As AI adoption continues to surge, the tech infrastructure market is undergoing a significant transformation. Traditional IT infrastructure providers are facing increasing pressure to innovate and adapt to the evolving demands of AI-powered applications. This shift is driving the development of new technologies and solutions that can support the intensive computational requirements and data-intensive nature of AI workloads.
At Lenovo’s recently held Asia Pacific summit in Shanghai they detailed their ‘AI for All’ strategy as they prepare for the next computing era. Building on their history as a major force in the hardware market, new AI-ready offerings will be prominent in their enhanced portfolio.
At the same time, Lenovo is adding software and services, both homegrown and with partners, to leverage their already well-established relationships with client IT teams. Sustainability is also a crucial message as it seeks to address the need for power efficiency and zero waste lifecycle management in their products.
Ecosystm Advisor Darian Bird comment on Lenovo’s recent announcements and messaging.
Click here to download Lenovo’s Innovation Roadmap: Takeaways from the APAC Analyst Summit as a PDF
1. Lenovo’s AI Strategy
Lenovo’s AI strategy focuses on launching AI PCs that leverage their computing legacy.
As the adoption of GenAI increases, there’s a growing need for edge processing to enhance privacy and performance. Lenovo, along with Microsoft, is introducing AI PCs with specialised components like CPUs, GPUs, and AI accelerators (NPUs) optimised for AI workloads.
Energy efficiency is vital for AI applications, opening doors for mobile-chip makers like Qualcomm. Lenovo’s latest ThinkPads, featuring Qualcomm’s Snapdragon X Elite processors, support Microsoft’s Copilot+ features while maximising battery life during AI tasks.
Lenovo is also investing in small language models (SLMs) that run directly on laptops, offering GenAI capabilities with lower resource demands. This allows users to interact with PCs using natural language for tasks like file searches, tech support, and personal management.
2. Lenovo’s Computer Vision Solutions
Lenovo stands out as one of the few computing hardware vendors that manufactures its own systems.
Leveraging precision engineering, Lenovo has developed solutions to automate production lines. By embedding computer vision in processes like quality inspection, equipment monitoring, and safety supervision, Lenovo customises ML algorithms using customer-specific data. Clients like McLaren Automotive use this technology to detect flaws beyond human capability, enhancing product quality and speeding up production.
Lenovo extends their computer vision expertise to retail, partnering with Sensormatic and Everseen to digitise branch operations. By analysing camera feeds, Lenovo’s solutions optimise merchandising, staffing, and design, while their checkout monitoring system detects theft and scanning errors in real-time. Australian customers have seen significant reductions in retail shrinkage after implementation.
3. AI in Action: Autonomous Robots
Like other hardware companies, Lenovo is experimenting with new devices to futureproof their portfolio.
Earlier this year, Lenovo unveiled the Daystar Bot GS, a six-legged robotic dog and an upgrade from their previous wheeled model. Resembling Boston Dynamics’ Spot but with added legs inspired by insects for enhanced stability, the bot is designed for challenging environments. Lenovo is positioning it as an automated monitoring assistant for equipment inspection and surveillance, reducing the need for additional staff. Power stations in China are already using the robot to read meters, detect temperature anomalies, and identify defective equipment.
Although it is likely to remain a niche product in the short term, the robot is an avenue for Lenovo to showcase their AI wares on a physical device, incorporating computer vision and self-guided movement.
Considerations for Lenovo’s Future Growth
Lenovo outlined an AI vision leveraging their expertise in end user computing, manufacturing, and retail. While the strategy aligns with Lenovo’s background, they should consider the following:
Hybrid AI. Initially, AI on PCs will address performance and privacy issues, but hybrid AI – integrating data across devices, clouds, and APIs – will eventually dominate.
Data Transparency & Control. The balance between convenience and privacy in AI is still unclear. Evolving transparency and control will be crucial as users adapt to new AI tools.
AI Ecosystem. AI’s value lies in data, applications, and integration, not just hardware. Hardware vendors must form deeper partnerships in these areas, as Lenovo’s focus on industry-specific solutions demonstrates.
Enhanced Experience. AI enhances operational efficiency and customer experience. Offloading level one support to AI not only cuts costs but also resolves issues faster than live agents.
While there has been much speculation about AI being a potential negative force on humanity, what we do know today is that the accelerated use of AI WILL mean an accelerated use of energy. And if that energy source is not renewable, AI will have a meaningful negative impact on CO2 emissions and will accelerate climate change. Even if the energy is renewable, GPUs and CPUs generate significant heat – and if that heat is not captured and used effectively then it too will have a negative impact on warming local environments near data centres.
Balancing Speed and Energy Efficiency
While GPUs use significantly more energy than CPUs, they run many AI algorithms faster than CPUs – so use less energy overall. But the process needs to run – and these are additional processes. Data needs to be discovered, moved, stored, analysed, cleansed. In many cases, algorithms need to be recreated, tweaked and improved. And then that algorithm itself will kick off new digital processes that are often more processor and energy-intensive – as now organisations might have a unique process for every customer or many customer groups, requiring more decisioning and hence more digitally intensive.
The GPUs, servers, storage, cabling, cooling systems, racks, and buildings have to be constructed – often built from raw materials – and these raw materials need to be mined, transported and transformed. With the use of AI exploding at the moment, so is the demand for AI infrastructure – all of which has an impact on the resources of the planet and ultimately on climate change.
Sustainable Sourcing
Some organisations understand this already and are beginning to use sustainable sourcing for their technology services. However, it is not a top priority with Ecosystm research showing only 15% of organisations focus on sustainable procurement.
Technology Providers Can Help
Leading technology providers are introducing initiatives that make it easier for organisations to procure sustainable IT solutions. The recently announced HPE GreenLake for Large Language Models will be based in a data centre built and run by Qscale in Canada that is not only sustainably built and sourced, but sits on a grid supplying 99.5% renewable electricity – and waste (warm) air from the data centre and cooling systems is funneled to nearby greenhouses that grow berries. I find the concept remarkable and this is one of the most impressive sustainable data centre stories to date.
The focus on sustainability needs to be universal – across all cloud and AI providers. AI usage IS exploding – and we are just at the tip of the iceberg today. It will continue to grow as it becomes easier to use and deploy, more readily available, and more relevant across all industries and organisations. But we are at a stage of climate warming where we cannot increase our greenhouse gas emissions – and offsetting these emissions just passes the buck.
We need more companies like HPE and Qscale to build this Sustainable Future – and we need to be thinking the same way in our own data centres and putting pressure on our own AI and overall technology value chain to think more sustainably and act in the interests of the planet and future generations. Cloud providers – like AWS – are committed to the NetZero goal (by 2040 in their case) – but this is meaningless if our requirement for computing capacity increases a hundred-fold in that period. Our businesses and our tech partners need to act today. It is time for organisations to demand it from their tech providers to influence change in the industry.
