Blog & Newsroom
Featured Blogs
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Product knowledgeThe observable enterprise: Navigating complexity in workload automation
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Articles about Long Form
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Long FormState of AI and data pipeline automation in financial services 2026
Only 18.6% of financial institutions have achieved enterprise-wide orchestration, despite widespread automation investment. Find data-driven insights on automation maturity, fragmented data pipelines and what it takes to build AI-ready operations.
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Long FormMaster the touchless close
Discover how to remove manual work from your close and achieve an end-to-end, touchless record-to-report process.
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Long FormThe automation void
Most compliance tools track the close, but they don’t execute it. Use this playbook to identify where manual journal entries still exist in your financial close.
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Long FormAssess your R2R maturity
Test how automated your financial close really is with this full R2R maturity guide that helps you score your current state, uncover manual effort and plan next steps.
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Long FormPayments modernization 101: What it is and why it matters now
Payments modernization has become a strategic priority for financial institutions facing rising transaction volumes, real-time payment demands and increasing regulatory complexity. Modernizing payment systems is no longer about replacing a single rail — it’s about strengthening orchestration, automation and visibility across the entire payments ecosystem. Institutions that take a structured approach improve reliability, reduce operational drag and position their payment infrastructure to scale with confidence.
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Long FormAgentic process automation: What the emerging model means for enterprise workflows
Agentic process automation supports complex workflows by introducing intelligent agents capable of interpreting goals and adapting to real-time data. Discover how this technology complements your existing tools to handle the ambiguity and variation that predefined rules can’t anticipate.
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Long FormAgentic automation: The intelligence layer transforming enterprise orchestration
Agentic automation adds an intelligence layer to enterprise orchestration, enabling AI agents to interpret context, make real-time decisions and keep outcomes on track across hybrid environments. Agents complement Service Orchestration and Automation Platforms (SOAPs) to handle disruptions, optimize workflows and lay the groundwork for closed-loop, policy‑aware automation fabrics.
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Long FormManufacturing AI and automation outlook 2026
Seven in 10 manufacturers have automated 50% or less of core operations, and only 20% feel prepared for AI. Get data-driven insights into automation maturity, the perception gap between leadership and front-line teams and what orchestration unlocks.
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Long FormThe autonomous enterprise
Global AI spending is projected to surpass $2.8 trillion, yet only 41% of projects reach production. Overcome this ROI paradox by shifting from automation to governed orchestration: get a roadmap for the autonomous enterprise and strategies to ensure humans remain in control.
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Long FormAgentic AI vs. generative AI: Defining their roles in workload orchestration
Enterprises use many types of artificial intelligence to support automation, but generative AI and agentic AI dominate current conversations. While generative AI systems excel at creating new content from existing data, agentic AI systems are built to pursue specific goals on their own. This distinction is key to understanding the future of workload automation, moving from content generation to autonomous, real-time decision-making.
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Long FormThe evolution of agentic AI in enterprise automation
Artificial intelligence is no longer confined to predicting outcomes or generating content. A new path is emerging, one defined by agentic AI systems that reason, plan and act with intent. This shift creates automation that doesn’t just follow a script but understands goals and adjusts to meet them.
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Long FormIntentional AI systems: The difference between AI agents and agentic AI
We’re moving from systems that execute commands to systems that understand purpose and can adjust plans when reality pushes back. For enterprises, this evolution bridges a critical gap between automation and intelligence. It signals the arrival of agentic AI — a design approach that allows systems to reason, plan and act with intent.
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Long FormAgentic AI: The future of autonomous workload automation
Traditional automation is like a highway sign that merely reports congestion. Agentic AI is the traffic controller that proactively predicts jams and reroutes cars in real time without waiting for instructions. Learn what this powerful shift could look like in your environment.
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Long FormAgentic AI: The next frontier in autonomous systems
Most artificial intelligence systems today are reactive, responding only when you ask them to perform a task. But imagine an assistant who proactively drafts a report, schedules the meeting and shares the results without waiting for instructions. That’s the promise of agentic AI: moving from reactive to proactive and from static outputs to meaningful outcomes.
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Long FormModernization in motion: How agentic AI is redefining workload automation
Agentic AI represents a new class of artificial intelligence — beyond generative AI and large language models (LLMs) — that plans and reasons about goals and adapts autonomously when conditions change. Rather than executing one specific task at a time, it orchestrates outcomes, adjusting strategy to maintain flow even when disruptions occur.
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Long FormAgentic AI and the future of supply chain operations
Global supply chains sit at the intersection of volatility and expectation, where traditional automation excels at repetition but fails to improvise when reality shifts. Agentic AI changes that, moving beyond static rules toward systems that can perceive, reason, plan and act in real time. Instead of just generating insights for a person to review, agentic AI links insight directly to execution.
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Long FormEnterprise automation index 2026
Automation spend is up, yet just 10% of organizations prioritize adoption, and under 30% fully utilize their tools. Get exclusive insights into what’s standing in the way of autonomous processes, how top performers feel about AI-driven automation and more.
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Long FormEscape the data maze
Read this complete guide to orchestrating SAP and non-SAP data for your use cases. See end-to-end process examples for manufacturing, retail, utilities, life sciences and financial services.
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Long FormThe journey to automation fabrics
Download this practical guide to determine your organization’s automation maturity stage and steps to level up for greater efficiency, productivity and innovation.
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Long FormMapping your journey to SAP S/4HANA Cloud
This guide offers insights into migration strategies, key benefits, and how to ensure a smooth transition with workload automation.
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Long FormWorkload automation software comparison guide
Explore our workload automation guide to learn how choosing the right orchestration solution can drive business growth, with insights from 93% of IT leaders who have seen success through process automation.
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Long FormSAP ERP integration: Streamline business processes across platforms
Learn more about how SAP ERP Integration can streamline business processes across platforms. Understand the benefits and challenges of integrating SAP ERP with other business applications. Discover Redwood’s solution for efficient SAP ERP integration.
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Long FormFuture-proof your SAP ecosystem
As SAP’s #1 job scheduler, RunMyJobs by Redwood pairs seamlessly with your SAP and non-SAP solutions to drive efficiency across your tech stack and enable your cloud migration.