AI is here to stay

Artificial Intelligence (AI) is no longer a futuristic concept; it is a present-day reality beginning to transform industries worldwide. I head up Data Science and AI at QIAGEN – I have always worked with data, so I understand AI’s potential. Yet, grasping this potential effectively can be quite challenging without the right technical background.

At QIAGEN, AI is already helping us to reduce costs, improve quality, speed up processes, and work more efficiently. Currently, the area with the greatest potential for AI is Service and Customer Support.

If I ask our Service team about their most important objectives, they emphasize call efficiency and call avoidance. A draft response that is automatically generated for you from information in the knowledge base can help you handle a request far more efficiently, while AI troubleshooting can also help the customer to help themselves.

Supporting Service with such tools is something that we are continuously developing.

One challenge with any type of request is that you will have multiple hits in your knowledge base. Imagine you are doing a search on thousands of manuals and articles from a CRM system. Not all of those hits are going to be equally helpful. The results may all be related to your question, but you need to filter out the bad from the good ones. This is where AI proves its value.

There is an understandable concern in many sectors that AI could replace jobs. However, our goal here is to have people working on those customer requests that cannot be automated. This will allow people to focus on very specific, perhaps more complex, requests – removing a lot of the more mundane activities.

AI has been identified as a top priority for many companies. A recent report from the Boston Consulting Group (BCG) found that almost 90% of executives rank AI as a top-three tech priority (1). It is also rapidly changing the way companies do business.

Doing nothing is not an option

However, there is a certain tendency to say, “Let’s wait until we can move beyond the hype,” and that is understandable. When people say that AI is ‘hallucinating’, for example, generating misleading or incorrect information, they have a valid point.

However, I suggest focusing on the things AI already excels at. For instance, in text comprehension and information extraction, language models now perform nearly flawlessly. If you ask a question and the answer is within the provided text, you are very likely to receive an accurate response.

There are undoubtedly challenges - technical, personnel, legal and security concerns - and of course a cost-benefit analysis is necessary. So there are many unknowns. But there are ways to tackle those challenges. And it is important to note that there is a bigger risk – one that comes with just waiting, with doing nothing. That is the risk of being left behind.

Setting up necessary data cloud infrastructure and recruiting a team of experts takes time because there is a talent shortage, and, perhaps more importantly, training your users and decision-makers in AI will also take time.

There is never going to be good external data on the best AI use cases for a company like QIAGEN. So, to a certain extent there might always need to be something of a trial-and-error approach, and most valuable use cases might only be revealed via that approach.

It may involve doing some proof-of-concepts quickly to see if something is feasible, then having a proper business case for the things that you develop further. It is often only after a proof-of-concept that you’ll know enough to even do a business case. Otherwise you won’t have enough knowledge about possible solutions that you can properly quantify.

We must invest in data

To make the transition to an AI-enabled organization there are a number of things that need to be done. Firstly, to invest in cloud and data centralization, but also in data curation – because everything starts with the data. If the data is not of the right quality, you have a problem. Further, digitalizing processes is crucial so data is not just on paper. And if the data is not available in the cloud, it is difficult to use it efficiently. At QIAGEN a lot of our data is stored in what is called a ‘Data Lake’ – a central data repository in the cloud.

Bringing AI and business experts together is vital to identify valuable use cases. At QIAGEN, we currently perform AI Ambition workshops across the organization to systematically identify AI use cases with high value potential. To this end we review key processes, pain points and objectives that can be supported by AI, derive possible use cases and then further prioritize those based on value on effort. It is remarkable how many valuable ideas come from all areas of the company.

Investing in training and AI literacy is also essential. We have a so-called AI Academy that educates colleagues on AI principles and applications, but that is just the first step. Each AI initiative must include planned investments in change management and strategies to ensure the new solutions are accepted and integrated seamlessly into existing workflows. And you also need guidelines and regulations: What is a safe use of AI? What guidelines are important for us as a company in terms of issues like data handling and preventing data leakage?

At QIAGEN, stringent quality assurance in a regulated environment means not all use cases are possible, a valid concern. However, there is growing enthusiasm. Colleagues are increasingly approaching me with AI ideas. They ask, for instance, “We have all this textual data, can a language model analyze this?” This shift shows people are keen to apply this powerful technology in their areas.

The pace of evolution is amazing. We really cannot predict where it will have led us in two years’ time, but the fact remains that AI is here to stay; it is not just a trend but a cornerstone of future innovation.

So the question is not whether AI will be a key value driver. The question is, where does it have the most value for our company? At QIAGEN, we are investing in the long-term vision of an AI-enabled organization. By prioritizing AI today, we can ensure sustained growth, efficiency, and excellence for tomorrow. Let's work together to make this vision a reality.