Artificial intelligence (AI) is rapidly becoming a foundational layer of the global digital economy.
Across industries, companies are incorporating AI into their products, operations, and customer experiences to improve efficiency and unlock new capabilities.
For digitally native companies, this transformation is reshaping their entire business model. From real-time video generation to cloud gaming and intelligent digital platforms, AI-powered services rely on powerful computing infrastructure to deliver the instant and seamless experiences users now expect.
As AI workloads expand and user demands increase, the ability to scale high-performance computing quickly and reliably has become a key competitive advantage.
a Report by Infocomm Media Development Authority According to , over 70% of businesses in Singapore have already adopted AI technology to enhance product development, streamline operations, and optimize supply chains.
The AI adoption rate among small and medium-sized enterprises (SMEs) will increase to 14.5% in 2024 from 4.2% a year ago.
Despite growing interest in AI, adoption among small and medium-sized businesses remains relatively limited. Many small businesses recognize the potential of AI, but translating their ambitions into production-ready systems isn’t always easy.
One of the biggest barriers lies in the computing infrastructure. Building and managing high-performance systems in-house requires significant capital investment and specialized engineering expertise.
At the same time, many enterprise-grade solutions are designed for large organizations with dedicated IT teams and long planning cycles, making them difficult for fast-growing small businesses to implement.
For small businesses and startups, lack of vision is rarely a challenge. Instead, you’ll have access to the level of compute performance you need to support modern AI workloads in a cost-effective, scalable, and growth-aligned way.
To address these challenges, a new generation of specialized AI cloud platforms, called neocloud providers, are emerging.
These platforms provide high-performance graphics processing unit (GPU) computing and scalable infrastructure, allowing enterprises to run demanding AI workloads without the complexity of owning and managing infrastructure.
Bitdeer AI Cloud is one of the platforms that supports companies building compute-intensive AI applications.
By using its own data centers that are already up and running, Bitdeer AI gives small and medium-sized businesses access to AI computing power much faster, without having to wait months to build new infrastructure.
Photo: Bitdia AI
Bitdeer AI Cloud combines global data center capacity and high-performance GPU resources with an integrated full-stack AI cloud platform. It also provides critical tools to support the entire AI lifecycle, from model development and training to deployment and inference.
Bitdeer AI Cloud brings together these capabilities to give small teams access to enterprise-grade computing and scale their AI applications as their business grows. This lowers the barrier to entry for AI innovation, allowing teams to focus on building and scaling applications rather than managing complex infrastructure.
For many organizations, especially small and medium-sized enterprises, balancing innovation and cost control remains a key consideration when considering AI implementation.
“As AI adoption is still in its infancy, industry benchmarks for ROI are not yet well established,” said Retainna Lin, marketing and commercial director at Bitdeer AI Cloud.
That uncertainty makes it all the more important for companies to manage risk and adopt incremental scaling methods, she added.
To reduce that risk, Bitdeer AI allows customers to pilot, deploy, and scale AI applications in stages, increasing investment only as results are proven and needs evolve.
Businesses can take advantage of Bitdeer AI’s pay-as-you-go option initially and move to long-term leases once workloads stabilize and demand becomes more predictable.
Over the next 18 months, advances in AI will force businesses to run heavier workloads than before, Lin says. Companies will move beyond simple chatbots to heavier tasks such as agent AI systems that can make and execute decisions and compute-intensive tasks such as simulating factory operations or accelerating drug discovery.
“Speed in the industry is a double-edged sword. New AI models and tools emerge every day, making it extremely difficult for small teams to keep up.
Lin says the most important question for small businesses to ask is not just whether to implement AI, but how to do so in a way that delivers clear business value.
“This burden is most evident in the absence of a coherent AI strategy that maps technology choices to business outcomes,” Lin says.
Retainna Lin, marketing and commercial director at Bitdeer AI Cloud, says many companies struggle with knowing when and how to invest in AI infrastructure, rather than ambition.
Photo: Bitdia AI
Without such collaboration, AI adoption is likely to remain piecemeal. Teams choose tools on an ad hoc basis, and leaders have a hard time predicting how much computing power they really need, making it difficult to justify investments with tangible benefits. This is a particularly acute challenge for small and medium-sized businesses operating with limited budgets and small teams.
Bitdeer AI has access to 3 gigawatts of power capacity and land resources to bring AI-enabled facilities online faster. The company also One of the early NVIDIA cloud partners in Singaporehas an infrastructure powered by high-performance NVIDIA GPUs used to train and run advanced AI models for its customers.
Backed by the broader Bitdeer Group, which has extensive experience operating large-scale computing infrastructure through its long-standing involvement in crypto mining, the company is leveraging capabilities built over the years to accelerate the expansion of its AI-enabled capabilities.
Operating high-density computing environments at scale has enabled the group to develop expertise in infrastructure management, energy optimization, and system reliability, which now underpins the development and operation of AI data center infrastructure.
Large enterprises can also secure long-term resources and access the latest hardware for demanding AI workloads, including next-generation AI GPUs such as NVIDIA’s GB200 NVL72 server.
“Our brownfield advantage allows us to bring high-performance AI infrastructure to market at a speed and scale that is difficult to replicate,” Lin said.
“We believe in democratizing access to computing and ensuring that innovation is not protected by exorbitant pricing or artificial scarcity.”
Raw computing power is only part of the equation. Bitdeer AI’s cloud platform is up to 30% more affordable compared to hyperscalers’ cloud platforms, Lin said, allowing small businesses to start experimenting with AI from day one and confidently scale up as their needs grow.
“As small and medium-sized businesses mature and strengthen their strategies, the need for a robust AI infrastructure will grow exponentially,” she points out. “We are preparing for this by advancing our data center plans at our own pace and ensuring we have capacity for when the maturity curve steepens.”
In addition to budget constraints, another hurdle small businesses face in their AI journey is talent, Lin says. Many small teams lack the specialized skills to effectively implement AI and must choose between time-consuming in-house upskilling or costly external help.
Bitdeer AI’s cloud platform offers a user-friendly interface and comprehensive tool set, while the company continues to provide training and upskilling opportunities to small and medium-sized businesses through local partners.
Beyond infrastructure, Bitdeer AI supports local research, training and skills development to help Singapore businesses build AI capabilities over the long term.
Photo: Bitdia AI
“By partnering with local service providers, we contribute to strengthening the domestic supply chain,” says Lin.
“A strong local ecosystem naturally attracts foreign talent and investment, creating a virtuous cycle for Singapore.”
According to Research conducted by NTUC LearningHub Last October, three out of four business leaders in Singapore said their organizations were already exploring, testing and deploying agent AI, but many felt their teams were not ready. In fact, three out of five people don’t understand how agent AI will impact their operations.
This is where Bitdeer AI can bridge the gap and align efforts. Singapore National AI Strategy 2.0.
By localizing R&D to Singapore, we are building more local capacity. Advance the nation’s goal of tripling the AI talent pool.
Bitdeer AI’s R&D team in Singapore is building local technology capabilities by hiring and training specialized engineering talent, and supporting R&D efforts by providing much-needed GPU compute resources to Singaporean research institutes.
“For countries looking to move quickly with AI, Singapore will benefit from a greater diversity of AI vendors, providing a strong choice for businesses seeking an AI partner to grow their businesses,” says Mr Lin.
“If this leads to further successful proofs of concept and deployment, Singapore stands to benefit by strengthening its global position in AI.”
Learn how Bitdeer AI Cloud can support your AI efforts.
