For generations, formal education has been designed so that we learn to work. People go to school, acquire knowledge and skills, and then apply for jobs where that knowledge and skill can be applied. People learn so that they can work. This model motivated generations of individuals to become teachers, engineers, nurses, business leaders, and accountants during the twentieth century. However, the learn-to-work model has been losing its appeal for decades. Consider the possibility that this steep decline is not because any particular generation or segment of the population is addicted to social media, lazy or fragile. Consider instead that it is because our system of education (cradle-to-grave) is producing exactly what it was designed to produce. It was not designed to appeal to every person. It was not designed to serve every segment of the population. It was designed to rank and sort.

Generative AI, sometimes called gen AI, is artificial intelligence (AI) that can create original content—such as text, images, video, audio or software code—in response to a user’s prompt or request.

Generative AI relies on sophisticated machine learning models called deep learning models—algorithms that simulate the learning and decision-making processes of the human brain. These models work by identifying and encoding the patterns and relationships in huge amounts of data, and then using that information to understand users' natural language requests or questions and respond with relevant new content.

Artificial Intelligence (AI) represents a once-in-a-lifetime change management opportunity that might decide who wins and loses across every industry. As the AI era takes shape through digital transformation initiatives, executives and employees alike are contemplating how it affects employment and the skills needed to stay ahead. This is where AI upskilling and reskilling come into play.

ChatGPT is by far the most widely recognized generative AI product – around 50% of the online population in the six countries surveyed have heard of it. It is also by far the most widely used generative AI tool in the six countries surveyed. That being said, frequent use of ChatGPT is rare, with just 1% using it on a daily basis in Japan, rising to 2% in France and the UK, and 7% in the USA. Many of those who say they have used Generative AI have used it just once or twice, and it is yet to become part of people’s routine Internet use.

Remote Work was far from the norm before 2020 and now, thanks to the pandemic pushing millions of people to figure out how to work from home, it’s much more common. Hybrid work has grown in popularity as workers want the best of both worlds, to have the freedom remote work offers as well as the social interactions from working in the office with coworkers.

Now that society is four years out from the beginning days of the pandemic, how many people are still working fully remote or hybrid work from home jobs? Read on to find the answer, along with a plethora of interesting and eye-opening facts and statistics about remote work in America and beyond.

La IA ha ido evolucionado hacia redes neuronales autoajustables que pueden identificar patrones y predecir comportamientos sin necesidad de que intervenga el ser humano. Las ingentes cantidades de datos externos recopilados de clientes y empresas de la competencia permiten identificar las tendencias y necesidades futuras, lo que ha hecho que la innovación pase de ser un proceso lento y costoso obstaculizado por los límites de la capacidad humana a convertirse en un flujo de información en constante evolución al que es posible acceder usando lenguaje natural mediante interfaces como Alexa. 

Este conocimiento, que es invisible a simple vista, podría transformar la innovación abierta. Para que haya innovación, es necesario conectar la información de nuevas formas y, gracias a la innovación abierta alimentada por IA, los directivos pueden hacerlo de modo constante. Permite ampliar y complementar las prácticas humanas y los procesos de innovación convencionales, generar ideas, lanzar nuevos productos y procesos y, en última instancia, acelerar la innovación.  

El metaverso empresarial está formado por las plataformas de metaverso y sus aplicaciones que desbloquean nuevas oportunidades para las empresas. Combina las diversas tecnologías utilizadas en entornos de metaverso, desde la realidad extendida y la IA hasta el IoT, para ayudar a las empresas a lograr una variedad de objetivos.

Las empresas pueden crear sus propios ecosistemas de metaverso, diseñados para todo, desde la colaboración inmersiva y el trabajo remoto, hasta el desarrollo de productos y la ingeniería. En comparación con el metaverso de consumo, el metaverso empresarial aún se encuentra en sus primeras etapas. Sin embargo, muchos proveedores líderes en el mercado están comenzando a reconocer las oportunidades en este paisaje.

• ¿Cuántos puestos de trabajo que hay hoy en España cree que serán sustituidos por el trabajo de robots u ordenadores dentro de 15 años?. El 62% de los trabajadores contesta “la mayoría”. Sin embargo, cuando se pregunta por el efecto de la robotización en su propio empleo.
• ¿Cree que su trabajo actual podría ser realizado por un robot en los próximos 15 años? Casi la mitad (47%) están tranquilos. Contestan “no, de ninguna manera”, además de un 38% que considera su puesto solo parcialmente automatizable.

Creating high quality content — an eye-catching logo, an e-commerce site, paid advertising or compelling social media content — typically involved a production journey that few would call quick, efficient or inexpensive.

Faced with increasing pressure to work more resourcefully, decision-makers are now embracing A.I. and generative A.I. in the quest to transform marketing content development and help offer more personalized, relevant content experiences at scale while keeping schedules in check. Imagine a world where marketers and creatives can focus less on rote tasks, such as re-sizing images or generating boilerplate copy, and do more of what they love — designing and building experiences that delight customers across every digital touchpoint — all with ease.

In the fast-evolving landscape of artificial intelligence, two concepts often spark vigorous debate among tech enthusiasts: Generative AI and Artificial General Intelligence (AGI). While both promise to revolutionize our interaction with machines, they serve fundamentally different functions and embody distinct potential futures. Let's dive into these differences and explore what each form of AI means for tomorrow.

In an era where AI is reshaping the boundaries of what machines can do, we find ourselves at a pivotal moment in history. AI isn’t just a technological upgrade; it's a mirror reflecting our potential to evolve as a species. As these intelligent systems take over routine and repetitive tasks, they challenge us to delve deeper into what makes us uniquely human: our creativity, empathy, and the ability to navigate complex social dynamics. Let’s explore why the rise of AI might actually be the best thing to push humanity towards realizing its full potential.

Los datos de nuestra encuesta muestran el creciente optimismo y la confianza en la IA. Al profundizar en las tendencias de inversión, observamos que las empresas están recalibrando sus carteras de inversión y priorizando el edge computing y las nubes públicas y privadas. Cabe destacar que las empresas están volviendo a enfocar sus presupuestos en la modernización de aplicaciones y la migración a la nube, al tiempo que reducen las inversiones en infraestructura de servidores y hardware.

En 2024, las expectativas y la realidad convergen para la IA. Aunque la IA ha acelerado considerablemente la innovación y ha mejorado los procesos de toma de decisiones, no siempre los aumentos de productividad y de ventas previstos se materializaron. Nuestra investigación explora la tracción de los casos de uso de la IA, los desafíos para medir el retorno de la inversión (ROI) y el incipiente pero crítico dominio de la gobernanza de la IA.

En el uso de la nube, un cambio hacia la infraestructura de nube privada es claro, mientras que las organizaciones lidian con las complejidades de la migración a la nube, los recursos limitados y las preocupaciones relacionadas con la seguridad. Un análisis comparativo del ROI de las nubes privadas frente a las públicas revela una creciente inclinación hacia las soluciones de nube híbrida. Combinan la escalabilidad y la rentabilidad de las nubes públicas con la seguridad y el control optimizados de las nubes privadas, al ofrecer un enfoque flexible y mejorado para satisfacer diversas necesidades comerciales.

La escasez de talento presenta su propio conjunto de desafíos, en particular en los sectores de IA y tecnología. Las organizaciones se enfrentan a las dificultades de contratar profesionales con experiencia en un mercado en el que la demanda supera a
la experiencia. Este informe explora estrategias para abordar estas deficiencias, y hace hincapié en la importancia de la mejora de habilidades y las opciones tecnológicas inteligentes para ampliar la reserva de talento.

A new report from the Georgetown Center on Education and the Workforce found a “great misalignment” between projected job demand in many local labor markets and the mix of credentials available to workers seeking jobs requiring more than a high school diploma but less than a bachelor’s degree.

Automation is the application of technology, programs, robotics or processes to achieve outcomes with minimal human input.

Automation is becoming increasingly ubiquitous in the modern world and has countless applications, including: enterprise applications such as business process automation (BPA), AIOps, and enterprise automation, industrial automation applications such as robotics used in automotive manufacturing, and consumer applications such as home automation.

• Coworking spaces offer a diverse and dynamic environment that facilitates networking and community-building opportunities.
• These spaces provide flexible membership models along with high-quality amenities and infrastructure, such as high-speed internet, modern office equipment, meeting rooms, and additional amenities.
• Coworking spaces are cost-effective due to shared resources, and they offer significant psychological benefits by combating isolation and enhancing motivation, thereby contributing to overall professional and personal well-being.

La Oficina de Marcas y Patentes de los Estados Unidos (USPTO) ha publicado una nueva guía para invenciones asistidas por inteligencia artificial (IA).

Las invenciones asistidas por IA no son categóricamente no-patentables; sin embargo, el análisis debería centrarse en el alcance de las contribuciones humanas.

La inteligencia artificial (IA) ha dejado de ser una mera promesa futurista para convertirse en una realidad presente que redefine la manera en que las organizaciones operan y toman decisiones. La adopción de IA puede parecer un desafío monumental, pero con el enfoque adecuado, puede transformar cualquier negocio en una entidad más eficiente, innovadora y competitiva. Aquí es donde entra en juego el Modelo AVANZA.

El Modelo AVANZA es un marco integral que diseñé para guiar a las organizaciones a través de un proceso estructurado y seguro para la adopción de la inteligencia artificial. Este modelo aborda los desafíos específicos y maximiza las oportunidades que presenta la IA, asegurando una implementación exitosa y sostenida.

In an era where artificial intelligence (AI) features prominently in both our daily lives and our collective imagination, it's common to hear concerns about these systems gaining too much power or even becoming autonomous rulers of our future. Yet, a closer look at the current state of AI technology reveals that these fears, while popular in science fiction, are far from being realized in the real world. Here's why we're not on the brink of an AI takeover.

In today's digital era, Artificial Intelligence (AI) has emerged as a transformative force across diverse sectors. It promises not only heightened efficiencies and personalized customer experiences but also innovative solutions to longstanding challenges.

However, despite its considerable potential, numerous organizations struggle to effectively adopt and integrate AI technologies. This article explores 11 prevalent obstacles that impede companies from harnessing AI's full power and offers practical strategies to overcome these hurdles, paving the way for successful implementation and integration.

The advent of artificial intelligence (AI) is going to change the world. While AI has not yet disrupted all businesses, the road that leads to a fundamentally reshaped workplace is short and in sight.

Understandably so, there are questions, fears, and apprehensions about what this means for employees within an organization that might be looking to adopt various AI technologies. The most important thing to remember as we navigate this new wave is that humans are adaptable.