database, which lists the fines and penalties levied by European Union authorities in connection with its General Data Protection Regulation (GDPR).

Beyond the fines themselves, legal costs are a significant and often underestimated component of non-compliance. Regulatory norms are shifting constantly and navigating them requires specialized expertise. As quickly as the rules change, outside counsel and compliance specialists must keep pace, and that knowledge comes at a price. Every alleged compliance violation triggers an immediate need to engage qualified counsel, adding to a cost burden that compounds quickly and unpredictably.

Then there is reputational damage, perhaps the most enduring consequence of all. The cost of business disruption, including lost productivity, lost revenue, lost customer trust, and operational expenses related to cleanup efforts, can far exceed regulatory fines and penalties. Consider , whose compliance failures around its anti-money laundering (AML) efforts became a cautionary tale for the industry. TD Bank’s massive $3 billion in fines from US authorities wasn’t just the result of a few missteps; rather, it was caused by years of deep-rooted failures in its AML program, pointing to a culture that prioritized profit over compliance.

The findings from both the 2011 and 2017 studies provide strong evidence that it pays to invest in compliance.

TD Bank’s failure to make compliance a priority not only led to a huge fine but also seriously damaged its reputation, with revising TD’s outlook to negative in May 2024, where it remains. This is the kind of a reputational stigma that can take years to repair.

Leveraging compliance as a competitive advantage

There is also a positive side of the ledger that often goes unacknowledged. A robust compliance program signals to investors, partners, and clients that an organization is well-governed and trustworthy. That reputation doesn’t just retain market value; it actively attracts it.

Organizations that cut corners in compliance risk engaging in a short-sighted, high-risk strategy that will ultimately result in a negative outcome for the organization. Businesses that take compliance seriously tend to operate with greater predictability, fewer surprises, and stronger stakeholder confidence.

The 2017 Ponemon and Globalscape and study found that, on average, only 14.3% of total IT budgets were spent on compliance then, not much of an increase from the 11.8% reported in 2011. This clearly indicates that organizations are underspending on core compliance activities in the short term and aren’t prepared to allot further resources as the years go on. That gap represents not just risk, but a clear missed opportunity.

“The findings from both the 2011 and 2017 studies provide strong evidence that it pays to invest in compliance,” explains Dr. Larry Ponemon, Chairman and Founder of the Ponemon Institute. “With the passage of more data protection regulations that can result in costly penalties and fines, it makes good business sense to allocate resources to such activities as audits and assessments, enabling technologies, training, and in-house expertise.”

The organizations that recognize compliance as a strategic function, not a reactive one, are the ones that will earn the trust of clients, the confidence of investors, and the operational resilience to weather an increasingly complex regulatory environment. The data is clear, and the choice is a critical one.

Please add your voice to ��������’ flagship , a global study exploring how the professional landscape continues to change.��

Key insights:

• • • A significant visibility gap persists between legal departments and the C‑Suite — Most general counsel believe their legal department contributes strategically, yet senior executives often fail to see or understand that value.

    • Strong internal relationship‑building is critical (and often underdeveloped) — This capability enables legal teams to spot risks earlier, stay embedded in decision‑making, and make their work more visible across the business.

    • Closing the gap requires communicating legal’s value and increasing true AI fluency — For legal teams to be seen as proactive, strategic partners rather than task executors, communication and strong AI fluency are essential.

General counsel (GCs) have spent years doing more with less, tightening their legal spend, and aligning the law department’s priorities with the wider business. And yet, despite all of this effort, a striking visibility gap persists. While 86% of GCs believe their department is a significant contributor to overall organizational objectives, only 17% of the C-Suite agrees, according to the , from the Thomson Reuters Institute, which was based on more than 2,300 interviews with corporate general counsel. Meanwhile, 42% of C-Suite executives say the legal function contributes little or not at all to company performance.

The challenge for GCs is whether their staff have the skills and capabilities to make their work visible, relevant, and understood by the business at large. To address this perception gap in 2026, every GC needs to prioritize building richer internal relationships with business leads, moving from task-based to outcome-focused messaging, and improving the team’s collective AI fluency.

Empower teams to build internal relationships

Nearly half of all GCs surveyed for the report cited staffing and resource constraints as the top barrier to delivering additional value, a concern that has remained stubbornly consistent for years. Beyond headcount, the report underscores that the deeper challenge facing legal departments is relational.

Internal relationship-building is one of the most critical and underrated people skills in a legal department’s collective skill set. Indeed, 68% of GCs rate internal dialogue as their most valuable source of information about emerging risks. In fact, the most successful GCs use a deliberate combination of formal and informal methods to build connections with the internal business units that they serve.

You can learn more about how to assess your legal department’s strategic positioning with the��Thomson Reuters Institute’s Value Alignment toolkit, here

Some run structured weekly face-to-face sessions with business departments, complete with schedules, plans, and frameworks. Others rely on walking the halls, open-door policies, and ad-hoc conversations that keep the corporate law department visible and accessible on a human level.

The report offers a five-dimensional framework to help GCs audit where, with whom, and how often legal is in dialogue with other parts of the business.

Use communication tactics that focus on business outcomes

Even when legal departments are doing excellent work, they often describe it in the wrong language. Many in-house lawyers categorize their contributions in task-based terms — such as “We support M&A” or “We analyze contracts” — rather than in value-creating terms.

Some in-house legal leaders have progressed to stakeholder-level framing, such as, “We protect the company from competitive threats” or “We support new business opportunities.” Still, neither of these levels truly communicates value to a C-Suite audience, the report shows.

To effectively align the law department’s priorities with business goals, in-house attorneys need to develop the skill of communicating through a business lens. For example, one GC states that the primary goal of the law department is to “find the fastest and most compliant way for the sales department to sell products.” This response reframes the legal function’s activities as much more business fluent and value-added.

Legal teams are not always good at touting their accomplishments, however, and this is a challenge when a lot of the work can be categorized as invisible. For example, when protecting the company is done right, threats are eliminated before they occur and no one notices. When efficiency is unlocked through process improvement, the C-Suite only sees the outcome if someone connects the dots explicitly. This is why surfacing invisible value is now a business imperative for corporate law departments.

Advancing from AI literacy to AI fluency

The most significant skills challenge facing legal departments in 2026 is how to best use AI strategically. Mentions of AI as a strategic priority among GCs have doubled in the past year, according to the report. In fact, almost half of all GCs now reference AI in their survey interviews. Yet the report draws a sharp distinction between being AI literate and being AI fluent, with most departments being the former but not the latter.

To close that gap, the report recommends a six-layer model covering learning, empowerment, ownership, accountability, usage, and expectations.

At its core, the model asks GCs to start with open encouragement and access to AI tools to build momentum, then shift toward more formal expectations around adoption to make AI use a daily habit.

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

Key takeaways:

• • • Human trafficking is a financial crime — Without the financial system, human trafficking networks cannot operate at scale. Banks, compliance officers, money transmitters, and casinos are uniquely positioned to detect suspicious patterns.

    • The 2026 World Cup amplifies existing risks — With 5.5 million additional visitors expected in Mexico City alone, criminal networks will exploit the surge in cash flows, new customers, and cross-border movement.

    • Red flags are observable in financial behavior — Human trafficking networks often leave detectable financial footprints, which is why financial institutions must update monitoring systems and stay alert to unusual transaction spikes during the tournament.

MEXICO CITY — As the 2026 FIFA World Cup get ready to hold its tournament in June and July across three North American countries, anti-human trafficking experts are meeting as well and attempting to address the challenges facing the three host countries of the largest World Cup in history.

To that end, the Association of Certified Anti-Money Laundering Specialists (ACAMS), in partnership with ��������, organized one such event, focused on the scourge of human trafficking that often surrounds large sporting events like the World Cup.

One speaker at the event noted an important clarification in the difference between human trafficking and human smuggling — two terms that are frequently confused yet carry vastly different legal and humanitarian implications. The key distinction lies in consent and the nature of the crime. In human smuggling, the individual being transported across borders consents to the movement, typically driven by socioeconomic necessity, and the offense is considered a crime against the state. Human trafficking, by contrast, is a crime committed directly against the victim, often involving exploitation through force, coercion, threats, or deception, and does not require the crossing of any international border.

The ACAMS event challenged the common belief is that human trafficking is exclusively sexual in nature. In fact, there are 10 additional forms of exploitation beyond sexual abuse, including slavery, forced labor or services, use of minors in criminal activities, forced marriage, servitude, labor exploitation, forced begging, illegal adoption of minors, organ trafficking, and illicit biomedical experimentation on human beings.

As the World Cup approaches, financial institutions’ compliance teams must recognize that the same operational conditions that make major sporting events exciting are precisely the conditions that money launderers and traffickers seek to exploit.

Still, sexual exploitation remains the dominant form of human trafficking. Indeed, it is the second most lucrative illicit business in the world after drug trafficking, with every 15 minutes of sexual abuse of a trafficking victim generating approximately $30.

Of course, without clients, there is no demand, said one speaker from the ÁGAPE Foundation, an organization that works to raise awareness against gender-based violence and human trafficking.

Financial sector as a key line of defense

When identifying human trafficking, it’s wisest to examine it from a financial perspective to find important indicators, according to several speakers. Indeed, the financial sector plays a critical role given its capacity to detect suspicious accounts and payments, shell companies, cash movements, digital platforms, and commercial operations.

For example, when a customer opens an account or conducts a transaction, certain red flags can be visible, including whether the customer needs to consult notes to answer basic questions such as their address or occupation, or that their responses are not spontaneous or natural. Also, another indicator is if the customer’s profile is inconsistent with the type or volume of transactions being conducted.

For financial institutions, there are other patterns that have triggered alerts in illicit activity in the past, including near-immediate deposits and withdrawals with no clear justification for the cash flow, or multiple individuals registered at the same address or linked to the same account.

Similarly, another red flag would be if there’s a high number of accounts opened from the same state or municipality with similar patterns, particularly in areas identified as origin points for trafficking networks; or, payment of multiple short-term rentals or payments abroad to unverifiable recruiters or employment agencies.

Financial institutions should be on the lookout for companies that file no tax returns or invoice simulated transactions, or that use of front men to open accounts or conduct operations.

Also, new businesses whose declared activity does not correspond to their financial operations should be flagged, as well as any frequent, large-volume purchases of condoms, lingerie, or women’s clothing inconsistent with the declared business activity.

Indicators at the 2026 World Cup

In the context of major sporting events such as the World Cup, existing risks are significantly amplified, several speakers pointed out. Sexual tourism, including the commercial sexual exploitation of children and adolescents, is a known and serious threat. Indicators that are relevant not only for the financial and banking sectors, but also for the real estate, tourism, transportation, hospitality, and restaurant industries including unusual accommodation requests, such as deactivating security cameras, delivering keys through third parties, or inquiring about the presence of neighboring guests.

When identifying human trafficking, it’s wisest to examine it from a financial perspective to find important indicators, and the financial sector plays a critical role given its capacity to detect suspicious accounts.

These industries should also be on the lookout for any adult or group of adults traveling with an unusually large number of minors, or individuals who travel in silence and are accompanied by someone who appears to exercise visible control over them.

As the World Cup approaches, financial institutions’ compliance teams must recognize that the same operational conditions that make major sporting events exciting — high transaction volumes, new customers, cross-border flows, and institutional attention diverted toward the event itself — are precisely the conditions that money launderers and traffickers seek to exploit.

For these compliance teams, monitoring systems must be updated, know-your-customer processes must go beyond documentation and reflect a genuine understanding of the client’s activity and context, and on-site verification visits must be conducted by personnel who know exactly what they are looking for.

The financial sector does not need to become an investigative body; however, it does need to remain alert, informed, and willing to report. Indeed, this is exactly what the compliance function exists for, and in the context of human trafficking, the cost of silence is measured not in fines or reputational damage, but in human lives.

Please add your voice to ��������’ flagship , a global study exploring how the professional landscape continues to change.��

Key insights:

• • • Nature-related risks underreported — Companies’ nature-related interfaces are underreported across industries, despite being increasingly seen as decision-useful information for investors and regulators.

    • Stricter requirements for disclosure growing — Both voluntary and mandatory frameworks are increasing their requirements for nature-related disclosure.

    • Organizations should be proactive — Getting ahead of disclosure trends means that organizations should be measuring their nature-related interface as well as integrating nature-positive transition planning to their business strategy.

As the impacts of nature loss become more prevalent, companies are on business risk and performance. This is due to both physical nature-related impacts and increasing stakeholder pressure on organizations to integrate long-term nature-positive strategies. Managing nature-related impacts and dependencies is a framework-driven mandate for all boards of directors to consider.

Why nature matters

All businesses impact and depend on the four realms of nature: land, freshwater, ocean, and atmosphere to some extent, with the highest impact sectors being . These dependencies could include the provision of water supply to an organization, or services provided by nature to a business, such as flood mitigation. A could result in a $2.7 trillion GDP decline annually by 2030. In turn, most businesses also positively and negatively impact nature.

Financial flows that were determined to be harmful to biodiversity reached , including private investment in high impact sectors, with only $213.8 billion (€184.6 billion) invested in conservation and restoration. Despite this financing gap, less than 1% of publicly reporting companies currently disclose biodiversity impacts, indicating the need to align incentives and policies with nature-related outcomes.

Indeed, nature does not have a single indicator, like greenhouse gas (GHG) emissions; instead, its measurement involves multiple complex, location-specific factors. Despite this, disclosure of nature-related risks and impacts are increasingly being required by regulators.

Regulatory incentives to disclose

The disclosures being driven by regulatory frameworks include material information on all nature-related risks, particularly those requested by the International Sustainability Standards Board (ISSB) and European Sustainability Reporting Standards (ESRS). The ISSB Biodiversity Ecosystem and Ecosystem Services project (BEES) was initially considered a research workplan but was modified to a standard-setting approach.

Through its work, the ISSB due to: i) the deficiencies in the type of information on nature-related risks and opportunities reported by entities, which are identified as important in investor decision-making; and ii) the requirement of nature-related information that is not included in climate-related disclosures, including location-specific information on nature-related interface and nature-related transition planning.

On Jan. 28, all 12 ISSB members voted to , which included two important implications. One is that standard setting is to cover all material information on nature-related risks and opportunities that could be expected to affect an entity’s prospects. And two, it mandated that entities applying International Financial Reporting Standards��S1 and S2 for climate-related disclosures supplement these with nature-related risks and opportunities disclosures as well.

Similar to the ISSB requirements to report material nature-related risks and opportunities, the ESRS also requires information to be disclosed for material impacts, risks, and opportunities found in an entity’s double-materiality assessment. The Task Force on Nature-related Financial Disclosures (TNFD) and its European counterparts have been in close collaboration since 2022, and all 14 TNFD recommendations have been incorporated throughout the ESRS environmental standards.

Companies that are required to comply with the EU’s sustainability reporting mandate also will be required to collect similar data for their future ESRS data points disclosure.

Alongside regulatory requirements, there are voluntary requirements and investor pressure to consider for many organizations. These include investor coordination initiatives on nature such as Nature Action 100 and considering which investors look at Carbon Disclosure Project (CDP) data.

To use the CDP as an example, 650 investors with $127 trillion in assets they needed in 2025. Further, the CDP is increasing its disclosure requirements for nature-related data in its questionnaire as it progresses to . This includes, for example, requiring disclosures on environmental impacts and dependencies for disclosers, enhancing commodities included in the forests questionnaire, and introducing oceans-related questions in 2026.

All of these heightened requirements underscore the need to measure a company’s nature-related impacts and proximity to its nature-related issues.

Implications for company boards

To align with these additional requirements and investor expectations, corporate decision-makers should consider the questions they are asking related to nature, as well as what data is being collected in relation to the organization’s impact on nature. The following steps can give leaders a starting point for how boards should consider this information:

Track relevant developments in regulatory and investor standards — Ensure there is a management-level understanding of how nature is considered in relevant standards for the company based on its current and anticipated locations of operation and specific industry.

Measure nature-related risks and opportunities — Given that identifying material nature-risks, with a particular focus on location specificity, is a common first step across current mandatory and voluntary regulatory frameworks, organizations should conduct a regularly updated, location-specific assessment on the company’s interface with nature, especially in instances in which these issues are material. Organizational leaders should also produce financial quantification of these risks within an overall materiality assessment and corporate risk register. For guidance, the best practice across these regulatory and disclosure frameworks is to utilize the .

Make further disclosure of any material nature-related information, including financial quantification — Frameworks such as the ESRS require further disclosure of any risks that are found to be material, including financial quantification and scale of the risk.

Integrate mitigation of nature-related risks in business strategies — Upcoming standards and research, such as that from the ISSB, indicates that missing disclosure includes company’s nature-positive transition planning. Consider how to integrate nature into long-term business strategies for full alignment with upcoming regulations and standards, including establishing nature-related governance.

Adopting these processes and integrating nature into corporate decision-making will provide corporations with a more future-proof and resilient business model. The increased adoption of nature within these frameworks is driven by the clear economic impact that our current loss of nature is having. This will only continue to become more of a priority as the impacts of nature loss are increasingly felt worldwide.

You can find out more about the��sustainability issues companies are facing around the environment��here

Key takeaways:

• • • Disconnect between legal departments and C-Suite perceptions — While many general counsel believe their departments are significant contributors to business success, most C-Suite executives do not share this view. Fully 86% of GCs say they believe their department is a significant contributor, but only 17% of C-Suite executives agree.

    • A need to find new ways to demonstrate value — Legal departments are under increasing pressure to do more with less, as nearly half of GCs surveyed cite staffing and resource constraints as their top barrier to delivering additional value. Despite these limitations, expectations from the C-Suite continue to rise.

    • AI adoption accelerates, business strategy comes next — Legal departments are rapidly embracing technology to improve efficiency, manage resources, and address cost pressures. Not surprisingly, the proportion of GCs calling AI a strategic imperative has doubled.

Over the past several years, general counsel and corporate law departments at large have transformed their operations. Many have become more efficient enterprises, leveraging technology, in particular AI, at an increased pace. GCs have adjusted their hiring practices to conform with the modern corporation, taking new ways of working into account. And they have embraced data-driven decision-making, evaluating outside counsel and their own operations alike with a wider suite of new metrics and KPIs.

But do you know who hasn’t yet realized the fruits of that labor? The corporate C-Suite.

Jump to ↓

2026 State of the Corporate Law Department Report

The , released today by the Thomson Reuters Institute, reveals a disconnect between how GCs and their corporate law departments view their own alignment to the wider business, and what C-Suite executives believe the legal department contributes. Within this gap, the message is clear: GCs not only need to align with their organizations’ overall business strategy, they need to learn how to prove that alignment to the rest of the company.

Indeed, when asked how they view legal’s contribution to the rest of the business, 86% of GCs surveyed said they viewed the legal function as a significant contributor. However, only 17% of other C-Suite executives said the same — and 42% said legal contributes little or not at all.

As the report explains, this disconnect lays the inherent groundwork for the tension facing many GCs today. While they are increasingly aiming to align to business standards, the rest of the organization is not recognizing those actions. Instead, many C-Suites are looking for even more out of today’s legal departments to prove their contributions to organizations’ business imperatives.

As in past years, many in-house legal departments are being tasked to do more with less. Nearly half of GCs cited staffing and resource constraints as the top barrier they face to delivering additional value. Indeed, many said they expected outside counsel spend in some key areas — such as regulatory work and mergers & acquisitions — to remain high. As of the fourth quarter of 2025, more than one-third (36%) of GCs said they expect to increase overall spend on outside counsel over the next year, while only 20% said they plan to decrease their spend.

Despite legal departments’ gains, their C-Suites are looking for them to take the next step, turning operational excellence into business success.

Not surprisingly, many GCs said they view technology as one of the primary ways they have to combat these resourcing and cost issues. In fact, the proportion of GCs mentioning technology as a strategic priority entering 2026 doubled over the year prior. Legal departments have begun to feel positive effects of AI in their own organizations, the report notes, such as increased efficiency or time feed up for strategic work.

Despite these gains, C-Suites are looking for are looking for their legal functions to take the next step, turning operational excellence into business success. This can take a number of different forms, such as explicitly tying advice to client business objectives, presenting legal spend in the context of the business by showing it as a percentage of revenue, or approaching risk management with the goal of aiding business imperatives. “When we have a risky legal subject, the company never prefers just to see the legal opinion,” said one retail GC. “They’re also requesting you to drive them how to make a decision.”

AI and technology should also be approached in this same way, the report argues. Although almost half of all corporate legal departments have some type of enterprise-wide GenAI tool, according to the survey, very few are collecting success metrics around AI’s implementation or linking its use to business revenue. Put a different way, many legal departments are focused on unlocking capacity, rather than deploying capacity in a business-centric way — much to the chagrin of their C-Suites.

Although legal departments have established a solid foundation upon which a business can stand, ultimately, C-Suites don’t want just a foundation. They want help building the entire house, the report shows, directly enabling the services that companies provide to customers. In that, GCs and legal departments have more work to do, not only tying strategy to overall business initiatives but actively communicating how the legal function’s work aids the company as a whole.

You can download

a full copy of the Thomson Reuters Institute’s “” here

Key takeaways:

• • • Become truly client-centered — Legal departments claim to be client-focused yet frequently make strategic decisions about effectiveness without systematically understanding stakeholder needs.

    • Decide where to automate — As AI transforms legal services delivery, decisions about where to automate versus where to deploy human judgment require evidence, not assumptions.

    • Build intelligence with continuous feedback — Systematic stakeholder intelligence reveals where speed matters more than depth, which services lack visibility, and where relationships can create differentiated value.

Today’s general counsels face a fundamental challenge as AI capabilities expand, that of determining where to deploy technology and where to deploy human judgment. Getting this formula right can create irreplaceable value for an organization. Yet many GCs may be making these critical decisions based on assumptions about what stakeholders need rather than evidence.

The paradox is that while corporate legal departments consistently say they want to be effective, client-focused, and responsive partners in service of the business, many are making strategic decisions about how to be that way without systematically measuring or understanding the stakeholder experience they’re trying to optimize. It’s like declaring customer satisfaction as your goal while never actually asking customers how satisfied they are. This blind spot doesn’t just undermine service quality; it undermines one of the four core accountabilities of every legal department which is that of being Effective.

This is the third part��of our series on the “Four Spinning Plates” model, which frames the GCs’ evolving responsibilities as:

1. 1. 1. delivering effective advice
      2. operating efficiently
      3. protecting the business, and
      4. enabling strategic ambitions.

This article focuses on the��Effective��plate.

The information gap

Being Effective as a legal department means delivering high-quality, practical legal advice that is responsive to business needs, and this requires knowing what those needs are. Most legal departments rely on hallway conversations, occasional feedback during business reviews, and organic complaints or praise. While these interactions are valuable and should continue, what they lack is systematic intelligence that could be used to determine the best strategic decisions.

Ad hoc feedback is reactive, incomplete, and reflects the loudest voices rather than the broader reality. You hear from the very satisfied or the very unsatisfied, rarely from the middle majority of stakeholders whose experience shapes overall effectiveness.

As AI transforms legal delivery, this information gap becomes more costly. Without understanding which feedback touchpoints stakeholders prefer as human interactions and which they’d rather handle on their own, how can you decide which legal services to automate and where your team’s judgment and relationship-building are essential?

When legal departments systematically gather stakeholder feedback, they uncover patterns that challenge assumptions about what effectiveness means to the business.

Consider response time, for example. Many legal teams pride themselves on providing thorough, carefully crafted advice. However, stakeholder feedback often reveals that the speed of an initial response matters more than depth, at least for the first touchpoint. What lawyers see as diligence, stakeholders may experience as delay. This insight doesn’t mean the legal team should compromise quality; rather, true effectiveness comes from knowing when a quick acknowledgment is sufficient and when an issue demands thorough analysis right away.

Varied responses needed

Of course, different stakeholders have different expectations of responsiveness. For example, sales colleagues working under targets and time pressure need speed to drive momentum in contract negotiations. Understanding different stakeholder personas can help manage expectations and educate junior lawyers about the different business rhythms that the legal department must respond to.

Or, as another example, take service awareness. It’s common to discover that stakeholders simply don’t know the full extent of what the legal team can offer. Business leaders may not realize their legal team provides training, templates, or advisory services that could prevent issues before they escalate. The problem here isn’t service quality, it’s visibility — and that distinction matters enormously when deciding where to invest limited resources.

You can learn more about how the��Thomson Reuters Institute’s Value Alignment toolkit��allows you to assess your legal department’s strategic positioning here

More importantly, these insights directly inform AI integration strategy for corporate law departments. Routine, high-volume work in which speed matters is a prime candidate for automation and self-service tools. Complex matters in which stakeholders specifically value a lawyer’s business understanding and strategic judgment is where to protect and focus human capacity.

Perhaps the most valuable output of fostering systematic feedback is when that feedback reveals where satisfaction varies across departments or stakeholder groups. A legal department might assume it delivers consistent service, only to discover that one business unit rates the department highly for responsiveness while another complains that it struggles to receive timely answers. These variations point to either inconsistent delivery or improperly communicated expectations. which are exactly the kinds of problems that process standardization, better intervention systems, or technology can address.

Without this type of intelligence, GCs risk automating services that should stay personalized, or maintaining high-touch approaches for work that stakeholders would happily handle themselves through self-service options.

The human value imperative

As AI handles more legal work, the question becomes: What can legal professionals do that technology cannot? The answer lies in the distinctly human elements of legal service such as judgment, knowledge of the business, relationship building, and strategic counsel.

The challenge for corporate law departments, however, is that without first knowing which touchpoints stakeholders value as human interactions, you can’t strategically deploy your team’s capabilities. Systematic stakeholder feedback allows evidence-based decisions on where the legal team’s relationship adds value and where speed or self-service could better serve stakeholder needs.

The question for every General Counsel then becomes: Are you making decisions on the department’s effectiveness based on systematic stakeholder intelligence, or operating with a blind spot that may be costing you more than you realize?

This then becomes critical intelligence for decision-making around resource allocation and restructuring, as well as for demonstrating the legal team’s value to the C-Suite in terms they can recognize. When a GC can articulate not just what their department does but how effectively it serves broader stakeholder needs, they are speaking the same language as the business they support.

This also allows a GC to shift from defending their department headcount based on workload volume to justifying resources based on stakeholder-defined value — and that’s a fundamentally stronger position.

Understanding the Spinning Plates

The Four Spinning Plates model — Effective, Efficient, Protect, and Enable — represents the complete picture of a legal department’s role and value within the organization. Yet research consistently shows a perception gap. For example, C-Suite executives over-emphasize the Effective plate while under-recognizing Protection and Enablement contributions.

This gap exists partly because legal departments lack metrics that capture effectiveness in business terms. They can report cost savings and matter volumes but struggle to demonstrate how well they’re actually serving stakeholder needs. Stakeholder feedback mechanisms bridge this gap by making effectiveness measurable and visible through the lens of those the department serves.

Indeed, it’s not about running surveys for the sake of feedback. It’s about grounding strategic decisions about AI integration, service design, and where to focus human talent, in evidence not assumptions. For those GCs navigating AI transformation specifically, this isn’t optional. Rather, it’s the difference between guessing where to automate and knowing where automation serves stakeholders.

Leading legal departments are already using stakeholder intelligence as their compass for AI transformation, leveraging that intelligence to best determine where to standardize, where to automate, and where human judgment remains irreplaceable.

The question for every General Counsel then becomes: Are you making decisions on the department’s effectiveness based on systematic stakeholder intelligence, or operating with a blind spot that may be costing you more than you realize?

You can learn more about the challenges that corporate GCs face every day

Key insights:

• • • ESG is becoming more operationalized — ESG is being conducted with a lower public profile while also playing an increasingly strategic role in supplier governance frameworks.

    • Data collection remains widespreadand robust — Companies continue to collect comprehensive ESG data from their suppliers.

    • Technology usage in ESG is increasing — Greater investment in automation demonstrates continuing commitment to effectively managing ESG.

Environmental, social and governance (ESG) issues have played an increasing role in global trade operations in recent years. As the United States government sharply pulled back its role in encouraging ESG in global trade in 2025, concerns were raised over whether that would impact ESG efforts globally.

However, ESG-related efforts in global trade have not diminished, although they are evolving in form and positioning, according to the Thomson Reuters Institute’s recent 2026 Global Trade Report. In fact, the report’s survey respondents said that ESG data collection from suppliers is now largely structurally embedded in trade operations, although at the same time, it is being carried out with a lower public profile than in previous years.

ESG management remains a core trade function

Managing ESG remains one of the most widespread responsibilities among trade professionals. Almost two-thirds (62%) of those surveyed said their role includes ensuring ESG compliance throughout the supply chain. That represents a higher percentage than for other responsibilities, such as procurement and sourcing, supplier management, trade systems management, risk management, customs clearance, and regulatory compliance. The only more widespread role being done by those global trade professionals surveyed is business strategy for global trade and supply chain.

More importantly, ESG remains integral and nearly universal when it comes to the supplier selection process. All respondents in the Asia-Pacific region (APAC), Latin American and the European Union-United Kingdom, as well as 99% of US respondents, report that ESG considerations remain moderately important, important, or very important in influencing their decisions around using a supplier. And overwhelming 78% say it is an important or very important consideration.

Clearly, as the report demonstrates, ESG remains a core component of the trade function for most businesses.

ESG moves toward structural governance frameworks

Only a very small proportion of respondents — 3% in the US and 4% globally — said they stopped ESG-related data collection entirely in 2025. Meanwhile, ESG data collection has increased across several major metrics.

As companies move to embed ESG expectations directly into their supplier governance frameworks, they are shifting these efforts from being a publicly declarative initiative to becoming operationalized as a permanent compliance and sourcing discipline alongside other operational considerations.

Businesses are focusing on supplier information in areas that have direct operational relevance. For example, companies collecting data on Free Trade Agreement (FTA) eligibility status for ESG purposes can also leverage the data to reduce costs, ensure supply chain security through Customs Trade Partnership Against Terrorism (CTPAT) participation, and better maintain compliance with country-of-origin requirements. Similarly, Country of Origin (COO) and Authorized Economic Operator (AEO) status are both classified under ESG but are also highly trade operations specific. These metrics merge the lines, representing areas in which ethical considerations intersect with practical trade strategy.

Supplier data collection is shifting to operational relevance as well. Indeed, the scope of supplier data being gathered remains broad and reflects a holistic view of the supply chain. The most common areas for ESG data collection in 2025 were: i) environmental metrics, such as water usage, waste management, energy management, and carbon emissions, including Scope 3 emissions; ii) social metrics, such as health and safety, labor standards, human rights including modern slavery or indentured service, and diversity in employees; and iii) governance and compliance, including data privacy, business ethics, and anti-corruption.

Data collection from suppliers

Meanwhile, ESG data collection has been scaled back in areas such as trade evaluation, AEO/CTPAT status in some jurisdictions, diversity in ownership, and anti-corruption assessments. The most cited reason for the pullbacks was insufficient cost-benefit return for collecting data in areas in which customer scrutiny was minimal. This trade-off reflects a rational reprioritization: companies are focusing their ESG diligence in areas in which regulatory risk is more material rather than reputational.

Integrating ESG into broader trade workflows

The report also shows that businesses are leveraging ESG to make it more operationally effective, drive greater efficiency, reduce costs, and add greater value for the organization. ESG is becoming less of a marketing and brand building exercise, and more of a compliance and sourcing discipline that factors into strategic decision-making — it is subject to the same analytical rigor as financial or operational risks.

To this end, organizations are less prone to make a string of bold public goals and commitments, or issue standalone ESG reports, updates, or scorecards that tout their progress. Instead, ESG data is being seamlessly embedded into supplier evaluation and selection alongside non-ESG business metrics and other considerations. As such, organizations are using ESG to quietly build the structural frameworks, data infrastructure, and management approaches they’ll need for more strategic planning.

ESG is shifting to strategically supporting business growth and away from reputational focus

Helping this shift along, the report shows, is that the use of technology to manage ESG has accelerated significantly in 2025. One-third of respondents said their organizations use automated ESG solutions, a major increase from only 20% in 2024. This provides a clear indication that more organizations are not only continuing but strengthening their commitment to effectively managing ESG.

And this provides a boost, because greater automation can improve the efficiency and ability of trade professionals to manage ESG efforts, further enhancing the integration of ESG data into other operational workflows as organizations incorporate ESG data to drive greater value.

What lies ahead for ESG

ESG practices and organizations’ embrace of them remain near-universal across trade operations. This continuation presents a clear indication that there is no widespread retreat from ESG management. For trade professionals, ESG is here to stay and is evolving into an operational discipline to help grow their business.

For organizations to have continued success in this evolving ESG environment, they should take several steps that require strategic thinking, including:

• • • Identify which metrics truly matter — Connect ESG metrics that affect trade operations, particularly those that impact supply chain cost, efficiency, and reliability.
    • Invest in the technology infrastructure — Improve efficiency in tracking and analyzing key ESG metrics.
    • Articulate ESG value — Develop the ability to demonstrate the value of ESG to the trade function and communicate it in business terms to senior management.

The shift of ESG towards operational trade management may represent a more sustainable long-term path forward than the earlier wave of ESG enthusiasm — embedding ethical considerations into core business processes rather than treating them as separate compliance exercises. By focusing on metrics that genuinely matter to business operations, companies are building practices that will persist regardless of any political winds or public relations trends.

Those corporate trade departments that can skillfully navigate this evolving environment will be positioned to more effectively leverage ESG considerations as a strategic asset and competitive differentiator. And in an increasingly complex and volatile global trading landscape, they will find themselves playing a more central role in their organizations’ success.

You can download a copy of the Thomson Reuters Institute’s 2026 Global Trade Report here

Key highlights:

• • • Treat AI use as a material sustainability driver — Bring AI explicitly into financial materiality and impact assessments so you can see where AI changes the scale or severity of existing issues or introduces new risks or opportunities.

    • Map, measure, and baseline AI demand to make it governable — Create an inventory of in which situations or how often AI is used and establish utilization metrics over time so you can spot growth, redundancy, and hotspots.

    • Control AI impact through policy, oversight, and supplier expectations — Set rules for appropriate AI use and triggers for extra review before scaling AI, and manage impacts whether AI is in-house or provided by vendors.

While AI clearly already is changing how companies operate and deliver, it’s also demanding changes in how sustainability systems are designed and governed. Indeed, much focus to date has been on the environmental impact of AI’s energy use, water consumption, and supply chain challenges.

Yet, there is another side to consider that involves examining how AI itself is used within organizations. It is important to understand where AI is applied throughout an organization, how often it is used, and whether those uses are necessary — and most crucially, how and when the review processes is applied. By including AI in materiality assessments, a clear track is set for its deployment, with systems in place to address any environmental and social impacts and risks that arise before they become problems.

To ensure effective value creation of AI use, organizational leaders need to focus beyond the footprint, by mapping their AI use, defining control and review processes, developing systems for ongoing quantification, and reporting transparently. The goal is to manage AI’s impact from the inside out, making sure the benefits are worth the risks and that sustainability remains a priority.

Bringing AI use into materiality and impact assessments

Financial materiality and impact assessments provide a practical basis for governing AI through the structured process of identifying and prioritizing significant impacts. Many sustainability topics influenced by AI use — including energy demand, emissions, water use, and workforce effects — are already assessed in existing materiality exercises. What is often missing is an explicit examination of how AI alters the drivers of those impacts.

The International Sustainability Standards Board’s centers on financial materiality, which is defined by whether a topic could reasonably be expected to influence the decisions of investors or other users of financial statements. How AI is used within companies undoubtedly influences the risks and opportunities the company faces and certainly can affect a company’s financial position.

Early closures aligned with the European Union’s Corporate Sustainability Reporting Directive (CSRD) suggest that AI is typically addressed within broader topics such as workforce impacts, digital governance, or business conduct rather than identified as a standalone source of dependencies, impacts, risks, and opportunities. This reflects the difficulty of assessing impacts that are indirect, cumulative, and demand-driven, and topics in which regulations and best practices are still evolving.

Bringing AI into materiality assessments requires assessing whether its use alters the scale or severity of existing impacts, introduces new risks and opportunities, or creates dependencies that warrant prioritization.

In practice, determination of the materiality of AI hinges on understanding scale and concentration — such as in which situations it is used or embedded in critical workflows and the scale of applications across functions, tools, and systems. Mapping AI use across use cases and delivery models can help provide the basis for determining in which instances AI meaningfully alters environmental, social, or financial exposure.

Once these priority areas are identified, organizations then can move from qualitative assessment to structured oversight by establishing a baseline for AI utilization and its associated potential impacts.

Governing AI demand through policy

Once a basis of materiality for AI is determined, the next governance step is to shift towards control, primarily through policy that’s supported by proportionate measurement of demand.

As access to AI expands, it can become a default tool for routine tasks, increasing demand through duplication and persistent use cases without sufficient oversight or challenge. Policies then can set expectations for appropriate application, conditions to assess depth relative to task value, and crucially, what conditions should trigger additional review before AI is scaled or embedded into core work processes.

Quantification underscores these policies by making AI use visible over time and by tracking its impact. For most organizations, the starting point for measuring AI impact is obtaining a consistent view of utilization and its evolution. This determination of scale will then later support the precise attribution of energy or emissions. Comparing precise indicators to utilization will enable leaders to establish a baseline and then support effective identification of growth, potential redundancy, and overall impact.

Managing AI’s impact

Where organizations own or operate their own AI infrastructure, management responsibility will sit within established operational controls, including decarbonization of electricity supply, managing cooling water use, and overseeing hardware lifecycles, such as refurbishment, reuse, and recycling. Governance also explicitly needs to cover model training and retraining, especially in areas in which concentrated energy and water demand can arise. In fact, it should be subject to planning and review rather than treated as a purely technical decision.

Where AI capability is accessed through external or third-party providers, these same impact areas must be addressed through policy and a rollout of supplier engagement practices that link disclosure with procurement decision-making. Management without direct control necessitates setting expectations and engaging external providers on energy sourcing, water stewardship, hardware management, and transparency around model training practices and associated impacts.

Governing AI as an impact on sustainability

AI’s sustainability effects depend on infrastructure efficiency, energy sources, and governance of its use in organizations. That means that effective management must include assessing material impacts, setting policies for demand and monitoring, measuring results, and making transparent reporting.

Treating AI as a source of managed sustainability can better help mitigate risks and ensure that the environmental and social effects of AI use are aligned with value creation.

You can find out more about here

Key insights:

• • • Elevate AI governance to the board — Companies should tie their AI deployment to enterprise risk management with explicit KPIs for energy intensity, water withdrawals and consumption, and supply‑chain human rights.

    • Make transparency a competitive asset — Implement auditable disclosures on AI workload footprints, water stewardship, and supplier traceability, and then link executive compensation and vendor contracts to measurable efficiency and resiliency outcomes.

    • Demand transparency despite practical challenges — Although demanding transparency from suppliers may not be practical now due to current challenges, collectively asking for detailed information sends a notable requirement to AI infrastructure providers that the company is seeking to drive change and preserve trust in an AI-driven economy.

AI now sits at the center of corporate sustainability governance as it supercharges data gathering, analytics, and reporting. Indeed, there is is areas of energy optimization, emissions monitoring, land‑use assessment, and climate scenario analysis.

At the same time, AI’s rise is colliding with sharply growing electricity and water demands from data centers and concerns over geopolitically exposed supply chains. The governance challenge for companies therefore is to manage risk at this intersection. This means treating AI as a capital‑intensive, cross‑border infrastructure program whose environmental footprint and supply dependencies must be actively governed.

Why electricity and water are now board‑level AI risks

AI has turned electricity and water from background utilities into constraints that should be dealt with on the board level. Indeed, AI magnifies water risk across cooling, power generation, and chip manufacturing. This makes sourcing and efficiency choices strategic imperatives for many organizations.

Electricity demand — AI use and the data centers that power the tools already account for a significant and rising share of electricity use in the United States. The finds , a figure poised to grow as AI workloads scale. Forward‑looking projections from the U.S. Department of Energy indicate that by 2028 could be attributed to AI workloads.

If you translate those projections into , you can get an idea of the potential magnitude of the problem. Together, these sources suggest that the fastest‑growing part of AI’s energy appetite is not just for training models, but the steady, pervasive inference capabilities��required to power AI features in everyday products and operations.

Direct and indirect water use — Data centers powering AI also negatively impact local water footprints. It shows up in three places: i) data‑center cooling; ii) the electricity feeding those facilities, including thermoelectric and hydroelectric generation; and iii) AI’s own hardware supply chain. In regions already facing scarcity, these demands compound local stress. For example, the average per capita water withdrawal is 132 gallons per day; yet a large data center consumes water .

This makes data centers one of the�� in the country, which incidentally is home to . At the end of 2021, around�� from moderately to highly stressed watersheds in the western US. This is a common situation as well.

Geopolitical exposure — The hardware that powers AI includes advanced logic and memory chips, which depend on concentrated manufacturing nodes and supply chains with access to critical minerals. Extraction and processing of inputs, such as lithium and cobalt, are often clustered in jurisdictions with elevated levels of human‑rights, environmental, or geopolitical risk. This potential amplifies exposure to export controls, sanctions, or resource nationalism, especially directly for companies’ supply chains and indirectly for those companies using AI.

Companies need to ensure their communication on legal and policy issues are pointing in the same direction in regard to these concerns. Indeed, companies need to deepen value‑chain due diligence while navigating evolving supply‑chain and AI‑specific regulatory regimes.

Recommended actions for companies

These intersections have clear implications for corporate governance. AI’s promise to accelerate decarbonization, improve transparency, and strengthen decision‑making will be realized only if leaders can properly manage the physical, political, and social realities underpinning the technology. Recommended actions to manage risk in areas in which AI and geopolitics converge include:

Demand transparency in electricity and water consumption of AI infrastructure — Companies building AI infrastructure need to conduct AI workload planning. Companies using AI can demand transparency of their suppliers’ 24- to 36-month forecast of training and inference by region with overlays in grid carbon and local water stress to better understand their indirect environmental impacts.

De‑risk impact by incentivizing clarity in supply chains — Companies using AI can begin asking AI infrastructure companies to provide due diligence in tier 2, 3, and 4 suppliers, all the way down to smelters, refiners, and miners to make sure that companies are not indirectly contributing to environmental and social harms.

The bottom line

While these recommendations generally align with evolving corporate practices in sustainability and risk management, the challenge of implementation will vary based on the company’s size, influence over suppliers, and existing governance structures. The most challenging aspect will likely be achieving transparency and clarity in supply chains, which requires cooperation from suppliers and the investment of potentially significant resources.

At the same time, however, if more companies collectively ask for this level of detailed information from their AI infrastructure providers, it will send a notable demand signal. Indeed, AI is both a sustainability tool and a sustainability liability, but its benefits will be realized only if leaders confront the physical and geopolitical constraints that make AI possible.

Those companies that begin asking for this level of transparency can preserve the trust that underwrites their license to navigate successfully in an AI‑driven economy.

You can find out more on the sustainability issues companies are facing around the environment here

Key insights:

• • • Growing pains with expanded AI use — The surge in AI adoption is creating new compliance, governance, and security challenges for businesses, with nearly all firms planning to expand AI use.

    • Many compliance teams are faltering — Current compliance approaches are falling short, with 88% of firms struggling with AI governance and data security, and 37% reporting gaps in their search and e-discovery capabilities.

    • New communications tech tools might help — To address these challenges, organizations need to invest in innovative digital communications governance and archiving platforms that can handle the complexity of AI-generated content and provide forensic-level insight into potential issues.

Human-to-AI communication is accelerating across the workplace, creating new compliance, governance, and security challenges for modern organizations. The rise of AI assistants, generative AI (GenAI) tools, and agentic AI introduces a new category of communications — known as aiComms — and a new workplace participant: AI itself. Organizations now face added complexity as they work to manage, monitor, and retain these evolving forms of communication.

Surge in aiComms as firms plan to expand AI use

The results of Theta Lake’s 7th annual , based on independent data gathered from 500 IT and compliance leaders in the financial services sector, highlights both the scale of AI expansion and emerging governance challenges.

Nearly all respondents (99%) say their firms plan to implement or expand AI features within their unified communications and collaboration tools, including GenAI assistants (with 92% saying this), AI-powered meeting notetakers and summarization (81%), and customized agentic AI (77%).

Indeed, the widespread adoption of popular GenAI capabilities such as summarization, prompts, and responses is transforming productivity and offering opportunities for firms to realize numerous efficiency gains and improvements. However, the volume of communications is set to accelerate, which will require entirely new approaches to governance, compliance, and content inspection.

In fact, 88% of respondents say their firms already report challenges with AI governance and data security, with the top challenge, identified by nearly half of respondents (47%), is ensuring that AI-generated content is accurate and compliant with regulatory standards. Respondents also cited factors such as difficulties in detecting whether confidential or sensitive data has been exposed in GenAI output (45%), concerns around identifying risky end-user behavior with AI tools (41%), and their ability to track where problematic AI content is shared and with whom (40%).

Fragmented communications compound risk

The report also reinforces the idea that AI is only one part of a broader compliance challenge. Firms are continuing to use multiple unified communications and collaboration platforms, many of which rely on multiple compliance, surveillance, and e-discovery solutions that in turn create inefficiencies, complexity, and gaps in oversight.

Fully 82% of survey respondents say their firms use four or more communication and collaboration platforms. Most organizations also rely on at least three different vendors or repositories for recording, archiving, and supervising communications, the survey shows.

These single-purpose compliance solutions are increasingly inadequate for today’s meshed communications environments, in which text, audio, video, and AI-generated content are created and consumed simultaneously. The limitations of these platforms result in incomplete capture, viewing, and reconciliation, the survey shows, including:

• • • 37% of respondents say their firms report search and e-discovery gaps, up from 31% last year
    • 36% cite surveillance gaps that affect risk detection, remediation, and controls
    • 62% report their firms have difficulties reconstructing and replaying conversations that span multiple communication tools and include textual, voice, visual, and AI-generated interactions

Another continuing concern is the use of off-channel communications, respondents say. Despite more than $4 billion in global fines from government regulators for organizations’ recordkeeping and supervision failures in recent years, more than two-thirds (67%) of respondents say they remain concerned about employees using unmonitored channels.

The findings align with the United Kingdom’s Financial Conduct Authority’s multi-firm , released in August, which found that most firms in its sample continue to identify breaches of internal communication policies.

Regulatory expectations

Regulators have made it clear that AI tools are encompassed by existing compliance frameworks. For example, FINRA’s Regulatory Notice 24-09 reminds member firms that:

FINRA’s rules — which are intended to be technology neutral — and the securities laws more generally, continue to apply when member firms use GenAI or similar technologies in the course of their businesses, just as they apply when member firms use any other technology or tool.

This means that highly regulated organizations must be able to confidently enable AI tool while continuing to maintain full oversight of how those tools are used, what they produce, and how their outputs are managed.

Innovative digital communications governance and archiving platforms now include features designed to support AI compliance and security guardrails, helping organizations maintain oversight and transparency in their use of GenAI tools.

Investing in the future

As the report illustrates, confidence in existing compliance approaches remains extremely low at just 2%, down from 8% last year. This underscores the recognition that traditional compliance systems cannot accommodate the volume, diversity, and dynamic nature of today’s digital communications.

As a result, firms are significantly increasing their investment in communications compliance to keep pace with the growing complexity of digital communications, including aiComms. In fact, 86% of respondents say their organizations are already investing more — up from 65% last year — and a further 12% plan to do so.

As human-AI collaboration becomes an integral part of business communication, governance frameworks must evolve to ensure accountability, transparency, and trust. Organizations will need forensic-level insight into AI-generated content to detect potential issues, confirm appropriate use, and respond quickly — all without slowing productivity. Platforms can better support safe GenAI adoption by ensuring AI-generated content aligns with internal policies and regulatory obligations, enabling swift action on risky or non-compliant content, and allowing firms to retain only what’s necessary to meet oversight and recordkeeping requirements.

For more, you can download a copy of here