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Why ADP, Tesla, and Intuit Are Investing in Content as AI Infrastructure.

Knowledge Management • AI Readiness • Ground Truth

Why ADP, Tesla, and Intuit Are Investing in Content as AI Infrastructure.

What hiring signals about where the market is heading: ground truth.

Market signal: Enterprise teams aren’t “upskilling documentation.” They’re rebuilding content into AI Infrastructure — because AI reliability depends on a governed Ground Truth Layer.

Everyone is talking about AI.

But quietly, underneath the hype, some of the world’s largest companies are doing something far more foundational:

They’re investing in content as AI Infrastructure.

Over the past week, we analyzed DITA-related job postings across global enterprise organizations, looking for market signals about why companies are investing in structured content and what outcomes they’re actually chasing.

What we didn’t do
We weren’t tracking salaries. We weren’t cataloging writing skills.
What we did do
We asked one strategic question: why are enterprises investing in structured content now — and what outcomes are they optimizing for?

The question behind the hiring

Why are companies like AMD, Tesla, KONE, ADP, ServiceNow, Okta, Rubrik, Synopsys, Huawei, Xylem, and others rebuilding content — and why does it matter now?

The answer wasn’t surprising — especially given the direct relationship between content quality and AI outcomes.

This isn’t about documentation anymore. It’s about AI reliability, operational scale, and enterprise trust.

AI doesn’t fix bad content. It amplifies it.

AI amplifies content quality — good or bad

When knowledge is fragmented or inconsistent, AI systems don’t “average it out.” They reproduce the inconsistency at scale.

  • Conflicting answers
  • More hallucinations
  • Higher support costs
  • Lower customer confidence
  • Compounding operational risk
Content quality is now a systems problem.
You can’t scale AI on top of content chaos.

The Ground Truth Layer

As organizations deploy assistants, agents, and automated support, they’re learning a hard lesson: reliability starts upstream.
You need AI Infrastructure anchored by a Ground Truth Layer — clear, accurate, and managed content humans and machines can trust.

That’s exactly where DITA and CCMS enter the picture.

Not as a publishing standard — but as AI Infrastructure.

DITA is moving up the org chart

The hiring shift is visible: DITA is showing up beyond Technical Publications. These roles now live inside functions that own scale and business outcomes.

Where DITA roles are landing
  • Engineering
  • Product
  • Strategic Enablement
  • Knowledge Management
  • Customer Experience
  • Centers of Excellence
Titles that signal “infrastructure”
  • Director of Content Strategy & Architecture
  • AI Content Team Leader
  • Content Platform Engineer
  • Documentation Operations Lead
  • Knowledge Management Specialist

This is an interesting shift.

Content is increasingly treated as part of enterprise architecture, not an afterthought that ships with the product.

What companies are really solving

Across industries, the same constraints keep showing up, and they look a lot more like systems engineering than technical writing:

Legacy documentation doesn’t scale for AI
AMD is migrating FrameMaker and Word content into structured DITA, implementing advanced information architecture and automation to support hardware, software, and AI platforms.
Product knowledge must stay AI-ready in a changing system
Tesla uses DITA and CCMS platforms to keep owner and safety content synchronized with rapid software updates. By structuring knowledge at the source, Tesla creates a trusted system of record that powers consistent experiences today and provides clean inputs for AI-driven support tomorrow.
Reuse and consistency for global operations
Xylem runs a Global Technical Communication Center of Excellence, using structured topics and metadata to standardize documentation across 150+ countries.
Content becomes part of the AI-enabled product platform
ServiceNow embeds technical writers with engineering and product teams to evolve its DITA-based information model. Writers are expected to integrate AI into workflows while delivering structured, modular knowledge inside globally distributed software environments — signalling a shift from documentation to knowledge engineering.
Content must be structured to power AI-first experiences
Intuit has built an AI Content Team to deliver next-generation customer experiences across QuickBooks and its ecosystem. Their mandate includes optimizing content structure and annotations to feed LLMs, accelerating GenAI adoption, and ensuring accuracy through trusted-source content. By investing in structured content (including DITA), metadata, and taxonomies, Intuit is engineering a knowledge layer designed for retrieval, grounding, and generative AI — not just human consumption.
Documentation is now operated like software
Roles increasingly require Git, DITA Open Toolkit, pipelines, automated validation, and CCMS platforms.
This isn’t just technical writing. It’s content systems engineering.

Mini Case Study

Why ADP Treats Content Like AI Infrastructure

At ADP’s scale, accuracy and trust aren’t optional — content gets managed as operational infrastructure.

ADP supports payroll, HR, benefits, compliance, and workforce operations for organizations employing millions of people. At that scale, operational content becomes a critical system of record.

What ADP is hiring for

Senior roles centered on DITA, CCMS, and enterprise content architecture — not just writers, but strategists and architects.

Director of Content Strategy & Architecture

Leads enterprise content strategy, GenAI readiness, and omnichannel delivery.

View the role ↗

Responsibility areas
  • DITA-based information architecture
  • Metadata and taxonomy
  • Governance for GenAI grounding and RAG
  • Content migration and quality frameworks
  • Publishing across Salesforce Knowledge, Experience Cloud, SharePoint, and future client portals
Measured outcomes
  • Case deflection
  • Time-to-answer
  • Content reuse
  • Self-service adoption

ADP is hiring Senior Content Developers (DITA/CCMS) to build structured in-product help that “serves people and today’s GenAI tools.”

Translation: ADP isn’t modernizing documentation. They’re building AI Infrastructure.

Anchored by a Ground Truth Layer, structured content becomes a trusted system of record for customers, associates, and AI alike — reducing friction and ensuring reliable outcomes.

Why this matters to executives

Leaders don’t buy tools. They buy outcomes.

What we’re seeing across ADP, AMD, Tesla, Intuit, and ServiceNow isn’t a documentation trend; it’s a shift in how enterprises manage knowledge as an operational system and AI input layer.

Operational outcomes

Structured content enables:

  • Faster product and platform adoption
  • Lower support costs through improved self-service and case deflection
  • Consistent global operations from a single source of truth
  • Faster time-to-market as content moves in sync with engineering and product
AI outcomes

When content is structured, governed, and machine-readable, organizations get:

  • More reliable AI answers grounded in trusted source content
  • Fewer hallucinations and less manual correction
  • Reduced operational and compliance risk
  • Higher customer confidence in AI-driven experiences

This is about scaling trust.

You can’t automate what you don’t trust. AI can only perform as well as the content it’s trained and grounded on. The companies experiencing success with AI aren’t starting with models.

They’re starting with the content.

Our takeaway

Structured content is becoming AI Infrastructure, anchored by a Ground Truth Layer supported by DITA and CCMS.

DITA isn’t the destination. It’s the foundation.

If your organization struggles with:

  • Inconsistent procedures
  • Slow or error-prone updates
  • Fragmented documentation across teams and tools
  • Disappointing AI pilots

You don’t have an AI problem.

You have a content infrastructure problem. Fix the inputs, and everything downstream gets easier.

Build a Ground Truth Layer your people & AI can trust

If your AI pilots are inconsistent, start upstream: standardize, govern, and structure the content that grounds every answer.

Book a Ground Truth Readiness Call

The analysis in this post is based on independent research using publicly available job postings and market information. Company names and examples are referenced solely to illustrate observable industry trends. Precision Content is not affiliated with, endorsed by, or acting on behalf of the organizations mentioned.

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