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Accounting

How AI is forcing a rethink of services, skills and pricing

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The part of my job I love the most is speaking with accounting professionals each week, and connecting with the small and midsized businesses we jointly serve. Lately, those conversations have been pointing me toward the same conclusion: what triggers a business to engage with a firm is changing. 

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Business owners trust their own instincts more when their work is augmented with AI. Compliance events are still the primary trigger for SMBs to consider working with an accounting professional, but as compliance tools mature their use of AI, SMBs are holding on to the accounting work longer. By the time they reach out, they either need a lot more clean-up work, or they’re ready to scale and looking for a strategic partnership with an advisor.

A fundamental shift for the profession

The accounting community is focused on how AI is changing what accountants do. But the more central truth, considering the shift in the way SMBs are operating, is that AI is changing what accounting professionals are for.

For decades, the value of an accounting professional was providing highly consequential, expertise-driven, time-consuming work that business owners simply couldn’t do while running their businesses. The model worked because it was genuinely hard to operate a new business and manage compliance at the same time.

Now, routine tasks that used to anchor billable hours are getting compressed into minutes. Clients defer bringing an accountant on until later, and when they do, the ask is bigger. Yes, they want to outsource financial operations, but only to someone whom they can trust to guide them.

New research from Bill puts it plainly: 87% of accounting firms plan to expand into new services — tax planning, client advisory services, business consulting, fractional CFO work.

This is not a small pivot. It’s a fundamental rethink of what firms are selling, and to whom.

The services AI makes possible

Here’s what I find most interesting about this moment. Every past wave of technology — paper to PC, PC to web, web to cloud, cloud to phone — left firms asking themselves the same question: how do we leverage this for efficiency? They’re asking themselves that same question about AI too, but there is also a second question they’ve got to grapple with. Because of the scale of efficiency firms are poised to benefit from, once automation is doing its job, what are you actually offering? 

Consider what happens when processing a vendor bill drops from 15–20 minutes to just one minute, as it has for firms like Belay that redesigned their AP workflows around AI. What they’ve done is create capacity in a way that doesn’t keep them beholden to a talent pool that just isn’t out there.

Advisory is the assumed answer, and it’s the right one, but for plenty of firms it still feels abstract. They can see the destination but not the road from where they stand.

The way I’ve seen firms find that road depends on the services they’re already delivering. Firms offering CAS, for example, can also help clients design budgets, manage cash flow and set KPIs that guide decisions. AI can surface patterns and anomalies. The firm steps in to frame what they mean and what to do next.

In tax and strategic planning, instead of a relationship centered on a once-a-year filing deadline, I see firms using always-current financials to model scenarios, smooth tax liabilities over time, and advise on things like compensation strategies. AI can support forecasting and what-if analysis, while professionals evaluate trade-offs and risk.

New skills for a new mandate

In our research, roughly two-thirds of firms said they expect the skills they need from their people to change meaningfully in the next few years. Emerging priorities include:

  • Data interpretation and storytelling: Turning AI-generated reports into clear recommendations. The insight is only as valuable as the conversation it sparks with a client.
  • Systems thinking: Understanding how tools connect across AP, AR, spend, payroll, banking and the general ledger — and designing workflows that hold together as an integrated system, not a collection of point solutions.
  • Client education: Helping clients understand new processes and trust what’s happening behind the scenes. As firms adopt AI-driven workflows, the clients who understand and trust the automation get more value from the relationship.

Pricing for outcomes

The firms I find most interesting right now are the ones questioning their billing models outright.

Hourly billing made sense when effort was the primary input. As automation improved, the community started to shift toward value-based billing. Now AI is compressing effort even further, and billing by the hour is starting to work against firms, both economically and in terms of how clients perceive what they’re getting.

Subscription models and outcome-based pricing are gaining ground for exactly this reason. The firms making this shift aren’t just changing how they invoice. They’re changing the conversation from “what did you do for me?” to “what did I gain from working with you?”

Building a transformation roadmap

None of this has to happen all at once, but it does have to start. A pragmatic roadmap might begin with auditing your current services and workflows. Begin by identifying manual, low-margin or error-prone work and flag it for automation or retirement.

Next, standardize your core tech stack. Choose integrated platforms for AP, AR and spend, alongside your general ledger, and commit to them across the firm.

Then, pilot one or two new advisory offerings. Select a segment of clients who are open to change, define a clear value proposition, and experiment with packaging and pricing.

Lastly but most importantly for long-term impact, invest in people and training. Develop your team’s analytical, communication and systems skills so they can step into more strategic roles as transactional work declines.

Key takeaway

AI will likely result in business owners holding on to more of the work, for longer, before they feel the weight of it. But they will feel it. And when they do, the question won’t just be whether to bring in a firm. It’ll be whether the firm they bring in is worth it.

The steps above aren’t just about automating workflows to create capacity for advisory. They’re about building a firm whose value is so clearly tied to client growth that the answer to that question is never in doubt. The kind of firm where holding on would have held the client back, and the partnership is what moved them forward.

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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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