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Sage Copilot AI aims to pair power and simplicity for small and medium businesses

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Small and mid-size business platform Sage is already well experienced with AI, having woven it throughout their products for years, but its new generative AI Sage Copilot solution has been touted as a dramatic step forward in the company’s long term vision of simplifying accounting to make it more accessible to all. 

Aaron Harris, Sage’s chief technology officer, said that the company has long had classic AI deep learning models that perform functions users have relied on for years. These tasks often require the use of many different models working in concert, with Harris noting that invoice processing alone requires the use of 27 different models: 15 to 20 are required to read the data alone, and more are needed to perform the calculations. 

Sage Copilot coordinates between these models and acts as an interpreter between them and the human users who are requesting they perform a task. Effectively a “mouth” attached to a larger whole, the LLM works by translating the user request, usually inputted through a conversational interface, into machine language. This then goes to the various AI models on Sage’s servers, which then get to work on whatever the user asked them for, eventually sending instructions back to the LLM. The LLM reads back the machine language and implements the command or, in the case of an informational query, translates it back to human language. Harris stressed that it is not the LLM itself that does this work, referencing their well-known difficulties with math, but the other AI models that the LLM interacts with. 

“We don’t trust them to do math. There’s much better ways to do math… We’re not using the AI to do the math on the results, we’re using AI to write the [structured query language] exactly as you described,” said Harris during an interview. 

He added that, rather than being a feature of any one particular solution, Sage Copilot can be used across its products through the use of specialized “agents.” The company creates AI “agents” purpose built to do one thing really well, such as interacting with certain types of data, executing specific queries, or engaging with specific software products. Sage Copilot has access to multiple agents, each built to communicate with a different product, whether Sage Intaact, Sage HR or something else.

“The intention is that Copilot can work across the portfolio of Sage products,” he said. 

Having Copilot act as a coordinator for all the other models also means its automation capacities go far past what it had previously accomplished. Harris raised the example of processing an invoice. This act alone requires multiple steps, but many of them have already been automated in Sage, taking out much of the work. Copilot goes a step further by allowing wholesale workflow automation through coordinating among several models that each enable a different automated process. “We can now really accelerate our ability to automate with large language models, and we can use AI to do more of the orchestration. So, giving it the ability to not just process the invoice but to move it on to the approval stage, to understand after it’s approved [it needs to] move it through the payment process,” he said. 

He added that, in the future, “that invoice will have been created for you, automatically.” His team had recently conducted a hackathon where it was found Copilot can automatically generate invoices based on events happening around the user, like if it knew they were going on a job using geofencing, and act proactively. 

Harris said that certain companies today will attach their solution to a ChatGPT account and call that generative AI functionality. In contrast, developing Copilot was a meticulous process that required a lot of trial and error even before its UK release earlier this year. During this time, the development team encountered many challenges that needed to be overcome, such as teaching the model that there can be more than one kind of cash balance. 

“I got in and I asked Copilot ‘what is my cash balance?’ And Copilot said it’s at zero. And I dug around and what I learned was that Copilot inferred from my question ‘what’s my petty cash?’ It didn’t actually understand that what I was asking for was the balance of cash across my bank account,” he said. “Fast forward a month. We’ve done a lot of work to train the model the way we wanted to when you ask that question. … [Now] it’ll give you a table with your bank accounts and your balances in total. If that is what you’re asking, this is the answer.” 

Getting these kinds of interactions right was vital to ensuring Copilot was easy to use and reliable in its outputs without having to possess a lot of arcane technical knowledge. Interacting with Copilot in plain language allows people to access accounting information and perform business tasks on their own, a major component of the wider goal of making accounting more accessible to a wider base of people. 

“Generative AI and copilots, and their natural conversational interface, enables us to bring accounting outside the finance team to the rest of the business. One of the biggest blocks is getting [accountants] to approve things or to answer questions, finance teams are spending time supporting me instead of getting the books closed. With Copilot having a conversational interface, it now becomes much more natural and easy for me to approve a purchase order or to ask a question like ‘how am I trending on my travel expenses?'” Harris said. 

While Sage wants to make accounting more accessible to the layperson, he added that professionals can be excited too. The big promise, he said, is that it will free them from things they don’t want to do. He compared it to having an army of interns at one’s disposal who can take care of the numerous mundane demands that pop up throughout the day. The result, according to Harris, will be “faster and smarter decisions.” 

“Unpacking that, what we’re really saying is [this can be] how you, across the whole of the business, understand the patterns of activity in that business in real time to discover when there is a change in performance—when there’s something that can indicate an opportunity or risk—that the more strategic specialists can address in real time… We’re enabling more decisions to be made confidently,” he said. 

Harris said the name “Copilot” represents what he felt was a good bet that the term copilot would become generic, versus being permanently associated with Microsoft’s product. He said that the term has, over time, emerged as standard in a similar manner as “band-aid,” “Xerox” and “Google.” 

The large language model was released in the UK in February and is set for release in the US at the end of this year. 

Part of a larger strategy

Copilot is one component of the company’s larger product strategy to promote continuous accounting, real time assurance and continuous insights. But this, itself, is part of Sage’s overall strategy, particularly for the North American market; Mark Hickman, the managing director of North America, said Copilot is “critical to our success.” 

“As we move forward, [we want] to really be that leader, we want to be ahead of the competition when it comes to AI and how we bring that to market, into that ecosystem of 2 million customers globally and hundreds and hundreds of thousands in North America,” said Hickman. 

To this end, Sage has been busy making new alliances and deepening current ones with companies like Microsoft, Amazon and PwC. They have collaborated on technology solutions with the aim of eventually driving integration into products like Office and other platforms, as well as on distribution and implementation of said solutions. With Microsoft and Amazon in particular, Hickman said they have whole partnerships where they go to market together and close new customers. Given these companies’ focus on large enterprises, Sage’s focus on small and medium businesses has acted as a bridge to this larger community. 

“What we’ve discovered here is that [Microsoft and Amazon], they don’t really play in the small to medium businesses with the cloud. So 90% of their new customers are net new customers so they’re actually getting into new customers because they’re working with us and closing new deals to get into these accounts and … using their amazing, world class platforms and their brands to work together,” he said. 

This is especially germane as the UK-based Sage expands further into the North American market, which makes up more than 44% of the company’s global revenues already. The company is making heavy investments in this region, which include technology but also additional staff as well as new facilities. Hickman said they will be building a whole new campus in Atlanta to serve as their new base for North American operations (in addition to the office they already maintain in that city), as well as new offices in Portland and Vancouver. 

Hickman said Sage’s thinking on these new locations came as the company emerged from the pandemic lockdowns, eventually settling on what he called a “hub strategy.” Previously, the company had over 80 offices around the world, but he said many of them were small and remote. The company chose a very deliberate strategy where they would instead have large offices in each of the major markets they really invest in, with fewer small satellite offices. This has allowed them to really focus their efforts around these flagship country “hubs.” He noted that the new offices in Canada is also a reflection of this hub strategy of “really increasing the investment in the offices where we want to concentrate our growth.” 

“So the North American businesses, the US businesses, are the fastest growing [sector] with great growth, and we hope to really accelerate that growth as we move forward,” he added. 

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Accounting

Mandatory ESG Reporting Standards Demand Standardized Non-Financial Audit Trails

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Mandatory ESG Reporting Standards Demand Standardized Non-Financial Audit Trails

Corporate accounting departments face an expanded regulatory mandate as mandatory sustainability and Environmental, Social, and Governance (ESG) reporting frameworks take full effect internationally. Governed by the European Union’s Corporate Sustainability Reporting Directive (CSRD) and the International Sustainability Standards Board (ISSB) IFRS S1 and S2 standards, enterprise financial controllers are now legally required to track, verify, and report non-financial data with the same internal controls and auditability as traditional financial statements.

The expansion shifts ESG compliance

This regulatory expansion shifts ESG compliance from marketing departments to corporate accounting offices. Financial managers are now responsible for gathering, consolidating, and verifying carbon emissions metrics, supply chain labor conditions, water usage, and climate risk exposures across multi-tiered corporate structures. These non-financial metrics must be integrated into standardized general ledgers to withstand rigorous third-party audit assurance processes.

To comply with these rigorous reporting mandates, accounting software providers have added dedicated ESG modules designed to aggregate data from IoT sensors, utility platforms, and vendor management systems. Controllers are implementing internal control frameworks—modeled after traditional COSO frameworks—to ensure the completeness, accuracy, and consistency of sustainability disclosures, protecting organizations against greenwashing penalties and litigation risks.

The transition requires significant cross-functional collaboration between accounting teams, legal counsel, and operational directors. Accounting professionals are expanding their technical expertise beyond financial ledgers to master carbon accounting methodologies, lifecycle assessment standards, and non-financial data governance protocols, fundamentally expanding the role of the modern corporate accountant.

Why This Information Matters
Mandatory ESG disclosures require companies to treat environmental and social metrics as audited financial records. Executives, accountants, and board members must institute formal tracking and assurance processes to satisfy legal mandates, maintain investor confidence, and mitigate regulatory non-compliance risks.

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Accounting

SEC’s Semiannual Reporting Proposal Faces Investor Pushback: What CFOs Need to Know

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U.S. Securities and Exchange Commission (SEC)

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.

 

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Accounting

AI-Driven Automation and Continuous Accounting Frameworks

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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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