AI Technology Archives - Página 4 de 14

ESG en la práctica: cómo convertir la sostenibilidad en inteligencia empresarial

En la última década, la sostenibilidad ha pasado de ser un aspecto secundario de la reputación corporativa a convertirse en un elemento central del rendimiento empresarial. El nuevo libro electrónico de Artefact, «ESG in Action: Cómo integrar los criterios ambientales, sociales y de gobernanza (ESG) data en inteligencia empresarial, documenta esta transición a través de entrevistas semiestructuradas con altos directivos de empresas globales como Accor, Legrand, Tarkett, Ardian, Heineken, Siplec y Schenker, así como de las perspectivas de la OCDE y de los expertos en sostenibilidad y data de Artefact.

¿Dependerá el futuro de Agentic AI de los grafos de conocimiento?

A medida que las empresas se apresuran a poner en marcha el modelo AI, la mayoría descubre que su infraestructura data nunca se diseñó para el razonamiento autónomo. Hoy en día, hasta el 80 % del tiempo de implementación de AI se dedica a la gestión de data y a la alineación de esquemas, un síntoma de que las infraestructuras se construyeron para el almacenamiento, no para la comprensión. Sin una base que capte las relaciones y el significado, los agentes seguirán siendo potentes, pero ciegos. A medida que los agentes AI se convierten en participantes activos en los flujos de trabajo empresariales, la naturaleza y la escala de las consultas data están evolucionando.

Definición de la estrategia AI en los sectores de la energía y la industria

Durante los últimos 18 meses, el 'Generative AI' ha acaparado todas las reuniones estratégicas de los altos directivos. Pero, ¿y si ese tema ya ha quedado obsoleto? En los sectores de la energía y la industria, el debate está pasando rápidamente del «Generative AI» al «Agentic AI». No se trata solo de una actualización incremental, sino de un nuevo paradigma que pasa de limitarse a mejorar las tareas a reinventar por completo los procesos industriales fundamentales.

AI: Anuncios controlados: el futuro de la publicidad

Cuando OpenAI presentó Atlas, su nuevo navegador basado en ChatGPT, no se limitó a lanzar otro producto. Abrió una puerta que conduce a la próxima era de la interacción entre humanos y ordenadores y, inevitablemente, a una nueva frontera para la publicidad.

Data: Plataformas para la era de la agencia

La mayoría de las empresas no están preparadas para sustituir una pila de data de la era de los paneles de control por una pila de AI. El último informe «State of Data & Analytics» de Salesforce indica que el 84% de los responsables de data y análisis afirman que sus estrategias requieren una revisión completa antes de que las ambiciones en materia de AI puedan tener éxito. Los líderes estiman que el 26,1 % de su data no es fiable, solo el 43,1 % cuenta con marcos formales de data governance y alrededor del 50,1 % no confía en su capacidad para generar y ofrecer información oportuna. Al mismo tiempo, el 70 % cree que los insights más valiosos se encuentran en datos no estructurados. La conclusión es clara: el obstáculo no es el entusiasmo, sino los cimientos, y esos cimientos deben cambiar antes de que los sistemas de agencia puedan escalar.

Enriquecer la experiencia del bricolaje: cómo ADEO utiliza AI para conectar contenidos y conocimientos

Assortment optimization is a critical process in retail that involves curating the ideal mix of products to meet consumer demand while taking into account the many logistics constraints involved. The retailers need to make sure that they offer the right products, in the right quantities, at the right time. By leveraging data and consumer insights, retailers can make informed decisions on which items to stock, how to manage inventory, and what products to prioritize based on customer preferences, seasonal trends, and sales patterns.

MotherDuck al detalle: cómo encaja la solución de análisis y AI de última generación en tu entorno Data

MotherDuck extends DuckDB's analytical performance to the cloud with collaborative features, delivering 4x faster performance than BigQuery and cost savings over traditional data warehouses through serverless, pay-per-use pricing. Following the announcement of MotherDuck’s new European cloud region, we were impressed by its performance and attractive pricing. MotherDuck can already be integrated into your gold layers in order to accelerate the serving of data use cases while saving costs at the same time. See performance benchmark.

Cómo está cambiando AI el mundo de las búsquedas y qué significa esto para los clientes, los profesionales del marketing y las marcas

AI is transforming search, shifting it from ranking and retrieval towards reasoning and synthesis. This whitepaper charts this evolution, explains the mechanics of large language models (LLMs), and sets out the implications for marketers and brands. At the center of the new measurement landscape is the golden triangle of MROI: Marketing mix modeling (MMM) provides the strategic view, quantifying the impact of marketing on sales and offering optimizers and simulators to guide budget allocation.Incrementality testing validates whether campaigns truly drive additional outcomes, using test-versus-control experiments to establish causality. It also calibrates both MMM and attribution models.Attribution informs in-flight optimization by assigning credit across customer journeys. In 2025, advanced models use deep learning and attention mechanisms to capture channel interactions more effectively.These methodologies are most powerful when used together: MMM for long-term planning, incrementality for ground truth, and attribution for real-time agility. Companies also face the decision of in-housing vs. SaaS solutions. In-housing brings customization and control but requires talent and investment, while SaaS offers speed and expertise. The right choice depends on resources and data maturity. Real-world examples highlight best practices: Google’s Meridian introduces an open-source MMM toolkit to improve calibration, upper-funnel measurement, and bias correction.Accor uses incrementality testing to question assumptions and optimize budget allocation.Nike demonstrates the power of persistence and cultural change, embedding measurement into processes and democratizing insights.Artefact stresses the 95-5 rule, showing how brand equity measurement links long-term growth with short-term performance efficiency.Looking forward, five trends will shape measurement: improved data quality, new frameworks for retail media and connected TV, in-housed MMM with testing, privacy-first approaches, and attention-based metrics. The conclusion is clear: marketing measurement is now a strategic enabler. By integrating methodologies, embedding them in culture, and focusing on both performance and brand, CMOs can defend their budgets and unlock sustainable growth.

Guía para la Alta Dirección sobre Medición de Marketing en 2025

In 2025, marketing measurement has become a top priority for the C-suite. While generative AI is transforming campaign execution, measurement is what proves value and secures budgets. Yet maturity remains low: most CMOs still struggle to dynamically adjust spend based on performance. The challenge lies in balancing brand and performance marketing, coping with fragmented data, and aligning decisions across strategic and operational levels. At the center of the new measurement landscape is the golden triangle of MROI: Marketing mix modeling (MMM) provides the strategic view, quantifying the impact of marketing on sales and offering optimizers and simulators to guide budget allocation.Incrementality testing validates whether campaigns truly drive additional outcomes, using test-versus-control experiments to establish causality. It also calibrates both MMM and attribution models.Attribution informs in-flight optimization by assigning credit across customer journeys. In 2025, advanced models use deep learning and attention mechanisms to capture channel interactions more effectively.These methodologies are most powerful when used together: MMM for long-term planning, incrementality for ground truth, and attribution for real-time agility. Companies also face the decision of in-housing vs. SaaS solutions. In-housing brings customization and control but requires talent and investment, while SaaS offers speed and expertise. The right choice depends on resources and data maturity. Real-world examples highlight best practices: Google’s Meridian introduces an open-source MMM toolkit to improve calibration, upper-funnel measurement, and bias correction.Accor uses incrementality testing to question assumptions and optimize budget allocation.Nike demonstrates the power of persistence and cultural change, embedding measurement into processes and democratizing insights.Artefact stresses the 95-5 rule, showing how brand equity measurement links long-term growth with short-term performance efficiency.Looking forward, five trends will shape measurement: improved data quality, new frameworks for retail media and connected TV, in-housed MMM with testing, privacy-first approaches, and attention-based metrics. The conclusion is clear: marketing measurement is now a strategic enabler. By integrating methodologies, embedding them in culture, and focusing on both performance and brand, CMOs can defend their budgets and unlock sustainable growth.

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