Interview by our Technology partner Altair: "Breaking the Barriers of Becoming an AI-driven Enterprise"

In an enlightening conversation with our partner Altair, we delve into the transformative role of Artificial Intelligence (AI) in the enterprise world. As companies across the globe increasingly adopt AI, we explore the reasons behind this shift, the challenges faced during implementation, and the critical factors that lead to success.  

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Embracing AI for business innovation and efficiency

Our Business Development Director Sam Verdonck shares his insights on navigating the complexities of AI integration, the impact of AI on operational efficiency, and the bright future AI promises for businesses willing to embrace its potential. This interview aims to shed light on the importance of AI in leveraging time-series data for predictive insights and the pathways to achieving enterprise transformation through successful AI adoption. 

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AI transformation in business: An in-depth conversation with Altair

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Altair: Why do we need AI and why are more companies adopting it? 

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Sam: "First and foremost companies need AI to become more efficient and make better use of their data. Because why else would you be collecting and storing all that data? Look at the big success of GenAI. Over the past decades knowledge workers got overloaded with information and data. And because of this information overload we were losing efficiency. GenAI is now providing a way to put a filter on this huge amount of text data and efficiently turn it into bits and pieces of truly useful information and insights. GenAI is a game-changer for text, but at the end companies don’t run on text but rather on time-series data, tables of numbers evolving over time. The next step is to also put an AI engine and filter on this numerical data overload to automatically turn it into valuable predictive insights. That’s what we are here to do." 

Altair: According to Gartner, 85% of AI projects fail. From your perspective, what is one of the main causes of these projects failing? 

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Sam: "Having a data platform with AI-ready data in place is a must but we mainly see lots of AI projects failing because they are driven by data scientists who typically take an academic R&D approach thereby ending up in lengthy and complex trial and error processes. To become successful with AI, companies need to put processes in place supporting an agile handover from R&D to production with operational AI pipelines managed by IT delivering daily predictive insights to the business." 

Altair: For organizations that have successfully transitioned to being an AI-driven enterprise, what made them successful? Can you give an example where an organization successfully made the transition? 

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Sam: "Taking the example of our customer Shell. Their success in becoming an AI-driven enterprise is not just about adopting a data platform and instilling a data-driven culture. It's about recognizing that AI deserves a central place in daily operations and not just in R&D or innovation departments where AI projects often get stuck and don’t deliver business value. Shell understood that investments in AI automation would pay off, providing predictive insights that are invaluable for decision-making. To achieve business agility you need to start your AI projects with automation, maintainability and scalability in mind. By establishing a full-scale AI business unit and starting to integrate AI into their daily operations and putting a real-time spotlight on time-series trends, Shell is achieving a level of agility that sets them apart in the industry."  

Altair: This is a fast-changing industry. In order to continuously advance, we have to look 5-10 years ahead. Where do you see AI in 5 years and what are you doing now to prepare your customers? 

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Sam: "Five years from now, the leading companies will be using AI at full scale on most of their business data to power daily operations across their business units. Today this is not yet the case. Most companies are still very busy setting up their data infrastructure and making their data AI ready whilst running pilot projects driven by innovation or R&D departments rather than the business. With our automated AI we are helping our customers to facilitate and accelerate their journey, find predictive value in their time-series data and operationalize and scale their AI platforms. Our customers are therefore ahead of the curve and well-prepared for the dynamic AI-driven future." 

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Conclusion

Throughout this interview, it becomes clear that the journey toward becoming an AI-driven enterprise is both challenging and rewarding. By addressing the common pitfalls and embracing a strategic approach to AI implementation, companies can significantly enhance their operational efficiency and decision-making processes.  

Sam's perspective underscores the importance of agility, scalability, and a forward-looking mindset in harnessing the power of AI. As we look towards a future where AI is seamlessly integrated into every aspect of business operations, this conversation with Altair serves as a valuable guide for organizations aiming to navigate the dynamic landscape of AI with success and foresight. 

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Article by Sam Verdonck, Chief Growth Officer at Tangent Works

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