What are we going to do with artificial intelligence?

Artificial intelligence (AI) is knocking on the doors of many professions and industry sectors, and knowledge and quality management is by no means an exception. The question we are facing is not whether AI has any value or can be useful to us in the quality management of organisations, but rather how we can use it to make our work easier and achieve our corporate objectives.

Taking it to a higher level

When we consider AI from the perspective of quality management, with all the technical possibilities offered by current software and hardware, it is almost imperative for us to start with the use, management, arrangement and structuring of an organisation's data.

Before introducing software or aspects strictly related to AI, it is necessary to consider that there is commercial software like Microsoft Power BI, SAP BI, SAS Business Intelligence or Sisense that, without resorting to AI, can be very useful for organising, ordering, modelling and fixing data so that it can show trends, hidden patterns, relationships, or other numerical correlations in large and complex data sets. This type of software is very useful to support decisions based on the facts that reflect such data. It can help companies identify areas for improvement and make informed decisions to optimise their quality management systems.

AI can take this data management to a higher level, by opening up the possibility of automating repetitive and monotonous tasks associated with quality management. This can free up time and resources for employees to focus on more strategic and higher value-added activities.

"The future has already reached us, so it would be valuable to consider the inclusion of AI aspects to enhance these audit automation processes, instead of limiting themselves to managing documentation."

Pedro Mejias, Senior Auditor with Consorcio Kaizen in Venezuela

Learning the language

For professionals in quality management, a very wide window of competency training opens, as it is necessary for us to learn topics that are probably new, such as natural language processing (NLP) or automatic learning algorithms (machine learning).

Through the use of advanced algorithms and machine learning techniques, AI can help identify and analyse quality management processes and areas in companies by playing a role in detecting and preventing quality issues in real time. Through online data analysis, AI can proactively identify potential deviations or anomalies in quality processes and alert those responsible to take corrective action immediately.

AI can be used, for example, to improve the performance of audits of quality management systems in organisations in various ways. One such way is by analysing the current audit processes in the quality management systems of an organisations.

To do this, NLP techniques can be used to extract relevant information from audit-related documents and records. This would make it possible to automate the review and analysis of a large amount of information, which allows the samples on which decisions are made to be expanded and, in turn, would reduce the time and resources necessary to carry out the audit.

Furthermore, AI can be used to identify patterns and trends in the data collected during audits. This would help identify areas for improvement in an organisation's quality management systems and offer recommendations for optimisation. For example, through the use of machine-learning algorithms, correlations between certain processes or practices and the overall performance of the quality management system could be identified. This would allow organisations to make informed, data-driven decisions to improve their systems.

Fraud detection

Additionally, AI can play an important role in detecting possible fraud or irregularities during audits. AI algorithms can analyse large volumes of data and detect anomalies or suspicious patterns that could indicate fraudulent practices. This would help improve the accuracy and effectiveness of audits, providing greater confidence in the results obtained.

This condition is a major wake-up call for auditing and management system certification organisations that are just implementing software to automate audit reporting and record management processes. The future has already reached us, so it would be valuable to consider the inclusion of AI aspects to enhance these audit automation processes, instead of limiting themselves to managing documentation.

Summary

The possibilities on the horizon are many and varied, However, when it comes to such comprehensive, complex, novel and hot topics it is always better to listen to the opinion of experts in the field. In this regard, keep an eye on the activity of the CQI Cambridge and Peterborough branch, which is working on AI and Governance and could bring some outreach activity on AI assurance and governance towards the end of the year.