GenAI has been around for more than a year and a half now. We are now at the point where most news brands have actively experimented with GenAI and built various products. But, based on my conversations with INMA members, one challenge now popping up is that the users for whom they were built — generally, newsrooms — are often slow to embrace them.

Indeed, we saw similar results in a poll conducted during a GenAI Webinar on July 10, attended live by about 70 INMA members:

Similarly, the Online News Association polled 35 journalists and found that only about half used AI tools often or always:

This challenge is not specific to the media industry or to a particular part of the world. A survey conducted by SAS and Coleman Parkes of 1,600 decision-makers in key global markets looked at where different regions ranked in fully using and implementing generative AI into their organisation’s processes:

• North America: 20%

• APAC: 10%

• LATAM: 8%

• Northern Europe: 7%

• South West and Eastern Europe: 7%

“With any new technology, organisations must navigate a discovery phase, separating hype from reality, to understand the complexity of real-world implementations in the enterprise. We have reached this moment with generative AI,” said SAS CTO Bryan Harris. “As we exit the hype cycle, it is now about purposefully implementing and delivering repeatable and trusted business results from GenAI.”

Harris’ sentiment is echoed by media leaders: “This is revolutionary technology, but it has not produced revolutionary changes,” despite being integrated into the CMS, where journalists should find it easy to use, one executive told me. 

One reason is that staff members are so busy that learning how to use a new tool appears to be another chore they need to set aside time for. Many news organisations have extensive training programmes, which include Slack channels, training videos, as well as human-to-human workshops — but dragging busy employees away from their day jobs to pay attention to these is a challenge.

Another is the fear of losing jobs. “We actually had staff using the tools and then pretending not to use them because they were so effective and they were worried about losing their jobs,” a technology leader at a news publisher told me.

Again, this is not a problem that is specific to the media industry.

“Lack of trust remains a major barrier to large-scale generative AI adoption and deployment. Two key aspects of trust we observed are: trust in the quality and reliability of generative AI’s output, and trust from workers that the technology will make their jobs easier without replacing them,” Deloitte’s Q2 State of Generative AI report found.

Gartner found a different barrier to adoption topped the list: the ROI calculation.

“The primary obstacle to AI adoption, as reported by 49% of survey participants, is the difficulty in estimating and demonstrating the value of AI projects. This issue surpasses other barriers such as talent shortages, technical difficulties, data-related problems, lack of business alignment and trust in AI,” Gartner wrote in May after surveying 644 respondents in the U.S., Germany, and the U.K. 

“Business value continues to be a challenge for organisations when it comes to AI. As organisations scale AI, they need to consider the total cost of ownership of their projects, as well as the wide spectrum of benefits beyond productivity improvement.”

The survey also found that, on average, only 48% of AI projects make it into production.

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