Felix Van de Maele, the CEO and co-founder of Collibra, has made it clear that in today’s rapidly evolving technological environment, a candidate’s lack of engagement with artificial intelligence is not merely a gap in knowledge—it constitutes what he calls a significant “red flag.” He emphasized that any individual aspiring to join his data governance platform should already exhibit a concrete understanding of AI technologies and their practical implications for enhancing professional performance. According to Van de Maele, contemporary interviews are no longer simply exercises in assessing core competence or industry experience; they are examinations of a person’s ability to incorporate AI-driven reasoning and tools across every dimension of their role. He told Business Insider that prospective employees are now expected to think “AI first,” meaning they should instinctively consider how intelligent systems can streamline workflows, elevate efficiency, and foster innovation. If an applicant cannot articulate or demonstrate direct experimentation with AI solutions—or if they lack awareness of how these tools can make their tasks more effective and precise—then, in his words, the conversation quickly reveals a concerning absence of curiosity and adaptability.
Collibra, which Van de Maele founded in Belgium in 2008, has grown into one of the leading names in the global data governance domain. The privately held company, having secured a valuation of $5.2 billion in 2021, has cemented its reputation as a strategic data partner for some of the most recognized brands in the world, including McDonald’s, Credit Suisse, Adobe, and Heineken. This pedigree underscores its influence at the crossroads of data management, compliance, and enterprise intelligence. Yet, even as the company holds this premier market position, its leader remains acutely focused on integrating artificial intelligence into every operational layer, seeing AI not as a peripheral enhancement but as a central catalyst transforming the very nature of digital collaboration and analytics.
When discussing AI expertise, Van de Maele was careful to note that the specific competencies he seeks vary according to role and professional background. For example, when interviewing engineers, he is particularly attentive to whether they actively incorporate AI-powered development assistants—such as advanced coding agents like Cursor—into their daily processes. These tools, he remarked, provide telling insight into an individual’s willingness to embrace innovation and augment their own capabilities. By probing how candidates employ such resources, he can discern not only their technical fluency but also their mindset: whether they are open, exploratory, and driven by experimentation, or whether they approach technological shifts with hesitation and defensiveness. For Van de Maele, this distinction is crucial, as Collibra’s internal culture depends heavily on curiosity and proactive adoption of intelligent systems that push the boundaries of productivity.
Within Collibra itself—an organization he has described metaphorically as “ServiceNow for data”—the transformation brought by AI over the past year has been striking. The company’s global workforce of approximately 1,000 employees incorporates AI across a wide spectrum of daily functions: from automating mundane administrative tasks, such as transcribing and summarizing meetings, to constructing sophisticated custom agents that serve as personalized digital collaborators. These initiatives are not simply about convenience or incremental gains; rather, they reflect an intentional effort to reimagine how work gets done at every level. By embedding AI into the company’s DNA, Van de Maele seeks to redefine efficiency and empower employees to operate with unprecedented levels of speed, insight, and innovation.
Turning to broader strategic considerations, Van de Maele envisions Collibra’s position in the enterprise AI ecosystem as that of a neutral, integrative layer—an independent connective tissue capable of uniting vast amounts of organization-specific data in a structured manner. This framework, he believes, is key to unlocking the full potential of AI, especially in realizing the long-term promise of autonomous or “agentic” AI systems. To illustrate this idea, he offered a vivid analogy: imagine hiring an experienced senior employee and asking them to perform an extensive data analysis within a large organization. Even a skilled human analyst can struggle to locate and interpret the required data due to complex access protocols and fragmented systems. Similarly, an AI agent would encounter the same constraints unless the company made its context—its data relationships, definitions, and hierarchies—explicit and accessible. As Van de Maele explained, the formalization of context is therefore indispensable; if humans cannot navigate the system fluidly, an AI agent will be equally hindered until that knowledge structure is systematically captured and integrated.
He noted that this need for contextualization parallels practices already established by other technology firms. Palantir, for instance, pioneered a model in which “forward-deployed engineers” work directly with clients to tailor software solutions to specific business challenges. Inspired by this consultative approach, companies like OpenAI and other advanced model providers are now establishing similar customer-facing teams to ensure that their AI tools deliver maximum relevance and value. Yet, according to Van de Maele, today’s enterprise AI landscape still faces a crucial obstacle: overreliance on a single model or vendor can severely restrict agility. For sophisticated organizations such as global banks or major corporations, such dependency represents a strategic vulnerability. Businesses, he argued, must maintain the flexibility to switch between AI models and providers as technology evolves, especially given the rapid rate at which new models are released—each potentially far more capable or cost-efficient than its predecessor. “If I’m operating a large organization,” he observed, “I cannot afford to be locked into just one vendor, because next month a superior or more economical model might emerge. The ability to pivot quickly is not a luxury; it is a strategic imperative.” In that sense, Van de Maele’s stance captures a broader truth about the modern digital economy: success belongs to those who not only use AI but also build the adaptive infrastructures and mindsets that allow them to evolve alongside it.
Sourse: https://www.businessinsider.com/collibra-ai-first-employees-felix-van-de-maele-enterprise-2025-12
