Florian Douetteau is co-founder and CEO of Dataiku, a Universal AI Platform.
The AI wave already feels like it’s been cresting for a decade. Entire industries are being transformed—from pharma and financial services to manufacturing and marketing—through the power of machine learning systems once too complex to even talk about outside research labs. There is hype, for sure, but there’s also evidence that AI is dramatically reshaping how businesses operate.
Amid this transformation, three groups—AI Ph.D.s seeking new jobs, old-school data analysts, and European enterprises entangled in regulation—find themselves fearing for their future and experiencing a peculiar case of the “AI blues.” In truth, they shouldn’t worry. There are unique opportunities for each group to thrive, if they’re willing to adapt.
The Rise And Fall (And Rise Again) Of The Ph.D. Rock Star
Just a few years ago, AI Ph.D.s were the ultimate unicorns. Armed with cutting-edge credentials, they were courted by the biggest names in tech and commanded compensation packages that rivaled the budgets of small nations. However, that gilded era is closing. In 2025, companies are less enamored with research for its own sake. They still need the science, but they need practical results more urgently.
The reason for the fretting? As AI tools become commoditized, the field has broadened dramatically. Building production-ready models requires not just academic brilliance but large-scale data engineering, DevOps and specialized workflows. If a company must choose between a Ph.D. focused on theoretical frameworks and a machine learning engineer who can build an operational model by Tuesday, the choice is clear.
Why Ph.D.s Shouldn’t Panic
While there are fewer roles for open-ended research, a Ph.D.’s intellectual horsepower can be harnessed in surprising new directions. Some are rediscovering realms like applied physics or computational biology, both of which can benefit immensely from advanced AI modeling. As entire fields are reinvented with new data-driven approaches, AI Ph.D.s are more essential than ever. The next breakthroughs will be cross-pollinations between scientific domains—like using generative models to simulate quantum effects or optimizing global supply chains. Ph.D.s are essential for these new connections—just with a dash more practicality.
The Data Monarchy That Lost Its Crown
Historically, data analysts had a special seat at the corporate table. They were the only ones who knew where the bodies were buried in those endless rows and columns. Generating sophisticated charts or extracting hidden insights was a form of sorcery few dared to question.
AI-driven tools now serve as the translator between humans and big data. Executives can use natural language to craft queries for everything from sales forecasts to anomaly detection. With insights from an AI agent, they can suss out answers without the wait. For data analysts, proficiency in specialized tools no longer seems so special, and their role of providing pixel-perfect dashboards is gravely threatened.
Why Data Analysts Shouldn’t Fret
Despite their anxiety, data analysts will remain vital in 2025. An AI system is only as good as the data it’s fed and the context in which it operates. Data doesn’t yet organize itself, so analysts can become the “guardians of metadata,” focusing on data integrity, context and regulatory compliance. Moreover, advanced AI systems require continuous auditing and tuning. Somebody has to ensure the analytics pipeline isn’t drifting or that an odd spike in the model output is actually just a glitch in the raw inputs.
So while the “pixel-perfect” aspect of analysts’ jobs might fade, the “data stewardship” role will be indispensable. If you’re an analyst, think of it this way: You’re leveling up from a skilled barista to the master roaster of coffee beans, ensuring everything that comes out is high quality and ready for the business to consume. As a result, companies will find your role as addictive as your output.
Europeans In The Regulatory Straightjacket
Europe has long prided itself on strong data protection and regulatory frameworks. The GDPR set the standard for privacy worldwide. But in 2025, its strict rules may stifle the rapid deployment of next-generation AI solutions. Meanwhile, the U.S. continues to host the largest cloud and chip giants, while China maintains its sprawling AI ecosystem.
Some pundits envision a doomsday scenario where Europe’s regulatory environment, combined with its service-heavy economy, creates an insurmountable drag on innovation. The fear is that AI breakthroughs will happen elsewhere, leaving Europe scrambling to catch up. Factor in labor market protections that complicate restructuring and the continent’s labyrinthine bureaucracy, and Europe faces potent challenges.
Europe’s Silver Lining And Freedom To Flourish
Despite the hurdles, Europe’s emphasis on “responsible AI” could become a hallmark of the next phase of globalization. As AI grows more powerful, there’s increasing pressure to ensure systems are transparent, fair and aligned with human values. Europe’s approach—though sometimes slower in execution—often results in more sustainable and ethically robust solutions. That’s no small feat in a world struggling with deepfakes, algorithmic biases and privacy breaches.
Moreover, strong regulations and an emphasis on safety can be a powerful selling point. Think of an AI-driven medical device that’s labeled “compliant with EU safety standards”—this can become an instant badge of trust in global markets. Europe can also tap into the synergy of multiple countries working together. More than just forming a coalition of EU champions of the cause, this group can form a uniquely powerful “AI Third Front,” echoing the spirit of the Non-Aligned Movement from the Cold War. Such a group could provide an important alternative and counterweight to Silicon Valley and China—the regions that dominate today.
The Blues Are A Passing Phase
The year 2025 is no utopia—AI hasn’t eradicated disease or ended global warming (yet). But nor will it be an apocalypse with armies of jobless humans and unstoppable robots. For AI Ph.D.s, data analysts and European businesses, the changes that have come in today’s “Age of AI” can feel unsettling, even destabilizing. Yet each of these groups has unique strengths and avenues that will allow them to remain highly relevant, and even indispensable, if they ditch the “AI Blues” for their own respective new tunes.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
