Core Transformations and Future Prospects of Individual Learning and Development in the AIGC Era

Core Transformations and Future Prospects of Individual Learning and Development in the AIGC Era

Li Sun., Lu Gao*

Software School, Harbin Information Engineering Institute

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.903SEDU0459

Received: 25 July 2025; Accepted: 31 July 2025; Published: 04 September 2025

ABSTRACT

Artificial Intelligence Generated Content (AIGC) is transforming the way individuals learn, with significant implications for future skill demands and personal development. Drawing on recent academic literature, authoritative reports, and practical cases from 2023 to 2024, this paper proposes a new framework for personal learning and growth in the AIGC era. AIGC enables collaborative learning between humans and AI, supports the intelligent generation of learning content, and allows learning to occur anytime and anywhere, thereby reshaping learning interactions, content formats, and the boundaries of educational access. Alongside these opportunities, new trends are emerging, such as the rise of augmented individuals, people whose capabilities are substantially enhanced through strategic AI use highlighting the need for continuous skill renewal and adaptation to AI-driven lifelong learning environments. However, these advancements also raise concerns regarding critical thinking, ethics, and fairness. Addressing such challenges requires coordinated efforts from individuals, educational institutions, and society to cultivate AI collaboration skills, promote critical and responsible AI use, and ensure that technological progress supports human-centered development. This paper offers both theoretical and practical insights into the evolving landscape of personal learning in the AIGC era, emphasizing the central role of human agency and values in shaping future educational and developmental pathways.

Keywords: Artificial Intelligence Generated Content (AIGC); individual learning; core competencies; lifelong learning; human-AI collaboration; AI ethics

INTRODUCTION

Artificial Intelligence Generated Content (AIGC) is advancing at an unprecedented pace, profoundly transforming global economies, societies, and the ways in which we live, learn, and develop (Brynjolfsson & Raymond, 2023). AIGC is produced by generative AI models, which create content based on intentional input derived from human-provided instructions (Shao et al., 2024). In the education sector, AI introduces innovative solutions that enhance learning experiences, streamline administrative tasks, and personalize instruction (Rane et al., 2023; Sajja et al., 2023).

This surge in AIGC innovation represents more than just a technological breakthrough. It marks a fundamental shift in how knowledge is acquired and constructed. Learners are no longer passive recipients of information; instead, they are actively engaging with content and shaping their own learning processes. This shift challenges traditional conceptions of essential skills, especially in areas such as critical thinking, adaptability, and interpersonal communication (Ellingrud et al., 2023). Consequently, there is an urgent need for new approaches that support long-term career development and foster lifelong learning.

At this pivotal juncture, the ability to engage meaningfully with AIGC for personal growth and value creation has become a critical skill across all sectors. Yet, much of the existing research remains narrowly focused, either emphasizing the technical mechanics of AIGC or its use in isolated educational contexts. What is missing is a comprehensive, interdisciplinary perspective that connects developments across domains and examines the broader forces shaping individual learning and development in the age of AIGC.

This paper seeks to fill that gap. Drawing on recent research and real-world practices in educational technology, cognitive science, AI ethics, and the future of work, it aims to provide a clear and integrated understanding of how AIGC is reshaping learning processes, redefining core competencies, and influencing personal development pathways. It also explores potential future directions and offers actionable strategies for individuals aiming to adapt and thrive in this rapidly evolving landscape.

LITERATURE REVIEW

Disruption and Reconstruction of Individual Learning Paradigms Under AIGC

AIGC technologies are fundamentally transforming the ways individuals acquire knowledge, engage with information, and construct understanding. Key developments include the emergence of more intelligent and adaptive forms of collaborative learning, the diversification of learning modalities, and the increasing accessibility of education anytime and anywhere.

Human-AI Collaboration: Leap from Tool Assistance to Intelligent Partnership

The role of AIGC in education has evolved significantly from serving as a simple support tool to becoming an active partner in the learning process (Hao et al., 2024). Today, AI provides a wide array of support mechanisms that go far beyond content delivery, including cognitive scaffolding, motivational reinforcement, emotional regulation, and the facilitation of collaborative learning.

For instance, AI can act as a personal tutor, offering individualized guidance based on a learner’s progress, or function as a “Socratic partner,” prompting deeper thinking through reflective questioning. AI-powered adaptive learning systems are capable of analyzing vast amounts of data on student performance, behavior, and preferences, allowing for highly personalized instruction (Gligorea et al., 2023). By utilizing tools such as knowledge graphs and behavior analysis models, AI can accurately identify learners’ strengths and areas for improvement, enabling it to design customized learning pathways that respond to each student’s unique needs.

Emerging research highlights the potential of AI, particularly through Natural Language Processing (NLP), to support learners as they process complex information, effectively enhancing comprehension and learning outcomes. Moreover, the success of collaborative learning environments depends heavily on how human–AI interactions are designed. Early findings from neuroscience suggest that well-timed AI interventions, such as offering help after a learner has attempted independent problem-solving may positively influence learners’ metacognitive awareness and understanding of their own thinking processes.

To fully leverage this potential, it is essential to teach learners how to engage critically and responsibly with AI in what is termed “learning with AI” (Long & Magerko, 2020). This involves equipping them with AI literacy skills that enable them to evaluate AI-generated suggestions, maintain control over their own learning, and avoid becoming overly reliant on automated systems. Ensuring that learners remain active participants in their education is critical for this evolving model to succeed.

Intelligent Generation and Ubiquitous Learning: Unlimited Expansion of Content and Scenarios

In recent years, AIGC has garnered substantial attention well beyond the discipline of computer science, as the broader public increasingly engages with content creation tools developed by leading technology companies (Yunjiu et al., 2022), such as ChatGPT (Schulman et al., 2022) and DALL•E 2 (Ramesh et al., 2022). AIGC refers to content produced using advanced generative artificial intelligence (GAI) techniques rather than by human authors, enabling the rapid, large-scale, and automated generation of diverse materials (Cao et al., 2023). For example, ChatGPT, a conversational language model created by OpenAI, is designed to process and respond to human input in a natural, contextually relevant, and meaningful manner.

Beyond its technological novelty, AIGC carries significant potential to reshape educational content and learning environments. It offers an innovative means of autonomously producing varied content formats by leveraging algorithms, machine learning models, and other AI-based technologies (Zhu et al., 2024). Advanced generative systems, including models capable of transforming text into high-quality video (OpenAI, 2024), are redefining traditional educational resources by replacing static text-and-image materials with dynamic multimedia content better aligned with cognitive learning processes. Early evidence suggests that AI-generated instructional videos can effectively communicate complex concepts, while educational platforms powered by large AI models are beginning to incorporate real-time “learning comments” to foster more interactive and collaborative classroom dynamics, enhancing both student engagement and participation.

AIGC also supports personalized learning experiences. AI-generated audio resources, such as educational podcasts, provide flexible opportunities for on-the-go learning, making efficient use of otherwise fragmented time. Similarly, AI-enabled microlearning systems break down knowledge into manageable units, adapt delivery to specific learning contexts, and apply evidence-based techniques, such as spaced repetition to improve retention. These developments decouple learning from fixed schedules and locations, creating truly ubiquitous access to education.

However, the unprecedented accessibility and flexibility enabled by AIGC present new challenges. Learners are required to take greater ownership of their motivation, develop critical skills to assess information from multiple sources, and synthesize fragmented inputs into coherent and structured knowledge. In parallel, the growing prevalence of AI-generated misinformation poses significant risks. Content produced by AI systems can occasionally be factually inaccurate, misleading, poorly substantiated, or incoherent (Cunha & Estima, 2023; Deng et al., 2023; Hagendorff, 2024). Sources of such misinformation include noisy or low-quality training data (Cui et al., 2024; Liu et al., 2023), stochastic sampling methods that introduce randomness (Cui et al., 2024), outdated knowledge repositories (Liu et al., 2023), and fine-tuning approaches that encourage overly agreeable or uncritical responses (Cui et al., 2024). Exposure to false or misleading information can shape inaccurate beliefs and perceptions, potentially leading to a range of adverse individual and societal consequences (Slattery et al., 2024).

Reconstruction and Cultivation of Individual Core Competencies in the AIGC Era

Facing profound transformations brought by AIGC, the landscape of individual core competencies is fundamentally reshaped, and their cultivation models urgently await innovation.

AI Literacy: Foundational Capability in the Digital Era

In the era of AIGC, AI literacy has become a core competency comparable in importance to reading, writing, and numeracy. Because AI systems can replicate and even intensify existing societal biases, AI literacy education must explicitly address these issues (Noble, 2018). However, AI literacy encompasses far more than the ability to operate digital tools. It requires a clear understanding of the foundational concepts underpinning AI, an informed awareness of its strengths and limitations, and a critical perspective on its ethical, social, and cultural implications.

Equally critical is the capacity to employ AI effectively to improve learning outcomes and workplace performance. This includes emerging competencies such as prompt engineering, the ability to craft precise and effective inputs to elicit accurate, relevant, and high-quality outputs as well as the skill to critically evaluate AI-generated content. At a deeper level, AI literacy demands the cultivation of ethical awareness and moral reasoning concerning AI’s role in society. A comprehensive AI literacy framework should therefore integrate technical proficiency with ethical reflection, critical thinking, and creative application. Such education should be continuous, spanning early childhood, formal schooling, higher education, professional training, and lifelong learning, with content tailored to developmental stages and specific learning contexts.

At present, AI literacy education remains fragmented and lacks a coordinated, systemic approach. Curriculum design should incorporate real-world case studies illustrating AI bias and its social consequences, alongside practical strategies for detecting and mitigating such biases (Baskara, 2025). There is a pressing need for a cohesive, age-appropriate, and lifelong curriculum that connects learning experiences across different educational phases, equipping individuals to navigate an AI-driven society with both competence and responsibility.

While technical expertise is a central element of AI literacy, the cultivation of humanistic values and independent critical thinking is equally vital (Aoun, 2017). Achieving the right balance between these dimensions presents a significant challenge for educators. Instruction should reinforce that AI is a tool designed to augment rather than replace human judgment and creativity. As AI capabilities advance, there is a growing temptation to delegate decision-making and problem-solving to machines (Paes et al., 2023). Although such delegation can yield efficiency gains, it also risks diminishing human engagement in cognitive processes that foster creativity and analytical reasoning. Over time, this could erode the capacity for independent critical thinking and problem-solving (Fui-Hoon Nah et al., 2023). Addressing this risk requires fostering an understanding of AI’s inherent limitations and emphasizing the enduring importance of distinctly human qualities such as empathy, ethical reasoning, and innovative problem-solving (Brynjolfsson & McAfee, 2014).

Higher-Order Cognitive Skills: “Hard Currency” in the AI Era

As AIGC excels at tasks involving information processing and content generation, the unique value of human cognition is shifting toward higher-order skills such as critical thinking, creativity, and complex problem-solving, abilities that are difficult for AI to replicate quickly or effectively (World Economic Forum, 2023). Yet AI plays a paradoxical role in developing these abilities: while it can support and enhance them, overreliance or misuse can undermine human cognitive engagement.

For instance, in developing critical thinking, AI can provide diverse perspectives, argument structures, and real-time fact-checking support. However, it is essential to teach users how to critically assess AI outputs through the practice of “AI fact-checking,” rather than accepting responses at face value. Similarly, in the realm of creativity, AIGC tools can expand creative boundaries and accelerate production, but human creativity remains distinct from the algorithmic “creativity” AI exhibits by remixing data. AI should be seen as a catalyst, offering inspiration and efficiency while the essence of originality remains a human domain.

To maximize the benefits of this relationship, an “AI double helix” model where humans and AI work in iterative, complementary cycles can foster enhanced creativity without diminishing human input. In light of these changes, traditional assessments that rely heavily on memorization are increasingly outdated. Educational evaluation must prioritize the learning process, cognitive strategies, and the application of higher-order skills to authentic problems.

Moving forward, developing innovative assessment methods, such as those based on learning processes, AI collaboration, project-based tasks, or even neurocognitive interfaces will be crucial in aligning evaluation practices with the demands of an AI-enhanced future.

Human-Centric Soft Skills: Irreplaceable Human Advantages

Although AIGC can imitate certain patterns of human thinking, it still falls short in areas that define our humanity, such as understanding genuine emotions, navigating subtle social dynamics, and making complex ethical decisions. This makes human soft skills including emotional intelligence, empathy, effective communication, and collaboration more important than ever for building meaningful connections, working in teams, and contributing uniquely in ways machines cannot (PwC, 2023).

Take emotional intelligence, for instance, it helps people build trust, lead with compassion, and respond sensitively to others’ needs. While AI can mimic emotional cues through learned patterns, it lacks real emotional depth or the ability to offer true comfort or moral judgment. That said, AI can still serve as a useful tool for practicing interpersonal skills, for example, by simulating conversations with virtual “patients” or role-play scenarios.

However, continued massive investment in AI research and development raises the possibility that AI systems could eventually rival or surpass human intelligence. AIs could cause permanent and severe harm when the objectives of human or superhuman-level AI are misaligned with human values and goals, and if they evade our control (Hagendorff, 2024; Yampolskiy, 2016). Studies have identified several technical challenges that may impede robust alignment, such as reward hacking, reward tampering, proxy-gaming, goal misgeneralisation, or goal drift (Gabriel et al., 2024; Hagendorff, 2024; Hendrycks et al., 2023). Further studies have also identified a range of harmful behaviors that AIs may exhibit if these misalignment challenges cannot be solved and if systems reach a certain level of advancement. For instance, misaligned AIs may resist human attempts to control or shut them down (Gabriel et al., 2024; Hagendorff, 2024).

Therefore, strong, nuanced communication is also essential in the future of work, especially as humans and AI increasingly collaborate. People not only need to interact clearly with AI systems but also communicate effectively within diverse teams that may include both humans and intelligent tools. Leaders, in particular, may need to develop the ability to shift seamlessly between different modes of communication, translating between technical language, business language, and public discourse. This requires a blend of empathy, subject knowledge, and clarity of expression.

In light of these shifts, education in the AIGC era must place greater emphasis on cultivating soft skills, not just delivering knowledge. Learners need hands-on opportunities to practice these abilities in real-world, emotionally rich, and socially complex situations. When paired wisely with technology, these human strengths can help ensure that innovation benefits not only individuals but also the broader society.

Innovation and Prospects of Individual Development Pathways in the AIGC Era

The AIGC tech wave changes how people learn and their main skills, and it also shakes up old career paths and lifelong ways of growing, so how people adjust to these changes and use AI to go beyond their own limits has now become a big new question for our time.

Rise of Augmented individual: AI-Empowered Productivity Revolution

Advancements in artificial intelligence are giving rise to augmented individuals and even “one-person enterprises,” as AI tools greatly extend what a single person can achieve independently. In this context, an augmented individual refers to a person whose capabilities are significantly enhanced through the strategic use of advanced technologies, particularly AI, enabling them to perform tasks, manage projects, and make decisions at a scale, speed, and quality that would traditionally require the coordinated efforts of a larger team or organization. This augmentation stems not only from access to technical tools, but also from the individual’s domain expertise, adaptability, and capacity to integrate human judgment with machine capabilities.

Tasks and projects that once required entire departments or large organizations can now be managed by one individual or a small, well-equipped team. A comprehensive AI toolkit may include systems for idea generation, process automation, and data-driven decision-making, each contributing to substantial gains in productivity and efficiency.

Emerging real-world cases illustrate this shift, demonstrating how AI serves as a powerful amplifier of individual capability. Yet, as this trend accelerates, the need for robust mechanisms of quality assurance and accountability becomes increasingly pressing. While AI acts as a critical enabler, the creativity, direction, and value-based judgments remain firmly within human control. At the core of this transformation lies effective human–AI collaboration, where individuals learn to leverage advanced technologies while retaining authority over outcomes. This evolution is reshaping organizational structures, redefining talent demands and prompting education systems to prepare people for a technology-integrated future. At the same time, it raises pressing questions of equity, including the risk of widening disparities between those who are highly augmented and those who are not, a dynamic sometimes referred to as the “barbell effect.” 

Career Transformation and Skill Reinvention: Embracing Dynamic Change

AIGC is rapidly transforming the landscape of job skills, raising urgent concerns about job security and the long-term relevance of existing competencies. According to Pearson (2024), many current skills are evolving or becoming obsolete, and a significant portion of the workforce will require extensive skill renewal. The traditional notion of “learn once, use for life” is no longer applicable. In its place, continuous learning, rapid adaptation, frequent skill updates, and even complete career shifts have become the new norm.

AI plays a dual role in this transformation: it is both a driving force of change and a powerful enabler that can help individuals navigate these disruptions. For instance, AI-powered personalized learning systems can recommend relevant resources, design customized skill development pathways, and deliver real-time feedback based on individual learning styles and evolving market demands. Furthermore, AI systems that incorporate career development frameworks can offer targeted support at different stages of a person’s career journey.

One of the most promising aspects of AIGC is its ability to enhance the efficiency and effectiveness of skill renewal. During times of career transition, individuals can use AI tools for self-assessment, identification of transferable skills, and planning tailored learning trajectories. To remain competitive and adaptable, individuals must focus on building “future-proof” skill sets, those that combine technical competencies in AI with uniquely human skills that are difficult to automate, such as emotional intelligence, ethical reasoning, and creative problem-solving. In addition, fluency in data, comfort with AI tools, and the ability to collaborate in hybrid human–AI teams are becoming essential for future workplaces.

In response to this evolving landscape, individuals must embrace change and adopt lifelong learning not just as a necessity, but as a core mindset and strength. Leveraging AI for self-directed learning and career planning will be critical. Ultimately, staying resilient, adaptable, and growth-oriented will empower individuals to thrive in a world where AIGC continuously reshapes the nature of work.

AI-Driven New Lifelong Learning Ecosystem

In the AIGC era, personal and professional growth increasingly depends on a new kind of lifelong learning system, one that supports continuous learning, ongoing skill development, and individual empowerment. Traditional models of education are no longer sufficient. What’s needed now is a smart, AI-powered, user-centered system that is flexible, personalized, and constantly evolving.

Research shows that AI can provide personalized learning experiences, improving student engagement and learning efficiency (Alam & Kachanac, 2023). For example, emerging platforms like Learning Experience Platforms (LXPs) use AI to understand each learner’s needs, suggest personalized content and learning paths, and adjust pacing in real time. As AI constructs user profiles by analyzing learning behavior data, creates personalized learning resources, and achieves adaptive learning, effectively enhancing student motivation and performance (Khan et al., 2023). These platforms integrate diverse learning resources with intelligent recommendations to make learning more relevant and efficient. At the same time, innovative tools like “learning accounts” and “skill passports” enabled by AI are being developed to securely track individuals’ learning journeys and work experiences. AI plays a central role in identifying skill gaps, recommending next steps, and helping individuals navigate their growth over time.

Looking ahead, future learning systems may include AI-adaptive content delivery, real-world ability assessments, and globally accessible shared learning platforms replacing outdated, one-size-fits-all curricula. Key components of this ecosystem could include credit banks, digital skill records, AI-based cloud learning environments, and immersive virtual training programs breaking down traditional barriers and widening access for learners everywhere.

In addition, AI-backed skill assessments and certifications will become foundational. By combining AI with secure technologies like blockchain, these systems could offer reliable, portable proof of skills acquired through various paths, whether formal education, online courses, or workplace experience. The goal is a future where a skill can be “verified once and recognized everywhere,” while individuals retain full control over their personal data.

However, building such a comprehensive AI-powered lifelong learning system will not be easy. It requires sustained collaboration across governments, educational institutions, technology companies, and individual learners. Continuous innovation, clear governance, and shared responsibility will be essential to ensure that this new learning infrastructure is inclusive, trusted, and effective for all.

DISCUSSION

This study investigates the transformative impact of AIGC on learning, essential skillsets, and pathways for future personal and professional development. It examines how AI is redefining individuals’ interactions with knowledge and shaping trajectories of personal growth. A central contribution of this paper lies in its integrated perspective, linking these changes while underscoring the critical role of individual agency in adapting to evolving technological landscapes.

The findings indicate that AIGC is driving a shift toward a learning paradigm characterized by human–AI collaboration, intelligent content generation, and ubiquitous access to information, positioning AI as a learning partner. Yet, this transformation also brings significant challenges, including the urgent need for broad-based AI literacy, the potential for cognitive offloading, and the risk of eroding deep, meaningful learning experiences. Future research should therefore investigate the influence of AI on learning processes and explore how interactive human–AI task design can sustain active learner engagement.

In relation to essential skills, the study highlights the broad dimensions of AI literacy, the rising significance of advanced cognitive abilities, and the enduring importance of human-centric soft skills. It also acknowledges AI’s complex and at times contradictory role in both enhancing and undermining these capabilities. Accordingly, further research should focus on identifying effective strategies for cultivating and evaluating these competencies across diverse learner demographics.

From a personal development standpoint, the study examines the emergence of augmented individuals, evolving career trajectories, continuous skill renewal, and AI-enabled lifelong learning. These developmental pathways rely not only on technological infrastructure but also on enabling policies, supportive organizational cultures, and sustained personal motivation. Future investigations could usefully assess the conditions that foster the success of augmented individuals and analyze the equity implications of AI-mediated learning, particularly in the context of sustaining human-centered skills.

At the same time, the advancement of AIGC has intensified risks associated with powerful dual-use technologies such as voice cloning, deepfakes, automated content generation, and large-scale data collection (Cunha & Estima, 2023). As these tools become more affordable, efficient, and accessible, they are increasingly within reach of actors with malicious intent. AI-driven capabilities can amplify disinformation by producing personalized, persuasive, and widely distributed content (Gabriel et al., 2024). For instance, integrating advanced AI into phishing schemes enables cybercriminals to automate the creation of highly sophisticated images, videos, and audio messages (Cunha & Estima, 2023; Gabriel et al., 2024).

This study is not without limitations. The rapid pace of AIGC development means that its long-term effects remain uncertain, and the analysis relies primarily on recent data. Moreover, space constraints limit detailed exploration of the specific needs of different learner groups. Future research should undertake targeted investigations into particular populations or sectors to generate more nuanced and context-specific insights.

CONCLUSION

The rise of AIGC is profoundly reshaping learning processes, core skill sets, and future development paths, with individual agency playing a central role in navigating these changes. In the learning domain, human–AI collaboration is becoming the norm, with AI-generated content and anytime-anywhere learning significantly improving access to resources and enhancing efficiency.

When it comes to essential skills, a broad foundation in AI literacy is now fundamental, while the responsible use of AI requires higher-order thinking skills and a renewed emphasis on human-centric soft skills such as creativity, empathy, and communication. In terms of career trajectories, the emergence of augmented individuals, learners and professionals who strategically integrate AI into their workflows to amplify productivity and adaptability illustrates how AI can elevate personal growth. Alongside this, AI-assisted career planning, continuous skill development, and systems for lifelong learning are becoming more prevalent.

Looking ahead, maximizing AIGC’s benefits while minimizing its risks will require coordinated efforts from all sectors of society. Individuals must commit to lifelong learning, strengthen their AI literacy, and cultivate both cognitive and interpersonal abilities. Educational institutions should update curricula to reflect the dual need for technical and human skills. Researchers are encouraged to investigate human–AI learning dynamics, ethical implications, and innovative forms of assessment. Policymakers must create governance frameworks that support innovation while ensuring fairness, data responsibility, and sustainable technology integration.

However, several challenges remain, including the risk of cognitive offloading, ethical concerns around data use, the inadequacy of outdated assessment systems, and persistent educational inequalities. Ultimately, thriving in the age of AIGC demands a deep, symbiotic relationship between humans and intelligent technologies built on shared evolution and mutual value creation. Individuals should approach AIGC openly, critically, and systematically while keeping human values at the core, working collaboratively with intelligent systems to create a more inclusive and meaningful future.

ACKNOWLEDGEMENT

Project Plan: This study is one of the outcomes of the 2023 annual planning project (School Development Category) of the China Association for Non-Government Education. The project title is “Research on the Adjustment and Optimization of the ‘Three-Stage’ Talent Cultivation Model for Applied Undergraduate Software Engineering in the Context of AIGC,” with the project number CANFZG23244. The project leader is Sun Li, and the participants are Gao Lu, Niu Yanhui, Jiang Haihong, and Li Yuehui.

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