Blog — The Vested Group

From Data to Decisions: How NetSuite's AI Analytics Are Changing Business Intelligence

Written by Aprille Tenorio | Jan 26, 2026

Most executives aren't short on data. Their enterprise resource planning (ERP) system captures transactions across various operations in remarkable detail. Despite that abundance, some teams struggle with using data to extract meaningful insights. 

This tension is a common feature of modern business intelligence. Traditional ERP reporting tells you what happened, but it often falls short of explaining why performance shifted and how those metrics influence decisions. 

What's changing dynamically is the evolution from static reporting to artificial intelligence (AI) driven analytics. These tools help you surface insights automatically, explain drivers and forecast likely outcomes. Oracle NetSuite sits at the center of this shift, with a growing suite of AI-powered analytics capabilities embedded across the platform and supported by various technologies. 

Discover how NetSuite's AI analytics are changing business intelligence and best practices for implementation. 

1. Provides Automated Insights and Generative Narratives

Executives may not complain about missing reports, but they may experience challenges with clarity. Dashboards may be full of charts, yet teams may lack a clear understanding of what changed, what drove the variance and why it matters.

NetSuite addresses this challenge through AI-powered automated insights and generative narratives. Features such as Auto Insights and Explain use machine learning to scan datasets and surface anomalies and outliers. They pair those findings with narrative explanations that clarify what changed and why. 

NetSuite's data insights help you understand cause and effect. For example, Auto Insights may reveal a margin decline and indicate that it is concentrated in one region because of logistics costs, while the Explain function can isolate the cost components driving the change. 

2. Uses Predictive and Prescriptive Analytics

When analytics only report on past events, they limit your ability to steer the business confidently. NetSuite's predictive and prescriptive analytics use historical performance, machine learning models and cross-functional data to forecast outcomes and flag risks early. 

The models train on your existing data and support: 

  • Risk mitigation through earlier detection of churn and operational anomalies.
  • Revenue optimization by aligning pricing and sales activity with forecast demand. 
  • Resource planning based on projected needs. 

3. Streamlines Self-Service With Natural Language Processing

Organizations may experience bottlenecks due to their reliance on technical teams to answer simple questions. Learning how to use NetSuite AI tools effectively often starts with removing this dependency. NetSuite integrates the Oracle analytics AI assistant, allowing users to ask questions and get immediate visual answers. 

Examples include: 

  • Show me the revenue from new customers by month for the last quarter.
  • What inventory items are most at risk of stockouts in the next 60 days? 

The system then responds with charts or narrative summaries in real time, allowing organizations to validate decisions faster.

4. Unifies Visibility via SuiteAnalytics and NetSuite Analytics Warehouse

Data silos remain one of the biggest barriers to meaningful analytics. Financial data often lives in different systems and platforms, resulting in teams relying on disconnected reports or manual reconciliation to understand performance. 

SuiteAnalytics addresses this challenge by providing real-time visibility into operational data within an ERP business intelligence platform. It allows teams to analyze transactions and key performance indicators using workbooks and dashboards that reflect system activity. 

As analytics needs expand, NetSuite Analytics Warehouse extends visibility across systems. It consolidates NetSuite and third-party data into a single environment using prebuilt pipelines that standardize and prepare data with minimal manual effort. 

These tools enable analysis across functions, allowing you to:  

  • Link marketing spend to customer acquisition costs.
  • Connect supply chain performance to margin outcomes.
  • Blend e-commerce data with operational metrics to identify growth opportunities.

5. Enhances Productivity and Risk Management 

AI capabilities also improve productivity and strengthen risk management. Features such as Text Enhance reduce manual data entry and improve record quality, while SuiteAnswers Expert delivers context-aware support that helps users resolve questions faster and stay productive. 

AI models also help detect compliance risks and transactional anomalies that may signal emerging operational issues. When paired with predictive churn analysis, you can gain insight into internal and external pressure points. 

Real-World Examples of Clients Who Implemented NetSuite AI Analytics

Various organizations are using these tools to solve complex operational challenges. The following examples illustrate the tangible impact of AI tools in NetSuite. 

Thread Consolidates Data in NetSuite Analytics Warehouse

Thread, an accessories brand that refines wallet design, faced a data organization challenge as it expanded from e-commerce to wholesale and physical retail. Their data was tied up across multiple sources, and their previous business intelligence software, Grow, could not effectively organize it. 

Thread replaced their legacy system with NetSuite Analytics Warehouse. This allowed them to use prebuilt data pipelines to combine data from NetSuite, Shopify and Google Sheets into a single view. By using the data warehouse's machine learning capabilities to analyze historical sales, Thread can now combine system forecasts with manager insights to order inventory with far greater precision.  

Marine Layer Strengthens Demand Planning With NetSuite Planning and Budgeting

Marine Layer, an apparel brand that grew from a single t-shirt concept to a national chain, found itself hindered by manual processes during its expansion. The planning team spent inordinate amounts of time manually building reports on inventory and sales from a cumbersome 10-tab spreadsheet. This inefficiency made it difficult to manage inventory replenishment during seasonal transitions. 

To support scale, Marine Layer implemented NetSuite Planning and Budgeting for demand planning. The shift moved replenishment from a guessing game to a strength. The team now uses data on sales trends to make smarter decisions around weekly supply targets. 

Best Practices for Implementing NetSuite AI Analytics

Organizations looking to see consistent returns can follow a few best practices that align with decision-making: 

  • Assess data hygiene: AI analytics depend on the quality and consistency of the data they analyze. When datasets contain conflicting definitions or weak governance, AI models still generate output, but the results lack reliability. Assessing data hygiene means validating core metrics and ensuring clean data flows into NetSuite. 
  • Have a clear goal: Successful AI initiatives begin with clearly defined business objectives. Whether the priority is improving forecast accuracy or optimizing workflow efficiency, a specific goal keeps analytics focused and measurable. 
  • Create an implementation strategy: AI analytics deliver results when they are embedded into everyday workflows. An implementation strategy typically includes phased rollouts and change management. Organizations can benefit from collaborating with experienced implementation partners who understand NetSuite's capabilities and the operational needs of businesses of all sizes. 

Turn Data Into a Strategic Asset With NetSuite AI-Driven Decision-Making Tools

When looking to turn your data into a strategic asset, you need a partner who understands the technology and grasps the challenges you face in your business. The Vested Group combines deep technical expertise with decades of hands-on experience guiding organizations through NetSuite implementation and ongoing support

We've worked with small and medium-sized businesses that need tailored solutions that fit lean teams, and helped larger, more complex enterprises handle customization and governance challenges. 

Our approach spans strategic advisory, NetSuite system health check and ongoing managed services. 

Contact us today to learn how we can help you strengthen decision-making using new NetSuite AI tools.