It’s pretty clear now that the LLMs and generative AI we are currently working with aren’t the birth of Skynet, and the battle against the machines isn’t just around the corner. But that doesn’t mean entrusting AI too much won’t mean Armageddon for your brand or your company.
We know that GenAI should simplify content creation, reduce costs and streamline workflows, but maintaining brand integrity and ensuring product accuracy every time remains a very real and justifiable concern. One false move and the implications could be catastrophic for your brand – even the slightest error could damage your reputation irreparably.
One of GenAI’s primary challenges is maintaining this level of consistency – it’s good, but with errant hallucinations and an inability to art direct the details, it’s far from flawless. When you factor in the need to scale up your work across different markets, the scope of the problem (and the propensity for disaster to strike) increases tenfold.
At a time when trust and accuracy have never been more important, it’s imperative to address these issues and ensure pixel-perfect accuracy consistently across all your marketing assets.
This is where the digital product twin comes into play – a distinct entity outside your GenAI workflow that ensures precision. A digital twin is a new type of 3D master file that enhances realism and functionality with GenAI while being grounded in detailed CAD data for accuracy.
Think of it as a pixel-perfect, hyper-realistic, and interoperable 3D file your brand or agency can use infinitely across all marketing needs, from OOH and print to VR. It works seamlessly with conventional 3D backgrounds or AI-generated scenes and sets, making it an essential component of any product marketing strategy.
Why is this so crucial? Because a product is a brand’s most valuable asset – it must be flawless every time. Any distortion or error renders it unusable, whether for a TV ad or social media post. A digital twin guarantees product accuracy every time.
Moreover, it plays a critical role in reducing wasteful production – whether in terms of time, money, or carbon. Once created, your product twin can be utilised by anyone, eliminating the need to recreate multiple assets across agencies and platforms and reducing the reliance on costly shoots, post-production and reshoots.
Another significant benefit is that digital product twins can be created and updated in real-time. Gone are the days of long rendering delays. Ideas can be quickly realised and explored, and platforms like Nvidia’s Omniverse make collaboration effortless, allowing creatives and brands to contribute to the creative process with ease. Over time, you can build a library of reusable brand assets, including AI-generated backgrounds, sets, and props.
By integrating AI-driven digital twin technology into your content production ecosystem, you can achieve real-scale content creation. Your “single digital truth” is interoperable across 3D platforms, easy to reuse and amend, and tools can be developed to automate rendering, further scaling content production.
The need for change in our workflow is undeniable. By minimising the need for real-world shoots, a digital twin-first approach can significantly reduce your production carbon footprint and help meet ESG targets. Most importantly, it ensures a brand-safe integration of GenAI, providing accuracy, consistency, and ultra-high quality at scale.
Explore the potential of GenAI and engage with customers through compelling, personalised, and immersive experiences using cost-effective and reusable AI-enabled digital product twins.
Steve Barnes is a founding partner at Collective
