Muitos líderes de marketing enfrentam o mesmo paradoxo: apesar dos grandes investimentos no Generative AI, o impacto esperado nos custos, na velocidade e no desempenho não está se materializando. Por quê? Porque a maior parte do AI apenas “pensa”, não age. O AI autêntico muda isso.
For the last 18 months, 'Generative AI' has dominated every C-level strategy session. But what if that's already the old conversation? In the energy and industry sectors, the discussion is rapidly shifting from GenAI to Agentic AI. This isn't just an incremental update; it's a new paradigm, one that moves from simply augmenting tasks to completely reinventing core industrial processes.
Quando a OpenAI anunciou o Atlas, seu novo navegador com tecnologia ChatGPT, ela não lançou apenas mais um produto. Ele abriu uma porta que leva à próxima era da interação humano-computador e, inevitavelmente, a uma nova fronteira para a publicidade.
Most companies are not ready to replace a dashboard era data stack with an AI stack. Salesforce's latest State of Data & Analytics indicates that 84% of data and analytics leaders say their strategies require a complete overhaul before AI ambitions can succeed. Leaders estimate that 26% of their data is untrustworthy, only 43% report formal data governance frameworks, and around 50% are not confident in their ability to generate and deliver timely insights. At the same time 70% believe the most valuable insights are locked in unstructured data. The conclusion is straightforward: the obstacle is not enthusiasm but foundation, and that foundation must change before agentic systems can scale.
Os varejistas operam em um ambiente competitivo e dinâmico, enfrentando desafios que vão desde a sensibilidade aos preços até a logística complexa. Para prosperar, eles precisam adotar soluções inovadoras que simplifiquem as operações e aumentem a satisfação do cliente. Este artigo explora como os agentes AI - sistemas autônomos que observam, raciocinam e agem - estão redefinindo o varejo e posicionando o setor para seu próximo nível de competitividade.
For two decades, Master Data Management (MDM) gave organizations a single source of truth for customers, products, and suppliers so analytics and operations could run on clean, governed data.
When a leading global commodity trading company sought to accelerate its AI transformation, it turned to Artefact to turn potential into measurable performance. The goal was to make generative AI a daily productivity tool across departments while ensuring robust governance, compliance, and lasting cultural change.
Every decade or so, the way companies organize themselves quietly changes – not through grand announcements, but through a series of accumulated decisions that suddenly reveal a new pattern. We saw it with digital transformation in the 2000s, when data and connectivity became the fabric of the modern enterprise. Then came the agile revolution, which redefined how teams collaborate, iterate, and deliver value. Each shift didn’t just alter tools or processes—it changed what we believed possible about work itself.
At Artefact, we have designed a proven methodology to help corporations move from exploration to sustainable impact. This article explains the journey, the challenges, and the pragmatic steps to success.
