AI Agents are revolutionizing commercial operations by automating tasks, enhancing customer relationships, and providing actionable insights. From boosting salesforce efficiency to optimizing pricing strategies, these intelligent systems help businesses achieve measurable growth and competitive advantage.
Artefact, in partnership with Societe Generale and Sorbonne University, presents a new AI approach to identify atypical customer profiles. Tested on real banking data, this open-source algorithm improves scoring accuracy while ensuring interpretability and practical applicability.
In the evolving landscape of enterprise AI, the rise of agentic systems marks a pivotal shift. AI agents are autonomous applications powered by large language models (LLMs) capable of reasoning, memory, and action. They are no longer passive responders to user input; they are active decision-makers influencing business processes in real time. But with autonomy comes risk, and with risk comes the need for structured supervision. In this new paradigm, supervision of tech systems is no longer optional, it is foundational.
As search progressively shifts toward conversational engines such as ChatGPT, Gemini, Le Chat, Claude or Perplexity, brands must fundamentally rethink how they exist online. Visibility becomes central: it is no longer about pleasing Google’s algorithms but about appearing within generated, synthesized, and contextualized answers.
Sidney Zeder is Director of Data & AI Consulting at Artefact. She works in the practice dedicated to the travel, tourism and transport sector in Europe, supporting major industry players across the entire data value chain, from strategy to operational activation.
In today’s data-driven companies, analytics & reporting - through dashboards are expected to deliver fast, actionable insights that support critical business decisions. Yet, according to a 2022 Forrester study, 60% of analytics initiatives fail to meet expectations because often the data feeding those dashboards is unreliable, incomplete, or misaligned (Forrester, 2022).
The artificial intelligence market is on an explosive growth trajectory – GlobalData forecasts it will reach $909 billion by 2030, up from about $100 billion in 2022, driven mainly by the rise of generative AI. This category of AI, exemplified by popular tools like ChatGPT, DeepSeek, Google Gemini, etc. has sparked widespread innovation by enabling businesses to generate original content and automate complex tasks. Companies in the MENA region are rapidly adopting generative AI, aiming to harness its potential for significant productivity gains, deeper personalization, and innovative customer experiences, while also confronting the critical need for responsible and ethical deployment.
Generative AI has compressed delivery times: what took eight hours now takes three. But where do the remaining five hours go?
Something subtle but seismic is happening in enterprise software. For years, SaaS thrived on UX—well-crafted interfaces designed to guide humans through increasingly complex workflows.
