The successive industrial revolutions have profoundly reshaped the fabric of human life and productivity through landmark breakthroughs in science and technology.Historically,each revolution has been characterized by the pivotal role of new production elements that redefine economic opportunity.While the first three industrial revolutions were primarily driven by mechanization,electrification,and automation,the ongoing Fourth Industrial Revolution heralds a new paradigm—one propelled by data as a core element,powered by intelligent technologies and the digital economy,pivoting towards significant productivity leaps.

One of the most salient features of the Fourth Industrial Revolution is the emergence of data as a potent factor of production.In prior epochs,particularly before the first industrial revolution during agrarian civilization,human labor constituted the linchpin of production,heavily reliant on population size to determine a nation’s economic volume.As industrial revolutions unfolded,capital gained prominence,further revolutionizing productivity mechanisms.Currently,we find ourselves at the precipice of the Fourth Industrial Revolution,where data has evolved into an even more dynamic and potential-rich element,driving qualitative changes and transformational surges in productivity.

As data ascends to prominence alongside traditional production elements like capital and technology,the composition of these factors is subject to change.Innovation can be viewed as the introduction of previously non-existent production factors and conditions into production systems,leading to the birth of emergent industries and enhanced efficiencies within traditional sectors through subsidiary innovations.In contrast to past industrial revolutions,which mainly showcased a new production function,today’s innovators harness algorithms to create diverse and efficient combinations of production factors.This leapfrogging of traditional constraints allows for increased connectivity along production chains,positioning data as an indispensable driving force fueling productivity enhancements.

In the contemporary landscape where data increasingly saturates production processes,human capacity for value creation is being propelled to new heights.At the macroeconomic level,the infusion of data has become a catalyst for the digitization of traditional sectors,enabling profound transformations that propel forward the dual paths of digital industrialization and industry digitization.This duality is spawning new production models and societal demands,increasingly directing industries toward becoming data-intensive economies.At the micro-level,the unique characteristics of data—as dynamic and rapidly accumulating—allow it to break free from previous production constraints,accelerating productivity development faster than conventional production factors.

Smart technologies represent a key trend in scientific innovation,essential for realizing transformative shifts in societal productivity.Throughout history,the advancement of science has been intertwined with disruptive technologies that cultivate universally applicable competencies.In the context of the Fourth Industrial Revolution,while the trajectory of technological innovation remains to be fully illuminated,it is apparent that smart technology is emerging as a significant focal point.Data’s extensive and self-reinforcing presence is catalyzing the rapid evolution of intelligent technologies.With the arrival of advanced AI systems like ChatGPT and DeepSeek,we witness a direct correlation between large-scale data training and technological emergence.

The overarching conception of smart technologies,as highlighted by McKinsey’s report on globally impactful emerging technologies,underscores the predominance of intelligent tech.These span mobile internet,IoT,cloud computing,advanced robotics,autonomous driving,automation of knowledge work,and 3D printing.Importantly,data enables these intelligent technologies to solidify their status as vital tools across various sectors,shifting the groundwork of technological efficacy from mere capital investment in equipment to dependency on data-driven insights and innovations.Smart technology is rapidly finding applications in diverse domains—including new materials,renewable energy,and environmentally sustainable practices—significantly enriching technological research processes with algorithms and computational power.

In practice,smart technologies manifest both in hardware and software innovations,with notable progress achieved.Robotics exemplifies how hardware is becoming increasingly intelligent.Previously,machines excelled at processing hard data; however,contemporary advancements aim to enhance their ability to comprehend complex human-centric ‘soft information.’ Concurrently,software applications have progressed—empowered by AI technologies,these applications not only serve as passive tools,but adapt to user habits while proposing targeted solutions and executing tasks autonomously.

This rapidly changing technological landscape necessitates a deeper examination of how data integration into production promotes systemic and diversified industrial forms.Unlike traditional production factors,data boasts impressive shareability and applicability,resulting in inclusive technology that is transformative.This gives rise to multifaceted industrial structures that are more holistic and interconnected,fostering a novel approach to building and evolving industrial systems.

Furthermore,nurturing the data-driven impetus can fluidly facilitate the establishment of a modernized industrial system.Initially,digital platforms served merely as marketplaces for matching supply and demand,akin to traditional market roles.However,with breakthroughs in smart programs and algorithmic learning,these platforms have metamorphosed,constructing unique business ecosystems and digital landscapes driven by relational dynamics as opposed to the efficacy of individual products or resources.

In these ecosystems,the value of platforms hinges less on product-specific quality,pivoting instead to the breadth and intricacy of the entire ecosystem,accounting for user interactions and network strength.Thus,as ecosystems develop,expand,and increase in value,they thrive on inclusivity—drawing on a diverse range of contributors and fostering synergies that reshape competition into a more collaborative model.

The rapid evolution of digital economies starkly contrasts the pace of progress in traditional industries.While sectors like automotive and steel required centuries for development,advancements in information industries can now occur within years or even months—showing undeniable evidence of the driving force exerted by data.Fully embracing the potential of data is crucial to harnessing the Fourth Industrial Revolution’s benefits.

Focusing on the pivotal role of data involves reinforcing the elements vital for productivity: labor,means of production,and labor object.To seize the moment presented by the Fourth Industrial Revolution,the cultivation and development of a new productive force will hinge on the effective empowerment of these elements through data-driven insights.

Significantly bolstering laborers’ digital skills is paramount.Unlike traditional labor characterized largely by repetitive tasks,the emerging talent required for new productive forces must adeptly navigate data and information technology,wield sophisticated digital tools,and exhibit agility in knowledge adaptation.This necessitates accelerated development of training pathways aimed at enhancing the digital acumen of the workforce while nurturing various roles,such as data entrepreneurs and data brokers,that will fortify human capital essential for fostering productivity evolution.

A robust digital infrastructure is equally decisive in promoting new productive forces,which mandates the establishment of cutting-edge production tools and materials.This entails enhancing advancements in 5G networks,IoT,industrial and satellite internet frameworks,as well as integrating AI,blockchain,and cloud-based infrastructures.Key infrastructural elements,such as big data centers and intelligent computation facilities,should be prioritized to enhance computational capabilities while cementing data exchange and accumulation.

It is also crucial to establish a resilient data industry ecosystem,focusing on the growth of big data and AI sectors.By guiding technological enterprises towards investing in generic technologies,we can lay the groundwork for emerging and future industries.This encompasses initiating industry clusters around automatic driving,drones,humanoid robotics,among others,providing essential scaffolds that will further deepen data accumulation and training scenarios.

Lastly,advancing new productive forces necessitates the cultivation of corresponding production relations.It is critical to establish a robust foundational framework to ensure seamless data rights management,trading,value distribution,and security governance,embedding data deeply into the processes of scientific innovation and productive advancements.