Building AI Control Systems When Commercial Vendors Cannot Keep Pace With Newly Developing Technologies

Can you spot the complex and focused systems error that is

embedded  in the illustration? Answer below.

During times of slow and modest changes in information technologies, corporate executives need not struggle to build their internal control systems. They can simply purchase the systems from organizations that have designed them to reflect existing governance standards.

At times of rapid progress, though, these vendors (and the standard setters that they follow) may not be able to keep pace with newly developing technologies. Thus, corporate executives may not be able to find appropriate systems of internal control that are available for purchase.

Nevertheless, insurance companies, investors, external auditors, regulators, and other parties always expect corporate executives to maintain effective internal control systems. But how can executives meet that expectation when such systems are not commercially available?

Their only option is to design their own in-house control standards and systems as best they can. Of course, they can always hire consultants to assist them, but they would still need to design their own assessment standards to evaluate their consultants' activities.

This challenge is particularly onerous in very broad fields like Artificial Intelligence (AI), fields in which user errors and other risk factors can occur at many different levels of complexity. Consider, for instance, a researcher who uses a Large Language Model (LLM) to seek information. She may inadvertently prompt her AI platform to produce erroneous information for a variety of reasons.

At a complex level, for instance, she may fail to notice a subtle logic error in the AI input, an error that causes a significant AI hallucination. Conversely, at a far simpler level, she may simply forget to conclude a lengthy and detailed AI query with a brief synopsis of her need. In each instance, the AI system may thus be compelled to produce erroneous output.

How should corporate executives address such broadly defined sets of risks in their self-designed control systems? An effective approach, consistent with the COSO models of internal control and risk management, involves the definition of a hierarchy of risk factors across a full range of complexity levels. After defining the complexity levels and risk factors, organizations can design controls that address the highest priority risk factor(s) at each level.

For instance, an organization may believe that the simplest and broadest risk factor during the composing of LLM queries is the user's ignorance of basic grammar and spelling concepts. A slightly more complex and focused level of risk may be the user's ignorance of general business vocabulary.

A higher level of complexity and focus regarding risk may be the user's ignorance of advanced technical business vocabulary. And the two most complex and focused levels may be the user's inexperience in applying such vocabulary to AI tasks, followed by his or her inexperience in incorporating large data sets into the tasks.

Can you see how each level of risk represents a more complex and focused extension of the previous level? This hierarchical structure is consistent with the COSO models. By understanding how each level influences (and, in fact, partly determines) the next one, we can more effectively design control systems that minimize overall risk across the multiple levels.

Eventually, of course, the pace of technological change will lessen, and control system designers will keep pace with AI technologies. Inevitably, systems will then be developed and made available for purchase by corporate executives.

Until that time, though, organizations will continue to develop their own in-house control systems. Fortunately, by adopting an effectively structured approach, organizations should be able to succeed at this task. 

Image Caption Note: Google Gemini created this illustration regarding an AI control system for producing budgets, one that (erroneously) generates output that fails to bear any resemblance to actual results. Can you also spot a more complex and focused systems error that is embedded in the illustration? All of the colleagues who are sitting at the conference table are twins! Clearly, the user's AI prompts and queries failed to anticipate or prevent this error.

Playing With FIRE: The New Complexities Of Developing A Personal Retirement Investment Plan

What aspirational message would you expect to see in the marketing material of a major retirement investment firm? Something, perhaps, that encourages investors to save aggressively, retire early, and live a long life of luxurious wealth?

That type of message has long been featured in such campaigns. The expression Financial Independence, Retire Early (FIRE), for instance, has referred to individuals who hope to leave the work force well before reaching the traditional retirement age of 65. And Fat FIRE, a colorful elaboration of FIRE, has referred to those who aspire to extremely luxurious retirement lifestyles.

More recent slogans, however, now refer to much more modest financial goals. UBS Wealth Management, for example, currently markets its services to "every day millionaires" who assemble portfolios with values as small as $1 million. And phrases like Coast FIRE and Barista FIRE now refer to individuals with even more limited retirement goals.

Coast FIRE goals apply to individuals who will not fully retire before age 65, but who plan to gradually reduce their working hours as they approach that traditional full retirement age. And Barista FIRE goals apply to individuals who will never fully retire at all, and who expect to work in relatively low paying jobs on a part-time basis well after 65.

Why are wealth management firms now marketing to investors with relatively modest retirement goals? Some may assume that the trend is a sign that the market is healthy and growing. Others, though, may suspect that the firms are "looking downstream" for new (and less wealthy) clients to replace the loss of traditional (and wealthier) clients. Those who ascribe to this worrisome explanation may believe that the increasing aggregation of capital in the hands of our society's wealthiest citizens may be reducing the number of individuals who can look forward to luxurious retirement lifestyles.

How do these trends impact mainstream personal investors? Financial advisors are increasingly asking them to define their retirement goals and lifestyles in accordance with these elaborately defined FIRE categories. To a significant extent, many of these categories apply to individuals who will not be able to achieve financial independence and retire early.

In the past, many financial advisors would simply work with clients to define their personal Retirement Numbers, i.e. the target values that their investment portfolios must reach to trigger decisions to leave the work force. Investment strategies would then be developed to help clients reach their personal Numbers by the end of their working years.

Today, though, investors and financial advisors are holding far more complex planning conversations. Thus, investors may need to engage in much deeper levels of self-reflection to prepare themselves for these advisory discussions.

Concerned That A.I. Will Destroy Your Accounting Career? Establish Your Future In The Profession's One (Obvious) Area Of Job Growth

Last week, at TXCPA Houston's annual Fall Accounting Conference & Technology Symposium (F.A.C.T.S.), speaker after speaker addressed the future prospects of A.I. Although much of the content was optimistic in tone, an undercurrent of concern permeated the presentations.

Why? It's likely that A.I. applications will soon be capable of performing many current human functions in accounting and finance. Thus, if you're a staff auditor who "traces and agrees" numbers that appear on different computer screens, or if you copy numbers from accounting documents to income tax forms, your activities are particularly vulnerable to automation via A.I. systems.

There is a specific career path within the accounting sector, though, that will likely experience explosive growth because of A.I.'s increasing use. The Symposium speakers referred to it as A.I. Governance and Risk Management.

Why is that a growth sector? Any new technology that performs an important activity inevitably malfunctions from time to time. Audit assurance activities must thus be applied to it, and measurements must be devised to manage the risk of technical failure. And over time, as any technology grows more proficient at lower-level tasks, it is inevitably applied to higher-level tasks, thereby generating the need for higher-level assurance activities.

It may seem ironic that this projected job growth is expected to arise within the assurance function, a traditional service on which the entire public accounting profession was founded in the late 1800s. Nevertheless, if you're concerned about establishing an accounting career path that is vulnerable to being rendered obsolete by A.I. applications, you may wish to consider a role that addresses the risks of implementing such activities.

Information about the A.I. Governance and Risk Management functions can be found on the web sites of the Big Four accounting firms and many other assurance practices. Consulting firms outside of the accounting sector publish helpful information too, including those owned by firms in the human resources sector. And more technical information can be found on the web sites of publications that focus on data security and process management.

Furthermore, to communicate directly with the authors, speakers, and thought leaders of the profession, you might consider attending future conferences of TXCPA Houston. The organization, for instance, has already begun to develop its 2026 Spring Technology & Accounting Resources Summit (S.T.A.R.S.). A.I. topics are sure to play a prominent role in the agenda of that event.

For Sustainability Accountants, New Entities Step Forward As The Federal Government Steps Back

Sustainability accountants may have been worried when the U.S. Securities & Exchange Commission (SEC) permanently withdrew its climate change (carbon emissions) reporting requirements. What would they do? Were their jobs in jeopardy?

Apparently, their employment prospects weren’t bleak after all. Last month, the private sector stepped into the void with the launch of the Task Force for Corporate Action Transparency (TCAT). The entity published new corporate standards regarding the reporting of climate change information, emphasizing the need for third party assurance (i.e. independent audit) activities on the data. The Wall Street Journal noted that Netflix, PepsiCo, and eleven other companies were already pilot testing the guidance.

Likewise, accountants in the medical sector may have been concerned when the U.S. Department of Health & Human Services ceased the collection and reporting of various health metrics. Once again, though, a new entity emerged to assume this function.

Which entity? Fifteen U.S. states announced the launch of the Governors Public Health Alliance. The group pledged to “share best practices, exchange data and collaborate on emergency response, vaccine policy and other technical issues,” activities that were once performed by federal government agencies. Two other alliances of U.S. states, one located in the Northeastern United States and the other on the Pacific Coast, previously announced similar pledges.

Professionals across the political spectrum may be well-advised to review the output of these new entities. Those who believe in the federal government’s efforts to limit public reporting may need to understand how these new initiatives are attempting to replace the data. Conversely, those who support the principle of public reporting may need to implement the new guidance.

Interestingly, it appears that sustainability accountants will continue to be “in demand,” regardless of the federal government’s role in defining relevant metrics and standards. As the federal government steps back and eliminates its requirements, other parties are stepping forward and establishing new expectations.

Worried About AI Hallucinations? You May Need To Add AI Sycophancy To Your List Of Concerns

Many AI users are now familiar with hallucination risk. A recent article, appearing on the web site of the U.S. National Institutes of Health, explained that:

"AI hallucination is a phenomenon where AI generates a convincing, contextually coherent but entirely fabricated response that is independent of the user’s input or previous context. Therefore, although the responses generated by generative AI may seem plausible, they can be meaningless or incorrect."

Such hallucinations create legal liability. Thomson Reuters Legal, for instance, recently discussed a well known case in the field:

"An example of failure to follow (rules regarding false statements) when using general-use generative AI in practice can be found in Avianca vs. Mata, more widely known as the ChatGPT lawyer incident. In short, the defense counsel filed a brief in federal court (that was) filled with citations to non-existent case law. When confronted by the judge, the lawyer explained he’d used ChatGPT to draft the brief, and claimed he was unaware the AI could hallucinate cases ...

The judge didn’t take kindly to the lawyer’s laying blame on ChatGPT. It’s clear from the court’s decision that misunderstanding technology isn’t a defense for misusing technology, and that the lawyer was still obligated to verify the cases cited in documents he filed with the court."

In a different Thomson Reuters Legal article, the author wrote that:

"In 2023, a judge famously fined two New York lawyers and their law firm for submitting a brief with GenAI generated fictitious citations. This was the first in a series of cases involving GenAI hallucinations in court documents, including a Texas lawyer sanctioned for similar reasons in 2024."

Fortunately, hallucinations can be individually checked for truth or falsity. AI sycophancy, though, may pose a much greater risk.

What is sycophancy? An article that was recently published by Georgetown Law School defined sycophancy as:

" ... a term used to describe a pattern where an AI model single-mindedly pursues human approval ... by tailoring responses to exploit quirks in the human evaluators ... especially by producing overly flattering or agreeable responses."

In other words, AI systems possess a tendency to tell users what they want to hear. As these systems learn more about the personal preferences and interests of their users, they may become much more skillful (and thus potentially more dangerous) in this practice.

Sycophancy risk may be harder to manage than hallucination risk because sycophancy doesn't necessarily produce discrete statements that can be individually confirmed or refuted. Instead, sycophancy can create a form of pernicious bias that subtly infects an entire AI response.

Many organizations are now performing internal control and review activities to address hallucination risk. They may need to expand their efforts to address sycophancy risk.

Public Accounting Firms: The Impact Of Alternative Practice Structures On The Career Paths Of Young Professionals

Many sources are reporting that the Graduating Class of 2025 is confronting an uncertain employment outlook in the public accounting sector. Some sources are noting, for instance, that firms are expanding their use of AI to complete tasks that were previously assigned to entry level staff accountants.

There are other explanatory factors, though, that may be contributing to the challenging nature of the current employment outlook. One such factor may be the continuing growth of private capital investments in public accounting firms. Many of these firms are adopting alternative (dual) practice structures, with one business entity focusing on traditional attestation (audit) work, and the other focusing on newer and more profitable advisory (consulting) work. The bulk of the private capital is often invested in the latter entity.

That may create a potential misalignment between the firms and their newly hired staff accountants. On the one hand, staff auditing and tax positions have traditionally served as the basic training positions for recent accounting graduates to enter the profession. But on the other hand, because the new investment capital is focused on consulting activities, these traditional entry points do not necessarily prepare new hires for long term career paths in advisory services.

What approach can address this concern? One solution may involve the development of career paths that initially place recent accounting graduates in attestation and tax positions, and that later rotate the young professionals into advisory positions. This policy would maintain the traditional role of staff audit and tax work as the primary entry point into the profession, while providing a subsequent career path into the growth areas of the sector.

This rotational approach should also prove attractive to young professionals who are inclined to agree with the sentiment that "I only have to prepare a tax return 15 times to know how to do it. I don’t need to do it 15,000 times." Indeed, an acknowledgement of the need for basic training is embedded in this sentiment. Nevertheless, an acknowledgement of the need for a more value-focused long term career path is embedded therein too.

Are there concerns about this approach? Certainly, given that firms would be tasked with the burdensome responsibility of developing such employment programs. Likewise, student applicants who seek career paths in the profession would be expected to develop resumes that contain (both) assurance and advisory service expertise.

Nevertheless, the approach does eliminate the potential misalignment between potential employers and prospective employees. As long as public accounting firms and young professionals can look beyond their short term employment needs, it should be possible to create such long term solutions to these career development challenges.

Storm Flooding Catastrophes: Assessing A Region's Response Capability

Two weeks ago, a storm flood surged through the Hill Country of central Texas, inflicting more than one hundred fatalities. Last year, Hurricane Helene caused a similar level of damage in North Carolina and other southeastern U.S. communities. Neither of these events, though, matched the destructive power of Hurricane Katrina in 2005; striking New Orleans and surrounding communities, it was responsible for more than 1,000 fatalities.

Commercial and residential property owners, insurers, and mortgage lenders must assess the capabilities of regional response functions to minimize the enormous social, financial, and environmental costs of such storms. Can they learn from the experience of the Hill Country storm, the most recent event to generate such catastrophic losses?

Yes, they can, if they utilize a standard set of analytical questions that should be applied to all regional catastrophic readiness functions:

a. Is an entity held responsible for assessing the region's catastrophic readiness?

b. Does that entity develop and publish a plan to maintain its readiness?

c. Can the region implement the plan when a storm strikes?

d. Does the plan employ standardized metrics that are defined by credible organizations?

e. Does an independent entity review the assessment process on a periodic basis?

Professional analysts will inevitably agree on certain answers to these questions and disagree on others. It's important, though, that they all utilize the same publicly available information to develop their informed opinions. For instance, regarding the Hill Country case:

a. The web site of the Texas Water Development Board's State Flood Planning function contains material information about flood assistance programs, management training, community resources, and other relevant functions.

b. The web site of the Development Board's State Flood Plan contains significant supporting information about the state's "... effort to perform comprehensive planning to reduce flood risk and take a broad look at flood hazard across the state."

c. The 245 page PDF document entitled 2024 State Flood Plan is the most recent comprehensive state-wide plan; thus, it reflects the current status of the region's readiness to respond to catastrophic floods.

Reasonable minds may certainly differ about how the data in such sources may impact an assessment of a regional response function. Nevertheless, reasonable minds should all agree on the relevance of the (above) five questions and the need to utilize a region's published information for assessment purposes.

A.I. Queries, Implicit Variation, and the Practice of Due Professional Care

Are you aware that your A.I. queries provide documentary evidence of your practice of "due professional care" in researching business information? If you utilize an electronic platform with A.I. technology to search for business data, you could be held legally responsible for relying on inappropriate information that is generated by flawed queries.

Let's review an example or two of a flawed query. On June 19, 2025, I submitted the following query to Google Gemini: Please create an image of a person who is conducting his banking business at a very well managed community bank with strong internal controls. Gemini replied: Here is an image of a person conducting banking business at a well-managed community bank: 

Then I initiated a new chat and submitted the following query: Please create an image of a person who is conducting his banking business at a very poorly managed community bank with weak internal controls. Gemini replied: Here is the image you requested:

Can you see the implicit variation? It's not an easy task. Indeed, at first glance, both images appear to present a community bank that is serving a customer's needs. And neither is employing a clearly visible set of particularly strong (or weak) internal controls.

But look more closely. In comparison to the well-managed bank, the poorly managed institution uses far more paper to process transactions. The customer is informed of business procedures via a cluttered array of temporary signs. Even the technology in the poorly managed bank is inferior, as evidenced by the obsolete "chunkiness" of the computer screens.

Those factors do not, however, represent terribly weak internal controls in community banks. After all, it is certainly feasible to effectively manage a paper-based business with temporary signs and relatively old technology. And the common factors that normally differentiate strong control environments from weak control environments, such as a visible security presence and enclosures that protect the privacy of shared financial information, do not exist in either image.

There's also a subtle bias that is embedded in the images. The well managed bank features younger individuals with friendly facial expressions who wear more stylish clothes. The poorly managed bank features older individuals with neutral facial expressions who are less stylish in appearance.

Those are not distinctions involving internal controls. They are marketing images that pervade the internet. And yet Gemini offers them as differential factors that illustrate relatively strong or weak management conditions.

These are two visual examples of the types of queries that may produce undesirable implicit variation in A.I. output. Because they lack specific information, the queries can be "red flagged" as deficient by auditors as falling short of the minimum standards of "due professional care."

What specific information? Co-founder and current President of OpenAI (the firm that owns ChatGPT) Greg Brockman uses layperson's language to define what Inc. called the basic structure of the perfect AI prompt. To exercise an appropriate degree of "due professional care," all firms should integrate such guidance with other supplemental material to develop their own policies and procedures for defining A.I. queries.

End Note: Many thanks to my colleague Alan White of CU Accelerator and the Association of Credit Union Audit and Risk Professionals for their invitation to present this information at the ACUARP's 35th Annual Insight Summit in San Antonio TX next week.

The Perrier Mineral Water Violation: Sustainability Enters The Business Mainstream

Last month, the French government accused Nestle of a serious legal violation. Although the firm has always advertised its Perrier mineral water brand as one that represents "natural" water, the government charged that Nestle actually disinfects and processes the water before bottling it. Thus, according to French law, it isn't "natural" at all, and must not be advertised in that manner.

Before sustainability accounting and reporting became a public concern twenty to thirty years ago, this event would have been perceived as an internal management issue. In addition, it would have been seen as an external brand management and public relations matter.

So what has the rise of sustainability accounting and reporting processes contributed to our ability to assess Nestle's exposure to this type of problem? We can now review Nestle's Performance and Reporting web site section, noting that the firm utilizes the two major sustainability reporting standards (the GRI and the SASB) to guide its selection of sustainability metrics.

We can also see that Nestle employs a Big Four global public accounting firm (EY) to perform assurance activities on those metrics. And we can compare Nestle's supply chain management  and water processing measurement and reporting choices to the choices that were made by its major competitors, thereby assessing its levels of corporate performance against comparative industry data.

Conversely, the absence of reported data may compel us to feel concern. Nestle does not appear to rely on the U.N Sustainable Development Goals (SDGs) to the same extent that it does the GRI and the SASB. The SDGs provide an important complementary view because they define sustainability metrics from a public interest perspective.

Furthermore, Nestle does not directly address the impact of its "natural" emphasis on its brand value. That's an important factor because Interbrand has estimated that the Nestle brand is the 71st most valuable brand in the world. However, Interbrand estimates that the value of its brand shrank by 1% last year; thus, controversies involving its Perrier product line may reinforce this negative trend.

Clearly, a business analyst who is ignorant of this sustainability data will be unable to assess the implications of Perrier's "natural" controversy in a comprehensive manner. Likewise, an analyst who focuses exclusively on sustainability data (and not at all on supply chain or brand valuation information) will not be able to assess the implications either.

These observations explain why many corporations have not created fully staffed "Departments of Sustainability" in their organizations. It's not that the firms are ignoring sustainability business processes. In fact, the reverse is true; these companies have indeed embraced such practices, and have absorbed them into their mainstream business activities.

The Implications Of "Peak Shale"

During the past fifteen years, technological advancements in extracting crude oil from shale rock have propelled the United States into the unfamiliar role of the world's top oil producer. Recently, though, representatives at several leading fossil fuel companies predicted that American oil production is peaking and will soon decline.

The causal factors that they cited for their "peak and decline" prediction are all foreseeable ones. There is a limited amount of crude oil reserves in American territory that can be extracted in an affordable manner, and much of it has already been processed by oil companies. Furthermore, the market sales price of crude oil is very low by historical standards, and thus there is limited revenue to pay for the costs of production. Finally, the costs of production are increasing for various inflationary reasons, further reducing potential profits.

Business planners and data modelers throughout many industry sectors may need to factor "peak shale" into their forecasts and projections. As domestic crude is replaced by imported substitutes, the increased costs of raw materials will "flow through" into higher costs of finished goods. Other production materials that are transported by fossil fueled cargo ships, airplanes, and freight trucks will also generate cost increases. And government tariffs on imported products will further increase costs.

Supply chains may also become more unstable. Domestic oil production is less vulnerable to many types of disruptions, such as weather events, political crises, and social protests. Product shortages may thus become more common throughout the American economy.

None of these potential impacts is necessarily new to U.S. industry sectors, though. During the 1970s, for instance, the Arab oil embargo caused severe shortages and price inflation in the gasoline and other energy markets. For a brief period of time, the Securities and Exchange Commission (SEC) and the Financial Accounting Standards Board (FASB) both mandated special financial reporting requirements involving "changing prices."

Thus, planners and modelers do have historical examples that can be consulted for guidance. Although the American economy has not experienced these phenomena recently, it may be reassuring to keep in mind that they are not black swan events.

End-To-End Supply Chain Management Systems: Have A Cup Of Coffee!

How has life changed for organizations in this era of tariff-induced supply shortages? For starters, it's more important than ever to prioritize the risk that running out of a single critical part can halt an entire production process.

As a result, holistic and comprehensive end-to-end supply chain management systems are soaring in popularity. Enterprise Resource Planning (ERP) systems may have existed for three decades, but they are now considered more important than ever.

Thus, organizations that seek to gain a market advantage over their direct market competitors may choose to look outside of their industry sectors for ERP exemplars in redesigning end-to-end supply chains. If you're engaging in such an activity, you may decide to have a cup of coffee.

Why? Because coffee bean growers, distributors, and sellers are now adopting the most advanced supply chain management systems to comply with the European Union's Deforestation Regulation (EUDR). This regulation requires that companies throughout the global coffee supply chain institute the internal controls, capture the data, and then complete the necessary "due diligence" to provide assurance that the industry is operating in an environmentally appropriate manner.

The EUDR has been delayed, but it's still on schedule for implementation at the end of this year for large firms and the end of next year for smaller ones. It can take a very long time, though, to develop the necessary systems to comply with it.

Thus, developmental guidance already exists for organizations that are required to implement it. If you're searching for such guidance to inform your own efforts, you may wish to grab a cup of coffee and review the documentation.

Entrepreneurial Capital: A Very Old Sector Produces New Options

Are you an entrepreneur in need of capital? You may have been focusing on private equity, venture capital, and other alternative investment sources. Next year, however, an unexpected sector may present you with new opportunities.

It's the Stock Exchange sector, a source of capital that has existed for centuries. Operating under the TXSE acronym, the new Texas Stock Exchange will launch in Dallas. Meanwhile, using the GIX moniker, a group of former New York Stock Exchange executives will launch a new sustainability-themed entity called the Green Impact Exchange.

During the nineteenth and twentieth centuries, numerous Stock Exchanges operated across the United States. Most of them, however, merged into a handful of trading conglomerates. The NASDAQ, for instance, acquired the Philadelphia Stock Exchange after the venerable organization absorbed the Baltimore, Washington, and Pittsburgh Exchanges.

Until recently, few believed that newly formed Stock Exchanges could compete with much larger rivals in a cost-effective manner. New technologies, though, are expected to level the playing field and bring significant cost efficiencies to these smaller entities.

Furthermore, the ongoing evolution of the American economy may enable certain entrepreneurs to leverage multiple new opportunities. Because Texas is now the nation's largest producer of renewable energy, for instance, regional entrepreneurs in the sustainability field may be eligible to consider both the TXSE and the GIX for their capital requirements.

Will these Exchanges find a niche in the investment sector? They'll clearly face many competitors in the market. Nevertheless, the new entities will likely improve conditions for entrepreneurial firms in need of capital.

AI On The Road: Driverless Freight Trucks To Begin Cruising Interstate Highway This Month

Since Artificial Intelligence (AI) systems seized the spotlight with the initial release of ChatGPT in November 2022, business analysts have been waiting for the technology to be placed in widespread use in major economic sectors. The outcome metrics from such case applications are required to assess the financial implications of the technology on sales, cost, distribution, insurance, and other functions of their business models.

One such case application was just announced by Axios and other news platforms. Aurora Innovation, a self-driving vehicle technology firm, has been testing its driverless (but with human passengers available to assume control) freight trucks in northern Texas. By the end of this month, it plans to begin directing driverless trucks on Interstate 45 between Dallas and Houston.

Driverless freight trucks barreling down an interstate highway? What could go wrong? Will the benefits exceed the risks? Business analysts expect to find out soon.

If you wish to track Aurora's progress, you may visit:

• the home page of Aurora's web site at https://aurora.tech
• Aurora's description of its "verifiable approach to self-driving" at https://blog.aurora.tech/engineering/aurora-verifiable-ai-approach-to-selfdriving
• Aurora's Driverless Safety Report and Safety Case Framework at https://ir.aurora.tech/news-events/press-releases/detail/117/aurora-releases-safety-report-in-preparation-for-driverless

Freight trucks, of course, play a centrally important role in the supply chains of many industry sectors. Driverless freight is thus an attractive sector to begin assessing the business impacts of AI technology.

United Airlines' Scenario-Based Investor Guidance Isn't Worrisome At All

United Airlines is drawing attention over its recent decision to release two different sets of investor guidance. Some commentators are correctly noting that two sets of guidance is a "novel" occurrence.

Usually, companies release one set of guidance that reflects its assumptions about the economy's probable future path. Alternatively, on rare occasions, companies may decline to release any guidance at all, asserting that the economy (at that moment) is so unpredictable that any information would be too speculative to be useful.

So why two? And why now? According to United's economic forecasters, we will either experience an economic recession in the near future, or we will not. If we do, the future will feature one set of economic conditions. If we don't, it will feature a very different set.

That's a classic case of circumstances that warrants an approach called Scenario Analysis. It's different than Sensitivity Analysis, an approach that is employed when future conditions are relatively predictable, but when specific quantitative assumptions (such as sales volume or the cost of labor) may vary by a few percentage points in either direction. 

In Scenario Analysis, one can define two or more (very different) potential future paths. One can also define the economic conditions that would exist for each potential path. However, one cannot be certain (and, instead, one is very uncertain) which specific future path is more likely to become our future reality. 

That's the situation in which United finds itself today. It may be novel from a historical perspective, but it isn't worrisome at all, given the extremely volatile state of our contemporary global economy. Thus, it would not be surprising if other companies adopt United's approach and decide to issue multiple sets of guidance for their own investors.

A Plastics Power Hour

Many thanks to Johns Hopkins School of Advanced International Studies (SAIS) graduate student Shiyuan Liao for an objective and sobering webinar presentation about the uses and risks of plastics in our supply chains and product lines. The webinar was sponsored by SolPods, a nonprofit student-focused community in the sustainability field, and introduced by its Co-Founder and Executive Director Amy Farrell.

Here in the energy corridor of Houston TX, plastics is a major industry sector. Petroleum (i.e. crude oil) is transformed into petrochemicals, which in turn is utilized to manufacture plastics. Thus, plastics is a significant wealth driver in our regional economy.

The recent news of microplastics being detected in human brains reminds some of the historic case of the now-banned insecticide DDT entering human bodies through the food chain and then causing damage in successive generations that inherit the chemical as fetuses.

Fortunately, unlike the situation in the DDT case, medical researchers have not definitively identified any harmful impacts of the presence of these microplastics in human bodies. Nevertheless, it is obviously a potential concern, one that was addressed by Shiyuan Liao in the Q&A discussion after her presentation.

Interested in learning more about the topic? You may wish to reference the Sustainability Accounting Standards Board's measurement and reporting standards for Chemicals. It can be accessed by visiting the "Resource Transformation" industry sector of the SASB standards.

Plastics and microplastics are also covered by the Global Reporting Initiative's standards for Agriculture, Aquaculture, and Fishing (GRI 13), for Materials (GRI 301), and for Waste (GRI 306).  Although the first standard only applies to a single industry sector, the latter two apply to every sector.

Finally, the Target Indicators of the United Nations' Sustainable Development Goals covers plastic debris density in SDG 14.1 (Life Below Water, Marine Pollution).

Incidentally, these resources are all freely viewable or downloadable on the following web pages:

https://sasb.ifrs.org/find-your-industry/

https://globalreporting.org/standards/download-the-standards/

https://sdgs.un.org/goals 

As you can see, the topic of plastics is a deeply complex one. Again, many thanks to Shiyuan Liao and SolPods for educating us on the subject matter.

Staying Focused On Regulatory Risk

What is the greatest short term threat to financial profitability? For many organizations, the obvious answer is now "protective tariffs." That's a reasonable reply, but regulatory risk may represent a potentially greater long term threat to corporate performance.

Earlier this week, for instance, Chevron lost an environmental lawsuit and was ordered to spend three quarters of a billion dollars to restore a damaged region of Louisiana wetlands. In certain respects, the case was reminiscent of General Electric's historic half a billion dollar legal order to remove toxic PCB waste from the bed of the Hudson River.

And a few days ago, the German financial institution Deutsche Bank was assessed a "greenwashing" penalty of 25 millions euros for making misleadingly rosy statements about its ESG practices. Though tiny in comparison to the Chevron penalty, the assessment served as a regulatory signal that firms will be held liable for unsupported public statements regarding sustainability and resilience.

Both firms faced regulatory risks related to sustainability concerns. Only Chevron, though, confronted a concern involving actual environmental damage. Thus, it "paid the price" in the form of a far greater penalty.

Tariffs can inflict tremendous harm on an economic system, but they can appear or disappear in the blink of an eye. Regulatory risks regarding sustainability and resilience, on the other hand, can impose damages that may linger indefinitely.

The Trump Tariff System And The Role Of Sustainability Accounting

A few hours ago, President Donald Trump issued his long-awaited announcement regarding a new tariff system for imports into the United States. The system includes an emphasis on "non-monetary barriers" that compel the U.S. federal government to assess higher tariff rates against certain countries.

The three examples of "non-monetary" barriers that Trump emphasized were currency manipulation, unfair tax policy, and the use of sweatshop labor.

Sweatshop labor is a very obvious example of a social sustainability factor. Unfair tax policy is defined as an economic sustainability factor by sustainability standards organizations like the GRI.  Only currency manipulation generally falls outside of most definitions of sustainability and resilience.

Sustainability accountants will obviously be needed to measure the performance of importers to assess whether nations, or specific companies within nations, are meeting or avoiding these threshold definitions of "non-monetary barriers."

President Trump has never described himself as a proponent of sustainability accounting. Given the need for metrics that define the parameters of "non-monetary barriers," though, he may agree that sustainability accounting will play an important role in the nation's new tariff system.