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How can CFOs build resilience while facing down challenges?

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2 years ago

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As businesses navigate turbulent economic waters, CFOs face mounting challenges in their mission to manage costs, optimize resources and maintain financial resilience. These challenges are made even more urgent by a well-documented global shortage of talent across many industries, including an accounting talent shortage that’s been building for several years. These shortages, along with unpredictability in markets, are not only ratcheting up the challenges for CFOs, they’re also underscoring the importance of creating agile, resilient organizations. 

How much of a problem is talent scarcity?

Hiring and retention were the hardest challenges CFOs dealt with in 2022 and 2023, and it’s increasingly expensive for companies to hire in-house talent. A Gartner survey found that 58% of CFOs plan to raise average employee compensation by 4% to 9% this year. Another 13% of CFOs will implement average raises of 10% or more. The only other category where CFOs plan to increase spending is technology.

A shortage of qualified hires creates work backlogs that fall on existing employees, which can stress them to the point where they decide to change employers, further exacerbating the problem. What’s more is unfilled seats and overworked team members contribute to operational challenges: when the work doesn’t get done, or contains human errors, the results can be dissatisfied customers and clients, financial reporting errors, and costly noncompliance, especially in accounting and finance roles. 

How can CFOs maintain or build flexibility in their organizations?

When talent scarcity problems accumulate, it’s virtually impossible for a company to scale efficiently or to stay flexible and resilient in a changing economic environment. To avoid reaching this point — or to start resolving existing inflexibility — CFOs can invest more in hiring, training and retention, and explore their options for automation to reduce the number of tasks that employees need to perform. CFOs can also consider outsourcing as a way to introduce a scalable team solution.

Double down on hiring?

Committing more resources to hiring and retention is the traditional option, but in today’s market it may not be the most effective or cost-efficient strategy. According to Deloitte’s Q4 2023 CFO Signals report, 42% of CFOs say their companies will hire more people than they let go in 2024. However, building and maintaining a full talent pipeline may require resources, such as internal recruiting teams or external acquisition feeds, that could be better allocated elsewhere, such as implementing automation for standardized and repetitive tasks. In some cases, it may be next to impossible to keep the pipeline and in-house roles full because the talent simply isn’t available in-market. While it’s important to invest in internal hiring, that alone may not be enough to support flexibility and scale. 

Add automation

In 2023, more than half of CFOs (51%) began automating tasks that had been done by employees, according to a Q1 2024 survey by the Federal Reserve and Duke University’s Fuqua School of Business. The top three reasons for automation were cost savings, quality control and employee experience. Among CFOs who implemented automation, 59% said it allowed them to maintain hiring, while 29% said automation allowed them to slow hiring and 16% said it allowed them to leave roles unfilled. 

Expect to see more organizations adopting automation. 80% of CFOs surveyed by Deloitte expect to leverage more automation in 2024. Of those respondents, 81% are planning to use automation to take rote tasks off current employees’ to-do lists so they can work on activities that create more value (and also improve the employee experience).

However, automation is not a quick fix. It requires resources that organizations may not have yet, which is one reason that the Fed survey found that 75% of the CFOs who deployed automation in 2023 worked for large firms. Automation requires investment to get the company ready, such as data unification and standardization. It also requires integrations with the organization’s existing enterprise software, which can take time to accomplish. Nonetheless, mid-sized and even small companies are now laying the groundwork for automation in targeted use cases, which can help position them for future expansion.

Explore AI now for greater leverage later

AI holds a great deal of promise for automation and operational assistance. However, because the technology is new, there’s a lot that has to happen before AI can take over any tasks, especially within the finance and accounting function. 

Not quite a quarter of CFOs told Deloitte they expect their organizations to prioritize AI governance this year, and that governance is critical for implementing use cases that can scale. A solid governance program is also important for meeting regulatory requirements as they emerge. In the meantime, non-AI automation for basic tasks can help build out an automation program that’s more ready to scale when the time comes to apply AI.

Outsource some roles or responsibilities

Outsourcing is another option for maintaining flexibility and resilience, and 35% of CFOs surveyed by Deloitte said their organizations will outsource more operational activities in 2024. A recent survey found that enterprises that outsource business processes save an average of 15%. That savings can arise from lower talent costs and less spending on more challenging recruitment and training for in-house hires. 

Outsourcing also opens up new markets of talent for organizations, and in the age of remote work, many business leaders are starting to see outsourcing as a natural extension of remote work. If an accounting team is working from home, the logic goes, it doesn’t necessarily matter where in the world that home is. One Stanford economist forecasts that “about 10% to 20% of U.S. service support jobs like software developers and human-resources professionals could move overseas in the next decade.” Exploring outsourcing now can give companies an advantage in controlling costs, filling roles, and maintaining operations for greater stability and flexibility, regardless of what the domestic labor market is doing.

Balancing the options for a stronger organization

Solutions for companies will vary, depending on their resources and stage of growth, and not every solution may fit or be attainable. At the same time, each of the solutions on its own is unlikely to achieve the CFO’s long-term growth and resilience strategies. By understanding how hiring, automation, AI and outsourcing contribute to operational efficiency, cost and quality, CFOs can identify the optimal combination of solutions to build resilience into their teams and meet the financial needs of their business now and over the long term.

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Accounting

AI-Driven Automation and Continuous Accounting Frameworks

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11 hours ago

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August 15, 2026

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The accounting profession is undergoing a fundamental structural transition as enterprise finance departments shift from periodic month-end closes toward automated continuous accounting models. By integrating specialized machine learning algorithms directly into enterprise resource planning (ERP) platforms, chief accounting officers are transforming financial reporting from a retrospective exercise into a real-time operational asset.

The Shift from Periodic Close to Continuous Financial Reporting
Traditional accounting workflows heavily relied on manual data reconciliation, spreadsheet calculations, and multi-week closing cycles at the end of each fiscal period. In contrast, continuous accounting frameworks utilize automated software agents to process, validate, and post transactional data in real time as business activities occur.

Automated bank reconciliation tools cross-reference incoming bank feeds, invoice records, and purchase orders automatically. By resolving transactional variances instantly throughout the month, corporate accounting teams eliminate the traditional workload spikes associated with quarterly and annual closes.

Machine Learning in Audit Trails and Anomaly Detection
Advanced natural language processing (NLP) and machine learning tools are redefining internal audit and financial control environments. Automated systems analyze 100% of general ledger entries, identifying anomalous transactions, duplicate payments, and unauthorized journal entries in real time.

Rather than relying on random statistical sampling, corporate internal auditors can focus their attention on high-risk flags automatically surfaced by algorithmic monitoring platforms. This continuous risk assessment strengthens internal controls over financial reporting (ICFR) and significantly reduces fraud risk.

Evolving Roles for Accounting Professionals
As routine data entry and manual reconciliation tasks become fully automated, the skill set required for accounting professionals is shifting toward data analysis, system design, and strategic business advisory.
– Systems Governance: Accountants are increasingly responsible for monitoring algorithmic accuracy and managing data integration pipelines.
– Business Partnership: Finance professionals leverage real-time financial dashboards to advise operational leaders on margin management and working capital allocation.
– Regulatory Compliance Management: Accounting teams utilize automated platforms to ensure compliance with dynamic tax codes and international accounting standards.

Core Implementation Recommendations
1. Deploy Automated Reconciliation Tools: Integrate continuous transaction processing modules into existing enterprise ERP architectures.
2. Establish Algorithmic Governance Controls: Implement strict internal testing protocols to ensure automated accounting rules comply with GAAP/IFRS standards.
3. Reskill Accounting Teams: Invest in training finance staff on data analytics, workflow automation, and predictive financial modeling.

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Accounting

Global ESG Reporting Standards and Double Materiality Compliance

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6 days ago

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August 9, 2026

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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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1 week ago

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August 5, 2026

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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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