Insights for Organisations

Overcoming Australia’s AI Integration Challenges in Business Operations

Paul Brown
02.11.23

In recent years, the implementation of AI in Australia’s businesses has undergone a significant shift, transforming a strategy for cost-savings into a powerful tool that can be used to achieve business objectives. Despite global uncertainty, Australian businesses remain growth-oriented, emphasising market differentiation, agility, and cost reduction. As a result, Australian businesses that have already implemented AI technologies have experienced significant advantages. Among these benefits are improved security, revenue growth, automation of internal processes, and optimal operational efficiency.

That being said, like many other nations, Australia currently faces several challenges when it comes to AI integration in business operations. From a severe AI skills gap and a lack of end-to-end solution support, to security threat concerns, businesses are navigating a challenging landscape.

McKinsey estimates that automation and artificial intelligence could contribute up to $4 trillion to Australia’s economy. If Australia is able to overcome the current challenges businesses face in the wake of AI integration, the nation will pave the way for improved operations, job opportunities, and innovation.

Let’s explore the current state of Australia’s AI landscape in more detail, delving into some of the key challenges these organisations face in the wake of AI integration, and the strategies that can be used to overcome them.

What’s in this article?

Executive summary

The current state of Australia’s AI landscape

According to Tortoise’s Global AI Index, Australia currently ranks 15th out of 62 countries across the world for AI adoption. This index is a reflection of each country’s readiness for AI, taking into account the level of investment, innovation, and implementation of artificial intelligence. As such, it is clear that Australia is making great strides towards AI adoption and towards revolutionising its businesses, governments, and society as a whole.

Despite Australia’s high international ranking, it scores just 34.2 out of 100 for talent in Tortoise’s 2023 AI study, which reveals that the country is experiencing a shortage in AI skills to facilitate the implementation of AI in business operations. In terms of infrastructure, Australia received a score of 54.3, showing that there is still some way to go in terms of the reliability and scale of access to relevant infrastructure. When it comes to government strategies and dedication to AI, Australia scores 83.3 out of 100, demonstrating a strong commitment from national governments, including high spending. On the other hand, a score of 7 out of 100 has been given for Australia’s commercial investment, revealing an extremely low level of AI startup activity, investment, and initiatives.

As such, Australia’s AI landscape presents a mixed picture. Ranking 15th out of 62 nations in AI adoption demonstrates a commendable commitment to embracing artificial intelligence in various sectors. However, it is clear that several key challenges remain, notably a talent shortage. These findings show that there are still ample opportunities for Australia to improve AI integration in business operations for better outcomes.

Australia’s AI capacity at an international level
(Score out of 100)
Talent34.2
Infrastructure54.3
Operating environment53.8
Research34.4
Development11.7
Government strategy83.3
Commercial7.0
Scale23.6
Intensity47.5

[Source: Tortoise’s Global AI Index]

4 Key challenges Australia’s businesses face in the wake of AI integration (and how to overcome them)

Here is a summary of the key challenges and setbacks many businesses in Australia face when integrating AI into their business operations:

1. Australian businesses adopt a cautious approach to AI adoption

CSIRO’s report on Australia’s AI ecosystem momentum reveals the tepid commitment shown by Australian businesses towards adopting AI. In particular, the report reveals that 53% of surveyed companies have either a neutral or negative position on AI adoption, with 7% having no plan to adopt AI, 44% not expanding or upgrading AI adoption, and 2% actually decreasing or removing AI from their business operations. This data not only suggests that many businesses are hesitant to expand AI operations, but that a substantial number of organisations are not actively pursuing AI integration or are ceasing AI involvement altogether.

AI has the potential to drive innovation and enhance business competitiveness across the board. Therefore, the fact that a significant portion of companies exhibit a neutral or negative attitude towards AI poses a hindrance to their ability to stay competitive in an increasingly AI-driven global market.

What can businesses do to change attitudes surrounding AI adoption?

A shift in attitudes towards AI adoption is imperative if businesses wish to reap the benefits of AI technologies. In order to do so, they must prioritise education and awareness, engage leadership support, initiate pilot projects, and showcase successful AI implementations. Moreover, investing in employee training and upskilling, facilitating collaboration between departments, and implementing structured change management strategies can ease the transition.

However, on a positive note, this slow adoption of AI among businesses in Australia presents a unique opportunity for early adopters of AI to experience the most growth and get a head start on the competition!

2. Working against a talent shortage

When implementing AI technology, another issue many businesses grapple with is the AI skills gap. In fact, the Australian Information Industry Association reports that cyber security and artificial intelligence are the most in demand skills in 2023, with AI skills being the most difficult to find.

According to CSIRO, the top three most difficult capabilities to source with AI providers are training, AI-specific data management, and AI governance. As such, many businesses are left to handle these aspects by themselves, although a more refined solution would be preferred.

Not to mention, the skills gap is amplified with many service providers operating on a temporary or project-based consulting basis or recruitment business model. In such models, AI professionals are brought in for specific projects or short-term assignments, often without a long-term commitment to the organisation. This exacerbates the skills gap because it can lead to a lack of consistent, in-house AI expertise. When AI experts come and go with each project, the organisation may struggle to build a stable and knowledgeable workforce capable of effectively managing AI-related tasks and projects over the long term.

Filling this talent shortage will certainly be no easy feat. McKinsey estimates that advancements in AI could lead to between 3.5 million and 6.5 million full-time equivalent positions being displaced, and between 1.8 million to 5.0 million workers requiring a change in professions to find a new job. However, for individuals who are able to adapt, this could result in $4,000 to $15,000 additional income per year by 2030!

What steps can businesses take to close the AI skills gap?

Outsourcing is a viable strategy to address the AI skills gap and help with seamless integration of AI within business operations. However, it is important that businesses opt for long-term partners, rather than short-term solutions as this leads to a lack of consistent AI expertise. Long-term tech talent partners enable businesses to tap into external AI experts and specialists to complement their in-house capabilities, as well as expedite AI adoption and implementation. This type of outsourcing can be particularly useful in providing access to a broader range of AI skills, such as AI-specific data management, AI development, and AI strategy. It offers flexibility, scalability, and cost-effectiveness, enabling businesses to effectively handle AI-related tasks and projects.

3. Lack of AI services providing end-to-end support with seamless integration

The lack of AI services* available to businesses in Australia that provide end-to-end support is a significant issue as it hampers the seamless integration of AI solutions into businesses. A lack of full-service project support with extensive integration capabilities leads to hindered technological advancements and innovation, an issue that is predominantly felt across small-to-medium-sized enterprises (SMEs).

Based on the CSIRO surveys, the ability to handle end-to-end projects from strategy through to implementation is the most critical factor when choosing an AI technology provider or service, according to decision-makers. Moreover, businesses are finding it challenging to find AI solutions that can integrate with their existing business solutions. One example in the same report found that a retail and wholesale business tried to adopt AI vision technology, however, they were unable to integrate this with their current point-of-sale system.

The AI ecosystem in Australia is still undergoing maturation, which means there are still significant gaps in service offering. In fact, AI service providers are working against a talent shortage of their own and are struggling to source business partners that are required to supply the end-to-end solution that businesses so desperately need. As a matter of fact, a shocking 30% of AI service providers state they cannot find the necessary AI technology and service partners to meet their clients’ requirements. The main gaps identified include data management, data analysis, and AI implementation.

*When referencing AI services, we are referring to any advisory or supporting services with AI expertise, including all stages of its lifecycle, from strategy, deployment, maintenance, and optimisation.

How can small-to-medium-sized enterprises overcome the lack of end-to-end AI support available?

Small-to-medium-sized enterprises (SMEs) face a pivotal question: how do you harness the transformative power of artificial intelligence (AI) when full-scale AI support appears out of reach? The answer lies in a strategic and informed approach. The apparent lack of comprehensive end-to-end AI support presents a unique opportunity for SMEs to become agile, innovative, and competitive players in their respective industries.

To surmount the challenge of limited end-to-end AI support, SMEs can take several strategic steps. The number-one most important strategy is investing in employee training and upskilling to bridge the AI skills gap. This will give your internal teams the knowledge and skills to lead on the management of AI-related tasks, reducing the reliance on external support.

Where the internal skills gap still exists, leaders must look to external sources to unlock AI’s full potential. Businesses must be prepared to partner with several providers in order to obtain the complete solution they desire and achieve business outcomes. Many who have already seen success have partnered with multiple providers, across data, services, and strategy. However, organisations are working towards the integration and expansion of AI technologies into a variety of dynamic use cases within their business environments, aiming to align AI investments with existing business technology, processes, and systems. As such, finding a service provider or talent solution that can facilitate the entire transformation journey is imperative.

Alternatively, cloud-based AI services, offered by tech giants like Google, Microsoft, and Amazon, provide ready-made AI tools and resources that are accessible to SMEs without the need for extensive in-house expertise. Leveraging these platforms can jumpstart AI adoption and reduce implementation complexities.

It’s essential to view AI adoption as a long-term strategy. Building AI capabilities may take time, but it can lead to substantial benefits in terms of efficiency, competitiveness, and innovation. SMEs that embark on this journey are not merely embracing AI; they are shaping their AI future, positioning themselves as agile and forward-thinking leaders in their industries.

4. Privacy, security, and data quality are three major AI concerns

CSIRO’s surveys reveal that one particular concern comes when utilising AI for customer insight analysis due to potential security threats, data quality issues, and privacy concerns. In fact, this acts as a primary barrier to AI adoption. However, Australian businesses are not alone here. On a global level, 49% of executives have identified cybersecurity vulnerabilities as a top concern, followed by 44% fearing making the wrong decision based on AI recommendations.

Maintaining privacy and security is essential to safeguarding sensitive information. When implementing AI, there is often a need to collect, analyse, and store vast amounts of data. If privacy measures are not adequately in place, this can lead to the unauthorised access, sharing, or misuse of personal or confidential data, which may result in legal, ethical, and reputational issues.

As for data quality, AI algorithms depend on high-quality data to produce accurate and reliable results. Poor data quality, including inaccuracies, biases, or incomplete datasets, can lead to erroneous conclusions, hindering decision-making and potentially causing harm. Ensuring data quality is a fundamental aspect of successful AI implementation.

How can businesses address ethics and governance challenges when implementing AI into their operations?

Ethics and governance in AI refer to the principles that ensure the responsible and accountable use of artificial intelligence technologies. They are essential aspects of AI implementation to address potential ethical challenges and societal implications, and should be a top priority for businesses planning to integrate AI into their business operations.

AI governance pertains to the rules, regulations, and frameworks that guide the use of AI technologies, ensuring that they are used responsibly and safely. This includes legal and regulatory mechanisms that address AI’s impact on society, data privacy, and data protection.

There are several steps leaders can take to build the right infrastructure for upholding ethics and governance in AI, and overcome this hurdle to adoption. First and foremost, you should recruit or assign dedicated roles responsible for overseeing AI ethics and governance, such as AI ethics officers or compliance officers. These team members should be responsible for developing and communicating clear and concise AI ethics guidelines that align with your organisation’s values and industry standards. Learn more about building a compliance team from scratch.

Similarly, provide comprehensive training to employees about AI ethics, governance, and compliance. Research shows that 90% of all security incidents involve staff, both deliberate and by mistake. So, it’s crucial that you equip staff with the knowledge and tools to recognise ethical dilemmas and navigate governance requirements. Consider third-party audits or reviews of AI systems to provide independent verification of ethical and governance compliance.

By taking these steps, businesses can build a strong ethical and governance infrastructure that ensures AI technologies are developed, deployed, and managed in a responsible and compliant manner.

FDM supporting businesses with AI integration around the world

At FDM, we specialise in providing our clients with expert consultants, trained to meet your unique business requirements. Across all stages of the AI lifecycle, we train our consultants to the highest standards so that they can provide real value when working within our clients’ teams. Partnering with a talent solutions partner like us will enable you to unlock the full potential of AI, putting your business at the forefront within Australia’s AI talent shortage.

Are you facing similar challenges in your business? Find out how FDM’s consultant services can help you in your journey to AI integration or get in touch for more information.