Why OpenAI Taps Ex-Chancellor Osborne for Global AI Push

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Former UK Chancellor George Osborne | Credit: by Jack Taylor/Getty Images for SXSW London
Former UK Chancellor George Osborne joins OpenAI to lead government partnerships as it pursues a potential US$10bn investment from Amazon

As governments worldwide strive to learn how to regulate and deploy AI, technology companies are aiming to shape policy frameworks before rules become fixed. 

OpenAI is now making its move by hiring one of Britain’s most connected political figures.

Former UK Chancellor George Osborne has joined OpenAI as Managing Director (MD) and Head of OpenAI for Countries, working from London. 

The appointment puts a veteran of British politics at the centre of the company’s efforts to build relationships with governments across more than 50 countries.

Osborne served as Chancellor of the Exchequer from 2010 to 2016 under Prime Minister David Cameron. 

His role at OpenAI involves working with national administrations on AI infrastructure, digital literacy programmes and the deployment of AI systems in public services.

“I recently asked myself the question: what’s the most exciting and promising company in the world right now? The answer I believe is OpenAI,” George writes in a post on X. 

“So it’s a privilege to be going to work for OpenAI as Managing Director and Head of OpenAI for Countries, based here in London.”

Sam Altman, OpenAI CEO (Credit: Getty Images)

He adds that from his conversations with CEO Sam Altman and Chief Operating Officer (COO) Brad Lightcap: “it’s clear they are exceptionally impressive leaders and that they care very deeply about their mission to ensure the power of artificial intelligence is developed responsibly”.

The importance of building government partnerships

The OpenAI for Countries programme launched in May with what Chris Lehane, the company’s Chief Global Affairs Officer, describes on LinkedIn as: “a clear goal: working with governments to ensure that global AI systems are built on democratic values and that AI benefits all of humanity by expanding global prosperity and freedom”.

Chris says Osborne’s decision to join OpenAI reflects “a shared belief that AI is becoming critical infrastructure - and early decisions about how it’s built, governed and deployed will shape economics and geopolitics for years to come”.

Chris Lehane, OpenAI's Chief Global Affairs Officer

The timing is notable – because government-level discussions between the UK and US over a broader technology partnership, which included AI cooperation, have stalled in recent months. 

Meanwhile, the Bank of England warned earlier this month that AI expansion could be financed by trillions of dollars in debt over the next five years, raising concerns about overheating in the sector.

Osborne says the initiative “intends to help societies around the world share the opportunity this powerful technology brings”.

Why Amazon talks centre on chips and infrastructure

While Osborne focuses on governments, OpenAI is pursuing private sector deals on a substantial scale. 

The company is in discussions with Amazon, the cloud computing and e-commerce provider, about an investment exceeding US$10bn, according to people familiar with the matter.

Any agreement would include OpenAI using Amazon’s Trainium processors, custom chips designed for training AI models, alongside leasing additional data centre capacity from Amazon Web Services (AWS).

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These talks follow OpenAI’s October restructuring of its partnership with Microsoft, which has invested US$13bn in OpenAI since 2019. 

That change removed Microsoft’s exclusive rights as OpenAI’s primary computing provider, giving the AI company freedom to pursue agreements with competing infrastructure suppliers.

OpenAI has committed to spending US$38bn over seven years with AWS. 

The company has also secured more than US$1.4tn in infrastructure commitments with suppliers including Nvidia, AMD, Broadcom and Oracle.

Nvidia alone has agreed to invest up to US$100bn in a multi-year arrangement linked to purchases of its processors.

Training models like GPT-4, which powers ChatGPT, requires thousands of processors running simultaneously for months, which explains the scale of these infrastructure commitments.