AI in Quality Guarantees Productivity, Efficiency, Top-line Growth, and Cost Benefits for Businesses
This study examines the increasing use of artificial intelligence (AI) in quality management. The rapid advancement of AI has led to its use across sectors, particularly quality management, as is evident in the growth of predictive quality analytics and enterprise quality management systems (EQMS). With increasing competitive intensity, it has become essential to proactively avoid quality issues instead of relying on reactive approaches. AI-driven predictive quality management tools can preempt quality issues early in the production process, ensuring waste reduction and enhancing overall product quality. Digital technologies such as machine learning (ML), natural language processing (NLP), and advanced analytics in EQMS solutions drive user adoption and result in informed business decisions, innovation, and heightened productivity. While the unclear return on investment (RoI) and a lack of awareness about these technologies present challenges, vendors are now responding by highlighting the increasing number of practical use cases. However, the full potential of AI in quality management cannot be unlocked without access to clean, reliable data. Therefore, formulating a strong data strategy before embarking on AI projects will be imperative to success.
This study analyzes the factors driving and restraining the use of AI in quality management. It also highlights key user cases and profiles the companies impacting this space. The base year is 2023, and the forecast period is from 2024 to 2028.
Strategic Imperatives
Why is it Increasingly Difficult to Grow?
The Strategic Imperative 8™
The Impact of the Top 3 Strategic Imperatives on the Quality AI Industry
Growth Opportunities Fuel the Growth Pipeline Engine™
Ecosystem
AI in Quality—An Introduction
Growth Generator
Growth Opportunities—AI in Predictive Quality
The Business Case for Predictive Quality
The Business Case for AI in Predictive Quality
AI in Predictive Quality (case study)
AI-enabled Systems and Machine Vision for Quality Control
Case Studies
Growth Opportunities—AI Use Cases
AI Use Cases and Manufacturing Value Chain
AI in Quality Control in Heavy Industries
Market Opportunity
Growth Opportunities—Autonomous AI
Autonomous AI Decisions
Autonomous AI Decisions (continued)
Growth Opportunities—Operationalizing AI and Data Strategy
Roadmap to Operationalize AI
Data Strategy in AI
Generative AI and Predictive AI
Growth Opportunities—Sustainability and ESG
Sustainability and ESG
Growth Opportunities—AI in EQMS
AI in Quality—Companies to Action
Companies
AI in EQMS—ComplianceQuest
AI in EQMS—IQVIA
AI in EQMS—ETQ
AI in EQMS—Honeywell (Sparta Systems)
Growth Opportunity Universe
Growth Opportunity 1: Predictive Quality Mangement in EV Component Manufacturing
Growth Opportunity 2: Stricter Quality Control for the Aviation and Transportation Sectors