Data & AI Trends for 2026

nts in AI models, particularly in coding assistance and AI agents. Andreas Horn notes the impressive progress in tools like Cloud Code and Lovable Base 44, which have significantly improved code generation capabilities. "It's just mind-boggling," he says, emphasizing the transformative potential of these tools. The discussion also touches on the competition among major players like OpenAI, Google, and emerging open-source models, which drives continuous innovation and improvement.

Data Governance and AI Strategy

Data governance emerges as a critical theme, with Andreas Horn stressing the importance of establishing a solid data strategy before starting AI implementation. He advises companies to focus on organizing their data and identifying high-impact use cases to ensure a successful AI strategy. "Start small and scale up," he recommends, highlighting the need for a structured approach to integrating AI into business operations. This sentiment is echoed by Alex Pentland, who emphasizes the necessity of breaking down data silos to enable effective AI deployment.

AI Investment and Hype

The panel explores the current hype surrounding AI investments, with Piyanka Jain expressing frustration over misinformation and exaggerated claims. She emphasizes the importance of critical thinking and discerning the real potential of AI applications. "There's so much nonsense being published," she laments, urging professionals to focus on genuine opportunities rather than getting caught up in the hype. The discussion also touches on the potential for AI to replace inefficient systems, offering both challenges and opportunities for businesses.

Skills for the AI Era

As AI continues to evolve, the panelists highlight the skills necessary for thriving in this new environment. Piyanka Jain advocates for active learning and critical thinking, encouraging individuals to build and experiment with AI tools. "The future of the world is not passive learning," she asserts, emphasizing the need for hands-on experience. Andreas Horn adds that understanding how to use AI effectively is just as important as technical expertise, noting that even AI developers are still figuring out the best applications for their creations.