The Evolving Role of the Quality Manager

AI and sustainability will soon be central to all areas of quality management, shaping the future of the field. And things are moving fast—so fast that even the most adaptable quality manager may struggle to keep up. What matters more—AI or sustainability? How and what do we prioritize?

Let’s start with AI: Artificial intelligence plays a vital role in driving innovative solutions to sustainability challenges and improving our ability to predict and understand possible environmental impacts.

At the same time, sustainability is equally crucial to the development and application of AI to ensure that the technology is used responsibly, and that it benefits our society as a whole. In a nutshell: These are not competing agendas. In fact, they complement each other—and we mustn’t make the mistake of overlooking the potential of either one.

The answer is: quite a lot. Because you play a key role in integrating AI and sustainability into your organization’s strategy and practices, defining the future role of the quality manager must evolve alongside the technology. As AI becomes increasingly central in optimizing processes and identifying patterns, your role will, figuratively speaking, shift—from that of an analytical, and perhaps relatively passive, spectator to an active, and slightly unconventional, midfielder. Think of it this way: With AI by your side, your place isn’t just in the field or on the sidelines—it’s somewhere in between. You step into the role of a data-driven, strategically important manager, working to strengthen the quality culture of your organization while feeding your IT team with promising challenges that AI solutions may be able to meet and help solve.

Of course, your role as quality manager also remains that of a culture bearer. AI may be able to identify areas with potential for improvement, but it’s up to you to anchor these insights in the values of your entire organization. It’s essential that every employee understands the importance of quality—and feels responsible for maintaining it. Finally, I’d advice that you aim to be an agile navigator, able to adapt to shifting market conditions. AI can provide you with insights in real-time, but your leadership is the key in making swift, well-informed decisions based on those.

Keeping up with the rapid developments and continuous learning can feel overwhelming. Now, more than ever, it’s a responsibility that lies firmly on our own shoulders. So, take a deep breath— and let’s take a look at the key skills to focus on:

• You need the ability to continuously learn and adapt to new technologies. Artificial intelligence, machine learning, tools for data analysis. Things like that.
• You need to be capable of processing and analyzing vast amounts of data.
• You need to develop a strong grasp of process optimization methods and be able to implement improvement initiatives to your systems and workflows.
• You need to have the skills to communicate effectively across the organization, ensuring quality goals and standards are upheld, while inspiring others to engage in quality improvement initiatives.

You need a solid understanding of business strategy and market conditions to help align quality management with organizational goals.

In addition to these skills, consider too what type of decision-maker is best suited for the overall challenges of the future quality manager: a Maximizer or a Satisficer?

• Team Maximizer is always striving to improve quality and achieve the best result possible. They eagerly adopt the latest methods, but their approach also runs the risk of adding excessive complexity and consumption of resources.
• Satisficers, on the other hand, are content achieving the acceptable result. They prefer to maintain existing practices and avoid risky, or overly complex, changes. Unfortunately, this sometimes means they miss out on opportunities for innovation.