As Robin Li, chairman and chief executive of Baidu, says: “Baidu knows you better than you know yourself.”

Baidu, Alibaba and Tencent, have embraced AI with alacrity: setting up specialist labs at home and overseas and hiring top engineers. Much like their US peers such as Google, they are using machine learning to push into newer fields of autonomous driving, medical diagnosis, facial recognition for payments and AI-enabled hardware that can be operated by voice.

“We regarded AI as one of our top priorities last year and treat it as a strategic focus,” says Mark Ren, Tencent’s chief operating officer last month.

Alibaba takes a similar view, saying AI permeates “every aspect of our business?.?.?.?we don’t see it as a separate business unit.”

The difference now, says Xiaofeng Wang, senior analyst at Forrester, the consultants, is the scale of the data companies have and the speed with which machines are able to process it. “You can easily do personalisation for a group of customers, but if its millions it’s very hard, and it’s about how fast you can provide that,” she says.

Alibaba began highlighting its AI-powered improvements in this year’s earnings report. Jeff Zhang, chief technology officer, told analysts earlier this year that the biggest change was the scope of data — which now tops 1,000 PBs, equivalent to about 580bn books — it is able to process.

“We are generating and collecting all different kinds of data,” he says. “We want to leverage this to enable personalisation, to power search, security, customer service in all of these areas we are providing support through our data products.”

Some of that was in evidence on Singles Day, when Alibaba used AI to generate 400m customised banner advertisements in the month leading up to the shopping day. It also used chatbots, to answer 3.5m simple queries a day over the presale period, such as “Where’s my package?”

All of this was possible previously, through the use of microphones and cameras, but not on the massive scale and at the split-second speeds afforded by AI technologies.

Edouard de Mezerac, head of data and analytics for Asia-Pacific at Oliver Wyman, the consultancy, highlights another change under way on Taobao, Alibaba’s third-party ecommerce platform. It allows users to search by image using deep learning, a technique designed to emulate the way a human brain works, to find a matching or similar item. This enables shoppers, for example, to source a dress worn by a celebrity. “That does not exist on Amazon today,” he says.

It is still early days for the industry but applications such as these hint at how the country could take the global lead, say analysts, especially as companies ramp up how they use the technology.

Anand Swaminathan, a senior partner at consultants McKinsey, highlights two further factors that set China apart from Silicon Valley. “Their consumer testing ground is bigger than anywhere in the world,” he says. “Here they are testing with 1bn-plus people so for that reason the US is automatically handicapped. And the pace and scale of investment is fundamentally higher.”

The Chinese also generate far more data that is far more accessible. While Apple and Google have sought to fortify user data against governments, most notably last year when it thwarted the FBI’s attempt to unlock the San Bernardino shooter’s iPhone. Chinese companies are less coy.

Delegates at this month’s Fortune Global Conference in Guangzhou enjoyed unusual access to Google, Facebook and Twitter, services that are normally blocked in China. “I spoke to a number of folks here who said, ‘How nice of them to provide free WiFi so I can access everything’,” says Mr Swaminathan. “But that means [the companies] can access everything of yours.”

A hint of what could be coming from China’s tech giants is how they might use AI in communications and healthcare.

Alibaba is taking the voice-activated personal assistant concept a step further than Apple’s Siri or Amazon’s Alexa, with a plan to deploy ticket dispensing machines in subway stations that can cancel out background noise and focus purely on the person ordering the tickets.

The technology itself — essentially combining microphones and cameras to identify the speaker — has “a long history in research”, says Zhijie Yan, who heads up the speech interaction research at Alibaba.

What is new, he says, is its application into a real product, helped by improving technology, which means personal assistants can move to public arenas: airports, train stations, restaurants and reception desks.

Smarter AI and bigger data caches apply to medical applications too. Tencent is among those looking to corral the technology into detecting lung cancer at an early stage.

Helping on that score are cross-border collaborations, led by university researchers, such as a project enabling researchers in Hong Kong to access American databases so computers can learn to recognise the features of malignant nodules.

David Lam, assistant professor and specialist in respiratory medicine at the University of Hong Kong, says it will be five years before early results from projects materialise.

One reason is that data sharing is complicated by the fact different ethnicities have different characteristics. Lung cancer affords one example: in the US, UK and much of the world, the main cause is smoking. That is not the case in Hong Kong, Taiwan and South China, where there is also far more prevalence among women.

But Si Chen, senior strategy manager at Tencent’s AI lab, says the requisite perception and decision-making learning to beat those games will resonate.

“In the real world that is the same as self-driving,” she says. “Based on your sensors or what you can see, you have an understanding of the environment and from that be able to make decisions and take an action, which could be to turn the steering wheel left or brake.”