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Managing expectations key to AI implementation for CAS

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AI implementation at a CAS practice is hard enough, but it becomes even more so when people don’t fully understand what AI can and cannot do. 

Speaking during the Information Technology Alliance’s spring collaborative in Memphis, Tennessee, Jessica Barnas, the partner leading the finance and accounting solutions advisory group for top 25 firm Wipfli, lamented that public discourse around AI has given people the impression it’s some sort of magic wand that can fix anything, which then leads to unrealistic expectations around its capabilities. 

“I talked to a lot of clients, I think they think that AI is like an elf that jumps out of the box and does things magically. They just say, ‘Can’t AI do that?’ I even had one of our partners [tell me this recently], we’re working on a five year revenue prediction—he said, ‘Well, can’t you just upload that to Copilot and have it spin up the business plan and everything?’ and I’m like, ‘Do you have any idea how generative AI works? It doesn’t do that.’ But I think that there’s just this misconception [that], oh, technology it is just this magic wand that’s going to make all of my accounting problems disappear,” Barnas said. 

Chris Gallo, director of outsourced business accounting services with Kansas-based firm Creative Planning and another one of the panelists, made a similar point, saying that it’s important to be realistic about what technology can do. While it can do a lot, he echoed Barnas in saying that some people seem to think it is magic. 

“If we believed everything that everybody told us you would be flying around in flying cars right now. I think we need to kind of take it with a grain of salt at some point. Because why wouldn’t we just say ‘ChatGPT build me a flying car,’ and then the bot people that you know Tesla’s building will just go do that. Right? It becomes a little bit ridiculous at some point too… There’s a lot of expectation, or unaligned expectations,” said Gallo. 

Misconceptions about AI capabilities also serve to drive fear on the part of accountants. Barnas said that a big part of the change management process when it comes to implementing AI is allaying fears from staff that they’re not going to fire everyone and replace them with bots. While there have been major improvements in AI over the years, she does not believe it is in the position to wholesale replace human accountants just yet. Instead, it has become a great way to augment those humans and make them more competitive against the humans who are not using AI. 

“They think ‘AI will eliminate my job!’ So we talk about our philosophy. We’re looking to adopt these tools to help you get bigger and better and embrace the advisory role, but the only way AI will replace you is if a person using AI will replace you. You need to give that level of comfort to your teams so that everyone knows we’re just trying to get better, we’re just picking up new tools, this is not a replacement for you,” Barnas said. 

There is a similar fear when it comes to billable hours, also explored in another panel (see other story), of what happens when a process that normally takes 8 hours now only takes 1. Barnas first described the billable hour as “the enemy of all of us here in the room” but also conceded it is a real anxiety for practices that have built their foundation on it. She suggested, in response to this concern, to take a page from Google and encourage people to develop pet projects using AI and rewarding them if it turns into something useful for the entire team; and if it really does lead to a reduction in billable hours, don’t punish people with less money when they’ve done what you wanted them do in the first place. Overall, a firm’s business model should not be one that punishes efficiency: a practice should value results, not burning hours. She conceded that, for certain firms set in their ways, this might need retraining. 

“Okay, I took this process down from seven hours to half hour every week. Now what? Teach me how to do advisory. Because being a CFO, doing modeling and projections, it is not something [you learn] from reading a book or sitting in on one webinar. We would all be doing that if that were the case. So how can we train our teams on what to do next? All of that is involved in change management: being a guide and providing the safety for each step,” she said. 

Gregg Landers, the last panelist and managing director of client accounting and advisory services and internal control services with Top 10 firm CBIZ, talked about how a lot of the misunderstandings and misconceptions regarding AI can be allayed from people just experimenting with it themselves, which not only lets them get a better impression of its current capabilities but will train them in using those capabilities to their fullest potential. 

“I’ve been encouraging some of my teams to use their personal generative AI a little Black Mirror-like, [where you] keep talking to it, and it talks back. You get accustomed to how to give a context, how to get better answers. Sometimes, if you’re nice to it, [you get] a tighter answer than if you’re not. So experiment around with it. 

He gave an example from his own life, where he needed to learn more about digital services taxes. Through an extended conversation with an LLM  he was able to understand what the DST is and how it works and how accountants manage it. He was able to get good outputs from the model, though, because previous experience taught him that he needs to provide more context and information for a decent answer, because these models can get tripped up by ambiguities. He compared it to a fortune cookie that could be interrupted in many ways, people should be clear and concise when prompting AIs. 

“We’ve become a society of fortune cookies. I may ask ‘how is that project going’ and you tell me ‘it’s going good’ but what I mean is ‘is it on time?’ and what you might mean is ‘I had this hiccup that put me two weeks behind but now it is resolved so it is good.’ We can’t have fortune cookies when interacting with generative AI. You need clear, concise, contextual communication,” he said.

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Accounting

Global ESG Reporting Standards and Double Materiality Compliance

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Corporate accounting departments face expanding reporting expectations as international sustainability disclosure standards achieve regulatory enforcement across major global jurisdictions. Chief Accounting Officers (CAOs) and corporate controllers are establishing rigorous internal accounting controls to treat Environmental, Social, and Governance (ESG) metrics with the same data precision, auditability, and governance as traditional financial statements.

Regulatory Harmonization Under Global Sustainability Frameworks
The implementation of standardized sustainability reporting frameworks—notably rules established by international sustainability accounting boards—has created unified expectations for public and large private enterprises. Corporations must report standardized metrics covering greenhouse gas emissions (Scope 1, 2, and material Scope 3), energy utilization, workforce demographics, and supply chain governance.

In Europe and other participating international jurisdictions, double materiality principles are mandatory. Under double materiality, organizations must report both how external sustainability risks impact corporate financial performance, and how internal corporate operations affect surrounding environmental and social structures.

Integrating Sustainability Metrics into Core ERP Systems
To provide auditable non-financial data, enterprise organizations are integrating specialized carbon accounting and ESG management platforms directly into core ERP systems. Automated data collectors capture energy utility invoices, logistics fuel consumption metrics, and vendor compliance records in real time.

Establishing automated, traceable data pipelines ensures that non-financial reporting is supported by clear audit trails. This structured approach allows external financial auditors to provide reasonable assurance on sustainability disclosures during annual corporate reporting cycles.

Financial Impacts and Capital Market Disclosure
Accurate ESG reporting directly influences corporate cost of capital and institutional credit ratings. Commercial lenders and institutional asset managers systematically incorporate sustainability metrics into risk pricing models. Companies that demonstrate transparent, verifiable progress in operational energy efficiency and climate risk mitigation benefit from expanded access to green bond markets and lower debt pricing.

Action Steps for Accounting Leadership
1. Implement Double Materiality Frameworks: Conduct comprehensive assessments to identify material financial and operational sustainability metrics.
2. Build Auditable Non-Financial Data Pipelines: Automate ESG data collection within core accounting software to ensure data integrity.
3. Align Sustainability with Annual Financial Filings: Prepare non-financial disclosures concurrently with financial statements to satisfy regulatory audit expectations.

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Accounting

Modernizing Internal Controls: Machine Learning and Continuous Monitoring in Auditing

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Internal audit departments and corporate risk managers are modernizing internal control frameworks by shifting from periodic sampling techniques to continuous monitoring and machine learning analytics. As operational data volumes increase across enterprise organizations, automated control testing ensures financial integrity, prevents corporate fraud, and streamlines annual audit engagements.

The Limitation of Periodic Audit Sampling
Historically, internal and external auditors evaluated internal controls by reviewing random samples of financial transactions—often analyzing less than five percent of total ledger entries. In complex enterprise environments, periodic sampling methods carry inherent risks of overlooking localized financial misstatements, unauthorized disbursements, or operational control breakdowns.

In 2026, progressive internal audit functions are utilizing automated continuous monitoring platforms that evaluate one hundred percent of financial transactions in real time. Continuous control auditing systems continuously monitor general ledger entries, procurement approvals, and expense reimbursements across all operating subsidiaries.

AI-Powered Fraud Detection and Anomaly Identification
Machine learning models trained on historical corporate financial data excel at identifying subtle transactional anomalies that indicate potential fraud or operational error. Automated systems instantly flag duplicate invoice payments, unapproved vendor creation, unusual journal entry timing, and unauthorized override of authority thresholds.

When an anomaly is detected, the automated auditing platform generates an instant risk alert, allowing internal audit teams to investigate root causes immediately. Early detection prevents minor operational errors from escalating into material weaknesses in financial reporting.

Streamlining External Audit Preparation
Continuous internal control monitoring delivers significant benefits during annual external financial audits. External audit firms can review continuous audit logs and automated control testing documentation, reducing the time required for manual field testing.

This integrated approach lowers overall audit compliance fees, reduces administrative burdens on corporate accounting staff, and provides senior management and audit committees with real-time visibility into the organization’s overall risk profile.

Core Implementation Guidelines
1. Transition to 100% Data Testing: Replace legacy sampling methods with automated continuous audit monitoring systems.
2. Deploy Anomaly Detection Algorithms: Implement machine learning models to identify unauthorized transactions and operational control overrides.
3. Align Internal and External Audit Workflows: Coordinate continuous control testing protocols with external auditors to optimize annual compliance cycles.

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Accounting

Automated Tax Compliance and Global Regulatory Harmonization in 2026

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Corporate tax accounting departments are navigating an era of unprecedented regulatory complexity as global tax harmonization frameworks take full effect alongside real-time digital tax reporting mandates. Tax directors and accounting teams are adopting cloud-based tax compliance automation tools to manage multi-jurisdictional tax liabilities and satisfy stringent reporting rules across international jurisdictions.

Implementation of Global Minimum Tax Provisions
The implementation of international tax reform agreements—notably the Pillar Two global minimum tax framework—has reshaped multinational corporate tax planning. Multinational enterprises with consolidated revenues exceeding established thresholds must ensure an effective tax rate of at least 15% across every jurisdiction in which they operate.

Accounting teams are implementing specialized tax calculation modules integrated directly into enterprise resource planning (ERP) platforms. These automated tools calculate effective tax rates per country, identify top-up tax liabilities, and generate standardized compliance documentation required by national tax authorities.

Real-Time Digital Invoicing and E-Reporting Mandates
Tax authorities across Europe, Latin America, and Asia-Pacific have enacted mandatory electronic invoicing (e-invoicing) and continuous transaction controls (CTC). Under these systems, corporate transaction data must be submitted electronically to government portals in real time at the point of sale or invoice issuance.

This shift toward continuous digital tax reporting eliminates traditional annual tax audits in favor of ongoing automated compliance monitoring. Accounting departments are upgrading invoicing software to ensure seamless XML data formatting, digital signature authentication, and real-time validation against tax authority databases.

Automation and Data Analytics in Corporate Tax Strategy
To keep pace with dynamic tax legislation, tax departments are transitioning from reactive compliance teams to proactive strategic advisors. Machine learning algorithms analyze corporate transactional data to identify tax credits, research and development (R&D) incentives, and cross-border transfer pricing adjustments.

By automating routine tax return filings and calculations, corporate tax directors can focus on long-term capital structuring, evaluating the tax implications of corporate mergers, and optimizing international supply chain networks.

Strategic Priorities for Tax Executives
1. ERP System Upgrades: Ensure enterprise software is capable of generating real-time, granular tax data required for global minimum tax compliance.
2. E-Invoicing Integration: Implement scalable e-invoicing platforms to satisfy regional continuous transaction control regulations.
3. Strategic Tax Analytics: Utilize predictive tax modeling tools to evaluate structural changes in corporate operations and cross-border trade.

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