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Channel partners across Asia Pacific will find a lot of opportunities coming from AI in the years ahead as businesses across industries rush to embrace it for new use cases, from fraud detection automation in financial services to enhanced disease diagnostics in healthcare.
IDC reports that the market will almost double by 2025, going from $17.6 billion to $32 billion. Furthermore, 89.3% of organizations in the region (excluding Japan) have made a start in AI, with 52% still in the earlier maturity stages.
Interest in the technology may be exploding, but AI projects are complex and solutions-driven, and many companies need to be guided by their channel partners in adopting and driving success with it. Simply investing in AI solutions wouldn’t yield meaningful results and CIOs know that. For the channel, this presents a consulting and services opportunity as much as a box-deploying one.
AI Adoption Challenges
Businesses wanting a bite of its benefits need to grasp the complexity of undertaking an organization-wide AI strategy.
First, we need to talk about AI’s foundation: data. Unlocking its potential is dependent on the data that fuels it. For data to be useful, it should be acquired, organised, and used in a continuous cycle that is constantly optimised as more data is accumulated—easier said than done given the volume and variety of data. More frustratingly, data often sit in different locations and in silos, adding complexity to getting AI projects into production.
Once businesses solve the data conundrum, they need to expect technology challenges, which might hinder their AI initiatives. These include:
- Complex DIY integrations
- Heavy AI workloads
- Difficulty in achieving predictable and scalable performance
- Lack of ML and DL skillsets/talent
AI solutions need to be tailored to the unique objectives of each business, and this means that off-the-shelf solutions only go so far. On the other hand, customisation can significantly increase complexity and lengthen deployment times.
AI is demanding on the IT environment, and the deployment of AI solutions often requires a refresh of everything, from the networking and storage environments to hyperscale cloud adoption and integration.
Most CIOs are aware that the best approach to AI is to start small, then scale. But scaling isn’t straightforward, particularly from a storage perspective. Traditionally, compute and direct-attached storage have been used to feed data to AI workloads but scaling with these can lead to disruption and downtime for ongoing operations.
Three in four APAC employers are facing an IT skills gap, and AI skills are particularly in demand. For most organisations, it’s simply not practical to develop and scale a full AI team internally.
“AI is one of the biggest opportunities of our generation, but few organisations have been able to fully harness the power of the technology. Besides putting in place the right resources and processes, enterprises need to properly integrate their data fabric across the edge, core, and cloud to drive business impact,” said Ray Chan, Sales Leader, NetApp Singapore. “Implementation-wise, technical integration between AI technology providers like NetApp and the full set of partner ecosystem players will help create powerful AI solutions that can truly meet customers’ needs and give them a competitive edge.”
Collaborating And Unlocking the Potential Of AI
How can channel enable customers on their AI Journey? An example would be Singaporean IT systems integrator PTC Systems—a member of SMARTLAB, Southeast Asia’s first industry lab for smart cities solutions development—which recently developed the AI Integration Hub in collaboration with NetApp.
The AI Integration Hub leverages NetApp ONTAP AI that combines NVIDIA DGX systems for compute and NetApp All Flash FAS for cloud-connected storage. Through a hybrid platform that combines machine learning and deep learning frameworks, data management software, and cutting-edge software, PTC Systems has the potential to play a pivotal role in support SMARTLAB projects and enabling businesses eyeing the AI potential.
“The idealization of AI projects should start today in any organization. Firstly, look at your internal processes and consider how you can automate these processes,” SS Lim, CEO PTC Systems said. “AI can write complex software so that we can automate anything. The journey is possible because the cost of acquiring hardware has become affordable. There are many templates of different applications, and software engineers can also be trained to develop AI applications.”
