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Powering Software-Defined Products with AI-Augmented Digital Threads

Overview

Is Your Digital Thread Ready for Software-Defined Development at Scale?

Software-defined products are transforming how products are designed, built and evolved. But with this shift comes unprecedented complexity—spanning mechanical, electrical and software domains and extending across diverse ecosystems of partners and suppliers. To stay competitive, enterprises need modern, integrated and intelligent engineering ecosystems that can unify data, streamline collaboration and enable seamless lifecycle management across the entire product value chain.

A digital thread connects product data across the lifecycle – from design and manufacturing to sourcing. But without intelligence, it remains manual. elevates it by automating integration, uncovering context and delivering actionable insights that enable true closed-loop traceability and smarter, faster decisions. This IDC Spotlight paper sponsored by HCLTech, draws on a global survey of PLM decision-makers at software-defined product (SDP) organizations. It builds a compelling business case for AI-augmented digital threads, highlighting how leading manufacturers are evolving their approaches to stay ahead. The paper uncovers what sets industry leaders apart—and provides a clear roadmap for engineering and product development teams to move beyond fragmented, reactive processes.

77% of manufacturers say that deploying AI agents for data integration is very or extremely important. Are you ready?

Overview

What’s Inside the Paper

What Defines Success: What High-Performing Manufacturers Do Differently

The Software-defined product imperative

Why SDP complexity is forcing manufacturers to rethink development models

As software replaces mechanical linkages, product programs span more disciplines, involving more suppliers and generating more data than most enterprise systems were built to handle. Understand the structural drivers reshaping engineering and R&D.

The digital thread under pressure

Where integration breaks down and what it costs

70% of manufacturers report that more than 10% of their products require design changes after release to manufacturing. This IDC research traces this back to a core challenge: fragmented PLM, ERP, SCM and MES environments that drive late-stage changes and missed quality and cost targets

AI as the intelligence layer

How AI augments digital threads to deliver real operational value

AI creates and maintains integration code, automates data mapping, infers context across disciplines and monitors macro-economic signals that affect product plans. This section details the five highest-priority AI use cases that manufacturers are investing in now

Leader vs. midfield: A measurable divide

What strategic AI adoption can look like and the results it can produce

Manufacturing leaders experience a 16% late-stage design change rate. For midfield peers, that number is 47%. Leaders rate AI for data integration, requirements synthesis and chatbot-based data access 13 to 18% higher than midfield organizations. This section unpacks the strategy gap

The HCLTech approach

From digital thread backbone to AI orchestration

Our digital thread services portfolio including lifecycle management, thread backbone accelerators, and gives manufacturers the integration foundation and AI orchestration layer needed to turn connected data into governed, actionable intelligence.

Implementation priorities and risks

Where manufacturers get stuck and how to move forward

Tool fragmentation, legacy integration debt, IP protection concerns and change management resistance are the four barriers most likely to stall AI-augmented digital thread programs. This section provides a clear-eyed view of the challenges and how to address them

What the Research Reveals About SDP Leaders

Software-defined product programs are becoming more complex, more distributed and increasingly data dependent – yet most enterprise systems were not designed to connect that data seamlessly. IDC's research quantifies this growing gap: the distance between industry leaders and the rest is widening and the decisions shaping that divide are being made right now.

55%

manufacturers rank AI-driven automation as their top strategic priority — displacing quality and cost for the first time in eight years

77%

say deploying AI agents for data integration is very or extremely important

47%

midfield manufacturers have late-stage design change rates above 20%, compared to just 16% for leaders

82%

manufacturers identify optimizing design practices as very or extremely important AI use case for product innovation over the next two years

IDC Spotlight, sponsored by: HCLTech, AI-Augmented Digital Threads for Software Defined Products: Turning Engineering Data into Faster Decisions, AP7897X, April 2026

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