One session to watch out for at Adobe’s annual Summit is the conversation between Shatanu Narayen, Chair and Chief Executive Officer, Adobe, and Jensen Huang, Founder and Chief Executive Officer, Nvidia. The 2026 edition has more than lived up to expectation.
There was enough substance in the conversation between Narayen and Huang to satisfy any technologist in the room. There was also enough wit to remind the audience that even two of the world’s most influential technology leaders can still make a stage feel conversational. That balance made the dialogue stand out. It was not merely a discussion on artificial intelligence. It was a glimpse into how two long-time industry peers see the next computing shift taking shape, and how they see it touching creativity, software, marketing, business operations and the physical world itself.
Narayen opened in a way that immediately set the tone, teasing Huang’s familiar black leather jacket and recalling an old dinner from years ago. Huang, in turn, leaned into the humour. The exchange was light, but it also carried the comfort of two leaders who have watched not only each other’s companies evolve, but also the wider technology industry transform several times over.
That ease made the larger points land better. And the larger points were significant.
From Software To The Physical World
A key theme of the conversation was Huang’s view that AI is now moving decisively beyond text and images into the physical world. He framed this as the next frontier for computing, arguing that some of the biggest industries in the world, from manufacturing and transportation to logistics and life sciences, can only truly benefit when computers are able to understand physical environments.
That, in his telling, is where physical AI and robotics begin to matter at scale. If language can be converted into images, and images into language, then the next step is to move from language into action, and from visual input into action. In other words, computing is becoming capable not just of understanding or generating, but of acting in relation to the real world.
This is where the conversation became especially relevant for enterprise leaders. The implication was clear: AI’s future is not confined to chat interfaces or productivity assistants. It is increasingly about connecting intelligence to systems, objects and environments in ways that make industries more responsive and more automated.
Narayen used that as a bridge to the idea that every physical object may eventually have a digital representation. Huang’s response was one of the most compelling parts of the discussion. For him, a product cannot be reduced to an approximation. A forest can be approximate. A mountain can be approximate. But a product, a brand asset, a car, a bottle or a person in a commercial context must begin with precision. That is where the digital twin comes in.
Precision First, Personalisation Next
Huang’s articulation of digital twins was especially striking because it connected engineering precision with marketing relevance. He argued that any meaningful digital representation must be truthful and high fidelity at its core. Only then can generative AI build on top of it, adapting or placing it in different environments without compromising brand identity or design integrity.
That is a useful way to understand where Adobe and Nvidia’s worlds increasingly intersect. The conversation suggested that the future of creative and marketing workflows will rest not merely on content generation, but on structured, precise digital assets that can be activated intelligently across channels and contexts.
For a larger tech audience, that matters because it pushes the AI discussion beyond novelty. It points instead to infrastructure, workflows and systems. It is one thing to generate content. It is another to build an enterprise pipeline where brand-perfect assets can be used repeatedly, accurately and at scale.
This was also where the humour continued to do useful work. When Huang joked that he was glad a software licensing deal had been negotiated before the rise of agents because tool usage inside Nvidia was going to skyrocket, he was making a serious point under the laughter. AI agents, as he sees them, will not diminish the value of software tools. They will dramatically increase how often and how deeply people use them.
The New Interface To Software
Perhaps the clearest business takeaway from the exchange was Huang’s argument that agentic AI is becoming the new interface to software. His point was not that traditional tools disappear, but that they become more accessible, more expressive and more powerful when paired with systems that understand user intent.
That is a particularly important idea for enterprise software. Huang described AI not simply as another feature layer, but as a new way of using tools that already exist. Instead of relying solely on menus, commands and point-and-click workflows, users will increasingly work through intelligent systems that can interpret intention and unlock more of a tool’s capability.
For creators, he suggested, this should be seen as elevation rather than replacement. For enterprises, it signals a redesign of how software is used and what productivity might look like in practice.
Narayen reinforced that belief by speaking of AI as something that amplifies human ingenuity. That line, in many ways, sat at the heart of the conversation. The tone throughout was not one of technological determinism. It was one of expansion.
Why AI Could Make People Busier, Not Smaller
One of Huang’s most persuasive arguments came when he addressed the fear that AI will simply erase jobs. His example from radiology was telling. Even as AI became central to reading scans, the demand for radiologists did not collapse. It rose. The reason, he argued, is that the task and the purpose of a profession are not the same thing. Once AI speeds up tasks, people are often able to do more of the higher-order work around them.
He extended that logic to software engineering, saying Nvidia’s engineers are already fully supported by agents and are busier than ever because experimentation and iteration are happening much faster. More ideas can be tested. More problems can be tackled. More work gets done.
That same logic applies to marketing and creative operations. Narayen summed it up neatly when he suggested that instead of one campaign, teams may now create hundreds. Scale is not just increasing output. It is changing ambition.
Huang’s broader point was even sharper: AI becomes valuable when it produces work. Not when it merely knows things, but when it collaborates, supports and acts in ways that create tangible outcomes.
A Conversation With Warmth And Weight
What made the dialogue memorable was not only the content, but the manner in which it was delivered. Narayen and Huang did not speak like executives reciting a scripted future. They sounded like two leaders who have spent decades building through multiple waves of computing and who can now see another one arriving with unusual clarity.
There was banter, yes. There were jokes about jackets, dinners, licences and who was in charge. But there was also a serious shared message underneath it all: AI is moving from possibility to utility, from experimentation to operations, and from digital abstraction into the physical, creative and commercial fabric of business itself.
That is what gave the conversation its edge. It entertained the room, but it also left behind a workable blueprint for how enterprises should think about what comes next.
The journalist attended Adobe Summit 2026 in Las Vegas at Adobe’s invitation |
