Papers Library

Why traditional technical publications, training packages, and support data contracts are no longer enough in an AI-driven world.

For decades, support data acquisition followed a predictable model: buy manuals, training packages, CSDBs — deliverables defined by specification. Once delivered, success was declared. But that model was built for a static world. Support data is no longer the end product; it is the fuel. And fuel is useless if it cannot be accessed, queried, or fed into analytics and AI. When organisations say they need training, a CSDB, or support data — they often mean capability. The acquisition model must evolve. This paper argues that we no longer buy outputs. We buy the ability to make governed decisions, integrate across disciplines, and generate insight.

You Can Ignore AI. The Market Won't.

A comfortable narrative circulates in parts of the IPS community: AI is interesting but not critical. This paper argues that narrative is dangerously short-sighted. Whether we embrace it or not, AI is reshaping how organisations think about data and lifecycle management — and the IPS engineer sits in the blast radius. The IPS engineer who understands AI orchestration, data governance, and retrieval logic becomes central. This is the emergence of the Through-Life Data Engineer. The question is not whether AI belongs in IPS. The question is: will you be architecting it, or reacting to it?

The Comfortable Lie of One-Size-Fits-All Learning

After delivering training across continents and industries for more than two decades, one lesson stands out: people do not learn the same way everywhere. Yet many training organisations roll out the same format globally. This paper argues that training is not a template — learning is cultural, forced interaction can produce anxiety not learning, and professional maturity means adapting the mechanism while preserving the standard. Training is not the transmission of slides. It is the transfer of judgement.

Why AI Makes Product and IPS Specialists More Critical — Not Less

For years, expertise meant being the person with the answers. But the way knowledge is stored, shared, and scaled is evolving, and AI is now part of that evolution. This paper argues that AI does not replace experience, judgement, or domain understanding — it amplifies structure. The expert's role is expanding from teacher and advisor to knowledge architect, model trainer, and curator of structured intelligence. The expert is not being replaced. They are being elevated.

Why committee membership, logo alignment, and commercial positioning should not be mistaken for independent expertise

There is an assumption in our industry that quietly shapes decisions: if someone sits on a steering committee, represents their country on a working group, or participates in specification development, then they must automatically be the authority. This paper argues that proximity to specifications and governance bodies is not the same as independent advisory authority. Committee membership, logo alignment, and commercial positioning should not be mistaken for expertise. True authority is earned through successful implementation and measurable outcomes — not through affiliation.

Who does training really serve?

Training has moved from event-based delivery to embedded, continuous learning. Yet much industry energy is spent debating who should be allowed to train, rather than how people actually need to learn today. This paper argues that the training industry must shift from gatekeeping (controlling who is allowed to train) to guidance (helping people learn continuously). The future belongs to trainers who act as guides, supporting learners over time and focusing on outcomes rather than control.

If advice cannot withstand questioning… It isn't expertise. It's position.

There was a time when knowledge was scarce and experience was the primary source of authority. But we now operate in a different environment where specifications are accessible, communities are connected, and AI tools enable rapid analysis. This paper argues that experience is valuable but no longer the only source of truth. Authority today must rest on contextual understanding, strategic alignment, evidence, and outcomes — not just years served. Experience becomes dangerous when it becomes defensive and unchallenged. The strongest professionals are those confident enough to say "Test it. Challenge it. Improve it."

How AI, Privacy and the TDW Digital Classroom™ Are Transforming Professional Training

For decades, professional training followed the same pattern: a trainer travelled to a classroom, slides were delivered, exercises were completed, certificates were issued, and then everyone returned to work — and the learning slowly faded. This paper explores how AI, privacy, and the TDW Digital Classroom™ are transforming professional training from a one-off event into a continuous knowledge relationship, where the trainer never truly leaves the room.

Why IPS ecosystems risk mistaking iteration for transformation

Innovation is a word that appears everywhere in the Integrated Product Support world — in strategy documents, conference themes, and tool roadmaps. Everyone agrees innovation is essential and happening. But are we truly innovating, or are we simply becoming more comfortable copying once the risk has passed? This paper argues that innovation leads, copying follows, and confusing the two can quietly shape the direction of an entire ecosystem.

Why the Next IPS Shift Is Architectural, Not Technological

AI is already embedded in IPS tools and workflows, but the conversation remains superficial, focusing on features rather than decision influence. This paper argues that AI will transform IPS not because it is intelligent, but because it exposes how poorly we have historically understood our own data, decisions, and accountability. The winners in the next IPS cycle will be those who recognise that AI is a decision lens, not just a tool feature.