Analytics and AI

Artificial Intelligence (AI) and analytics are indispensable in propelling digital transformation efforts, particularly influencing Enterprise Resource Planning (ERP). With the rapid progression of technology and computing power, organizations across various sectors are generating immense amounts of data daily, impacting ERP processes. The significance of this data lies in its potential to extract actionable insights, facilitate strategic planning, and drive innovation within the ERP framework. In this context, AI and analytics emerge as pivotal tools, facilitating the extraction of value from the vast amounts of data generated and collected across the enterprise, optimizing ERP functionalities. Analytics is commonly categorized into descriptive, prescriptive, diagnostic, and predictive types, enhancing the ERP landscape. AI algorithms contribute not only to predictive and prescriptive analytics but also empower companies to develop innovative ERP capabilities, exemplified by advancements such as Industry 4.0.

Analytics and AI
Five ERP Strategic Implications for Operations Leaders in 2026
As organizations face a pivotal shift in ERP to autonomous action-driven frameworks, leaders must prioritize rapid modernization, governance transparency, and adaptability to remain competitive.
Analytics and AI
Case Study: The Metropolitan Atlanta Rapid Transit Authority (MARTA)
MARTA needed Oracle Fusion data to land in Databricks reliably, repeatedly and with the right level of control without turning every new flow into a custom development project. Orbit Analytics implemented Orbit Data Pipelines, a no-code ETL and ELT framework purpose-built for Oracle Fusion.
Red Hat signage on a office building.
Analytics and AI
Red Hat Acquires Chatterbox Labs to Strengthen AI Safety and Governance
Red Hat acquires Chatterbox Labs to add AI safety, guardrails, and risk metrics across its enterprise AI portfolio.
M&A
Analytics and AI
Enterprise Software Faces AI-Driven Disruption as Development Productivity Gains Fail to Materialize
In 2026, the enterprise software industry will undergo significant disruption due to AI, leading to increased merger and acquisition activity among mid-market companies, while organizations struggle to convert productivity gains from AI into strategic business value.
Analytics and AI
Three Trends Changing Manufacturing ERP in 2026
The manufacturing ERP landscape is transforming by 2026 due to the emergence of autonomous operations, composable architectures and sustainability ledgers, shifting focus toward action, which requires new governance and integration strategies.
ERP
Analytics and AI
How Next-Gen EAPs Are Reshaping Manufacturing IT 
Nextworld's enterprise applications platform (EAP) empowers manufacturers to modernize their operations through a flexible, no-code/low-code architecture, enabling them to implement tailored modules and custom workflows.
The coast of Da Nang with the city against the beach and ocean
Analytics and AI
Vietnam Draws More Than $7 Billion in AI Data Center Investments, Reshaping Enterprise Infrastructure
Create Capital Vietnam and Haimaker.ai have unveiled a $1 billion joint venture to build a nationwide AI-focused data center network in Vietnam, part of a broader surge of more than $7 billion in AI infrastructure investment driven by policy incentives and rising enterprise demand.
ERP AI
Analytics and AI
Overcoming AI Adoption Challenges in Manufacturing and Supply Chain
AI is rapidly becoming essential in manufacturing and supply chain management, but uneven deployment due to barriers like data quality and user adoption persists, while vendors are focusing on domain-specific AI to integrate predictive insights directly into core processes.
Analytics and AI
The Cloud Velocity Trap for Testing
CIOs face significant challenges during ERP migrations due to inadequate testing strategies and a rush towards AI solutions, highlighting the necessity for continuous testing and thorough documentation to ensure successful system integration.
Analytics and AI
Oracle AI World’s IBM Sessions: What Enterprises Must Build Before AI Can Deliver
At Oracle AI World, IBM emphasized that successful AI adoption in enterprises relies not on flashy models but on robust foundational preparations, governance, and aligned business processes, showcasing that scalable AI implementations require clean data and integrated workflows.
Analytics and AI
Data Integrity is the New ERP Mandate
Data integrity is crucial for ERP success, as reliable information underpins automation and insights; organizations must modernize data handling without full system overhauls, confront legacy issues, and embrace governance to enhance efficiency and decision-making.
Analytics and AI
Creating Supply Chain Value Through Analytics and AI
AI and analytics are transforming supply chain management by automating repetitive tasks, redefining planner roles into strategic storytellers, and providing decision intelligence to navigate disruptions.
Analytics and AI
Year in Review: Testing, Transformation, and the Race to AI-Ready ERP in 2025
In 2025, the conversation around cloud migration shifted from why to how. According to SAPinsider’s 2025 research report on SAP S/4HANA deployment, for instance, 31% of the organizations who responded to the survey have transitioned to SAP S/4HANA, while another 27% are in implementation. Additionally, 54% of respondents said they plan to incorporate AI or...
Analytics and AI
Microsoft Research Maps 2026 AI Agenda: From Lab Assistants to Trusted Agents
Microsoft Research forecasts 2026 as a pivotal year where AI evolves into collaborative 'digital coworkers' across sectors, emphasizing security, agentic systems, and quantum advancements that align with human-centered goals and redefine enterprise resource planning.
Analytics and AI
Alphabet’s Intersect Buy Tightens Link Between AI Data Centers and Clean Energy Infrastructure
Alphabet is acquiring Intersect for $4.75 billion to enhance its data center and energy infrastructure capabilities as part of its AI strategy, while Intersect will operate independently and collaborate closely with Google on new facilities.
Analytics and AI
SAP, Partners Turn Embedded Business AI into Concrete ERP Wins
SAP and its partners are transforming AI from concept to implementation by integrating SAP Business AI and SAP BTP into workflows that enhance efficiency and collaboration, as illustrated by successful case studies from companies like FRoSTA and Aspen Pumps.
kyano
Analytics and AI
Why Industry-Built ERP Will Lead the Next Wave of Manufacturing Modernization
Manufacturing executives are increasingly favoring vertical ERP systems over generic platforms due to the former's ability to provide tailored, out-of-the-box solutions that align with industry-specific workflows.
Google Gemini Logo
Analytics and AI
Google Launches Gemini for Government, Supporting DOE Labs on Genesis Mission
Google launches Gemini for Government at 47 cents per year for federal agencies, partnering with DOE National Labs to enhance scientific productivity through agentic AI workflows, secure collaboration, and advanced research tools.
Analytics and AI
2025 Was a Pivotal Point for Oracle NetSuite: Where Is Its AI Roadmap Heading in 2026?
Oracle NetSuite laid the groundwork in 2025 for an AI-native ERP experience, with 2026 expected to see the launch of key features like NetSuite Next and Autonomous Close, which will embed AI into financial and operational workflows, moving AI from conceptual to operational use.
SYSRPO and DATASCOPE
Analytics and AI
Utilities Turn to Physical AI to Accelerate Grid Modernization
Utilities are increasingly utilizing robotics and physical AI to enhance inspections, mitigate risks, and optimize workforce efficiency amidst challenges like electrification growth, aging infrastructure and labor shortages.
MCP Platform
Analytics and AI
How to Choose an MCP Platform for Production-Scale AI Agents
Model Context Protocols (MCPs) standardize secure, real-time access for AI agents to enterprise systems. MCP features such as plug-and-play integration, real-time monitoring, and scalability become a differentiator as businesses embed AI into core workflows.
Coda
Analytics and AI
December’s M&A Sprint Signals AI Infrastructure Consolidation Era for Enterprises
In December 2025, a surge of over $100 billion in strategic technology acquisitions is compelling ERP executives to pivot away from fragmented solutions towards more robust, AI-native architectures amidst rising valuations and an emphasis on security.
ClickUp AI Agents
Analytics and AI
ClickUp Addresses Work Sprawl with Codegen Acquisition
ClickUp has acquired AI startup Codegen to enhance its platform with autonomous software engineering capabilities, integrating execution engines with enterprise context for a unified workspace that enables AI agents to perform tasks across multiple systems.
Analytics and AI
BlackLine Acquires WiseLayer in Bid to Enhance AI Capabilities
BlackLine's acquisition of WiseLayer marks a pivotal moment in finance as AI agents take on complex judgment-heavy tasks, transforming operating models and integration practices while significantly enhancing efficiency and accuracy in financial operations.
Analytics and AI
Palo Alto, Google Cloud Expand AI Security Alliance as 99% of Organizations Report AI Attacks
Palo Alto Networks and Google Cloud have expanded their partnership with a nearly $10 billion deal to enhance AI and cloud security, integrating Palo Alto’s Prisma AIRS platform with Google Cloud’s infrastructure to provide comprehensive security across hybrid multicloud environments.
Analytics and AI
BillingPlatform Adds Platform Capabilities for Advanced Revenue Insights
BillingPlatform's upgraded capabilities transform billing into a real-time decision system for revenue leaders, enhancing visibility, reducing manual reporting, leveraging AI for transparency and robust integration.
data maturity ai
Analytics and AI
Data Maturity Is the Strongest Predictor of AI Success in 2026, Says New CData Study
Despite investment in AI copilots, many enterprises' lack of robust data infrastructure hampers their ability to derive sustainable ROI from AI initiatives, with only 6% of organizations considered genuinely AI-ready due to fragmented data systems.
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