- Manufacturing companies face significant challenges in transitioning from “just-in-time” to “just-in-case” models due to data silos, rising costs, and labor shortages, but Generative AI (GenAI) can help by connecting fragmented information, improving productivity, and delivering measurable ROI.
- The key to smart manufacturing is not simply collecting more data, but providing shared context across teams and systems; GenAI solutions like Glean enable this by surfacing knowledge from both operational and IT systems, streamlining onboarding, accelerating innovation, and enhancing customer experiences.
- For successful Industry 4.0 transformation, manufacturers should adopt a horizontal Work AI platform that integrates with existing systems, enforces security and governance, and enables incremental adoption—allowing organizations to automate workflows, standardize procedures, and scale best practices across the enterprise.
For years, the manufacturing industry has pursued the vision of Industry 4.0—a rapid technological transformation by building connected operations through investments in robotics, IoT, and cloud computing technologies. But the challenge is no longer just collecting data—it's analyzing and orchestrating knowledge with precision to realize the potential of smart manufacturing. With the combination of unprecedented tariffs and re-shoring initiatives, the industry is increasingly looking to enterprise-level Generative AI (GenAI) solutions, like Glean, to help address the most pressing challenges of today.
This blog explores how powerful GenAI capabilities can drive Industry 4.0 transformation by contextualizing, not just collecting, data.
Why now: from “just‑in‑time” to “just‑in‑case”
Since 2020, a variety of major shocks have caused unprecedented disruptions to manufacturing operations—and exposed the fragility of hyper-efficient, centralized production models. In addition, customers—led by digital-native buyers—are demanding a greater level of real-time visibility and omni-channel consistency. As a result, “just‑in‑time” models are transitioning to “just‑in‑case" strategies that prioritize overlapping networks, strategic overcapacity, and near/friend‑shoring to withstand shocks.
However, three obstacles make this transition difficult to execute:
- Siloed data spread across disconnected systems prevents teams from anticipating risks from equipment, plants & supply chains—jeopardizing production planning
- Rising costs accumulating from tariffs, inflation, and increasing wages weigh on margins and necessary capital investments
- Labor shortages leave manufacturers at risk of losing critical institutional knowledge as aging workforces get ready to retire without a pipeline of skilled replacements
GenAI can address these challenges through connecting fragmented information, delivering proven ROI, and unleashing productivity throughout the enterprise.
Smart manufacturing relies on shared context, not more systems
Many manufacturers today don’t have a data collection problem—they have a context problem. Teams are required to access data across legacy ERP, PLM/MES/QMS, and collaboration systems in order to build a common operating picture and collaborate effectively. This results in operational delays precisely when speed matters most—unscheduled equipment downtime, supplier delays, and customer escalations.
GenAI solutions like Glean can manage the core accessibility problem by surfacing knowledge across connected OT & IT systems, empowering cross-functional teams with the tools to:
- Streamline onboarding & time-to-proficiency: Single, permissions-aware interface surfaces role-specific guides, SOPs, training materials, and more for frontline & corporate employees
- Accelerate product innovation: Instantly access structured & unstructured data in engineering archives and draft regulatory filings & concept briefs
- Scale AI-powered digital threads: Interact with digital twin simulations and receive real-time equipment troubleshooting support through an intelligent assistant
- Enhance customer experience: Automate key quoting, after-sales service processes and incident reports through agentic workflows
How GenAI helps across the manufacturing lifecycle
Through every stage of the manufacturing lifecycle, routine steps are dependent on the right information for a successful handoff. GenAI tools are capable of transforming these workflows by quickly providing users with recent and relevant answers, but they need the right foundation of enterprise understanding, permissions awareness, and connectivity across all your applications in order to do so. That foundation is how solutions like Glean transform workflows within multiple departments across the manufacturing lifecycle—whether core production functions, IT, or sales—and provide value across the enterprise.
R&D teams can surface structured & unstructured data across engineering archives to instantly explore years of proprietary research. Frontline workers can ask natural-language questions and receive step‑by‑step guidance for setups, changeovers, and maintenance—linked back to a sourced SOP or manual. Leaders gain cross‑program and cross‑plant visibility to replicate best practices globally. Governance, versioning, and strict permissions ensure teams collaborate without compromising security or compliance. As teams become proficient at integrating GenAI into their workflows, they can automate routine steps—and take back time to focus on the highest-value tasks.
What to look for in a Work AI platform
Many leading vendors are developing robust AI point solutions. While these are important in optimizing specific use cases, companies can unlock significant value through integrating them within a horizontal platform. A Work AI layer that sits above your stack—with strict security & governance policies—can synchronize outputs into cohesive workflows. The platform approach can drive effective AI adoption across the organization:
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<th class="rich-text-table_header">Capability</th>
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Enterprise-grade RAG over structured + unstructured data
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Precise, cited answers grounded in ERP, MES, PLM, QMS, and docs
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Trust and auditability at scale
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Native + custom connectors
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Unified context without re-platforming
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Fast time-to-value; minimal IT lift
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Security that mirrors source permissions
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Least-privilege, governed access
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Compliance without friction
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Assistant + Agents in one plane
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From search to execution
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Close the last mile between insight and action
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Incremental adoption patterns
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Pilot-to-plant replication
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Early wins while de-risking change
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Addressing the tough questions: integration, build vs. buy, ROI
- Integration with legacy stacks: Choose platforms that enforce permission‑aware answers, version control for procedures, and governance workflows—so only approved knowledge surfaces on the line.
- Build or buy: In‑house efforts often stall on fragmented data, scarce talent, and shifting security posture. A horizontal Work AI layer de‑risks governance and scale while preserving room for extensions.
- ROI: Start with high‑leverage journeys (frontline onboarding, IT/OT incident response, customer escalations) to prove value quickly, then layer agentic workflows to automate checks and handoffs.
How to get started (pilot‑to‑plant)
- Pick a flagship line or program: Connect core content systems first to deliver immediate answer value; then add live signal integrations.
- Standardize “golden” procedures: Assign owners, review cycles, and version control so only current SOPs appear at the point of work.
- Automate the handoffs: Use agents to draft escalations, route exceptions, and notify owners—reducing MTTR and rework.
- Measure and improve: Track time‑to‑proficiency, self‑service deflection, MTTR, and content freshness; close knowledge gaps with analytics.
Orchestrate knowledge with speed and precision
When every team shares the same context, manufacturing operations get smarter: R&D iterates faster on NPI, supply chain planners align production planning with real constraints, operations teams act with clarity & visibility, support resolves with confidence, and best practices scale globally. That’s how Industry 4.0 becomes real—not as a rip‑and‑replace project, but as a secure knowledge layer that compounds value with every decision.
This is the vision of smart manufacturing in practice—not just connecting disparate systems, but dispersed workforces. The firms that invest now will not only navigate disruptions better—they will compound advantages across innovation, operational efficiency, and customer trust.
To learn more about how Glean empowers smart manufacturing, download our whitepaper.
