As Egypt accelerates its transition toward a digital economy, cooperation with China is moving beyond telecommunications into cloud computing, data centers, smart cities and AI infrastructure, raising a broader question about whether technology transfer can also become knowledge transfer
Cairo - The technological partnership between Egypt and China is moving beyond traditional telecommunications and digital infrastructure.
As artificial intelligence emerges as one of the technologies reshaping the global economy, cooperation between the two countries is entering a new phase involving the infrastructure needed to power AI applications, data centers, cloud computing and smart cities, alongside efforts to train talent and connect education and scientific research more closely with market needs.
But behind this physical infrastructure lies a deeper question: Can Egypt benefit from Chinese technology not simply as a set of ready-made tools, but as knowledge that can be localized, developed and ultimately reproduced within the country?
Amer Tammam is a political analyst specializing in Asian and Chinese affairs. (Photo/Ayman El-Kady)
Amer Tammam, a writer, researcher and political analyst specializing in Asian and Chinese affairs, argues that Egypt-China cooperation in advanced technology has moved in recent years from telecommunications toward a more complex level centered on AI infrastructure and the digital economy.
For Egypt, he says, the shift offers an opportunity to draw on Chinese expertise in a field that has become a major priority for economies around the world.
The transition builds on a trajectory that began with cooperation in telecommunications but has gradually expanded into cloud computing, data centers and smart-city applications.
Tammam points to cooperation with Chinese companies, including Huawei, in cloud computing and data-center development, as well as the expansion of cooperation from government institutions into private-sector projects involving smart cities.
The significance of this new phase, he argues, lies not only in Egypt acquiring infrastructure capable of running AI applications, but in the long-term impact that infrastructure could have on knowledge and the economy.
Developing AI data centers in Egypt and positioning the country as a major hub for North Africa, and potentially for the wider African continent, could help localize knowledge and allow Egypt to benefit from Chinese expertise while creating an opportunity for the country to play a regional role in spreading that knowledge and technology.
This changes the meaning of infrastructure itself.
The issue is no longer simply about servers and data centers, but about building an ecosystem capable of absorbing technology and producing the talent, expertise and institutions needed to sustain it.
Tammam identifies two main areas in which Egypt could benefit from this cooperation.
The first is the transformation of the Egyptian economy from a traditional model toward a digital economy, a transition that countries around the world are pursuing as technology reshapes markets, institutions and services.
The second is knowledge transfer: developing data centers, training local talent and creating the digital infrastructure needed to turn technology from an imported product into expertise that can be developed within Egypt.
That distinction is crucial because AI cooperation is ultimately about more than purchasing technology.
If a country builds the infrastructure without developing the expertise needed to operate and advance it, the technology remains detached from the local knowledge base. But when infrastructure is linked to training, education and scientific research, it can become part of a broader process of capacity building.
Perhaps the most important element of the Chinese experience for Egypt lies beyond the technology itself.
Tammam argues that China has developed an important model for connecting knowledge, education and scientific research to the needs of industry and the market — an experience Egypt could draw on as it expands its own AI capabilities.
Egypt, he notes, has been moving in a similar direction through its growing focus on artificial intelligence and the establishment of technology-oriented universities and colleges.
In this sense, technology transfer does not have to be a one-way process. It can also provide an opportunity to rethink the relationship between universities, research centers, companies and the market.
The real challenge is therefore not simply importing the latest technologies, but building an environment capable of turning them into local knowledge, products, services and economic opportunities.
Tammam sees Egypt-China cooperation in AI and advanced technology through the lens of mutual benefit.
China has economic and technological interests in expanding the presence of its companies and business models in the Egyptian market. Egypt, meanwhile, can benefit from Chinese technology, expertise, training and knowledge transfer as it works to develop its economy and build local capabilities.
He also views China's approach as part of a broader international effort rather than a strategy focused exclusively on Egypt.
China, he argues, is seeking to expand access to AI technologies and knowledge globally, including through training for professionals from developing countries and the Global South.
That places Egypt-China cooperation within a wider framework in which commercial interests intersect with capacity building and knowledge transfer.
There is an important paradox here.
As AI infrastructure expands between Egypt and China, the technology itself is also entering one of the most sensitive areas of communication between the two countries: translation.
Amr Mogheth, Editorial Director at Bayt Al-Hikma for Culture, says machine-translation technologies have become a reality across the translation industry, but their use requires clear and rigorous standards.
In his view, AI should remain an assistant to the translator rather than become the engine driving the translation process.
Technology can help translators locate references and sources, understand concepts and cultural backgrounds, and work with certain types of reporting, tables and specialized terminology in areas such as economics, the arts and history.
But these functions do not mean that machines can replace human translators.
The limits become particularly clear in literary translation, where transferring the direct meaning of a sentence is not enough. The translator must also preserve the emotions, context and cultural weight of the original text.
Mogheth points to Chinese proverbs as a clear example. Their meaning is often inseparable from specific cultural and historical contexts, making them difficult to translate accurately even for a human translator.
AI tools may be able to translate the words, but that does not necessarily mean they can capture the cultural meaning behind them.
For that reason, Mogheth sees AI as a potential threat when it is used without sufficient awareness or understanding of the culture being translated. Used as an assistant, however, it can become an important tool for meeting the demands of the modern translation profession, particularly the need for speed, access to vast amounts of information and greater availability of resources.
Technology's role in translation goes beyond general-purpose AI tools.
Mogheth points to existing digital dictionaries and applications for Arabic and Chinese, including terminology databases capable of translating complete expressions.
But in his view, such tools are better suited to beginners and students than professional translators, who should not rely on them as substitutes for human expertise.
This brings the technology and translation stories together around a common principle: having the tool does not necessarily mean having the knowledge.
A data center capable of running advanced AI models is not enough by itself to create a knowledge economy. Likewise, a vast linguistic database cannot by itself produce a translation capable of fully understanding another culture.
In both cases, human expertise remains the link that turns technology into usable knowledge.
Tammam also argues that building these capabilities should not remain the responsibility of governments and companies alone.
Friendship associations and civil-society institutions, he says, can play a growing role in connecting companies, universities and research centers, particularly as their traditional role in cultural and scientific exchanges expands into areas linked to the market.
Such institutions can organize forums and meetings bringing together business leaders, startups, universities and research centers, creating channels of communication that extend beyond formal government institutions.
But the more important step, Tammam argues, would be to turn these activities from isolated events into permanent mechanisms.
He proposes establishing continuous communication networks between Egyptian and Chinese companies, platforms for presenting investment and partnership opportunities, programs for exchanging expertise and training, and training grants for universities.
In this model, friendship networks could evolve into innovation networks, complementing government-to-government engagement rather than simply operating alongside it.
Ultimately, the Egypt-China AI story is not simply a story about technology.
Data centers, cloud computing and smart cities represent an essential layer of the emerging digital infrastructure, but they cannot by themselves guarantee Egypt's transformation into a digital economy or a regional center for knowledge.
The other layer is human: researchers, programmers, translators, students, engineers, startups and universities capable of connecting scientific research with the market.
This is where the perspectives of Tammam and Mogheth converge, despite the different fields they represent.
The real benefit of technology does not come when machines replace people, but when technology gives people better tools to understand and engage with the world around them.
For Egypt and China, that may be the defining challenge of the next phase of their technology partnership: not simply building the infrastructure capable of running AI, but developing the human and knowledge infrastructure capable of understanding, localizing and using it to build a more knowledge-driven economy.
Technology can be transferred in servers and hardware. Knowledge, however, still needs people capable of understanding it.
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