While discourse often centers around the risk of AI eliminating jobs, recent data shows that at least some leaders expect they will actually be growing their headcount as they implement the technology in their organizations.
A recent Deloitte poll of 2,000 director-to-C-suite level professionals found, among other data points, that 39% of respondents predict they will increase headcount to implement their generative AI strategies at least slightly, versus the 22% who say they will expect to reduce headcount.
These figures differ based on respondents’ self-reported expertise with AI, with those who have more expertise generally expecting more headcount changes, either positively or negatively. Of those who say they are very proficient with AI, 45% predict their organization’s headcount will increase and 23% say it will decrease. Over half (57%) of those with the least expertise, meanwhile, generally expected things to remain the same; in contrast, only 28% of those with high reported expertise believe the same.
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These predictions are part of the overall anticipation that generative AI will change talent strategies. The poll found that three-quarters (75%) of the respondents expect this shift to happen within two years. Only 16% thought it would take longer than that, and 18% say they are making such changes now. As for what changes are expected, the most commonly cited at 48% was “redesigning work processes to take advantage of generative AI,” followed by “designing and implementing upskilling and reskilling strategies” at 47%.
“These survey results suggest a strong need for more attention paid to generative AI’s talent impacts,” said the Deloitte report. “In the near term, AI education and fluency will be especially important to fostering adoption and overcoming initial resistance to change. In the longer term, upskilling or reskilling and redesigning work processes and career paths will likely be essential for capturing generative AI’s full value and positioning workers for future success.”
This data is similar to that found in another recent survey from EY, which polled more than 250 leaders in the technology industry. It found that half of technology business leaders (50%) say they anticipate both layoffs and hiring at their company in the next six months as a result of AI adoption. More granularly, the data shows that 20% of the tech leaders surveyed said they anticipate layoffs and 27% said they anticipate hiring over the next six months. However, three out of five technology leaders (61%) say emerging technology has made it more challenging for their company to source top technology talent.
They are also working hard on upskilling talent. Over three in four technology business leaders (76%) say they have implemented internal technical certification to help employees keep pace with rapidly changing GenAI. Further, more than half (51%) say they have put external technical certification in place at their company to help keep pace with rapidly changing GenAI. Finally, nearly two-thirds of technology business leaders (64%) say their company has put internal development programs in place to help employees keep pace with rapidly changing GenAI.
“One thing is certain: Companies are reshaping their workforce to be more AI savvy,” said EY technology, media and telecom AI leader Vamsi Duvvuri. “With this transition, we can anticipate a continuous cycle of strategic workforce realignment, characterized by simultaneous layoffs and hiring, and not necessarily in equal volumes. But it’s not all doom and gloom. Employees and companies alike continue to show enthusiasm around AI, specifically when it comes to opportunities to scale and compete more effectively in the marketplace.”
This upskilling, reskilling and shifts to talent strategy are due at least in part to the technical skills and knowledge needed to successfully implement generative AI solutions in an organization. Getting value from generative AI is not always easy. Indeed, another poll from RSM found that while many are using AI in their workplace, a majority say implementing the technology has been harder than expected.
The poll, which included 510 middle-market decision makers in the U.S. and Canada, indicated a great deal of enthusiasm for AI. It found 78% of middle-market organizations are adopting AI, with 77% adopting generative AI in particular. With this enthusiasm has come investment: 89% of executive respondents reported their organizations plan to boost their budgets around AI technologies and 74% are focusing their dollars specifically on generative AI.
Yet, 54% of respondents report that generative AI has been harder to implement than they expected. Further, 67% say they need outside help to get the most out of their generative AI solutions.
“AI and generative AI are making significant impacts to our industry — perhaps more than any previous technology,” said Sergio de la Fe, enterprise digital leader and partner with RSM. “Our survey underscores the necessity for middle-market organizations to develop a comprehensive AI strategy that encompasses the entire value chain. Considering the complexity of AI technologies, it’s no surprise that roughly two-thirds (67%) of middle-market leaders surveyed recognize the need for external assistance to fully capitalize on the advantages of their selected AI solutions.”
Concerns
All three surveys named largely similar concerns regarding AI that give pause to even enthusiastic adopters. The concerns include opacity of the models and their decision-making process, outputs that may not be entirely trustworthy, potential data leaks and cybersecurity attacks, as well as ethical and legal considerations.
Another recent report from CPA.com, though, found accounting leaders are largely unperturbed. It found that 68% of accounting leaders have confidence in their organization’s responsible use of AI. This is in contrast to their subordinates, who aren’t as confident in their leaders: Only 29% of front-line employees believe their employers have sufficient measures to ensure that AI is used responsibly.
“Organizations will not be able to enjoy the full benefits of AI if it is not considered a safe and trustworthy tool,” said the CPA.com report. “… Failure to use AI responsibly could result in financial penalties under new regulations as well as reputational damage.”
A proposal from the U.S. Securities and Exchange Commission to potentially shift some public companies away from quarterly financial reporting toward a semiannual model is drawing significant pushback from investors, even as it continues moving through the regulatory process. The debate has direct implications for corporate finance teams, auditors, and the broader transparency of U.S. capital markets.
What the SEC Proposed
According to a summary published by accounting advisory firm Cohen & Co., the SEC issued a proposed rule on May 19, 2026, aimed at simplifying financial reporting requirements for many U.S. public companies. The proposal would potentially reduce the frequency of certain mandatory disclosures from quarterly to semiannual, a structural change that has not been made to core U.S. reporting requirements in decades.
The proposal follows an extended debate within U.S. policy circles, with proponents arguing that reduced reporting frequency could lower compliance costs and free up management time for longer-term strategic planning rather than quarter-to-quarter results management.
Why Investors Are Pushing Back
Comment letters submitted in response to the proposal have been extensive, and according to Cohen & Co.’s review of the public record, investors “appear to be largely opposed” to the shift, viewing frequent interim reporting as a core benefit of U.S. capital markets relative to other jurisdictions.
Accounting and law firms have taken a more measured position, generally urging any changes to remain aligned with the Financial Accounting Standards Board (FASB), whose existing disclosure requirements and guidance are built around a quarterly reporting cadence. A shift to semiannual reporting without corresponding changes to FASB guidance could create friction between SEC filing requirements and GAAP-based disclosure expectations.
Lessons From the U.K. Experience
The debate is not without precedent. The United Kingdom moved away from mandatory quarterly reporting for listed companies in 2014, returning to a semiannual disclosure requirement. According to Cohen & Co.’s analysis, that experience offers a cautionary data point: there was no measurable increase in capital expenditure or R&D investment following the change, while analyst coverage of affected companies declined as reliable interim information became less available — a particular risk for smaller and newly public companies that rely on analyst coverage to maintain investor visibility.
Practical Implications for Finance Teams
Beyond the debate over disclosure philosophy, the proposal carries practical complications. Many companies have debt covenants and credit agreements structured around quarterly financial delivery; a shift to semiannual reporting could require renegotiating those terms. Reduced reporting frequency would also extend the “window of market silence” between disclosures, a factor that governance and investor-relations teams would need to manage carefully to avoid information asymmetry.
Separately, and unrelated to the reporting-frequency debate, the SEC and FASB have continued finalizing more routine updates this year. New Accounting Standards Updates are taking effect for December 31, 2026, fiscal year-ends covering income tax disclosures, credit loss measurement, induced debt conversions, and stock compensation, according to Eide Bailly’s review of 2026 ASU activity. Additional guidance on paid-in-kind dividends and environmental credits is also on the near-term horizon.
What to Watch Next
The semiannual reporting proposal remains in the comment and review phase, and no final rule has been adopted as of this writing. Finance leaders should monitor the SEC’s regulatory agenda for further movement, while treating the current quarterly reporting requirement as the operative standard until any final rule is issued and an effective date is set.
Given the extent of investor opposition documented in the comment file, a full shift to mandatory semiannual reporting appears more likely to result in either a scaled-back compromise or continued study rather than swift adoption — though the SEC’s ultimate direction remains uncertain.
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.
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.