Two in three Australian organisations to appoint CAIO: 2027
New research from Datacom shows Australian organisations are increasingly appointing dedicated AI leaders to manage transformation, governance and workforce readiness.
For many large organisations, the question is no longer whether to use AI but how to move beyond individual tools and promising pilots to change how the organisation operates, serves customers and delivers value.
That challenge is reflected in Datacom's recent research report, The Emerging Role of the Chief AI Officer in Australia: Building Leadership for Transformation. Based on a survey of 507 Australian business and IT leaders, the research found 63% of organisations expect to appoint a Chief AI Officer by 2027. The finding points to a growing recognition that AI is no longer just a technology initiative. It requires leadership, governance and a coordinated approach to scaling AI across the organisation.
As AI investment accelerates, organisations are looking beyond experimentation and productivity gains towards broader transformation. The challenge is turning successful pilots and isolated use cases into capabilities that are embedded across operations, customer experiences and decision-making.
Rolling out an AI assistant, adding AI to an existing process or testing a proof of concept can produce useful early results. But isolated adoption is not the same as organisation-wide transformation.
"There is a big difference between adopting AI and adapting because of it," says Lou Compagnone, Datacom Director of AI. "Adoption is about deploying tools and running pilots. Adapting means reconsidering how your organisation works, how it serves customers and where AI can enable value that was not possible before."
The barriers are rarely limited to technology. Organisations may have several AI initiatives underway without a shared strategy or a clearly accountable leader and successful pilots often remain disconnected from core systems and processes. Governance is also critical for managing risk but at the same time can feel like a barrier if it is unclear or difficult to navigate. Other common challenges include fragmented or poorly prepared data resulting in subpar AI outputs and insufficient training is another barrier, with employees being given new tools without the skills, confidence or guidance to use them well.
At the same time, uncontrolled use of public AI tools can spread when approved options do not meet people’s needs. This creates new questions about privacy, security, cost and the handling of sensitive organisational information.
“A tool rollout is not an AI strategy,” says Compagnone. “Organisations need to be clear about the outcomes they are seeking, the problems worth solving and the conditions that must be in place to scale safely. Otherwise, they risk accumulating pilots without building the capability to turn them into lasting value.”
For enterprise and government leaders, this creates a complex set of decisions. They need to identify where AI can make a material difference, demonstrate value, manage regulatory and operational risk, and bring their workforce with them. These decisions also need to account for existing architecture, security settings, data environments and technology investments. There is no single product or platform that resolves all of those questions.
A practical AI journey starts with the organisation’s priorities. This could mean improving access to services, reducing the administrative burden on employees, modernising a slow process, strengthening decision support or creating a more consistent customer experience. From there, organisations can identify and quantify the use cases most likely to create value.
Datacom’s consulting approach brings together strategy, engineering, governance and workforce enablement. It can begin with an AI strategy and operating model, a review of governance and compliance, a prioritised use case, or an education programme for leaders and employees. The aim is to meet organisations at their current level of maturity and establish a realistic route from intent to execution.
For a priority use case, that can include developing a working prototype to test its feasibility and value before a larger investment is made. This gives decision-makers something tangible to assess and helps expose practical issues early, including data quality, integration requirements, security constraints, user experience and the cost of operating the solution at scale.
“Organisations get better results when they begin with the problem they need to solve, rather than a predetermined technology,” says Joel Macfarlane, Datacom Director AI & Engineering. “Our role is to understand the customer’s environment, identify the right approach and connect the strategy to something that can work in practice.”
This is particularly important in complex enterprise and government environments, where new AI capabilities must work alongside legacy applications, cloud platforms, security controls and sector-specific requirements.
Scaling AI requires more than repeating a successful pilot. It depends on a set of connected foundations.
The organisation needs a clear strategy, ownership model and investment roadmap. Governance must establish useful boundaries without preventing responsible experimentation. Data and security settings need to support the intended uses. Technology platforms must allow AI services and agents to be monitored, managed and integrated across the organisation.
People are equally important. Executives need enough understanding to make informed investment and risk decisions. Technical and operational teams need the skills to design, deploy and manage AI-enabled services. Employees need practical guidance on when and how to use AI, along with clarity about where human judgement remains essential.
Download Datacom's AI consulting brochure to unlock insights on AI foundations and strategy.
Datacom’s AI Consulting services span four key areas designed to support these needs: AI strategy, proof of value, AI education and AI compliance and governance. Together, they cover prioritised use cases, operating models, workforce capability, prototypes, regulatory alignment and practical action plans.
“Governance, skills and technology cannot be treated as separate workstreams that eventually come together,” says Macfarlane. “They have to develop in step. If the platform is ready but the workforce is not, adoption stalls. If people are ready but the data and controls are not, the organisation takes on unnecessary risk.”
Once the foundations are in place, organisations can begin to look beyond task-level productivity towards broader operational change.
In the front office, AI can support more responsive and personalised interactions by helping customers and employees find information, navigate services and complete tasks. In the back office, it can reduce routine work, support judgement and help processes move more quickly across organisational boundaries.
Modern software engineering and platform management are essential to both. AI can assist with software design, development, modernisation and ongoing management, helping organisations deliver new capabilities without treating every use case as a standalone project. Datacom’s approach spans organisational enablement, intelligent enterprise technology, customer and employee experiences, and AI-enabled operations.
The opportunity is not simply to automate the way work is done today. It is to ask whether a service, workflow or operating model could be designed differently.
That requires a wider view of AI than any one vendor, model or product. Datacom works across technologies and platforms, selecting solutions according to the customer’s needs, existing environment, risk settings and intended outcomes.
AI will continue to change quickly, but organisations do not need to pursue every new development. They do need a disciplined way to decide what matters, what is viable and what they are ready to scale.
External support can help organisations assess their current position, challenge assumptions and bring together the business, technical, governance and workforce decisions involved. Datacom combines consulting capability with more than 280 AI specialists who can help customers assess, strategise, prove, enable, govern and deliver AI initiatives.
Datacom is also applying AI across its own operations, giving its teams direct experience of the questions customers face, from leadership and literacy to governance, engineering and change.
The path will be different for every organisation. Some need to establish basic governance and workforce confidence. Others need to choose between competing use cases, prove the value of an idea or move an existing solution into production.
The common goal is to turn AI from a collection of tools and experiments into a managed organisational capability.
As Compagnone puts it: “The real opportunity is not just to add AI to the organisation you already have. It is to work out where AI allows you to operate differently, and then put the strategy, people and foundations in place to make that change achievable.”
Datacom helps New Zealand organisations move beyond AI pilots and experimentation to organisation-wide adoption and transformation. Our AI consulting services span strategy, governance, compliance, workforce enablement, AI literacy, use case prioritisation and proof-of-value initiatives. We help organisations identify where AI can create measurable value, build the foundations for responsible adoption and develop practical roadmaps for scaling AI across operations, services and customer experiences.
AI consulting helps organisations move from isolated AI initiatives to coordinated, organisation-wide transformation. Datacom works with Australian organisations to develop AI strategies, operating models, governance frameworks, workforce capability programmes and high-value use cases that support sustainable adoption. Rather than focusing solely on technology, we help leaders align AI investments with business objectives, customer outcomes and organisational change.
As AI becomes embedded across business functions, organisations need clear leadership, accountability and governance to manage risk, prioritise investment and drive adoption at scale. Datacom's research The Emerging Role of the Chief AI Officer in Australia: Building Leadership for Transformation found that 63% of Australian organisations expect to appoint a Chief AI Officer by 2027, highlighting the growing need for dedicated leadership to guide AI strategy, governance and transformation efforts.
Although AI use has become widespread, scaling it across core operations can be difficult. Ready to turn AI from experimentation into measurable business value? Datacom can help you identify the right opportunities, prove what works and build the technology, governance and workforce capability needed to scale AI with confidence. Book a consultation with us to discover how a clear strategy and an organisation-wide approach can turn experimentation into lasting value.
