Resources

Agentic 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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How agentic AI automation complements existing enterprise automation strategies

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Demystifying Job Scheduling for RISE with SAP: Insights from Arthrex

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Manufacturing 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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From Technical Debt to Optimized Execution: EWEB’s Automation Adoption with SAP BTP and Redwood

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Supercharge your Redwood experience

Redwood RangerAI brings practical, embedded AI to RunMyJobs, enhancing automation with intelligent assistants that accelerate troubleshooting, streamline workflow design and deliver faster, more reliable operations.

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The 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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Agentic 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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The 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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Intentional 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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Agentic 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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Agentic 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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Modernization 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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Agentic 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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Meter-to-cash automation for utilities

See how RunMyJobs by Redwood — a Premium certified SAP Endorsed App — streamlines the complete meter-to-cash process for utilities. From meter reading to billing, collections and compliance, RunMyJobs orchestrates SAP mass activity transactions with ease.

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Siemens and Redwood

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Assess your R2R maturity

Assess your organization’s record-to-report automation and unlock a tailored roadmap that helps you erase manual tasks from your close.

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Powerful automation for complex manufacturing processes

Automate your full plan-to-produce process with end-to-end visibility and control using RunMyJobs.

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RunMyJobs monitoring and observability with Redwood Insights

See how Redwood Insights helps you prevent failures, resolve incidents faster and optimize your automation strategy.

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Enterprise 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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Hybrid and cloud automation Webinar

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Activebatch 2025.2 + new extensions Webinar

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How American Water unified automation and file transfers with Redwood Software

Discover how American Water transformed its operations by consolidating automation and file transfers with RunMyJobs by Redwood.

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Next-level performance: Why the latest version of JSCAPE matters

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