In today’s rapidly evolving digital landscape, the convergence of data and artificial intelligence (AI) is emerging as a powerful force driving innovation and reshaping industries. As we witness the dawn of a new level of intelligence, spearheaded by foundation models and AI-generated content (AIGC), it is clear that enterprises must embrace this transformation to remain competitive.
The potential impact is staggering. By 2026, it is predicted that over 80 per cent of businesses will leverage AIGC in production, revolutionising 70 per cent of design and development work. Furthermore, by 2028, a remarkable 75 per cent of software engineers are expected to collaborate with AI assistants, a significant leap from the mere 10 per cent at the beginning of 2023.
In this digital wave, data is the cornerstone, redefining enterprise operations, management, decision-making, and innovation. Building a “data-driven modern enterprise” has become a core objective for a growing number of organisations. However, the path to realising this vision is not without challenges.
Firstly, the exponential growth of data, fueled by the widespread adoption of AIGC, demands robust infrastructure capable of receiving, storing, and processing massive volumes of information. The speed, scale, and diversity of data generation often surpass the capabilities of current systems, hindering the efficient extraction of valuable insights.
Secondly, data fragmentation poses a significant obstacle to seamless sharing and transfer. Many enterprises grapple with complex data processing technology stacks that operate in silos, impeding the free flow of information and hampering collaborative work.
Lastly, the development cycle for intelligent applications is often lengthy, with high entry barriers and diverse analysis dimensions. The cost of interdepartmental collaboration and the need for customised development strain resources and limit the potential for data monetisation and operational efficiency.
Yet, data’s true worth is unlocked only when it is shared and put into action. But unleashing the potential of data elements is a complex, multi-step journey that harnesses the power of big data and AI. These two technologies are inextricably linked, requiring deep integration to fully realise their potential. The foundation for successful, high-quality AI application implementation lies in effective data governance. By embracing automatic and intelligent management across the entire data lifecycle, organisations can make big data value mining accessible to all.
Innovative technology providers recognise this imperative. For example, Huawei Cloud has proposed an “AI for Cloud” and “Cloud for AI” strategy. By leveraging AI and foundation models, Huawei Cloud enhances customer experiences, reshapes industry applications, and elevates cloud services. Simultaneously, through architectural innovations, AI-native storage, and data-AI convergence, Huawei Cloud empowers enterprises to adopt and efficiently utilise AI technologies seamlessly.
Central to this approach is the concept of “Data4AI and AI4Data.” Quality data fuels the training and inference of foundation models, while AI engines intelligently govern data throughout its lifecycle. For instance, Huawei Cloud’s LakeFormation technology enables the creation of a unified logical data lake, allowing multiple data analytics and AI engines to share a single copy of data without the need for migration. The collaborative pipelines of DataArts, ModelArts, and CodeArts orchestrate data and AI workflows, facilitating real-time model training and inference.
Moreover, integrating data with large AI models accelerates digital intelligence across governments and enterprises. Digital Human Assistance, powered by advanced technologies like Text-to-Speech (TTS) and Speech-to-Text (STT), delivers a natural and efficient user experience. By incorporating large language models (LLMs), these systems enable multi-topic conversations, efficient information retrieval, and prioritise user safety.
As we navigate the digital and intelligent era, the convergence of data and AI emerges as the engine drives value reshaping and enables service innovation. Cloud is at the forefront of this transformation, striving to accelerate data intelligence innovation for governments and enterprises by building a robust data-AI convergence platform.
The time has come for organisations to embrace the power of data-AI convergence and embark on a digital transformation journey. By harnessing the potential of this synergy, enterprises can unlock new levels of efficiency, innovation, and competitiveness. The future belongs to those who dare to leverage the intelligence born from the union of data and AI. Will your organisation be among the pioneers shaping the intelligent world of tomorrow?
