Data Leaders Reshaping Australian Business with AI
The integration of artificial intelligence (AI) into Australian businesses is no longer a question of “if” but “when” and “how well”. As companies across sectors grapple with AI adoption, the demand for senior data and analytics professionals who can bridge the gap between cutting-edge technology and tangible business value has never been higher.
At Allura Partners, Principal Consultant Kaio Desouza has positioned himself at the forefront of this transformation, having recently placed Peet Vermeulen as AI Lead at Metcash.
The Market Reality: Strategic, Not Speculative
The current market has become more selective and strategic than ever before, with businesses increasingly demanding data leaders who can demonstrate clear returns on AI investments.
And according to Kaio, it’s the finance, healthcare, and retail sectors that have emerged as the primary drivers of demand for these leaders.
“They are particularly looking for professionals who can tie data work directly to business outcomes – whether that’s efficiency improvements, revenue generation, cost reduction, or innovation through AI,” he says.
This shift reflects growing market maturation. “Companies that have taken risks without sufficient due diligence have witnessed expensive failures… In tighter market conditions, you can’t afford to do that anymore. Everything has to be more planned, and companies are now more risk-averse.”
AI Integration: A Matter of Data Maturity
The relationship between AI adoption and data maturity has become a critical factor in hiring decisions. Some companies with years of machine learning experience and solid infrastructure are now building new use cases and expanding AI capabilities. Others are still establishing basic data governance teams and foundational systems. For the latter group, “until they get all that in place, AI won’t really add value.”
Kaio says the Metcash placement is a perfect example of the ground-up approach many organisations are now taking. The AI lead role was designed “to help drive innovation from the ground up,” moving from a wait-and-see approach to proactive AI strategy development across Metcash's business divisions. “Peet Vermeulen has gone in to start from scratch, speak to the business, build use cases, and then slowly integrate AI,” he explains.
The Governance Imperative
Perhaps the most significant development in the AI recruitment landscape is the emergence of AI governance roles. As Kaio points out, this trend reflects the dual challenge data leaders now face: implementing AI capabilities while ensuring compliance and ethical use. “It’s put pressure on data leaders to ensure everything is compliant and they’re using AI in the correct way,” he observes.
Consequently, he says, “there’s definitely been a change in the types of roles”.
“New titles are appearing – AI governance specialists, AI advisors, AI product managers – particularly in heavily regulated industries like finance and superannuation.”
As well, Kaio is observing increasing collaboration between traditionally separate functions. “Cyber and data are working closer together – there are multiple companies with heads of cyber and data combined. This reflects the interconnected nature of AI governance, data security, and business value creation.”
The Skills Evolution: Technical Meets Strategic
While technical capabilities remain important, soft skills are in highest demand. “I rarely see a candidate rejected because they can’t use a particular tool,” Kaio says. “It’s always about communication, stakeholder engagement, how they explain data to non-technical people, translate insights into actionable business outcomes.”
This shift reflects the evolution of data roles from isolated technical positions to strategic business functions. “Historically, many data roles just sat in the corner coding. This focus on driving value through data is relatively new,” he explains.
He said the emergence of tools like ChatGPT has only amplified this trend. “You can use ChatGPT to create a business plan quite quickly, but you still have to present that plan. At the end of the day, it’s still you who has to sell it and convince stakeholders. You can’t just put a ChatGPT-generated plan in a presentation and ask for funding.”
Fractional Leadership and Specialised Roles On the Rise
Over the coming 24 months, Kaio anticipates growth in fractional and contract placements, particularly for scale-ups and mid-market companies seeking strategic guidance or governance reviews.
He believes that traditional data engineering roles will evolve rather than disappear. “Data engineers will be expected to build for AI, with things like real-time data and machine learning architecture”.
In addition, he expects new specialised roles will emerge beyond traditional hierarchies. “I think we’ll see roles like Head of AI Enablement or Director of Advanced Analytics, but AI will still sit under the Chief Data Officer rather than a separate Head of AI function,” he notes.
Personal Leadership in AI Recruitment
Kaio’s approach to staying ahead involves direct engagement with market leaders and continuous learning.
“I’ve been actively meeting people in the space who are current or future leaders, to understand their views on what’s happening. By hosting events, roundtable discussions, and building relationships with AI professionals, I’m developing the market intelligence and track record necessary to serve clients effectively.
“So now I can create effective connections with candidates and hiring managers,” he explains. “Getting ahead of the curve and building these relationships now is definitely going to benefit our clients and candidates long-term.”
The Collaborative Future
For organisations ready to leap into AI, having the right recruitment partner – one who understands both the technology and the market dynamics – can make the difference between AI success and expensive failure. Contact Kaio Desouza today to find out more.
