An AI-driven transformation requires a partner with deep industrial expertise. PTC provides the foundational technologies and strategic guidance necessary to operationalize AI effectively across your value chain.
REDUCE COSTS
AND IMPROVE
QUALITY WITH AI
Reduce Costs and Improve Quality with AI Copyright PTC Inc. 2026 PAGE 2 < | >
Industrial manufacturers operate in a high-stakes environment where the machines
they build are mission critical. When equipment fails in the field, customers face
costly production downtime, while manufacturers shoulder warranty claims,
potential recalls, and the harder-to-quantify—but far more damaging—reputational
costs. In an industry where trust and reliability are paramount, even a single failure
can have long-term consequences for your brand.
For many industrial organizations, the cost of poor quality amounts to 15 to 20
percent of total sales revenue. Manual processes, fragmented engineering data,
and siloed systems often prevent teams from addressing quality issues proactively,
leaving them to react to problems after they’ve already caused damage.
A new approach is necessary to overcome these challenges. By integrating artificial
intelligence (AI) into core engineering and quality processes, industrial companies
can prevent defects at the design stage, avoiding downstream costs speeding up
time to market, and improving customer statisfaction.
• Enhance product quality by identifying potential design flaws early.
• Optimize product performance and reduce costs through simulation-driven
design validation.
• Ensure regulatory compliance through automated traceability.
• Build a unified digital thread connecting engineering, manufacturing,
and service teams.
THIS E-BOOK EXPLORES HOW AI TRANSFORMS QUALITY
MANAGEMENT BY ENABLING YOUR ORGANIZATION TO:
Reduce Costs and Improve Quality with AI Copyright PTC Inc. 2026 PAGE 3 < | >
THE HIGH COST OF
REACTIVE QUALITY
Most industrial manufacturers manage quality reactively.
Engineering, manufacturing, and service teams work in isolated silos
without real-time collaboration. This fragmentation leads to design
issues reaching production, manufacturing teams working from unclear
specifications, and service teams lacking current information.
These early decisions introduce flaws to the manufacturing, operation,
and service stages of complex industrial assets. Identifying and fixing
these issues downstream during production or field service costs
significantly more than addressing them during the initial design phase.
When product requirements get lost or modified as designs evolve,
companies lose clear traceability. If an engineering change occurs, the
impact on downstream processes is rarely evaluated systematically. This
results in costly rework, higher scrap rates, and delayed time-to-market.
OVER 60 PERCENT OF QUALITY
ISSUES ORIGINATE FROM DESIGN
CHOICES MADE IN ENGINEERING.
Reduce Costs and Improve Quality with AI Copyright PTC Inc. 2026 PAGE 4 < | >
HOW AI TRANSFORMS INDUSTRIAL
QUALITY MANAGEMENT
Rather than functioning as a standalone tool, the best use case
for AI is direct integration into the systems you already use to
manage the product lifecycle. This approach transforms vast
amounts of data into a strategic asset for proactive decisionmaking.
To operationalize AI effectively, organizations must embed AI
agents directly into enterprise systems like product lifecycle
management (PLM) software. These agents perform three key
functions that augment human expertise and drive operational
efficiency.
ADVISE: TURNING DATA INTO INSTANT
INTELLIGENCE
AI agents act as an intelligent knowledge base,
providing instant access to critical information
within the user’s workflow. This capability allows
engineering teams to make informed decisions
without searching across siloed databases.
For example, an engineer designing a new heavy
equipment component can ask the AI agent
to identify alternative parts that meet specific
performance, cost, and compliance requirements.
The agent analyzes data on approved vendors,
component lifecycles, and current supply
chain risks. It then provides a data-backed
recommendation in seconds. This ensures
design decisions are optimized for quality and
manufacturability right from the start.
ASSIST: STREAMLINING COMPLEX WORKFLOWS
AI agents function as intelligent partners that assist
users by completing specific steps within a larger
process. This reduces manual effort, minim