Amazon Web Services has initiated talks to sell its AI chips - the Trainium and Inferentia processors - to external data centers outside of AWS. This represents a significant shift in strategy. Until now, these chips were exclusively available within Amazon's cloud ecosystem.
CEO Andy Jassy has called this move a $50 billion opportunity. Therefore, AWS is no longer just competing with Nvidia on performance: it's now also entering the hardware distribution market. However, the challenge is complex. Nvidia holds a dominant share of global AI infrastructure, with an established partner network and a software ecosystem—led by CUDA—that is difficult to replicate.
For Italian cloud-native SMEs, this scenario opens concrete prospects. In fact, increased competition among AI chip providers tends to reduce computational costs in the medium term. We at SHM Studio we monitor these dynamics to guide our clients' infrastructural choices toward solutions AI more efficient and sustainable. In summary: the AI chip market is opening up, and SMEs would do well to follow its evolution.
Amazon's course correction in the AI chip market
Until a few months ago, AI chips developed by Amazon — processors Trainium for training and Inference for inference—they were only accessible through AWS infrastructure. No external data center could purchase them or integrate them into their own systems. Today, according to reports TechCrunch, This logic is changing.
AWS has entered into formal negotiations to sell its chips to third-party data centers. CEO Andy Jassy has publicly estimated the value of this opportunity at 50 billion dollars. This is a figure that signals a precise ambition: no longer just a cloud provider, but a global AI hardware supplier.
Therefore, Amazon no longer competes with Nvidia solely on cloud services. It is now entering the physical distribution segment of processors. This is a field where Nvidia has built a structural advantage in recent years.
Why Nvidia remains a formidable opponent
Nvidia currently holds an estimated market share of between 70% and 80% of the AI chip market, according to an analysis by Gartner. The advantage isn't just technological. It's ecosystemic.
The platform CUDA — Nvidia's parallel programming framework — is integrated into almost all major machine learning frameworks: PyTorch, TensorFlow, JAX. Furthermore, the hardware and software partner network built by Nvidia over time represents a considerable barrier to entry.
Amazon, on the contrary, is betting on an alternative ecosystem based on Neuron SDK. However, the maturity of this stack is still lower compared to CUDA. Consequently, convincing data centers to replace or augment Nvidia GPUs with Trainium chips will require a non-trivial amount of technical evangelization.
Despite this, the strategic signal is clear. Amazon has no intention of being confined to its own cloud. The move is reminiscent, in some ways, of the strategy adopted by Amazon itself with AWS in the 2000s: monetizing an internal infrastructure by transforming it into a commercial product.
The AI chip market in 2026: a sector in redefinition
The context in which this move fits is already in turmoil. In 2025, several hyperscalers had accelerated the development of proprietary chips. Google with TPUs, Microsoft with the Maia project, Meta with its own custom accelerators. Therefore, the trend to reduce dependence on Nvidia is not exclusive to Amazon.
What sets AWS strategy apart is its willingness to selling outdoors, not just for internal use. This creates a new market segment. In fact, independent data centers—those that don't belong to the large hyperscalers—could find an alternative supplier in Amazon at potentially more competitive prices.
In addition to this, diversifying hardware supply sources has become a geopolitical priority. Tensions in semiconductor supply chains, which became acute between 2022 and 2024, have prompted many operators to seek alternative suppliers. Amazon positions itself in this space with strategic timing.
Concrete impact for Italian cloud-native SMEs
For small and medium-sized Italian businesses operating in cloud environments—or considering integrating AI solutions in their own processes—this news has practical, albeit not immediate, implications.
First, increased competition among AI chip providers tends to reduce computational costs in the medium term. Therefore, machine learning workloads—from document classification to predictive sales analysis—could become economically accessible even for smaller organizations.
Secondly, the availability of alternatives to Nvidia chips could translate into greater flexibility in cloud provider offerings. For example, AWS might offer Trainium instances at lower costs than Nvidia GPU-based instances, incentivizing migration to more efficient AI architectures.
Finally, for SMEs already using AWS as their primary infrastructure, the news suggests a strengthening of the Amazon ecosystem. Therefore, investing in skills on Neuron SDK and Trainium instances could prove to be beneficial in the next two years.
What official statements don't say
Andy Jassy's statements are optimistic, as expected from a CEO introducing a new line of business. However, some issues remain unresolved.
The first concerns the Software compatibility. Selling chips to third-party data centers means that the latter must be able to manage them autonomously. Without a mature and documented software ecosystem, the risk of slow adoption is real. We at SHM Studio we often observe this dynamic in projects involving digital transformation: The technology is available, but adopting it requires time and expertise.
The second node concerns the Competitive positioning. Selling chips to competing data centers means, to some extent, strengthening infrastructure that could compete with AWS itself. It's a strategic tension that Amazon will have to manage carefully.
The third element concerns the times. Negotiations are still ongoing. There is no mass-market product yet. Consequently, SMEs should not expect immediate operational changes.
What to observe in the next 12-18 months
The most relevant time window for evaluating the impact of this strategy extends to the end of 2027. Some indicators deserve special attention.
- Partnership announcements between AWS and independent European or American data centers.
- Neuron SDK Updates that increase compatibility with standard frameworks.
- Price variations Amazon chip-based cloud instances versus Nvidia ones.
- Nvidia's reactionPossible exclusive agreements or price reductions to retain data center partners.
For those who manage SEO strategy, Google Ads campaigns o LinkedIn campaign with AI components, the cost of inference is already a relevant variable today. Similarly, those who develop applications on web platforms With integrated language models, you will find an element to monitor in this evolution.
To further explore how these dynamics influence the technological choices of SMEs, the team SHM Studio is available for consultation. Furthermore, on our blog We regularly publish analyses on AI, cloud, and digital infrastructure for the Italian market.
In summary: Amazon's move is ambitious and structurally consistent with its history. However, the path to a direct challenge to Nvidia is still long. Italian SMEs would do well to follow developments, without expecting immediate revolutions. The AI chip market is reopening — and this, in the medium term, is good news for those who invest in artificial intelligence applied al business.
Related articles
Discover other articles that explore similar topics in depth, selected to give you a more complete and stimulating view. Each piece of content is carefully chosen to enrich your experience.
