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There are two data points that stood out from Mckinsey’s ‘The State of AI in 2020’ survey published in November 2020.

  • One, 22% of the companies surveyed believe that 5% of their total earnings are because of AI initiatives
  • Two, 71% of the companies in the manufacturing sector, witnessed a 5% (or more) increase in revenues thanks to AI adoption

The data is extremely clear.

AI adoption is finding its way to the balance sheet. Well-planned AI initiatives are enabling both revenue growth and profitability.

Additionally, it is becoming clear that AI is finding its way into software solutions used by various departments. From a ComplianceQuest perspective, we are clearly seeing that a next-generation EQMS and EHS solution with AI-enabled features and capabilities will deliver a ton of value to enterprises.

Specifically, the most important use cases of AI in quality, health, and safety management comes in the following areas:

  1. Predictive maintenance of equipment
  2. Automated understanding of risk levels of a quality or safety event
  3. Proactive risk management with predictive analytics
  4. Automated triaging of complaints
  5. Data and AI-driven supplier quality management
  6. Automated “suggestions” for Corrective Actions, Preventive Actions
  7. Automated scheduling of “actions” for proactive quality control
  8. Forecasting of quality and safety trends for executive leaders
  9. Personalized training and development of employees
  10. Driving operational excellence with AI-enabled Continuous Improvement

Specifically, the role of AI in quality analytics cannot be emphasized enough. With so much data being collected from Customer Support, Operations, Quality, Sales, and other business functions – there is just too much information available and not enough employees to analyze all of that data, perform regression analysis, and identify problem areas requiring improvement in a more proactive and predictive way. Typically, what happens is that quality professionals become part of a SWAT team to solve a problem that has already occurred. This approach is reactive. What if AI could help predict and prevent that next recall before it becomes a fire?

Technologies, like Salesforce’s Einstein AI, can help capture insights using billions of records as input from across datasets. This helps predict, forecast and recommend almost instantaneously.

At ComplianceQuest, we are adding a wide range of AI features and capabilities into our QHSE product roadmap. With our domain expertise and capabilities to build AI and ML models, we are working on leveraging Salesforce’s Einstein platform as well.

In this Whitepaper titled “Impact of Artificial Intelligence in today’s world and the future of Next Generation Quality Systems,” we start right from the basics and talk about what Artificial Intelligence is and why it’s important to build AI capabilities into a QHSE software. The paper also breaks down the concept of AI into three layers – AI, Machine Learning, and Deep Learning. Download the whitepaper for more.

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