Global technology giants including Meta Platforms, Apple, Google, and Microsoft are increasing their investments in artificial intelligence (AI) hardware and wearable devices.
The move marks a transition from software-led AI strategies to a broader focus on physical infrastructure which powers intelligent systems.
Tech companies are positioning themselves to control the full AI value chain from custom-designed chips to consumer-facing wearables.
Adedayo Akande, specialist solutions architect at 54pay Technologies, described the trend as a long-standing play toward vertical integration.
“The ultimate vertical integration play has been in vogue for many years,” Akande said. “Think of it like a publisher that not only produces books but also owns the forests, mills the paper, and runs the press. By controlling the chips and hardware, these companies are not just participants but they own the stadium.”
According to him, the capital-intensive nature of AI infrastructure gives an advantage to cash-rich firms that can afford long-term investments in chip manufacturing and hardware ecosystems, ultimately securing a larger share of the AI market.
From cloud AI to personal AI
At the centre of this shift is the race to develop proprietary AI chips. These specialised processors are designed to handle complex machine learning workloads more efficiently than traditional CPUs, reducing costs and improving performance across both data centres and personal devices.
For major tech firms, controlling chip design is strategic because it allows them to reduce reliance on third-party suppliers such as Nvidia and optimise hardware for their own AI models, enabling faster and more responsive services from voice assistants to real-time translation.
The evolution also reflects growing demand for personal AI systems that adapt to user behaviour and operate seamlessly across multiple devices.
Wearables as next phase of computing
Wearable AI devices such as smart glasses, AI-powered earbuds, and body-integrated assistants are being positioned as the next phase of computing, moving beyond smartphones toward ambient, hands-free interactions.
Meta has already entered the space with AI-enabled smart glasses, while competitors are developing devices capable of capturing and processing real-world inputs continuously.
These tools promise features such as live transcription, contextual search, navigation assistance, and health monitoring.
Implications
For Nigeria, the development presents a mix of opportunity and challenge as Akande highlighted persistent infrastructure gaps, particularly unreliable power supply, as a major barrier.
“You can’t run world-class data centres on generators,” he noted, pointing to the limitations this creates for local AI advancement.
He also warned of increased dependency on foreign technology, as access to high-performance chips largely controlled by global suppliers which remains limited and expensive.
Without local manufacturing or large-scale hardware investment, Nigeria risks remaining a consumer rather than a stakeholder in the AI economy.
The rise of tightly integrated ecosystems could lead to hardware-software lock-in, making it more difficult and costly for consumers to switch between brands or combine different technologies.
Despite these challenges, opportunities remain as Nigeria’s growing pool of AI-focused entrepreneurs is already making strides in software innovation.
“If we can solve power and connectivity issues,” Akande said, “we move from catching up to actually hosting the future.”
