HiQ integrates artificial intelligence (AI), data, and automation into a service area

The goal is to assist HiQ's customers in understanding the practical applications of AI and addressing tangible business challenges.

HiQ integrates artificial intelligence (AI), data, and automation into a new service area. HiQ aims to assist their customers in understanding the practical applications of AI and addressing tangible business challenges. To support the change, Jonas Pomoell has been named as AI Lead Consultant at HiQ.

Over the years, artificial intelligence has played a prominent role in various HiQ projects, ranging from streamlining order reception and supporting product development to automating data collection. Proficiency in data collection and processing is crucial, as the right data is essential for creating a functional AI model. This intersects with automation, which helps streamline data collection from diverse sources and eliminate imprecise or inefficient processes.

Recognizing that AI, Data, & Automation collectively cater to evolving customer needs, HiQ is committed to assisting customers in discovering new applications for artificial intelligence and addressing practical business issues. Currently, HiQ has over 10 experts in this domain, with plans to add four new consultants to the team in 2024.

"We aim to educate our customers on how AI can address significant business challenges. As a company, we have well-defined practices and tools for leveraging AI effectively, allowing us to assist customers at varying levels and technological starting points," says Jonas Pomoell, HiQ’s AI Lead Consultant.

HiQ continually nurtures and advances its AI expertise, emphasizing the importance of understanding when to apply existing technology effectively, in addition to staying updated on the latest advancements.

We've accumulated valuable insights from previous projects, successfully applying generative AI in practice in different industries.

AI Lead Consultant

Jonas Pomoell

"We've accumulated valuable insights from previous projects, successfully applying generative AI in practice in different industries. We approach customer challenges with analytical curiosity, recognizing that the newest or trendiest technology may not always be the optimal choice," emphasizes Pomoell.

A crucial takeaway from AI projects is the significance of data processing expertise. Often managed more as a research project than a conventional software development project, data processing demands careful attention to quality verification and adaptation of hypotheses based on iterative learning from the customer's business.

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