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NetSuite touts AI enhancements | Accounting Today

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Business solutions provider Oracle NetSuite hailed the release of NetSuite Next, a cloud-based AI-driven ERP solution with embedded conversational intelligence, agentic workflows, and natural language search capabilities, which the company touted as “the future of NetSuite.” 

The suite is centered around a natural language assistant called Ask Oracle that can be used to  search, navigate, analyze, and act across the entire NetSuite dataset, with the ability to act across customizations and extensions built on the SuiteCloud Platform, including partner applications available in the SuiteCloud Developer Network. This allows it to not only execute agentic workflows but deliver context-aware answers, visualizations, interactive content, and reasoning that explains the “how” and “why” behind every response. This unified data model also enables NetSuite Next to help identify opportunities and risks before they become issues as well as understand individual users’ roles and context.

In terms of automation, the AI can help automate tasks such as payment proposals, vendor selection, reconciliations, and supply chain operations. These new agentic workflows give users the choice to approve key decisions or allow agents to act autonomously. The solution also provides automated explanations, available in record forms, reports, and other pages across the suite; the narrative summaries and insights proactively surface correlations and trends from NetSuite’s unified data model. The software can also access large language models that extract and validate information from a wide range of sources—including invoices, contracts, receipts, PDFs, policy manuals, training guides, customer testimonials, and purchase orders—which the AI can then read, interpret, and act on. These things can be done via a new collaborative workspace embedded in NetSuite, AI Canvas, from which users can analyze problems, brainstorm solutions, and trigger agentic workflows. 

NetSuite

“NetSuite Next puts AI to work for businesses by making it a natural extension of the way they already work,” said Evan Goldberg, founder and executive vice president of Oracle NetSuite. “With the latest AI innovations built in, NetSuite Next can deliver powerful insights as well as autonomously complete repetitive and complex tasks, all with enterprise-level reliability. Every insight and action is rooted in data and governed by the existing roles, permissions, and policies our customers depend on. It enables users to discover patterns in their business and engage with NetSuite in their own words, all while understanding an individual user’s context, so it can deliver answers and actions that provide immediate value.”

Customers can switch to NetSuite Next without having to migrate or disrupt existing customizations.

SuiteCloud updates

The company also announced several new AI-related updates for its SuiteCloud Platform, many of them related to crafting custom AI solutions and interacting with autonomous AI agents. 

The new AI Connector Service lets organizations select the AI models that best fit their business needs, define the data they can access, and govern how the models interact with NetSuite. This includes both NetSuite’s own models as well as those of third parties, as the software is built on open standards that include a Model Context Protocol, allowing the suite to connect with external AI assistants and agent platforms. To help align outputs with a customer’s policies, standards, and language, NetSuite plans to introduce Custom MCP prompts that will enable administrators to design prompts that guide external assistants on how to respond.

The SuiteCloud platform will also feature a new AI toolkit that includes a collection of APIs that expose NetSuite’s own AI services, including services for document analysis, reasoning, and narrative reporting, for direct use in SuiteApps, workflows, and customizations. Customers have access to Document AI APIs, with Narrative Insights AI and Knowledge AI APIs planned for future availability. Users will also have access to the AI Studio, which helps administrators and business users define, tune, and manage how AI operates inside NetSuite. The AI Studios enable customers to adapt the AI capabilities in NetSuite to their unique industry requirements and business processes by giving customers direct control over AI reasoning, outputs, and interactions. The solution also includes a new Prompt Studio, which lets teams design, test, and preview prompts to see how AI will respond before deployment, and Narrative Insight Studio, which will enable users to control how summaries, explanations, and insights are generated.

Users can create their own agents through the new SuiteAgent framework that lets customers, partners, and developers build, integrate, and deploy SuiteAgents directly on the SuiteCloud Platform. SuiteAgents developed using the new SuiteAgent frameworks in the SuiteCloud Development Framework (SDF) can leverage NetSuite AI toolkits and services to help businesses achieve outcomes faster, more intuitively, and with greater confidence. SuiteAgents will be supported by NetSuite Next’s new agentic workflow experiences, which will enable users to monitor agent progress, review results, and intervene when needed.

There is also a new set of AI assistants. They include SuiteCloud Developer Assistant, an AI-powered coding companion that will accelerate coding, documentation, customization, and testing by reducing time spent on repetitive tasks and SuiteFlow Assistant, an AI-powered assistant that will help admins and power users design and refine workflows using natural language in NetSuite Next.

“It has always been important to me that NetSuite is flexible and adaptable so that our customers can support their unique and ever-changing business needs,” said Goldberg. “Today, we are taking that flexibility and adaptability to a new level. The new capabilities in SuiteCloud will help our customers and partners transform how AI works for business by giving them the ability to quickly and easily build AI agents, connect external AI assistants, and orchestrate AI processes.”

More AI capacities are coming as part of NetSuite Next within 12 months. 

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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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