Automation is no longer just a back-office efficiency tool—it’s becoming the strategic layer that connects ERP systems, drives AI adoption and reshapes how businesses operate. In this exclusive ERP News interview, Charles Caldwell, Senior Vice President of Product Management at Redwood Software, explains why automation fabrics are overtaking traditional ERP automation modules, how organizations can prepare for AI-driven workflows, and what it takes to move from fragmented processes to intelligent, end-to-end orchestration.
Your recent data shows that 68.8% of respondents consider automation critical to business success. How have you seen this translate into ERP strategies across industries like manufacturing and retail?
Manufacturing:
In manufacturing, automation is becoming the backbone of ERP – enabling companies to orchestrate complex processes, enhance visibility and scale efficiently in response to shifting market demands. Here’s how this transformation is unfolding:
1- End-to-End Process Orchestration
Manufacturers are increasingly moving away from static, time-based job scheduling within ERP systems. Instead, they’re implementing event-driven, end-to-end orchestration that ties together core processes such as order-to-cash, supply chain execution, production planning and financial close.
2- Using Automation Fabrics as a Strategic Layer
Automation fabrics are being integrated with SAP and other ERP platforms to offer centralized automation management, cross-system job scheduling (SAP and non-SAP) and cloud-native scalability. This allows manufacturers to automate thousands of interdependent ERP tasks without relying on manual intervention or fragmented tools.
3- Improved Performance & Visibility
Automation gives ERP teams real-time insight into batch job execution, failure points and resource usage, which is critical in manufacturing environments where downtime can be costly. This helps teams shorten overnight processing windows, proactively resolve issues and improve SLAs for production support.
4- Scaling with Demand
As production scales or shifts seasonally, manufacturers now rely on automation to dynamically adjust ERP workloads. Automation enables faster response to customer demand, real-time material requirements planning (MRP) updates and smoother transitions between production cycles.
Retail:
Retailers are increasingly embedding automation into their ERP strategies to create more agile, responsive and customer-centric operations. Here’s how automation is transforming ERP in the retail industry:
1- A Focus on Supply Chain Integration
Retailers are embedding automation into their ERP systems to improve visibility across ordering, inventory and fulfillment processes. Automation fabric solutions help orchestrate workflows between legacy systems, suppliers and external partners, reducing manual handoffs and streamlining data transfers.
2- Task Orchestration for Inventory & Order Management
Processes such as demand forecasting, replenishment, order-to-cash and payment reconciliation are being automated within SAP/ERP systems. This takes human error out of the loop, speeds up task completion and frees staff for higher-value work.
Despite strong recognition of automation’s value, over 60% reported underutilizing AI tools. What do you think are the biggest barriers preventing organizations from fully embracing AI within their ERP ecosystems?
According to Redwood Software’s Enterprise Automation Index, the biggest barriers preventing organizations from fully embracing AI are:
- Legacy systems and cautious adoption hinder utilization (healthcare)
- Difficulty orchestrating across business functions (finance)
- Slow adoption due to lighter technical resourcing (retail)
- Infrastructure complexity (manufacturing)
- Orchestration gaps (software)
Redwood Software specializes in automation fabric solutions. How does this approach differ from traditional ERP automation modules?
While both aim to automate business processes within ERP ecosystems, the automation fabric provides a more flexible, comprehensive and scalable solution compared to the more siloed, ERP-specific automation tools typically offered by traditional systems. The key differences are cross-platform integration, holistic vs. siloed approach to automation, flexibility and scalability, centralized control and visibility and agility and speed.
Less than 40% of survey respondents feel prepared for AI-driven automation. What foundational steps should companies take today to get “AI-ready”?
1- Take a Big-Picture Planning Approach
AI is designed to operate within complex enterprise workflows. Organizations should evaluate how AI can connect different departments and systems, so that efficiency at scale can be achieved rather than creating fragmented automation solutions that can result in data silos between departments. Additionally, businesses still relying on legacy systems may need to modernize their infrastructure to fully capitalize on AI’s automation capabilities.
2- Prioritize User-Friendly AI
Both generative and agentic AI require intuitive interfaces for successful adoption, but the user experience differs significantly. Generative AI tools are typically designed for knowledge workers, requiring straightforward prompts to generate text, images or insights. In comparison, agentic AI interacts with operational teams, handling real-time decision-making tasks that directly impact workflows. Ensuring these systems are designed with end-users in mind—whether customer service agents, IT teams or security analysts—will improve adoption rates and maximize AI-driven efficiency gains.
3- Work with AI Experts for Guidance
Managing an AI-powered system requires specialized knowledge. While generative AI solutions often involve fine-tuning models or refining prompt engineering, agentic AI demands expertise in cybersecurity, process automation and regulatory compliance. Just like top athletes rely on coaches to improve their performance, companies should turn to professionals who can help make AI easier to implement, avoid common mistakes, hold users accountable to best practices and get the most value from automation.
Cost reduction was identified as a top priority and a key benefit of automation. Can you share examples of how Redwood’s automation fabric has helped clients achieve measurable cost savings within their ERP processes?
Redwood’s Enterprise Automation Index shows us that organizations are more likely to cut costs by over 50% with automation, and twice as likely to cut manual workloads in half. Together, those two figures really tell a story. When repetitive, manual tasks are automated, employees are free to focus on higher-value, human-centric work that drives innovation and strategic growth. Across industries, profitability hinges on operational efficiency, and Redwood’s automation fabric solutions are purpose-built to optimize ERP processes at scale—eliminating friction, reducing errors and enabling smarter, faster operations.
With digital transformation accelerating, what role should automation play in modern ERP migration or upgrade projects?
The role that automation should play in modern ERP migration is an integral one. Rather than being viewed merely as a tool for post-implementation optimization, automation must be embedded from the outset—guiding planning, execution, testing and even ongoing maintenance. As businesses accelerate their digital transformation, the complexity and volume of data, systems and processes demand solutions that are intelligent, scalable and seamlessly integrated.
Modern ERP platforms are increasingly built with AI and machine learning capabilities at their core. Automation enables faster, more reliable data migration, reduces human error, ensures compliance and significantly shortens project timelines. As companies modernize and upgrade different software and hardware, there is now, more than ever, a need for these pieces of tech to be able to communicate seamlessly.
What would your advice be to CIOs and ERP leaders who are hesitant about integrating AI into their core operational platforms?
Our data shows that less than 40% of companies feel prepared for AI-driven automation. This tells us that there’s a clear need for integration between the pieces in companies’ tech stacks before AI can be deployed. With that in mind, my advice is this: Start with addressing process orchestration. When your tech stack is fully integrated and communicating across processes, then you can focus on deploying AI.
Looking ahead, how do you envision the convergence of ERP, automation, and AI evolving over the next 3-5 years? What should businesses prepare for now?
Over the next 3-5 years, the convergence of ERP, automation and AI will fundamentally reshape how businesses operate—moving from static systems of record to intelligent, adaptive platforms that can anticipate needs, optimize processes in real time and drive autonomous operations. To prepare, businesses must take a dual approach:
1- Modernize and unify their tech landscape to ensure legacy systems and critical applications are ready to integrate with AI-driven ERP platforms.
2- Invest in data readiness and automation infrastructure. Clean, connected data and orchestration layers will be key enablers of future value.
The focus shouldn’t just be on adopting the newest tools, but on building a flexible, future-ready foundation that allows for continuous innovation and seamless AI adoption.
Charles Caldwell
Senior Vice President of Product Management, Redwood Software
