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The Impact of AI on the Advertising Industry in New Zealand

Research into the impact of artificial intelligence (AI) on the New Zealand advertising business was conducted by Associate Professor Angelique Nairn, Senior Lecturer Justin Matthews, and Lecturer Dan Fastnedge of AUT’s School of Communication Studies. The effort is a reaction to the growing popularity of generative AI picture technologies in advertising.

Focus groups were conducted using advertising creatives from eight different New Zealand advertising companies for this study. A wide variety of people, from junior to seasoned directors, were represented here, including creative directors, art directors, designers, copywriters, content developers, strategists, and account executives.

The study’s focus groups uncovered three primary themes: aesthetics, creative practice, and the human vs machine debate. According to Matthews, “We wanted to find out how AI is already affecting the industry in NZ, what issues have already been noted, and discuss its future potential.”

In which ads are purchased automatically based on big data interpretation, programmatic buying is one way AI has impacted the advertising industry. Ads may now be tested in real-time, helping maximise resources and save money for advertising agencies and their clients.

The study also analysed AI’s potential as a source of inspiration. For example, this group used a digital picture AI generative technology to reimagine a campaign for a car manufacturer that included a menagerie of hybrid animals with the slogan “small but ferocious.”

Participants in the focus group found the digital images generated using AI generative tools exciting and enjoyable, although they were not of production quality. The result demonstrates the need for human skills to reach optimal advertising results. However, it was clear that using AI tools, such as digital picture AI-generating tools, for brainstorming and prototyping campaigns would be beneficial.

Participants also saw a benefit in using AI-generated graphics rather than stock photography. However, they pushed back on the ‘human vs machine’ discussion, recognising that AI-generated photos still need to be at the same quality level as human production, though this might change rapidly. There was also worry that AI may provide biased or stereotypical results in image generation.

Fastnedge observed that several participants brought up the workforce implications of the shift in ‘creative practise,’ including the need to acquire new skills, the possibility of losing one’s job, and the necessity of making more significant contributions with fewer resources. However, the speed with which generative AI can generate ideas and complete projects was often viewed as a benefit.

The research indicates that generative AI is a technology that will inevitably impact the advertising industry, requiring professionals in the sector to adopt programmatic creativity. While there are certainly some obstacles, the advantages of using AI to generate ideas for and create mockups of advertising campaigns are too significant to ignore.

New Zealand has seen widespread adoption of AI outside of the advertising sector. Recently, scientists at the University of Canterbury used ML to determine what causes geothermal fields in New Zealand to become unstable and how to spot dangers before they happen. Taupo and Kawerau are particularly active geothermal locations because New Zealand sits on the margins of two tectonically-active plates. Minor earthquakes or hydrothermal eruptions pose a risk to energy generation even though geothermal areas are employed for electricity production.

Dr Ardid, one of the team’s researchers, has revealed that they are mining information gleaned from observations of geyser activity in Yellowstone National Park in the United States. Hundreds of Yellowstone geyser outbursts have been recorded on seismic recordings during the past decade. The team uses machine learning to uncover underlying patterns that develop in advance of eruptions and then incorporates these findings into models tailored to the geothermal systems of New Zealand.


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