Interview
We spoke with Liu Chao, CEO of the Huawei’s Manufacturing & Key Enterprise Account enterprise unit, concerning the seismic affect AI is having for the manufacturing trade
At Cellular World Congress 2026, AI lastly seemed to be coming of age. From myriads of economic AI brokers to early demonstrations of bodily AI, it was clear that AI was lastly turning into
For Huawei’s Liu Chao, the period of treating AI as a high-tech accent is over for the manufacturing sector.
“AI is now greater than instruments,” stated Liu in an interview with Whole Telecom. “It may be a singular distinguisher for producers to set themselves aside from their opponents[…] AI is now turning into an necessary paradigm shift in innovation and in management.”
““This shift is being pushed not solely by the rising maturity of AI, but additionally by the pressing want for producers to strengthen their competitiveness. Established leaders in conventional manufacturing sectors, similar to automotive, are dealing with growing strain as extra gamers actively embrace advance applied sciences.
Given the precision and excessive requirements required in manufacturing, industrial gamers place a powerful emphasis on confirmed reliability and predictable outcomes. This implies they have an inclination to attend for brand new applied sciences have demonstrated clear worth and stability. For Liu, this urge to attend is a “entice”.
“Adoption of AI isn’t elective. It’s a compulsory selection it’s a must to make. The query isn’t whether or not to do it or not, however how you can do it,” he stated.
Bridging the experience hole
Maybe the largest hurdle to adoption, Liu defined, is the dearth of cross-discipline experience. Industrial consultants are sometimes not AI consultants, and vice versa,
“I believe one of many key priorities for producers adopting AI is deepening their understanding of the expertise and its evolving traits,” stated Liu. “This additionally means strengthening capabilities in information and digital infrastructure, whereas creating extra expertise with AI and IT experience – each of that are important to totally unlock the worth of AI.”
For AI adoption to scale throughout trade, each producers and tech firms have to domesticate multidisciplinary expertise that mixes each industrial and digital experience.
“We’d like AI consultants who’ve the data and background within the manufacturing sector,” he stated.
It’s only with this shared experience, Liu argues, that the trade will be capable of develop AI fashions tailor-made to the manufacturing sector’s particular wants.
“Normal fashions like OpenAI reply questions based mostly on public info. However relating to the info a few particular firm, trade, or course of, these fashions are usually not good at giving very particular solutions,” stated Liu. “In manufacturing firms, the info about operation administration, manufacturing processes, and analysis and improvement is proprietary and personal. So, they want specialised options.”
Sensible first steps: Pilot tasks and infrastructure foundations
With this in thoughts, what does early AI adoption appear to be for manufacturing firms?
For Liu, preliminary focus ought to be not on general transformation, however on addressing particular challenges.
“When a producing firm involves us and says they need to start utilizing AI, we first talk about their ache factors of their enterprise,” Liu stated, noting that figuring out the correct use instances can generate early worth.
“We have now to seek out some typical instances the place AI could be utilized and provides a fast win to our clients,” Liu stated. These early tasks usually act as pilot programmes that assist organisations construct inner expertise and refine their information methods.
“Within the first stage we establish situations as the primary batch of AI adoption pilots,” Liu defined. “Then within the subsequent step we overview their extra confidential or non-public information in manufacturing or R&D and assist them standardise it, prepared to be used in AI fashions.”
Automotive taking a lead
One manufacturing trade main the pack relating to AI adoption is the automotive trade.
“Every year in China, 50% of recent automobiles are related to the web and are electrical automobiles. The modifications available in the market are very quick. Lately, auto producers are launching their new automobile fashions nearly as regularly as cell phone makers are launching telephones,” he stated, including that “autonomous driving and good cockpit capabilities are all enabled by AI fashions.”
Probably the most superior carmakers are utilizing AI throughout product improvement, manufacturing facility operations, and high quality inspection. That is permitting clients to take pleasure in a far better stage of personalisation as a part of a C-to-M (Shopper-to-Producer) framework.
“It’s an end-to-end course of that enables full customisation by the shoppers,” explains Liu. “It’s how auto producers in China are attempting to win in such fierce competitors.”
“Within the meeting line, a completely assembled automobile is constructed each minute,” Liu continued. “When the shopper chooses a particular configuration – say, for instance, a yellow security belt – it’s a must to be sure that yellow belt arrives at precisely the correct level within the meeting course of. That wants AI-enabled scheduling with the info flowing from the order aspect on to the manufacturing.”
Networks come first
After all, a powerful basis of digital infrastructure is a vital requirement on this journey.
“The precondition is that you’ve very strong community connections and excellent {hardware},” Liu stated. “With out this, placing AI into motion is extremely tough.”
For Liu, the tempo of change means producers should proceed studying and adapting as AI applied sciences evolve.
“You can not watch for the most recent expertise for worry of being left behind as a result of AI is altering so rapidly,” he stated. “You need to be taught all through the method of adoption.”
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