Intelligent automation: The new wave of artificial intelligence
What’s here — and what’s coming — for AI capabilities and automation? Redwood Software is looking beyond large language models and generative AI, into the next era of intelligent systems.
Future-proofing with Redwood’s built-in AI tools
Redwood is expanding the automation lifecycle with AI-powered enhancements designed to maximize productivity and reduce risk. Learn what’s possible today, and what AI-powered features are in the works, in RunMyJobs by Redwood.
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Predictive analytics
Apply machine learning to analyze end-to-end business processes based on datasets, metrics and configured rules for service-level agreements (SLAs).
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Advanced data analysis
Redwood Insights generates smart narratives in role-based dashboards, helping you understand and solve complex problems and accelerate decision-making.
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Full-scale integrations
Save your organization time, reduce human oversight and produce high-quality outcomes using built-in AI capabilities and your external tools.
The role of AI in driving business outcomes
Your organization has most likely been developing an AI strategy to streamline complex tasks and improve adaptability.
In this session, Redwood’s Chief Product Officer, Charles Crouchman, addresses real-world applications of AI in automation platforms, how agentic AI works and how to enable your teams to adopt new AI technology.
Bridging SAP innovation with intelligent orchestration
SAP’s evolving AI capabilities are reshaping how enterprises manage supply chains, analytics and other core business processes. RunMyJobs is a bridge to intelligent decision-making, connecting AI insights and automated workflows.
How AI redefines the ERP and automation landscape
Listen in to a fireside chat between SAP’s Chief AI Officer and Redwood’s Chief Product Officer about the impact of AI on complex workflows and the enterprise automation ecosystem.
They explore emerging AI trends, continuous learning frameworks and essential strategies for preparing to integrate AI use cases into your automation technologies.
More on AI and automation
Stay ahead of the curve with thought leadership on AI, automation and orchestration with Redwood solutions.
Insights from 2025 Gartner® Critical Capabilities for SOAP
See why Redwood was ranked first in all five Gartner Critical Capabilities Use Cases for Service Orchestration and Automation Platforms (SOAPs).
This analyst report complements the Magic Quadrant™ for SOAP analysis with deeper insight into providers’ product and service offerings.
Enterprise automation trends
See the latest exclusive automation industry research, revealing what IT, Operations, Finance and other teams are automating, how prepared they feel for AI and where automation adoption is falling short.
- Get key insights into investment trends and platform utilization
- See a breakdown of the top business goals automation supports today
- Find out what’s blocking automation success, from complexity to a lack of orchestration
- Benchmark your automation maturity and AI readiness
- Glimpse industry performance for manufacturing, retail, financial services and more
- Discover how the C-suite, middle management and individual contributors view automation
Integrate ChatGPT with RunMyJobs
Save time, reduce manual effort and boost scalability with the combined power of AI and process orchestration.
- Trigger and interact with ChatGPT in RunMyJobs to turn unstructured data into structured data and create data flows across pre-defined processes
- Perform a ChatGPT request that returns a string containing the ChatGPT response and a table containing a log of the conversation
- Access a real-time audit trail of triggers, results and processes
Intelligent automation and agentic AI FAQs
What is traditional AI?
Traditional artificial intelligence refers to rule-based systems and machine learning models designed to automate repetitive tasks, process structured datasets and support decision-making through defined algorithms. These AI applications often require human oversight and don’t act autonomously.
What is generative AI?
Generative AI (genAI) uses large language models (LLMs) and neural networks to create new content, such as text, code or images, based on learned data patterns. In business use cases, genAI enhances customer support, content generation and software development by automating high-volume outputs that once required human input.
What is natural language processing (NLP)?
Natural language processing (NLP) is a branch of artificial intelligence that enables computers to understand, interpret and generate human language. It powers chatbots, voice assistants and AI models that read and summarize text or respond conversationally.
In automation, NLP helps transform unstructured data into structured outputs, making it easier for AI tools and orchestration platforms to trigger actions, analyze vast amounts of data and support real-time decision-making. NLP also serves as a foundation for generative AI and agentic AI, allowing autonomous systems to communicate and collaborate with humans more naturally.
What is the difference between generative AI and agentic AI?
Generative AI (genAI) uses large language models (LLMs) and other machine learning techniques to produce outputs when prompted. Agentic AI uses AI models plus planning, decision-making and tools to achieve outcomes with minimal human intervention. In practice, genAI is typically reactive (prompt in, content out), while agentic AI systems are proactive: breaking a complex goal into subtasks, calling external tools/APIs, incorporating real-time data and adjusting via feedback loops (often with guardrails and human oversight). GenAI streamlines specific tasks, and agentic AI aims to orchestrate complex workflows across end-to-end business processes.
What is agentic AI automation?
AI agentic automation describes the use of autonomous AI agents to coordinate and optimize complex workflows across ecosystems. It blends the scalability of automation with the adaptability of intelligent agents, enabling systems to make decisions, monitor outcomes and improve processes continuously.
What is intelligent automation?
Intelligent automation combines AI, machine learning and robotic process automation to streamline complex workflows and reduce manual effort. It uses AI-powered tools to analyze real-time data, identify patterns and trigger automated actions that improve efficiency and adaptability.
Gartner, Inc. Critical Capabilities for Service Orchestration and Automation Platforms. Chris Saunderson, Cameron Haight, Daniel Betts, Hassan Ennaciri, etl. 26 Aug 2025.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
These graphics were published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from https://www.redwood.com/resource/gartner-critical-capabilities-soaps/.
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