Compute Power in 2025: Empowering SMEs to Scale AI

By Kevin Shepherdson, Founder and CEO, Straits Interactive

As AI-powered solutions such as generative AI apps, AI agents, automated reporting, and advanced analytics become integral to workplace operations, the demand for scalable compute infrastructure is surging. "Compute Power," the second trend in the ‘6Cs’ framework for 2025, highlights how small and medium-sized enterprises (SMEs) can leverage cloud-based and energy-efficient computing resources to stay competitive. This article explores key developments in compute power, real-world applications, challenges SMEs face, and actionable recommendations to ensure effective adoption and scaling of AI technologies.

Key Developments in 2024

1. Scalable Infrastructure Advancements

Innovations such as Amazon’s Ultracluster Supercomputer, Trainium chips, and NVIDIA’s Blackwell architecture have made high-performance computing (HPC) more accessible and affordable for businesses of all sizes. SMEs increasingly turned to these solutions for their ability to handle AI workloads efficiently.

2. Energy Efficiency Breakthroughs

The introduction of energy-efficient AI hardware highlights a growing focus on sustainability. This aligns with the Environmental, Social, and Governance (ESG) goals prioritised by many businesses.

Example: A logistics SME adopted cloud-based AI services powered by energy-efficient GPUs. The AI system analysed delivery routes in real time, reducing fuel costs by 15% while aligning with the company’s ESG targets.

2025 Trends in Compute Power

1. Cloud-Based AI Adoption

Hybrid cloud environments are becoming the go-to solution for SMEs, offering:

• Scalability: Resources can be scaled up or down based on demand.
• Affordability: Pay-as-you-go models reduce the need for significant upfront IT investment.
• Ease of Integration: Seamless integration with existing systems through software-as-a-service (SaaS) platforms.

Scenario: A small marketing agency uses a hybrid cloud setup to run AI-driven analytics tools during high-demand periods, such as seasonal campaigns, ensuring cost-effectiveness during off-peak times.

2. Prioritizing Energy Efficiency

With growing pressure to meet sustainability targets, SMEs are adopting energy-efficient computing solutions to:

• Minimise operational costs.
• Align with green initiatives and attract environmentally conscious customers.

Scenario: A manufacturing SME switches to an AI-driven inventory management system running on energy-efficient cloud servers, reducing data processing costs while lowering the company’s carbon footprint.

3. Democratised Access to AI Platforms

Advancements in SaaS-based AI platforms are levelling the playing field for SMEs by:

• Simplifying access to high-performance compute resources.
• Offering pre-configured AI solutions tailored to specific industries or business functions.

Scenario: A retail SME adopts a SaaS platform for automated customer segmentation, leveraging scalable AI capabilities without requiring in-house IT expertise.

Challenges SMEs Face

1. Limited IT Infrastructure

• SMEs often lack the on-premise infrastructure required for high-performance AI workloads.
• Dependence on legacy systems can hinder seamless integration with advanced AI tools.

2. Budget Constraints

• While cloud-based solutions are more affordable, ongoing subscription costs can strain tight budgets.
• Energy-efficient hardware remains cost-prohibitive for smaller businesses during its early adoption phase.

3. Data Security Concerns

• SMEs must ensure secure access to cloud-based systems to protect sensitive business and customer data.
• Compliance with data privacy regulations adds complexity to AI adoption.

Actionable Recommendations for SMEs

1. Leverage Cloud and SaaS Solutions

• Adopt SaaS-based AI platforms with pre-configured solutions to reduce the need for technical expertise.
• Use hybrid cloud setups to optimize costs while maintaining scalability.

Tip: Start with smaller AI projects, such as automated reporting or customer insights, to assess ROI before scaling.

2. Prioritize Cost-Effective Energy Efficiency

• Opt for cloud providers offering energy-efficient infrastructure to align with sustainability goals and reduce operational costs.
• Monitor energy consumption of AI workloads and optimize where possible.

Tip: Choose cloud services that provide transparency in energy usage, helping track your ESG progress.

3. Address Security and Compliance

• Use trusted cloud platforms with robust security features, such as encryption and access control.
• Regularly audit cloud usage to ensure compliance with regulations like GDPR or PDPA.

Tip: Partner with cybersecurity experts to secure sensitive data and reduce risks.

4. Build IT Partnerships

• Collaborate with AI and cloud service providers to customize solutions for your business needs.
• Explore government grants or SME-focused programs to subsidize AI adoption costs.

Tip: Join industry networks to share insights and learn best practices for scaling AI in SMEs.

Real- World Example

Transforming Customer Service with Scalable Compute Power

A boutique hotel chain implemented a SaaS-based AI chatbot for customer service. By integrating the chatbot with a hybrid cloud, the company scaled compute power during peak seasons to handle increased inquiries. The result was a 30% improvement in response time, enhanced customer satisfaction, and reduced operational costs.

Empowering SMEs with Scalable Compute Power

In 2025, scalable compute power is democratizing access to advanced AI solutions, enabling SMEs to compete with larger enterprises. By leveraging cloud-based AI, adopting energy-efficient infrastructure, and prioritizing data security, smaller businesses can unlock new levels of productivity and innovation.

Key Takeaways for SMEs:

1. Start small with SaaS-based AI platforms for immediate ROI.
2. Align AI operations with sustainability goals through energy-efficient cloud solutions.
3. Partner with trusted providers to navigate integration challenges and ensure data security.
   
   

With a clear strategy and thoughtful implementation, SMEs can harness the power of scalable compute infrastructure to thrive in the evolving AI landscape.