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Generative AI is the most hyped technology of the last decade, and while adoption rates are high in Australia, a lot of people are sceptical about whether AI will reach its full potential.
A few weeks ago we were faced with a new challenge from one of our property industry clients. A huge client had just left a longstanding lease for a purpose-built facility, meaning a huge building worth millions of dollars was suddenly standing idle.
Obviously they wanted to get it on the market as soon as possible. The problem was that because it was a long-term lease, there were no very recent images of it looking presentable, and to get those done would take weeks.
But this is where AI tools came to the rescue. We leaned into design tools to help retouch these images to show what the space could look like – something which would have taken days and days itself was instead delivered in a few short hours.
Of course, using real images is always a better option – but in this last-minute, rushed circumstance, an AI touch-up solved a very difficult problem for everyone. Suddenly that space is on the market, and the client is able to start what is often a long sales cycle to get a new tenant in.
I tell this story because I find most people don’t know what’s happening behind the scenes in their own industry and are hovering on the same precipice of understanding – generative AI is going to be important, and businesses should be using it, but it’s not being utilised in my industry.
Well, guess what, it’s likely some of your competitors are already out there experimenting and getting early wins with it. You are at risk of being left behind.
More than a thought starter
The conversation about generative AI has been relegated to discussing it as something of an excellent thought starter. It can provide the spark of inspiration that is so often the most difficult first step, and it can do so really well. But already, it is much, much more than that.
Generative AI isn’t just for initial ideation or for automating those manual tasks that no one wants to do. It’s a solution that can be leveraged at every stage of the business process, in every department.
Setting up a ChatGPT account is all well and good, but the wide world of generative AI goes far beyond that.
If you’re starting to feel nervous about what this may mean for your role, consider this – a hammer on a table is just a hammer. In skilled hands it becomes a useful tool. Any generative AI model is only as good as the people who not only know, but are trained, in how to use it, and it’s certainly not a magic wand that will autonomously solve all problems.
Rather, it requires human oversight, ethical considerations, and strategic input to be effective. The misconception that AI can function independently of human intervention is misguided. Businesses must foster a collaborative relationship between humans and AI, where the technology enhances human capabilities rather than replacing them.
Many businesses are unsure where to begin with integration beyond simple applications like chatbots or free models. While generative AI can indeed handle tasks such as creating reasonable copy or generating initial concepts, its utility extends far beyond these low-hanging fruits. To effectively integrate this technology, businesses should develop a comprehensive strategy that includes identifying key areas where AI can drive efficiency and creative output.
Driving efficiency
One of the primary advantages of AI is its ability to drive efficiency. We like to think of it as an “efficiency engine”, a system that employs various AI models to streamline different tasks. This can range from strategic planning and research to creative brainstorming and concept development.
The goal is to reduce the time required for tasks without compromising on quality. For instance, a process that traditionally took a week can be completed in significantly less time with AI, often with superior results.
Most times, identifying these opportunities for efficiencies will also mean preserving budgets and switching business models to a value-based rather than hours-centric approach.
Enhancing creativity with generative AI
For many years creativity has been sidelined as the jobs for people with “creative” in their title. But the most successful architects, developers, or agents are inherently creative people. Their success comes from finding new ways to problem solve, giving them a competitive advantage where many are left ploughing to old furrows.
AI is going to change the game because now everyone has a profoundly clever, creative assistant to help them reason out and crack day-to-day problems in a new and creative way.
For the property industry, there are new tools which can now create audio, video, graphics and much more to insanely high standards. Most jobs require some form of pitching or creative problem-solving, and suddenly anyone with an idea can see it come to life without an expensive Photoshop subscription and years of training. It is set to make the world of presentations and pitching much more creative and interesting for us all.
The realms of image and video generation are extremely promising and have run-on effects for creative and post-production pipelines. I would encourage businesses to play around with Large Language Models (LLMs), and find ways to embed them into the production pipeline. For example, if you’ve got an idea, feed that idea to the LLM and use it as a bounce board to further flesh out your strategy.
It can become an assistant throughout the creative journey. We constantly encourage all of our creative studio to test and learn its capabilities and are often surprised by what the AI machines give us back.
Creating boundaries
However, there needs to be some guidance and “look before you leap” warning signs erected as well. Free versions of public models will simply be used to train the next version – you don’t want your client’s confidential information being dragged out of the ether once the next iteration of an AI model is developed.
For this reason, businesses should be setting up the infrastructure to allow for the responsible use of generative AI, such as RAG (retrieval-augmented generation) within your owned, secure server environments. This is essentially where you can keep all your proprietary data secure and free from the public domain, and use it as context in your prompting and outputs. It is essential that if you are encouraging your employees to upskill in AI, that they are being supplied with privacy-safe tools and a framework around the kind of information they are allowed to play with with these tools.
For businesses looking to integrate generative AI, the journey begins with education and experimentation. Understanding the different AI models and their specific applications is crucial.
Market leaders such as OpenAI, Adobe, Anthropic, and Stable Diffusion provide robust platforms for various AI functionalities. Additionally, new start-ups are constantly emerging – it’s truly a space that is constantly changing.
Businesses should start by identifying key areas where AI can have the most significant impact. For instance, consider implementing AI in customer service to handle routine inquiries efficiently or in marketing to personalise content for different audience segments. In creative fields, explore AI tools for generating initial concepts or enhancing visual and audio content.
Generative AI holds transformative potential for businesses, but its success hinges on thoughtful integration and human collaboration. By focusing on both efficiency and creativity, businesses can leverage generative AI not just as a novelty but as a fundamental component of their operations.
Ryan Bodger is the managing partner of Now We Collide.
