gen‑ai.news
← Back
Multimodal

Adobe Brings Creative Cloud to Gemini Agentic Workflows

Adobe Brings Creative Cloud to Gemini Agentic Workflows

Adobe announced at Google I/O 2026 that it is bringing its Creative Cloud connector to Google Gemini, giving the AI model direct access to Photoshop, Illustrator, Adobe Express, and Premiere. The integration follows the same pattern as a deal Adobe struck with Anthropic several weeks earlier to connect its tools to Claude, suggesting the company is treating agentic AI access as a distribution channel rather than a threat.

The practical workflow being demonstrated involves a user describing a creative brief in conversational terms - a product campaign, a social asset, a video cut - and Gemini then orchestrating the relevant Adobe applications to produce output without the user opening any of the tools directly. Adobe handles the execution layer; the AI model handles interpretation and task routing.

For Adobe, the business logic is straightforward. If people are going to use AI to generate and edit visual content, having that process run through Adobe's tools rather than around them keeps the company inside the workflow and its formats in use. The Creative Cloud connector architecture also means Adobe can potentially charge for API access to its tools in addition to existing subscriptions.

The integration is aimed primarily at business users and small creative teams rather than professional designers, who are more likely to want direct control over the applications. Whether the output quality from AI-orchestrated Photoshop or Premiere is comparable to what a skilled user would produce manually is not yet clear from the announced details - that will depend on how well Gemini interprets creative intent and how granular the Adobe API access actually is.

Enjoy this story? Get the next one in your inbox.

Twice a week: the most important stories in generative image and video AI, distilled into a 2-minute read.

Free. Unsubscribe any time. No spam, ever.

Your next read

No image
Multimodal

Fine-tune video and image models at scale with NVIDIA NeMo Automodel and 🤗 Diffusers

NVIDIA and Hugging Face have joined forces to bring large-scale fine-tuning of image and video diffusion models into the NeMo Automodel framework, integrated with the Diffusers library. The collaboration aims to make distributed training more accessible for teams working with models that would otherwise be difficult to fine-tune on limited hardware. The result is a more streamlined path from a pretrained diffusion model to a customized one, without requiring deep infrastructure expertise.

No image
Multimodal

Thinking Machines Lab Releases Inkling: A 975B-Parameter Open-Weights Multimodal MoE With 41B Active Parameters And Controllable Thinking Effort

Thinking Machines Lab has released Inkling, a 975B-parameter open-weights multimodal model built on a Mixture-of-Experts architecture that keeps only 41B parameters active at any given time. Licensed under Apache 2.0, it accepts text, image, and audio inputs and offers a 1M-token context window. Rather than competing for top benchmark rankings, the model is positioned as a customizable base with adjustable reasoning depth.