Amazon SageMaker AI now supports serverless model customization for the NVIDIA Nemotron 3.5 Lightning model using supervised fine-tuning (SFT), Direct Preference Optimization (DPO), and reinforcement fine-tuning (RFT). This is one of the latest open-weight models from NVIDIA and employs a hybrid Mixture-of-Experts architecture with 3B active parameters and 30B parameters in total. In addition to deploying this model on SageMaker AI, you can now adapt it to your specific domains and workflows.
Model customization enables you to tailor foundation models with your proprietary data so a smaller, right-sized model can match frontier-model quality on your tasks, reducing cost and latency. You can use labeled data with SFT to improve accuracy on domain-specific tasks, preference data with DPO to align outputs with your organization’s tone, or reward signals with RFT to enhance performance on new tasks. With serverless customization, SageMaker AI handles all infrastructure provisioning and training orchestration, so you can focus on your data and evaluation rather than cluster management, and only pay for what you use.
Serverless model customization for NVIDIA Nemotron 3.5 Lightning on SageMaker AI is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland). To get started, navigate to the Models page in Amazon SageMaker Studio to launch a customization job, or use the SageMaker Python SDK for programmatic access. To learn more, see the Amazon SageMaker AI model customization documentation.
Amazon SageMaker AI now supports serverless model customization for the NVIDIA Nemotron 3.5 Lightning model using supervised fine-tuning (SFT), Direct Preference Optimization (DPO), and reinforcement fine-tuning (RFT). This is one of the latest open-weight models from NVIDIA and employs a hybrid Mixture-of-Experts architecture with 3B active parameters and 30B parameters in total. In addition to deploying this model on SageMaker AI, you can now adapt it to your specific domains and workflows.
Model customization enables you to tailor foundation models with your proprietary data so a smaller, right-sized model can match frontier-model quality on your tasks, reducing cost and latency. You can use labeled data with SFT to improve accuracy on domain-specific tasks, preference data with DPO to align outputs with your organization’s tone, or reward signals with RFT to enhance performance on new tasks. With serverless customization, SageMaker AI handles all infrastructure provisioning and training orchestration, so you can focus on your data and evaluation rather than cluster management, and only pay for what you use.
Serverless model customization for NVIDIA Nemotron 3.5 Lightning on SageMaker AI is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and Europe (Ireland). To get started, navigate to the Models page in Amazon SageMaker Studio to launch a customization job, or use the SageMaker Python SDK for programmatic access. To learn more, see the Amazon SageMaker AI model customization documentation.
Amazon Connect Customer now lets managers import a PDF of an evaluation form from a third-party quality management application, and automatically recreates it in Connect using AI, making it easier to migrate an existing quality program into Connect. Instead of rebuilding an existing form question by question, you upload the PDF and choose the preferred scoring method, either percentage or points-based, and Connect Customer automatically extracts the sections, questions, answer options, and scoring into a draft evaluation form. You can also provide natural language instructions to import the form more accurately or to adjust it as it’s created — for example, splitting a broad question into simpler ones — minimizing the manual edits needed before you activate the form.
This feature is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Canada (Central), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Europe (Frankfurt). To learn more, please visit our documentation and our webpage. For information about Amazon Connect Customer pricing, please visit our pricing page.
Amazon Connect Customer now lets managers import a PDF of an evaluation form from a third-party quality management application, and automatically recreates it in Connect using AI, making it easier to migrate an existing quality program into Connect. Instead of rebuilding an existing form question by question, you upload the PDF and choose the preferred scoring method, either percentage or points-based, and Connect Customer automatically extracts the sections, questions, answer options, and scoring into a draft evaluation form. You can also provide natural language instructions to import the form more accurately or to adjust it as it’s created — for example, splitting a broad question into simpler ones — minimizing the manual edits needed before you activate the form.
This feature is available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Canada (Central), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Europe (Frankfurt). To learn more, please visit our documentation and our webpage. For information about Amazon Connect Customer pricing, please visit our pricing page.
AWS Client VPN now supports MacOS 27 Golden Gate client with versions 6.0+ You can now run the AWS supplied VPN client on the latest MacOS versions. AWS Client VPN desktop clients are available free of charge, and can be downloaded here.
AWS Client VPN is a managed service that securely connects your remote workforce to AWS or on-premises networks. It supports desktop clients for MacOS, Windows x64, Windows Arm64 and Ubuntu-Linux. With client version 6.0 onwards, Client VPN now supports the latest MacOS Golden Gate 27.0. It already supports Mac OS version 13.0, 14.0, 15.0, and 26.0, Windows 10 (x64) and Windows 11 (Arm64 and x64), and Ubuntu Linux 22.04 and 24.04 LTS versions. To learn more about Client VPN:
AWS Client VPN now supports MacOS 27 Golden Gate client with versions 6.0+ You can now run the AWS supplied VPN client on the latest MacOS versions. AWS Client VPN desktop clients are available free of charge, and can be downloaded here. AWS Client VPN is a managed service that securely connects your remote workforce to AWS or on-premises networks. It supports desktop clients for MacOS, Windows x64, Windows Arm64 and Ubuntu-Linux. With client version 6.0 onwards, Client VPN now supports the latest MacOS Golden Gate 27.0. It already supports Mac OS version 13.0, 14.0, 15.0, and 26.0, Windows 10 (x64) and Windows 11 (Arm64 and x64), and Ubuntu Linux 22.04 and 24.04 LTS versions. To learn more about Client VPN:
Visit the AWS Client VPN product page
Read the AWS Client VPN documentation
Read the AWS Client VPN user guide
Builders can now sign up for a new simplified experience that makes it faster to turn ideas into running code on AWS. AWS services provide an array of configuration options so that the largest enterprises can customize settings for their distinct needs. Until now, builders with a new project idea had to decide among these options and configure their AWS environment before beginning to build. The new experience reduces setup effort by simplifying sign-up and automatically configuring an initial project with sensible defaults so builders can begin implementing their idea immediately.
When you sign up, you can use your existing Google, GitHub, Apple, or Amazon credentials. For most new customers, no credit card is required and you will receive up to $200 in free credits as part of the AWS Free Tier. Once signup is complete, you can connect your coding agent to AWS with a single prompt that automatically installs the AWS CLI and the Agent Toolkit for AWS. Your coding agent connects to your project and uses built-in guidance to deploy resources using best practices.
As your project expands, you can invite team members to collaborate with you by email. When a team member accepts your invitation, their project access is configured automatically. Similarly, many of the AWS resources you create can access resources in other AWS services automatically because the new IAM role manager capability is enabled for your projects. When you’re ready to upgrade to a paid plan, you can set a monthly spend limit for your project based on your usage patterns so that you stay within your budget. If a project’s usage reaches its spend limit, your project is paused for that month. You can create additional projects with one click, each with its own spend limit and distinct team members. At any time, you can activate advanced features without migration or downtime, enabling you to use additional features such as multiple AWS Regions and custom governance controls.
Builders can now sign up for a new simplified experience that makes it faster to turn ideas into running code on AWS. AWS services provide an array of configuration options so that the largest enterprises can customize settings for their distinct needs. Until now, builders with a new project idea had to decide among these options and configure their AWS environment before beginning to build. The new experience reduces setup effort by simplifying sign-up and automatically configuring an initial project with sensible defaults so builders can begin implementing their idea immediately.
When you sign up, you can use your existing Google, GitHub, Apple, or Amazon credentials. For most new customers, no credit card is required and you will receive up to $200 in free credits as part of the AWS Free Tier. Once signup is complete, you can connect your coding agent to AWS with a single prompt that automatically installs the AWS CLI and the Agent Toolkit for AWS. Your coding agent connects to your project and uses built-in guidance to deploy resources using best practices.
As your project expands, you can invite team members to collaborate with you by email. When a team member accepts your invitation, their project access is configured automatically. Similarly, many of the AWS resources you create can access resources in other AWS services automatically because the new IAM role manager capability is enabled for your projects. When you’re ready to upgrade to a paid plan, you can set a monthly spend limit for your project based on your usage patterns so that you stay within your budget. If a project’s usage reaches its spend limit, your project is paused for that month. You can create additional projects with one click, each with its own spend limit and distinct team members. At any time, you can activate advanced features without migration or downtime, enabling you to use additional features such as multiple AWS Regions and custom governance controls.
To try the new experience, create a new AWS account. To learn more, see AWS reimagines the getting started experience on the AWS News Blog.
Amazon Connect Customer now supports tag-based access control for custom metrics, so you can govern which users and roles can view, create, or modify each custom metric.
As more teams across your organization adopt custom metrics, they end up editing the same shared library. Without controls, one person can change a metric that other teams count on. The usual fix is to give only a handful of people permissions to custom metrics, but that shuts out every other team that wants to start using them.
Now you can tag each metric, then use those tags to set access: a team gets full control of their own metrics, view-only access to another team’s, and no visibility into the metrics you restrict. Search follows the same access rules, so people only see the metrics they’re allowed to view or manage.
Amazon Connect Customer now supports tag-based access control for custom metrics, so you can govern which users and roles can view, create, or modify each custom metric.
As more teams across your organization adopt custom metrics, they end up editing the same shared library. Without controls, one person can change a metric that other teams count on. The usual fix is to give only a handful of people permissions to custom metrics, but that shuts out every other team that wants to start using them.
Now you can tag each metric, then use those tags to set access: a team gets full control of their own metrics, view-only access to another team’s, and no visibility into the metrics you restrict. Search follows the same access rules, so people only see the metrics they’re allowed to view or manage.
Amazon WorkSpaces Personal and Amazon WorkSpaces Core now support Graphics G7 bundles, built on NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs and Intel Xeon 6 processors. Graphics G7 delivers up to 2.1x better performance for graphics-intensive workloads compared to previous generation Graphics G6 bundles. Four bundle sizes are available, ranging from 8 vCPUs, 32 GB of memory, and one GPU up to 48 vCPUs, 192 GB of memory, and two GPUs.
With Graphics G7, you can run demanding professional applications such as CAD/CAM, 3D rendering, scientific visualization, video editing, and AI-assisted design workflows at higher fidelity and frame rates. Each GPU provides 32 GB of GDDR7 memory, enabling larger and more complex 3D scenes and models. Graphics G7 bundles are available with Windows, including bring-your-own-license, and support both AlwaysOn and AutoStop running modes.
Graphics G7 bundles are available for both WorkSpaces Personal and WorkSpaces Core in US East (N. Virginia), US East (Ohio), and US West (Oregon). Additional Regions will be added as availability expands.
Amazon WorkSpaces Personal and Amazon WorkSpaces Core now support Graphics G7 bundles, built on NVIDIA RTX PRO 4500 Blackwell Server Edition GPUs and Intel Xeon 6 processors. Graphics G7 delivers up to 2.1x better performance for graphics-intensive workloads compared to previous generation Graphics G6 bundles. Four bundle sizes are available, ranging from 8 vCPUs, 32 GB of memory, and one GPU up to 48 vCPUs, 192 GB of memory, and two GPUs.
With Graphics G7, you can run demanding professional applications such as CAD/CAM, 3D rendering, scientific visualization, video editing, and AI-assisted design workflows at higher fidelity and frame rates. Each GPU provides 32 GB of GDDR7 memory, enabling larger and more complex 3D scenes and models. Graphics G7 bundles are available with Windows, including bring-your-own-license, and support both AlwaysOn and AutoStop running modes.
Graphics G7 bundles are available for both WorkSpaces Personal and WorkSpaces Core in US East (N. Virginia), US East (Ohio), and US West (Oregon). Additional Regions will be added as availability expands.
To get started, select a Graphics G7 bundle when creating a workspace in the Amazon WorkSpaces console, or through your Workspaces Core partner solution. For more information on available instance types, see WorkSpaces Personal Instance Families. To learn more about G7 GPU capabilities, visit the EC2 G7 Instance Types page. For pricing details, see Amazon WorkSpaces Personal Pricing or Core Bundles Pricing.
AWS Elemental MediaTailor now supports two additional lifecycle hooks for monetization functions: post ad decision server (ADS) response, and pre manifest insertion. MediaTailor is a video service that personalizes and inserts ads into live and on-demand streams. Monetization functions run customer-defined logic at defined points in an ad-personalized playback session, removing the need for a middleware tier between MediaTailor and the ADS.
The post ADS response hook runs after MediaTailor parses an ADS response and resolves all Video Ad Serving Template (VAST) wrappers, before ads are selected and transcoded. Customers use it to call a secondary ad source when the primary ADS returns less demand than the ad break can hold, remove ads that their content or brand policies do not permit, and add house ads or promotions from their own marketing systems. The pre manifest insertion hook runs at the last point before MediaTailor returns the ad pod to the viewer, and receives every newly personalized ad break in a single invocation. Customers use it as a final check on what is about to play, including inserting a personalized slate when a break cannot be filled any other way. Pre-built recipes in the MediaTailor console give customers a starting point for each of these use cases. Both hooks are fail-open: on a timeout, expression error, or resource limit, MediaTailor discards the function output and continues with default ad insertion, so viewer playback is unaffected.
AWS Elemental MediaTailor now supports two additional lifecycle hooks for monetization functions: post ad decision server (ADS) response, and pre manifest insertion. MediaTailor is a video service that personalizes and inserts ads into live and on-demand streams. Monetization functions run customer-defined logic at defined points in an ad-personalized playback session, removing the need for a middleware tier between MediaTailor and the ADS.
The post ADS response hook runs after MediaTailor parses an ADS response and resolves all Video Ad Serving Template (VAST) wrappers, before ads are selected and transcoded. Customers use it to call a secondary ad source when the primary ADS returns less demand than the ad break can hold, remove ads that their content or brand policies do not permit, and add house ads or promotions from their own marketing systems. The pre manifest insertion hook runs at the last point before MediaTailor returns the ad pod to the viewer, and receives every newly personalized ad break in a single invocation. Customers use it as a final check on what is about to play, including inserting a personalized slate when a break cannot be filled any other way. Pre-built recipes in the MediaTailor console give customers a starting point for each of these use cases. Both hooks are fail-open: on a timeout, expression error, or resource limit, MediaTailor discards the function output and continues with default ad insertion, so viewer playback is unaffected.
The new hooks are available in all AWS Regions where AWS Elemental MediaTailor is available. To learn more, see Monetization Functions in the AWS Elemental MediaTailor User Guide and the MediaTailor pricing page. To get started, sign in to the AWS Elemental MediaTailor console.
Amazon Elastic Container Service (Amazon ECS) now supports Amazon S3 Files for tasks running on the Amazon EC2 launch type, enabling customers to connect their containerized applications directly to data in Amazon S3 as a shared file system. With this launch, customers running ECS workloads on EC2 instances can work with their S3 data using standard file system semantics, so file-based applications, AI agents, and data processing workloads run on S3 data with no code changes and without duplicating or staging files first. S3 Files support was previously available for ECS tasks on AWS Fargate and ECS Managed Instances, and now extends to the EC2 launch type, giving customers consistent access to S3 Files across all three ECS launch types.
Amazon S3 Files, built on Amazon EFS, delivers a shared file system that connects AWS compute resources directly with data in Amazon S3, providing full file system semantics and low-latency performance without data leaving S3. S3 Files works with new and existing data in S3 buckets, with no migration required. Customers can mount an Amazon S3 Files volume in their Amazon ECS tasks to read and write data in an S3 bucket using standard file system operations, with no application code changes and no need to copy or stage data.
Amazon S3 Files support is available in all AWS commercial Regions and the AWS GovCloud (US) Regions. To learn more, refer our documentation.
Amazon Elastic Container Service (Amazon ECS) now supports Amazon S3 Files for tasks running on the Amazon EC2 launch type, enabling customers to connect their containerized applications directly to data in Amazon S3 as a shared file system. With this launch, customers running ECS workloads on EC2 instances can work with their S3 data using standard file system semantics, so file-based applications, AI agents, and data processing workloads run on S3 data with no code changes and without duplicating or staging files first. S3 Files support was previously available for ECS tasks on AWS Fargate and ECS Managed Instances, and now extends to the EC2 launch type, giving customers consistent access to S3 Files across all three ECS launch types. Amazon S3 Files, built on Amazon EFS, delivers a shared file system that connects AWS compute resources directly with data in Amazon S3, providing full file system semantics and low-latency performance without data leaving S3. S3 Files works with new and existing data in S3 buckets, with no migration required. Customers can mount an Amazon S3 Files volume in their Amazon ECS tasks to read and write data in an S3 bucket using standard file system operations, with no application code changes and no need to copy or stage data. Amazon S3 Files support is available in all AWS commercial Regions and the AWS GovCloud (US) Regions. To learn more, refer our documentation.
AWS Security Token Service (STS) now enforces a single 4,096-byte size limit on session tokens. Previously, STS enforced separate limits on session token size and passed-in parameters (i.e., inline policies, managed policies, and session tags). STS has removed that separation, providing more flexibility for larger combinations of session policies and session tags.
Additionally, STS now returns response elements indicating session token size and percentage utilization relative to the token size limit. STS logs these values in AWS CloudTrail and publishes corresponding metrics in Amazon CloudWatch. A new optional API parameter also lets you generate larger session tokens (up to the 4,096-byte limit) to test whether your applications and infrastructure can handle them.
These capabilities are available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the AWS European Sovereign Cloud Region.
AWS Security Token Service (STS) now enforces a single 4,096-byte size limit on session tokens. Previously, STS enforced separate limits on session token size and passed-in parameters (i.e., inline policies, managed policies, and session tags). STS has removed that separation, providing more flexibility for larger combinations of session policies and session tags.
Additionally, STS now returns response elements indicating session token size and percentage utilization relative to the token size limit. STS logs these values in AWS CloudTrail and publishes corresponding metrics in Amazon CloudWatch. A new optional API parameter also lets you generate larger session tokens (up to the 4,096-byte limit) to test whether your applications and infrastructure can handle them.
These capabilities are available in all commercial AWS Regions, the AWS GovCloud (US) Regions, and the AWS European Sovereign Cloud Region.
To learn more, please read the AWS Security Blogpost, AWS IAM User Guide, and AWS STS API Reference.
Por: Silvia Candiani, vicepresidenta corporativa, Telecomunicaciones, Medios y Entretenimiento a nivel mundial, Microsoft.
Cada conversación que mantengo hoy con líderes de medios vuelve a una pregunta importante: ¿Cómo convertimos la promesa de la IA en valor empresarial medible? Los medios y el entretenimiento pueden tener más que ganar con la IA que casi cualquier industria, pero se mueven más despacio. Solo se estima que un 10% de su plantilla califica como Frontier Professionals, frente al 16% en diferentes sectores y el 28% en tecnología, según el Informe Anual 2026 del Índice de Tendencias Laborales de Microsoft. Al mismo tiempo, el 51% de los usuarios de IA en medios y entretenimiento ya afirman que producen trabajos que no podrían haber creado hace un año, para subir al 80% entre los Frontier Professionals.
Esa brecha es la oportunidad. Las organizaciones que se mueven ahora pueden convertir la capacidad emergente de IA en una ventaja medible en producción, entrega, compromiso con la audiencia y monetización. Los más destacados no solo usan más IA. Rediseñan el trabajo en torno a las fortalezas complementarias de las personas y la IA, comparten prácticas exitosas y aplican el juicio humano donde la calidad, los derechos, la confianza y la rendición de cuentas más importan.
Esto es lo que hace que el momento sea tan emocionante. La IA puede ayudar a empoderar a equipos creativos y empresariales para ampliar lo posible, mientras las personas aportan la imaginación, la experiencia y la responsabilidad que definen grandes experiencias mediáticas.
Desde asistencia aislada hasta inteligencia orquestada
En Microsoft, a esto lo llamamos orquestación de inteligencia mediática: pasar de la asistencia aislada de IA a flujos de trabajo dirigidos por agentes que conectan personas, datos de confianza y sistemas especializados a lo largo del ciclo de vida de los medios. La seguridad y la gobernanza están integradas desde el principio para que las organizaciones puedan escalar la inteligencia sin sacrificar el control.
Las soluciones puntuales pueden optimizar tareas individuales, pero a menudo atrapan datos, contexto y decisiones dentro de herramientas separadas. La orquestación conecta inversiones existentes, por lo que una visión o acción en una etapa puede mejorar lo que ocurre a continuación. Las señales creativas pueden informar la distribución. El rendimiento operativo puede moldear la experiencia de la audiencia. Los datos de compromiso pueden guiar el contenido y las decisiones comerciales futuras.
Cuando estas conexiones funcionan en toda la organización, el valor se acumula. Cada flujo de trabajo exitoso puede informar al siguiente, para ayudar a los equipos a aprender más rápido, colaborar de manera más eficaz y generar impulso para una transformación más amplia de la IA.
Tres casos de uso Frontier
1. Acelerar la creación y producción de contenido
Los equipos creativos se enfrentan a una demanda creciente de más contenido, más formatos y una adaptación más rápida entre mercados. Cuando se conectan los flujos de trabajo de modelos, datos, infraestructura, derechos y aprobación, la IA puede ampliar su capacidad creativa a lo largo del proceso desde la idea hasta la producción. Galleri5 de Collective Artists Network ilustra el potencial. La empresa informa que sus flujos de trabajo nativos de IA pueden reducir los plazos de producción de películas de alrededor de tres años a tres meses, acelerar el tiempo de lanzamiento al mercado de las series de televisión entre 5 y 10 veces y reducir los costes de producción cinematográfica entre un 60 y un 70% en comparación con los flujos de trabajo tradicionales de VFX y acción real.
Kantar muestra cómo este cambio va más allá de la creación hacia una evaluación rápida a gran escala. Tras reconstruir su plataforma de eficacia creativa Link AI en Azure, Kantar redujo la puntuación publicitaria de una duración de solo una hora a unos pocos minutos y evaluó decenas de miles de anuncios para un cliente global de bebidas en cuestión de horas. El objetivo no es la automatización por sí misma, sino eliminar fricciones para que los equipos puedan producir, probar y perfeccionar más posibilidades creativas mientras la gente se centra en las ideas que hacen que el contenido sea distintivo.
El viejo mundo de pasar meses en un puñado de anuncios ha desaparecido. El nuevo imperativo es crear y evaluar cientos o miles de versiones personalizadas con rapidez para diferentes plataformas digitales.
Ashok Kalidas Ph.D., Científico Jefe de IA, Kantar
2. Entregar contenido de manera fiable a través de todas las plataformas
Las organizaciones mediáticas deben llevar la intención creativa, los derechos, los metadatos y el contexto operativo a través de plataformas de difusión, streaming, digital, social y partners. La inteligencia conectada puede ayudar a los equipos a monitorizar flujos de trabajo, identificar problemas, adaptar las rutas de entrega y actuar más rápido a medida que cambian las condiciones. Sanoma utilizó Azure AI para sustituir una única actualización meteorológica nacional por pronósticos automatizados adaptados a 26 regiones, lo que hizo a la localización escalable a nivel económico, para proporcionar información más oportuna y relevante, y crear nuevas oportunidades para la publicidad local.
En las pruebas de audiencia, el 70% de los encuestados dijo que la voz sintética era muy adecuada para las noticias. Esto demuestra el valor empresarial de la orquestación: mayor resiliencia, consistencia y control, junto con nuevas oportunidades para servir a audiencias y mercados de forma más eficaz. También muestra cómo la innovación puede empoderar a los equipos para escalar experiencias de alta calidad sin crear más complejidad para quienes las gestionan.
3. Aumentar la inteligencia de audiencia y contenido
Conectar contenido, identidad, interacción, publicidad, comercio y señales de derechos puede mejorar el descubrimiento, la retención, las decisiones de campaña, el rendimiento de inventario y las propuestas directas a los fans. La Premier League ha comenzado a reunir más de 30 temporadas de estadísticas, 300.000 artículos, 9.000 vídeos y datos de partidos en directo para impulsar experiencias personalizadas. El Premier League Companion, impulsado por Microsoft Copilot, lleva ese contexto a una base global de aficionados de 1.800 millones de personas en 189 países.
Esta es una de las oportunidades más inspiradoras que se avecinan. Las organizaciones mediáticas pueden transformar archivos extensos y datos en vivo en experiencias más ricas y relevantes, lo que ayuda a las audiencias a conectar más a profundidad con los clubes, historias, creadores y momentos que les importan.
La oportunidad también va más allá de la personalización. Cuando las organizaciones conectan de manera responsable la inteligencia de audiencia y contenido, pueden fortalecer la participación, desbloquear nuevos enfoques de monetización y crear experiencias que continúan con el aprendizaje y mejoran con el tiempo.
En estos escenarios, Microsoft proporciona una capa abierta de orquestación a través de la producción, datos, contenido, distribución, audiencia y entornos empresariales existentes. Las organizaciones pueden conectar contexto y aprendizaje sin reemplazar todos los sistemas especializados que ya impulsan sus operaciones. La infraestructura en la nube, los datos, la IA, la seguridad, la gobernanza, las herramientas de productividad y un amplio ecosistema de socios trabajan juntos como base para flujos de trabajo coordinados a gran escala.
La colaboración es esencial para dar vida a esta base. Al trabajar junto a clientes, socios tecnológicos, creadores y líderes del sector, podemos conectar la experiencia especializada y las inversiones existentes con la innovación de Microsoft Cloud y la IA. Este enfoque colaborativo ayuda a las organizaciones a modernizarse a su propio ritmo, mientras construyen sobre las herramientas, el talento y las relaciones de confianza que ya poseen.
La confianza debe mantenerse central en ese camino. A medida que la IA se integra más a lo largo del ciclo de vida de los medios, la responsabilidad humana, la seguridad, los derechos, la privacidad y las prácticas responsables de IA deben avanzar junto con la innovación.
Esa base importa porque la transformación exitosa de la IA no es un conjunto de pilotos. Es un modelo operativo que puede reutilizar datos y gobernanza confiables, escalar prácticas exitosas, medir resultados a lo largo del ciclo de vida y aprender de forma continua.
Empiecen con un flujo de trabajo prioritario
En IBC 2026, Microsoft mostrará cómo clientes y socios conectan la inteligencia a través de la creación, operaciones, entrega y compromiso con la audiencia. Animo a los líderes a tener en mente un flujo de trabajo de alto valor, identificar dónde los datos y decisiones fragmentados limitan el rendimiento hoy en día y explorar cómo una capa de orquestación abierta y gobernada podría mejorar la velocidad, la resiliencia, el control, los ingresos o el valor de la audiencia.
Empezar con un reto empresarial significativo crea un camino práctico a seguir. Ofrece a los equipos la oportunidad de medir el impacto, aprender de la experiencia y generar la confianza y el impulso necesarios para transformar flujos de trabajo adicionales.
Lo que más me entusiasma es la oportunidad que tenemos por delante. Las organizaciones mediáticas siempre han transformado la manera en que las personas se conectan con las historias, la información, el deporte y el entretenimiento. La IA nos da la oportunidad de hacerlo de formas nuevas, mientras empodera a las personas cuya creatividad y experiencia hacen avanzar la industria.
La innovación y la responsabilidad deben avanzar juntas. Cuando combinamos creatividad humana, datos de confianza, IA y alianzas sólidas, podemos crear experiencias de audiencia más enriquecedoras, desbloquear nuevo valor empresarial y moldear un futuro más dinámico para los medios y el entretenimiento.
