Australian businesses relying on partners to streamline their AI journey

Businesses in Australia are eager to adapt more generative AI solutions once their concerns on costs, data security and data governance are addressed.

Cisco recently announced a massive partner program renovation in the form of Cisco 360. Cisco 360 is a brand-new partner program that reflects a total change in how the company will incentivize, compensate, and go to market with its partners. While Cisco 360 will only launch in February 2026, partners are already gearing up to the near program.

According to Cisco’s Partner AI study, more than 25% of partners believe between 76% to 100% revenue will come from AI technologies over the next four to five years. Driving these investments will be spending on generative AI in cybersecurity and financial management.

During the Cisco Live APJ summit in Melbourne, Australia, several partners shared the opportunities and challenges organizations are facing in the Asia Pacific region. Looking specifically at partners in Australia, they believe that businesses in Australia are eager to adapt more generative AI solutions. However, there are several concerns that continue to cloud their decisions.

Lisa Fortey, National Sales Director for Logicalis commented that IT leaders in Australia fear adopting generative AI because of the security concerns that come with it. They want to make sure they have their data in the right place before going deeper into generative AI.

Given these concerns, the managed service provider has become the first global Cisco partner to launch Cisco Extended Detection and Response (XDR) as a Managed Service (MXDR). Logicalis' MXDR services are managed through its global network of Security Operations Centres (SOCs). Armed with the most up-to-date global threat intelligence, they ensure rapid detection, analysis, and response across a customer's digital fabric 24/7.

This global service forms part of the recently launched Intelligent Security portfolio and increases Logicalis' proactive threat-hunting capabilities worldwide. It provides advanced visibility into cyberattack chains, AI-driven automation, and global threat intelligence data.

Developing AI strategies

For John Tan, Chief Customer Officer at Data#3, the focus is on helping customers develop strong AI strategies, especially on security, governance and data. The challenge in the workforce is also one of the reasons why partners are evolving to help customers.

Data#3 which is an ASX listed cloud computing and ICT solutions provider is recognised as one of the largest onshore providers in Australia. One of the ways it helps customers in their AI journey is by providing a readiness assessment which Tan highlighted is currently a powerful tool in the industry currently.

“More customers are looking into Microsoft Copilot. So, we are leveraging the capabilities of Copilot in the workforce to encourage adoption across a variety of industries. We aim to help customers make that linkage of using AI in the workforce to other aspects in the organization such as in security,” said Tan.

Tan also mentioned AI adoption among mid-market organizations are actually higher compared to larger organizations. Most businesses already have some form of AI in workplace tools. The focus now is on bringing generative AI capabilities to these tools. For example, customers use AI in documents and such. The next step will be enhancing the capabilities of the data in the document by leveraging generative AI.

Interestingly, Tan also mentioned that when it comes to large language models (LLMs), Australia is still lagging behind compared to other countries in the Asia Pacific. However, he believes that its only a matter of time before this picks up as the readiness is already there.

Managing costs in AI deployment

Meanwhile, Chris Noonan, Vice President for Technology Solutions at NTT pointed out that while LLM is becoming increasingly accessible and localized by other nations in APAC, small LLMs are also becoming popular as it involves a smaller investment. The cost of developing and running small LLMs gives organizations the opportunity to customize LLM based on their requirements.

Given that costs remain a hurdle for organizations in their AI development, by being able to focus on small LLMs, they are able to reduce their cost by a lot and still access the capabilities of generative AI in their organization.

“We have developed lots of POCs and POVs on different use cases. Customers are looking at the best use case for their business to invest in. If we look at the rush to the cloud a few years ago, there was some remediation after the initial rush. The same can be said for generative AI now as well,” explained Noonan.

According to Noonan, most of their customers are focused on about two or three areas when it comes to generative AI, with virtual assistants, content creation and coding the popular use cases. These are also the areas where NTT is helping customers get around their unstructured data.

All three partners believe that the slower adoption of generative AI in Australia is also because of fear of cost blowouts. At the end of the day, customers want to get the best ROI and achieve productive gains from generative AI.

As Tan puts it, it's just a matter of time that businesses in Australia move from POCs to real use cases and the partners in the country will be ready to help in their journey.