Mid-Market Businesses Fretting About Generative AI More Than Enterprises

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Tom Fogden
By Tom Fogden



mid-market companies are more concerned about generative AI quality than enterprise companies in Australia.

The news comes off the back of research conducted by independent agency In Marketing We Trust, conducted in partnership with the University of Sydney. Participants interviewed by the university were mapped based on the size and regulation level of their company and clustered into four main groups: lightly-regulated mid-market, lightly-regulated enterprise, highly-regulated mid-market and highly-regulated enterprise.

When it came to barriers to Australian companies implementing generative AI, five categories were identified within organisational reluctance: regulation, caution, detrimental to business, quality, and personal preference.

Regulation and caution categories were mentioned by all types of businesses. For regulation, businesses cited changes in regulation and non-existing legal frameworks as barriers to adoption. All businesses also showed caution, citing a careful approach regarding marketing, and fear of jumping on the bandwagon of technologies.

Surprisingly, mid-market companies were more worried about quality than enterprises, citing it as a main barrier to generative AI implementation. Both lightly-regulated and highly-regulated mid-market grouped businesses were worried about the wrong information and instructions shared by generative AI and acknowledged better quality by humans.

A lack of technical knowledge was also recorded in the research by In Marketing We Trust and the University of Sydney, with almost half of the interviewees not currently using generative AI. 42 per cent of interviewees stated they did not use generative AI at all, while thirty-seven per cent were experimenting with it, and just twenty-one per cent were using it in their business.

An anonymous interviewee concerned about the accuracy risk of generative AI from a lightly regulated mid-market Australian business stated:

“It spits out wrong information because of the garbage that is already in the system, you’re like you’re getting a false response and then you’re going to, I don’t know, deploy a media strategy which is not correct.”

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