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The next generation’s view of risk management: career or steppingstone?

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1 year ago

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A great benefit of my five-decade career in internal auditing and risk management is the opportunity to work with young people. 

Whether working alongside freshly minted graduates early in my career, working as an adjunct college professor in my mid-career, or speaking at colleges and universities today, being around young, eager minds is simply uplifting and inspiring for me.

So, it should come as no surprise that a recent visit to a major university provided fresh inspiration and insights including this one: The next generation is more likely to see accounting or internal auditing not as a career but as a steppingstone. And here’s the shocker — that may not be a dreadful thing.

One of the biggest challenges facing internal auditing and accounting is recruiting the next generation of workers to each respective profession. The growing use of advanced technology, primarily artificial intelligence, promises significant changes in how accountants and internal auditors will work in the future. To be sure, some speculate AI could soon doom both professions to irrelevance. But as I noted in a recent blog post, the changing nature of our professions may position them for success in the AI era.

This is particularly relevant to how the next generation sees our professions and the kind of work that will attract them. As the first true digital natives, Gen Z and millennials are naturally comfortable with digital tools and platforms, often mastering them with ease. What’s more, this influences how they work, learn and what they expect from their jobs.

So, what does this mean to our professions?

Deloitte’s 2025 Gen Z and Millennial Survey addresses this question nicely. The survey of more than 23,000 young people concludes they are seeking a balance of money, meaning and well-being. From the report:

“Career fluidity is a defining feature of the modern workforce: Nearly one third (31%) of Gen Zs plan to switch employers in the next two years. And while millennials may be more settled in their careers, 17% say they plan to leave their employers within two years. Their job hopping is not driven by a lack of loyalty. Many Gen Zs and millennials see it as a strategy to seek stability, better work-life balance, a greater sense of purpose, and an opportunity to learn and acquire new skills.”

This observation is backed up by longer-term data collected by the U.S. Bureau of Labor Statistics. Its Employer Tenure in 2024 report found the median number of years that wage and salary workers had been at their current jobs dropped to 3.9 years in January 2024, the lowest since 2002. The report found workers between 25 and 34 years of age had a median job tenure of 2.7 years compared to 4.6 years for those 35-44, 7 years for those 45-54, and 9.6 years for those 55-64. 

This data supports my sense that the next generation is looking for jobs that will challenge them, give them opportunities to grow their skills, and provide the work-life balance they rate so highly. These factors also support the idea that young people are leveraging jobs in internal auditing and accounting as steppingstones to opportunity, not somewhere they will stay for a lifetime.

Here’s why that’s not a bad thing. If accounting and internal auditing are viewed as the front door to other career paths, we can succeed in recruiting top talent. The challenge is to present accounting and internal auditing as attractive, even exciting, steppingstones that offer stimulating and meaningful work, the opportunity to travel, competitive wages, and what I call a crow’s nest view of the enterprise. This last aspect could be particularly alluring to younger workers if they see it as an opportunity to identify where they might go next.

Interestingly, the Deloitte survey found that the traditional ambition of “climbing the corporate ladder” is not particularly attractive to Gen Z. Indeed, the report found only 6% say their primary career goal is to reach a leadership position. However, those views could change over time, and a broad base of experience gleaned over numerous stops could be the ideal training for leadership roles within internal audit, finance or the C-suite.

I’ve had a chance to meet many people who came to internal auditing early in their careers, had a prosperous tenure there, then went into the business, who were later tapped to come back to be the chief audit executive. I’m one of them. It’s not a badge of shame to leave internal audit because that may be your best strategy for a leadership role.

From an executive management perspective, this is an ideal strategy; leverage internal auditing and accounting to lure great talent into the organization.

I have written extensively in the past decade about how growing risk velocity, an increasingly volatile risk landscape, digital disruption and a sense of permacrisis are dramatically changing risk management. How we manage these new challenges will define the future not only for accounting and internal auditing, but for business. What I’ve learned is that trying to fit this new reality into traditional approaches to business will never succeed. We must accept change and embrace chaos.

And so it is with the views of the next generation of workers. They hold the key to balancing humanity with technology. We shouldn’t get caught up in whether we will capture the best and the brightest for the next 40 years. But while we have them, we must ensure they develop the key skills that accounting and internal audit offer that AI cannot deliver: critical thinking, relationship acumen, intellectual curiosity, empathy and ethical resilience.

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Accounting

AI-Driven Automation and Continuous Accounting Frameworks

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6 days 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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2 weeks 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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2 weeks 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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