New Zealand business leaders are proving slow to act on the transformative potential of Generative AI. According to a recent Deloitte report, Generative AI in Asia Pacific: Young Employees Lead as Employers Play Catch-Up, the emergence of a tech-savvy workforce—dubbed 'Generation AI'—is driving adoption across the region. However, the same report highlights New Zealand's cautious stance, ranking it seventh out of nine Asia-Pacific countries in terms of GenAI adoption.
The findings reveal that a significant portion of New Zealand's workforce remains hesitant to embrace the technology, citing a lack of understanding, concerns about risks, and the absence of clear strategies as primary obstacles. Dr Amanda Williamson, a GenAI expert at Deloitte, emphasises that New Zealand's approach reflects a preference for careful consideration over hasty implementation. While younger generations are eager to leverage GenAI—demonstrated by 72% of university students having engaged with it—many leaders are still grappling with how to effectively integrate these tools into their organisations. The challenge lies not only in understanding GenAI's vast potential but also in adapting to the changing workforce dynamics that it brings.
To further explore the challenges and opportunities surrounding Generative AI adoption in New Zealand, we interviewed James Bergin, EGM Technology Research and Advocacy at Xero, and Justin Flitter, Founder of NewZealand.AI. Both bring valuable insights into how business leaders can effectively engage sceptical decision-makers and highlight the benefits of Generative AI to fully harness the potential of this transformative technology.
Bridging the expectations gap
One major theme is the disconnect between expectations and reality. Many leaders envision GenAI as a tool that can seamlessly manage entire processes; however, the reality is that it primarily enhances specific tasks, acting as a powerful assistant rather than a complete replacement. James Bergin highlights this issue: “Many business leaders tend to skew a little more towards expecting too much rather than expecting too little regarding Generative AI. That changes, in my experience, as people experiment with the technology more and start to adjust their expectations accordingly”. Educating leaders about what GenAI can realistically achieve is crucial for fostering understanding and acceptance..
Engaging the sceptics
Convincing those who view generative AI as irrelevant requires more than just theoretical discussions. It’s about demonstrating practical applications and showing tangible benefits. Justin Flitter explains, “Most business leaders underestimate and undervalue GenAI capability, mostly because they aren’t using tools themselves. But those that do engage see its potential”. Structured experiments can provide the evidence needed to shift attitudes, transforming scepticism into curiosity and sparking those “aha” moments that make leaders see the technology’s relevance.
Managing risks with confidence
From data hallucinations to user over-reliance, managing risks of GenAI is essential. However, it’s important to approach this without discouraging exploration. As Bergin notes, “Any technology comes with risks that need to be managed appropriately. With fast-evolving tech, keeping an eye on the limitations as much as the promises is a good way to operate, in my opinion. This shouldn't stop safe, deliberate exploration and research, but should help with setting and managing the right expectations”.
“Everyone needs AI skills training to make informed decisions on which tools they should use, how they work and how to ensure data privacy”, says Flitter. “It’s pretty simple: knowledge is empowering”.
Closing the skills gap
Business leaders may also be hesitating to engage with AI due to a perception of a skills gap. But rather than focusing solely on acquiring new technical skills, organisations should leverage existing strengths. Flitter emphasises, “Success with generative AI is 10% tech and 90% people.” He advocates for a shift in work practices to incorporate AI tools, underscoring that “there’s just a better way of doing things in 2024”.
“I wouldn't point to ‘new’ skills so much as existing skills that have been overlooked”, says Bergin. “For example, the quality of results from a large language model is directly tied to the quality of the prompt used to garner a response. This means that creative and descriptive writing skills are now in the spotlight as a skillset that adds a lot of value as we start to change how we interact with machines. I would also remember the skills that have always been important – like data governance – which are even more important in this new world”.
Join us at the Generative AI Summit 2024 (New Zealand)
Hear more from James Bergin, Justin Flitter, and a host of other experts on 3-5 December, at Rydges Auckland. View the agenda here.