Key trends in AI
With 2024 marking the "First Year of AI Application at Scale", expectations around AI continue to rise.
However, discussions this year have already shifted towards accelerating progress towards Artificial General Intelligence (AGI).
Additionally, AI evolution is becoming more structured, with AI agents leading the way. This shift aims to move generative AI beyond simply providing answers to actively executing actions.
Another key trend is the gradual lowering of AI application thresholds.
The release of DeepSeek’s open-source model (R1) in January has significantly reshaped the AI landscape, shifting the focus from simply increasing computing power to optimising its usage.
Open-source models are becoming more competitive, signalling a future where AI is more accessible across industries. However, the true measure of AI’s value lies in its ability to enhance productivity and drive social and economic growth.
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Challenges in industrial intelligent transformation
To fully capitalise on AI’s potential, several key challenges in digital and intelligent transformation must be addressed:
Integrating AI into industry-specific scenarios: Data silos remain a significant challenge. A Gartner survey indicates that 83% of data-driven projects fail due to these barriers.
Building robust ICT infrastructure: With 52% of enterprise systems unable to connect directly to intelligent platforms, existing ICT infrastructure requires substantial upgrades to accommodate the exponential growth of AI workloads.
Ensuring inclusive AI adoption: Gartner predicts that by the end of 2025, at least 30% of generative AI projects will be abandoned due to high costs. Sustainable AI adoption requires cost-effective solutions.
Developing ICT talent: A shortage of skilled professionals remains a barrier to continuous breakthroughs in intelligent transformation.
Huawei’s four-step approach
Define industry-specific ICT architectures: Huawei has established eight integrated teams spanning over 20 industries and 255 scenarios, successfully supporting the transformation of over 200,000 enterprises. Its strategy aligns technological investments with business goals, ensuring information collaboration, risk control, and scalable innovation.
Build AI-focused ICT infrastructure: To address AI’s growing demands, Huawei develops high-performance AI products that integrate seamlessly with open-source models. This approach enhances AI development toolchains, making AI adoption as universal as water and electricity.
Strengthen AI accessibility and affordability: Huawei prioritises partnerships to drive AI adoption, ensuring solutions remain cost-effective and widely accessible.
ICT talent development in targeted manner: Training initiatives help bridge the skills gap, ensuring industries have the expertise required for ongoing intelligent transformation.
Huawei’s deep understanding of industry-specific needs allows it to tailor solutions effectively.
For example, the financial industry is transitioning towards real-time payments, requiring "always-on" services and rapid risk management. To support this shift, Huawei developed the RAAS (Reliability, Availability, Autonomy, and Security) infrastructure.
As a result, Thailand’s Kasikorn Bank (KBANK) has adopted this scheme. Consequently, KBANK has tripled system performance while ensuring zero data loss and achieving an annual transaction growth rate exceeding 40%.
However, it is important to recognise that every industry faces unique challenges in intelligent transformation. Generally, an industry's transformation follows three key phases: informatisation, digitalisation and intelligence.
Future collaborations will introduce intelligent substation solutions to improve efficiency and accelerate grid transformation.
Leading products and solutions with AI-oriented infrastructure
Huawei continues to innovate across various domains. In terms of AI-oriented technology and product solutions, Huawei leverages its unique full-stack strengths in networking, storage, computing and cloud to set industry benchmarks continuously.
For example, Huawei has developed an industry-leading Multilayer Ransomware Protection (MRP) solution. This solution uses AI to detect threats accurately. With six layers of protection, it prevents data leakage and ensures service recovery within seconds of an incident.
Meanwhile, in connectivity and data transmission, the telecoms giant has built a high-throughput data centre network (DCN) using the industry's first 100-terabit DC switch. Additionally, with its innovative NSLB (Network Scale Load Balance) algorithm and StarryLink optical modules, AI training efficiency has improved by 10%.
In data storage, Huawei's next-generation OceanStor Dorado system introduces an innovative data-control separation architecture, tripling IOPS performance.
To meet both general and AI-specific computing needs, Huawei has developed Kunpeng for general-purpose computing and Ascend for intelligent computing.
To date, the company has more than 6.35 million developers working with Kunpeng and Ascend.
Finally, in cloud technology, Huawei Cloud has introduced Model as a Service (MaaS), enabling AI models to be deployed out of the box. Huawei Cloud also offers high-performance distributed GaussDB databases, which support up to one billion daily active users.
Empowering inclusive AI adoption
To foster inclusive AI adoption, Huawei announced that it is focusing on three key trends:
Open-source AI models: Lowering access barriers and democratising AI technology.
Synthetic data for industry-specific AI: Enhancing AI model performance without excessive raw data requirements.
Efficient AI deployment: Optimising computational demands for flexible implementation on edge devices.
Meanwhile, Huawei also actively supports the open-source MindSpore community, enabling over 3.15 million developers worldwide to enhance AI applications.
Despite already training eight million ICT professionals globally, Huawei now aims to nurture 10 million more by 2030.
In 2025, it will focus on two key initiatives:
Industry elites in the ICT classroom programme: Providing specialised training to enterprise professionals, ensuring they can drive transformation within their organisations.
Leading ICT talent cultivation programme: Equipping university students with advanced ICT knowledge to meet industry demands upon graduation.
Alongside this, at MWC 2025, Huawei showcased its leadership in industrial intelligent transformation by unveiling 83 global showcases across 71 key industry scenarios and launching 10 innovative solutions in collaboration with partners.
Speaking at the Summit, Leo Chen, Corporate Senior Vice President, President of Enterprise Sales, Huawei, highlighted four key pathways essential for industrial intelligence: the deep integration of AI into industry-specific scenarios, the development of AI-oriented ICT infrastructure, the enhancement of AI accessibility, and the advancement of targeted ICT talent development.
Through these initiatives and its collaborative approach, Huawei is shaping the future of industrial intelligence, making AI more accessible, cost-effective and impactful across various industries.
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