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Responsible AI in accounting: Addressing firms’ top 5 concerns

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Generative artificial intelligence is making inroads into the accounting industry, promising to greatly increase efficiency and productivity while offering real-time, deep insights that help improve performance. As firms deal with labor shortages and expand their services amid elevated client expectations, they are avidly exploring AI’s possibilities.

AI doesn’t come without caveats, particularly for accounting firms that work with highly sensitive personal and financial information of their clients. Although Gen AI’s potential benefits are considerable, firms should proceed cautiously and understand its impact on business.

For all of its potential, AI may not immediately solve all of the industry’s challenges. As the initial excitement subsides, it’s critical that IT teams ensure that any AI initiatives align with the objectives of their stakeholders — including the firm itself, clients and regulatory bodies. 

The steps to implementing responsible AI

Building a responsible AI strategy starts with a clear understanding of the specific problems or opportunities the firm aims to address with AI, coupled with a commitment to educating leadership and employees on what AI can and cannot achieve. This foundation ensures AI is implemented and used thoughtfully, with resources aligned to deliver maximum impact. 

Accounting firms also need a strong data and analytics strategy to ensure their data is well-structured before implementing AI. Structured data is the backbone of responsible AI, enabling faster, more accurate insights and transforming data into a powerful decision-making tool. Without it, AI risks stumbling on inconsistencies and poor-quality data, leading to misguided outcomes and wasted resources. In short, well-structured data unlocks AI’s full potential.

Once these fundamentals are in place, firms can assess their current maturity and readiness for AI implementation. Using a Capability Maturity Model specific to knowledge work automation provides a structured framework for this purpose, helping firms evaluate their competencies across five key considerations when adopting new technologies:

  • Information strategy;
  • Governance/resourcing;
  • Technology/IT infrastructure;
  • Level of automation; and.
  • End-user capabilities.

By using the model, firms can identify their capability levels in each category, ranging from beginner to advanced. For example, in the area of information strategy, a firm with minimal IT and business alignment may be considered a beginner, whereas one with integrated alignment across IT, business and executive functions may be classified as more advanced.

Responsible AI will prioritize safety, transparency and trustworthiness. Firms need to strike a delicate balance between innovation and security, which first requires a thorough evaluation of data connectivity, curation, and confidentiality. 

To properly incorporate responsible AI, there are five essential areas accounting firms should consider:

Protecting client privacy

Because safeguarding client information is the foundation of building trust with clients, privacy protections must be a top priority when accounting firms add solutions to their tech stack or develop new tools.

Firms can ensure they meet client expectations of confidentiality by practicing techniques like data minimization, ensuring firms handle the least amount of information required for a specific purpose. That can reduce the risk of data breaches, privacy violations and misuse.

Firms should also never share client information on public platforms like ChatGPT, which are vulnerable to cybersecurity threats that the firm has no control over.

Guarding against bias

An AI model trains by analyzing enormous volumes of data and applying what it learns to perform its tasks. Data scientists and developers need to be wary of the information they use to train and create AI algorithms. If biases exist in the training data, those biases will be replicated in the AI model’s work and generate unrelated or incorrect information. 

For example, a model may be trained to scrutinize a particular account that has a history of misstatements while overlooking new accounts in the current year. Or it may apply a biased risk profile to particular groups of clients based on historical data rather than client-specific information. IT teams should scrutinize inputs and outputs regularly to detect biased results.

Promoting trust through transparency

AI’s performance should not be a mystery; the models used by accounting firms should be simple, auditable and explainable. Explainable AI methods and tools can show how AI arrives at its decisions, allowing humans to understand the outcomes or identify and address potential issues. Establishing this level of transparency will help foster and demonstrate trust and respect with customers, users, and stakeholders.

Enforcing accountability

Better transparency enables better accountability. A user or group of users — which can include developers, deployers and even end users — should be assigned to regularly monitor and audit the firm’s AI models. They should be able to explain the rationale behind the AI’s outputs and perform updates or make adjustments to correct issues or errors. 

Redefining roles

The truth is that AI isn’t going to replace accountants, but it will redefine their roles. AI has the power to transform the way accountants work, freeing employees from mundane tasks to drive growth. Accountants need to grasp the power of pairing their expertise with AI and learn to work with it to improve performance and efficiency.

AI will need accountants to provide extensive monitoring and oversight. But by taking over a lot of routine tasks that accountants spend time on now, AI will allow them to focus on more complex high-level initiatives. In the process, AI will help alleviate the labor shortage and could improve firm retention.

Future-forward accounting firms can reap immense benefits from GenAI as they embark on their digital transformation journey. However, they need to ensure they protect privacy and security. Implementing AI within a capable knowledge work automation framework can, for example, help ensure that data remains confidential, stays within internal system boundaries and that employees have access only to the data they need.

Making sure AI models are trained on complete, bias-free data. Having accountants monitor AI’s outputs can maintain transparency and ensure efficient, effective use of the technology. AI is part of the path forward for the industry, but firms need to be sure they step carefully.

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Accounting

Depreciation of Assets and Key Strategies for Accurate Valuation

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Mastering Depreciation: Key Strategies for Accurate Asset Valuation

Depreciation is a cornerstone of financial accounting, playing a critical role in accurately representing an asset’s value over its useful life. Beyond its technical definition, depreciation serves as a vital tool for financial reporting, tax planning, and operational strategy. This article dives into the primary methods of depreciation and their strategic importance for businesses aiming to optimize asset valuation.

At its core, depreciation is the process of allocating the cost of a tangible asset over its expected lifespan. It ensures that financial statements reflect the true economic wear and tear of assets, offering stakeholders a clear picture of a company’s financial health. Choosing the right depreciation method is crucial for aligning financial reporting with operational realities.

One of the most commonly used methods is the straight-line method, celebrated for its simplicity. This approach spreads the depreciation expense evenly across the asset’s useful life. While straightforward, it doesn’t always capture an asset’s actual usage pattern, especially for items that experience higher wear and tear in their early years.

For businesses with assets that lose value more quickly in their initial years, the declining balance method provides a better alternative. As an accelerated depreciation method, it assigns higher depreciation expenses in the earlier periods of an asset’s life. This approach can align better with revenue generation during an asset’s most productive years while potentially offering upfront tax advantages.

The units of production method is particularly suitable for assets whose depreciation is directly tied to usage, such as manufacturing equipment or company vehicles. This method calculates depreciation based on output, ensuring expenses reflect actual wear and tear. It’s a practical choice for industries with fluctuating production volumes.

Another accelerated option, the sum-of-the-years’ digits method, combines aspects of straight-line and declining balance approaches. By applying a weighted percentage to each year of an asset’s life, this method suits technology assets or other items prone to rapid obsolescence, offering a balanced middle ground for depreciation calculation.

Selecting the right depreciation method is a strategic decision that extends beyond regulatory compliance. It directly influences financial statements, tax liabilities, and even operational decision-making. Factors such as the asset type, industry norms, and specific usage patterns should inform this choice. For instance, a construction company might benefit from the units of production method, while a tech startup might prefer an accelerated approach for its rapidly depreciating hardware.

Advancements in financial management software have revolutionized depreciation modeling. These tools allow businesses to simulate various depreciation methods, providing data-driven insights to support strategic decisions. Automated tracking, scenario analysis, and real-time reporting capabilities further streamline the process, ensuring compliance and accuracy.

In conclusion, mastering depreciation methods is essential for businesses aiming to maintain accurate financial records and make informed decisions about asset management. Whether choosing simplicity with the straight-line method or leveraging the flexibility of accelerated approaches, businesses that understand and strategically apply depreciation can enhance transparency, optimize tax planning, and improve operational efficiency. By prioritizing accurate asset valuation, companies can better position themselves for long-term success.

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Terror suspects share strange similarities; FBI sees no link

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One suspect in the two New Year’s Day incidents being probed as terror attacks was a former U.S. Army sergeant from Texas who recently worked for Big Four firm Deloitte. The other was a U.S. Army special forces sergeant from Colorado on leave from active duty.

Law enforcement officials on Thursday said there appears to be no definitive link between the two deadly events: a truck attack in New Orleans that left at least 15 dead and the explosion of a Tesla Cybertruck outside of President-elect Donald Trump’s hotel in Las Vegas that killed the driver and injured seven. 

But in addition to the military backgrounds of the suspects — they both served in Afghanistan in 2009 — on the day of the attacks they shared at least one other striking similarity: Both men used the same rental app to obtain electric vehicles. 

The driver of the Cybertruck was identified as Matthew Alan Livelsberger of Colorado Springs. He rented the Cybertruck on Turo, the app also used by Shamsud-Din Jabbar, the suspect in the separate attack in New Orleans hours earlier. Turo said it was working with law enforcement officials on the investigation of both incidents.

There are “very strange similarities and so we’re not prepared to rule in or rule out anything at this point,” said Sheriff Kevin McMahill of the Las Vegas Metropolitan Police Department.

The gruesome assault on revelers celebrating New Year’s in New Orleans’ famed French Quarter and the explosion in Las Vegas thrust U.S. domestic security back into the spotlight just weeks before Donald Trump is sworn in as president.

Texas roots

As authorities combed through the macabre scene on Wednesday in New Orleans’ historic French Quarter, they said they discovered an ISIS flag with the Ford F-150 electric pickup truck that barreled through the crowd. Two improvised explosive devices were found in the area, according to the FBI.

Jabbar had claimed to join ISIS during the summer and pledged allegiance to the group in videos posted on social media prior to the attack, according to the FBI. An official said there’s no evidence that ISIS coordinated the attack.

Officials said the 42-year-old Jabbar, who lived in the Houston area, exchanged fire with police and was killed at the scene.

Jabbar has said online that he spent “all his life” in the Texas city, with the exception of 10 years working in human resources and information technology in the military, according to a video promoting his real estate business.

After serving as an active-duty soldier from 2006 to 2015 and as a reservist for about five years, Jabbar began a career in technology services, the Wall Street Journal reported. He worked for Accenture, Ernst & Young and Deloitte.

Jabbar was divorced twice, most recently from Shaneen McDaniel, according to Fort Bend County marriage records. The couple, who married in 2017, had one son, and separated in 2020. The divorce was finalized in 2022. 

“The marriage has become insupportable due to discord or conflict of personalities that destroys the legitimate ends of the marital relationship and prevents any reasonable expectation of reconciliation,” the petition stated.

McDaniel kept the couple’s four-bedroom home southwest of Houston. She declined to comment when contacted at her house in suburban Houston.

Fort Bragg

Jabbar moved to another residence in Houston, which the FBI and local law enforcement spent all night searching before declaring the neighborhood of mobile homes and single-story houses safe for residents. Agents cleared the scene shortly before 8 a.m. local time without additional comment.

Jabbar’s mobile home is fronted by an 8-foot corrugated steel fence that was partially torn apart to provide search teams access. Weightlifting equipment and a bow hunting target were scattered across the broken concrete walkway. Chickens, Muscovy ducks and guinea fowl roamed the property.

Behind the home, a yellow 2018 Jeep Rubicon sat with its doors left wide open and a hardcover book written in Arabic sitting atop the dashboard. The license plate expired in May 2023.

The other suspect, Livelsberger, was a member of the Army’s elite Green Berets, according to the Associated Press, which cited unidentified Army officials. He had served in the Army since 2006, rising through the ranks, and was on approved leave when he died in the blast.

Livelsberger, 37, spent time at the base formerly known as Fort Bragg, a massive Army base in North Carolina that’s home to Army special forces command. Jabbar also spent time at Fort Bragg, though his service apparently didn’t overlap with Livelsberger’s.

Las Vegas Sheriff McMahill said they found his military identification, a passport, a semiautomatic, fireworks, an iPhone, smartwatch and credit cards in his name, but are still uncertain it’s Livelsberger and are waiting on DNA records.

“His body is burnt beyond recognition and I do still not have confirmation 100% that that is the individual that was inside our vehicle,” he said. 

The individual in the car suffered a gunshot wound to his head prior to the detonation of the vehicle.

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Accounting

FASB seeks feedback on standard-setting agenda

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The Financial Accounting Standards Board today asked stakeholders for feedback on its future standard-setting agenda. 

The FASB published an Invitation to Comment and is requesting feedback on improvements to financial accounting and reporting needed to give investors more and better information that informs their capital allocation decision-making, reduce cost and complexity, and maintain and improve the FASB accounting standards codification. 

Stakeholders should review and submit feedback by June 30.

Financial Accounting Standards Board offices with new FASB logo sign.jpg

Patrick Dorsman/Financial Accounting Foundation

“As a result of the significant progress on the 2021 agenda consultation priorities, the FASB staff is once again seeking stakeholder input on the Board’s future agenda and initiatives,” FASB technical director Jackson Day said in a statement. “We encourage stakeholders to take this opportunity to review the ITC and share their views on financial accounting and reporting priorities they think the Board should address going forward.”

The FASB began the current agenda consultation in 2024, doing outreach to over 200 stakeholders, including investors, practitioners, preparers and academics. The discussion in this ITC is based on input received from those stakeholders and does not contain FASB views. Most of those stakeholders said “there is not a case to make major changes to generally accepted accounting principles at this time,” according to the announcement, so many of the topics that were suggested focus on targeted improvements to GAAP.

The board encourages stakeholders to continue to submit agenda requests about needed improvements to GAAP as they arise.

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