Nvidia’s record $100B OpenAI investment, Microsoft’s cooling breakthrough, and Google’s DORA report revealing 90% developer AI adoption mark a turning point. Soaring energy demands, trust gaps, and reliance on AI signal a workforce and infrastructure transformation reshaping global technology.
Perth-based operational technology firm Intellect Systems has been targeted by the Akira ransomware group, which claims to have stolen 10GB of sensitive corporate and personal data. The attack highlights the growing threat to the critical infrastructure sector through vulnerable network devices.
US casino operator Boyd Gaming has confirmed a cyberattack that resulted in the theft of employee data and information from a limited number of other individuals. The company is investigating the incident and has notified relevant authorities.
Nvidia’s record $100B OpenAI investment, Microsoft’s cooling breakthrough, and Google’s DORA report revealing 90% developer AI adoption mark a turning point. Soaring energy demands, trust gaps, and reliance on AI signal a workforce and infrastructure transformation reshaping global technology.
As September draws to a close, we have witnessed numerous pivotal developments in what has been an extraordinary year of AI announcements and Wall Street achievements. This is Part One of a two-part series, examining the surge in AI infrastructure investment and developer adoption. Part Two will explore Microsoft’s cooling breakthrough and the future of data centre technologies.
Nvidia's unprecedented $100 billion investment announcement in OpenAI this week represents the largest single AI infrastructure commitment in history, fundamentally reshaping the global AI development landscape. This massive capital deployment coincides with Microsoft's breakthrough microfluidics cooling technology, creating a perfect storm of infrastructure expansion that addresses both the processing power and energy constraints highlighted by industry leaders.
The accelerating cycle gains momentum from Google Cloud's 2025 DORA research report, released simultaneously with Nvidia's announcement, revealing that AI adoption amongst software developers has surged to a striking 90%, marking a 14% increase from the previous year. This near-universal adoption creates an exponential feedback loop: enhanced infrastructure enables broader AI access, which spawns a new generation of AI-native developers who drive even greater computational demands.
Google's comprehensive survey of nearly 5,000 technology professionals globally demonstrates that AI has transcended experimental status to become integral to modern software development. The DORA report states that AI adoption amongst software development professionals has reached 90%, with developers now dedicating a median of two hours daily to AI-powered tasks, integrating these tools into core workflows spanning code generation, testing, and security reviews.
A substantial 65% report heavily relying on AI for software development work, with 37% describing "moderate" reliance and 28% expressing "a lot" or "a great deal" of dependence. Ryan Salva, who oversees Google's coding tools including Gemini Code Assist, noted in a recent interview with CNN that the "vast majority" of teams at Google are incorporating AI into their workflows.
"If you are an engineer at Google, it is unavoidable that you will be using AI as part of your daily work," Salva explained.
The productivity implications are remarkable: over 80% of respondents indicate that AI has enhanced their productivity, whilst a majority (59%) report a positive influence of AI on code quality, according to the DORA findings. At Google itself, AI tools have increased engineering team productivity by 10%, with more than 25% of the company's new code now generated by AI systems under human oversight.
Nvidia's strategic partnership with OpenAI involves deploying 10 gigawatts of AI systems, equivalent to powering between 4-5 million GPUs, with the first gigawatt expected operational by late 2026. The investment structure operates through two interconnected transactions: OpenAI purchases Nvidia chips with cash whilst Nvidia acquires non-voting equity stakes in return.
This arrangement ensures Nvidia maintains its dominant position in the AI supply chain whilst securing long-term revenue streams from the world's most valuable AI company. The partnership will deliver vast GPU-powered facilities, enabling OpenAI to handle both the training and deployment requirements of its upcoming generation of AI systems.
“There’s no partner but NVIDIA that can do this at this kind of scale, at this kind of speed,” said Sam Altman, CEO of OpenAI.
Jensen Huang's characterisation of modern data centres as "AI factories" that convert energy into intelligence highlights the fundamental constraint facing AI expansion.
“AI is now infrastructure, and this infrastructure, just like the internet, just like electricity, needs factories,” Huang said. “These factories are essentially what we build today.”
The timing of this announcement follows Nvidia's recent investment spree, including a £3.9 billion commitment to Intel for AI processor collaboration and nearly £550 million in UK-based data centre startup Nscale.
Framing the Intel partnership as more than a supply deal, Huang described it as a union of platforms: "This historic collaboration tightly couples Nvidia's AI and accelerated computing stack with Intel's CPUs and the vast x86 ecosystem — a fusion of two world-class platforms. Together, we will expand our ecosystems and lay the foundation for the next era of computing."
Excited to team up with my good friend Jensen to jointly develop multiple generations of custom data center and PC products!
— Lip-Bu Tan (@LipBuTan1) September 18, 2025
Our collaboration brings together the best of @Intel and @nvidia to benefit customers – and shows how vital x86 architecture and NVLink will be in… pic.twitter.com/lnEtmJW73A
Intel CEO Lip-Bu Tan shared on X how excited he is to team up with Jensen Huang.
Despite widespread adoption, a significant trust gap persists amongst developers, with only 24% expressing high levels of trust in AI-generated code. The DORA research reveals that
"while most say AI makes them faster and more productive, only 24% say they trust it 'a lot' or 'a great deal.' Nearly a third admit they trust it 'a little' or not at all".
Nathen Harvey, the study's lead researcher and a developer advocate at Google Cloud, told Observer in an interview:
"Boardroom-level prioritisation shows that this change is likely here to stay. Every organisation is facing pressure to improve software performance even in the face of broad economic pressures and constraints".
This trust deficit paradoxically drives greater infrastructure demand, as verification, testing, and quality assurance processes require additional computational cycles.
The energy demands are staggering and accelerating: US data centres could consume up to 580 terawatt-hours annually by 2028, representing 12% of total US electricity consumption, compared to 4.4% in 2023. Individual AI data centres now require up to 2 gigawatts of power, equivalent to supporting 1.5 million homes.
The computational demands are growing faster than Moore's Law can address, with AI's insatiable appetite pushing toward 100 gigawatts of new demand in the US by 2030. This exponential growth directly correlates with the near-universal developer adoption Google's research identifies, as 90% of software professionals now depend on AI tools for daily productivity gains.
The convergence of universal AI adoption and massive infrastructure investment signals a fundamental shift in the technology workforce landscape. As developers become increasingly dependent on AI tools for productivity gains, organisations must balance the promise of enhanced efficiency with the need for robust verification processes and human oversight.
The data suggests we are witnessing not just a technological evolution, but a complete transformation of how software development teams operate, with implications extending far beyond the technology sector into every industry relying on digital innovation.
The convergence of Nvidia's investment strategy, Microsoft's cooling innovations, Google's developer adoption findings, and the relentless growth in AI computational demands creates a self-reinforcing acceleration cycle that will define the next phase of technological development.
Next week: Part Two examines how Microsoft's cooling breakthrough and emerging data centre technologies are reshaping the physical infrastructure required to support this AI transformation.
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