Craig Dunn, Stone & Chalk chairman, took a different perspective saying that, for a lot of start-ups, it is more a case of forging successful partnerships with incumbents rather than competing with them.

"This is happening, particularly in the fin-tech space," he said. "For many small technology firms, who might have pressures on their cash flow, it's a matter of partnering with incumbents and working on AI with them."

Microsoft Australia managing director Pip Marlow said that, for larger organisations wanting to embrace the opportunities offered by AI, it was a matter of "starting by dreaming big, prototyping small and then scaling fast".

"The cost of the failure of a small prototype is far less than the cost of failure if you are trying to lift and shift the Titanic," she said. "All innovation doesn't have to be on a grand scale."

Marlow said it was important for management boards to realise that, if a prototype AI project failed, it did not mean the whole management team should be fired. "In an innovation cycle, we know that that is going to happen and so you have to build that kind of culture around it."

The panel also discussed how access to AI was being democratised. Because any business can now make use of large, cloud-based computing resources with nothing more than a credit card, the barriers to entry when it comes to testing and using AI tools have been greatly reduced.

Kate Burleigh, managing director of Intel Australia and New Zealand, said the process of AI democratisation was being aided by the way in which large technology companies were opening up their technology for others to build upon.

She pointed to Intel's Nervana platform that had been designed to stimulate AI development and make a library of algorithms available for wider IT industry use.


"Like all areas of IT, there are still competing standards, but there are a lot of areas where you will find the big players like Intel opening things up," she said. "It is about the power of scale and volume and if you try and close things down too much around your own way of doing things, AI won't take off."

As well as access to large computer resources at relatively low price points, Burleigh said AI was also being driven by the copious amount of data that was now available for analysis.

"The third factor is the innovation explosion," she said. "There are enough examples appearing already that people's minds are exploding with ideas about what they could do. It is now a really interesting space."

Panel members agreed the predictive power of AI would continue to be transformational for businesses. With the ability to sift through vast amounts of data in almost real time, companies would soon be in a position to spot trends and make predictions that previously simply would have not been possible.

As well as commercial applications, the panel discussed how the technology had a wide range of roles in other areas.

UTS's Blumenstein pointed to examples such as understanding the worth of water. "We have been looking at how you can ensure we build the best infrastructure for the provision of water," he said. "We have been using deep learning and predictive analytics to go through all the data in the NSW government to predict the best places to build infrastructure."

Blumenstein said another project involved using AI in fields like robotics and drones. In one case, AI was being used with drones to spot sharks near popular swimming locations. "AI has a broad range of applications and the things we can do with it are endless," he said.

Microsoft's Marlow said regulations would have to be examined and potentially changed as AI tools continue to evolve and become even more powerful.

"For example, if you look at things like automated cars, the regulation in Australia is different from that in the US," she said. "In a Tesla, you can use more features in the US such as allowing the car to automatically stop for red lights. Here, you can't do that and we have to manually stop the car. Regulations will have an impact on the rate of adoption of AI."