As we enter 2025, artificial intelligence (AI) is transitioning from experimental research to real-world applications across industries. Below is a deeper dive into the critical trends shaping AI’s future, supported by relevant statistics and consumer-focused insights.
If your boss asks you for a critical number, and you use your company’s “Ultra Secure Internal GPT” to retrieve the information—only for the result to be incorrect—whose fault is it? The answer, as we all know, is yours for failing to validate the output. This creates a paradox: while companies push AI to accelerate decision-making, they place ultimate responsibility for AI-driven outcomes on humans. The question then becomes: What is the sweet spot between AI autonomy and human oversight?
Vincent shared positive outcomes on the benefits of generative AI boosting employee productivity and enhancing collaboration, with 92% of users reporting satisfaction.
Artefact, a European leader in data and AI, and Odoxa, an independent research institute, have published a pioneering study on the impact of artificial intelligence on the world of work.
CDP World was particularly exciting this year mainly because a huge theme of the event was around maximizing the potential of AI and GenAI in the CDP.
In a context where technological innovation is redefining standards of performance and efficiency, BNP Paribas' "AI for Efficiency" program, developed in collaboration with Artefact, stands out as an ambitious model for transforming commercial banking through artificial intelligence. This project demonstrates how a structured, value-driven approach can not only optimize processes but also address the challenges of an ever-evolving industry.
Since its explosive emergence in mid-2022, generative AI has quickly captured global attention. What initially centered on the language modality has since expanded into exciting new avenues, including image, audio, and video models. Early in 2023, speculation about the technology's potential impact on businesses across various industries grew, accompanied by exciting early adoption cases. As more developers began building solutions with these models, the general perception shifted toward the continuous emergence of newer, larger, and hopefully better versions of the most widely used models.
With market data costs soaring—some firms reporting increases of up to 50%—controlling these expenses has become a strategic priority for financial services organizations.
In today's data-driven world, understanding the journey of data—from its origin to its final destination—is more crucial than ever. This capability, referred to as data lineage, provides a comprehensive view of how data flows through an organization, detailing its transformations and dependencies along the way.
