Is DeepSeek AI a Blessing or a Curse for the Generative AI Industry?

By Richard Sebaggala

DeepSeek AI's entry into the generative AI race has sparked debate about what this means for the industry, competition, and the future of artificial intelligence. Some see it as a sign of progress, a force that will drive innovation and reduce costs. Others fear that this is another step towards an AI arms race that will take us further into uncharted territory where the risks outweigh the benefits. As economists, it is impossible to ignore the fact that this is not just a technological shift, but also an economic and geopolitical one. The big question is whether the arrival of DeepSeek AI is good for the world or whether we are simply moving towards a future that we haven’t fully thought through.

In most industries, competition is a force for good. It leads to better products, lower prices, and better accessibility. The emergence of DeepSeek AI challenges the dominance of OpenAI, Google DeepMind, and Anthropic and brings a new player into what is starting to feel like an exclusive club.  As Apple and Android went head-to-head, smartphones got better and more affordable. As budget airlines entered the market, flying became accessible to more people. DeepSeek AI could have a similar effect: AI tools are becoming cheaper, smarter, and more widely available. In addition, the accessibility of AI is a major concern. Currently, developing AI models at scale is costly, and access to leading technologies is often limited. If DeepSeek AI aggressively pushes into the market, it could force incumbents to rethink their pricing strategies and make AI more affordable for small businesses, researchers, and developing countries. This democratization of knowledge and computing power is a compelling argument for more competition.

However, more competition does not always lead to better results. It can lead to reckless behavior when companies prioritize speed over safety. The AI industry is already in the process of developing larger models without fully understanding their long-term implications. The entry of DeepSeek AI means that all players may feel pressured to accelerate their development cycles, which could lead to the use of unfinished technologies and the neglect of ethical considerations. The nature of the generative AI industry raises unique concerns. Unlike traditional markets, which typically involve the exchange of goods and services between buyers and sellers, the impact of AI extends far beyond consumers and businesses and can reshape entire economies, influence policy decisions, and change labor markets. This raises critical questions about how the market for AI will evolve, particularly in terms of its structure and competitive dynamics.

A key question is whether the emergence of DeepSeek AI signals the development of a truly contestable market or whether the industry will continue to be dominated by existing players. In economics, a contestable market refers to a market where entry and exit are relatively easy, meaning that new companies can challenge incumbents without major obstacles. In such markets, even a monopoly behaves competitively because the threat of potential entrants keeps prices fair and innovation high. In the AI industry, however, the presence of first-mover advantage —when early entrants establish a strong position by developing superior technologies, amassing big data, and building brand awareness — can solidify the control of existing giants such as OpenAI, Google DeepMind, and Anthropic.

DeepSeek AI’s strategy may be similar to OpenAI’s approach, which favors rapid adoption of its technology over immediate profitability. This is a common tactic in technology markets, where early market dominance can be more valuable in the long term than short-term revenue. However, the AI industry is characterized by network effects, i.e. the value of a service increases the more people use it. This and the huge demand for data and computing resources make it difficult for new entrants to compete on an equal footing with established market players who already have access to huge data sets, powerful computing infrastructure, and strong industry partnerships. The key question remains: Does DeepSeek AI’s entry signify a real power shift in the AI industry, where competition is thriving and innovation is flourishing? Or is the company merely adding another player to an already established system dominated by a few tech giants that are more likely to maintain the status quo than change it?

Furthermore, fragmentation is a significant risk. If AI development splits into competing ecosystems — one dominated by Western companies like OpenAI and Google, and another led by China’s DeepSeek AI and others — we could end up with two separate AI worlds. Competing AI ecosystems, possibly divided along geopolitical lines, could lead to different standards of safety, ethics, and governance. This is particularly worrying given that AI has the potential to disrupt economies and political systems. If AI development becomes a race for supremacy rather than a collaborative effort for global improvement, it could have detrimental consequences.

The presence of DeepSeek AI is therefore a double-edged sword. It offers the potential benefits of competition — faster innovation, better prices and improved access — but also carries the risks of fragmentation, reckless deployment and a focus on dominance rather than accountability. The key question is not whether DeepSeek AI is inherently good or bad, but whether we can effectively manage the impact of an industry that exceeds our ability to control it. AI is now about power, politics and economics. As history shows, those who set the rules for emerging technologies ultimately determine their impact on the world. We pray and hope that those governing AI will prioritize ethical responsibility, global cooperation, and the collective good over short-term gains and geopolitical rivalry. The future of AI should be shaped not only by competition but by wisdom and foresight.

 A Green Park in a Polluted City: The Economics of Human-AI Collaboration

In an era characterized by artificial intelligence, thriving is no longer about competition, but about finding the right balance. Just as a green park thrives as a tranquil sanctuary in the midst of a polluted city, the partnership between humans and AI thrives on mutual reinforcement. Humans contribute judgment, creativity and context, while AI provides speed, data processing and efficiency. Together, they create something greater than either could achieve alone — a powerful synthesis of creativity and productivity.

But this partnership is not without risks. The misuse of AI has highlighted the dangers of unchecked technological progress. As Susie Alegre pointed out in her article "Don’t Count Out Human Writers in the Age of AI" (January 8, 2025), "academic publisher Wiley shut down 19 journals in 2024 in the face of a flood of fake scientific articles. To err is human, but falsification on an industrial scale is primarily a technological problem. AI has no professional ethics, no soul and nothing to lose — but the people who use it or ask others to use it for them do." This stark example underscores the need for human oversight to uphold ethical standards and protect the integrity of creative and academic work.

Maintaining integrity in a flood of content

The challenge for human authors and researchers is clear: they must maintain their individuality and integrity in a landscape increasingly dominated by AI-generated content. With the rising tide of machine-generated material, the temptation to rely solely on AI is growing. But much like a green park needs dedicated gardeners to maintain its vitality, the creative world needs human judgment and ethics to ensure authenticity and maintain trust.

AI may excel at generating content on a large scale, but it lacks the soul, professional ethics, and accountability that define human creativity. Without human guidance, AI can contribute to a landscape of superficiality, undermining the quality and depth that readers and audiences value.

The power of collaboration: examples of human ingenuity and AI

One of the most powerful aspects of AI is its ability to complement human ingenuity. When AI is used as a collaborator, it can contribute to better results by combining machine efficiency with human creativity.

Take, for example, a journalist working on a report about climate change. Traditionally, gathering data, interviewing experts and crafting a compelling story would typically be labor-intensive and time-consuming. With generative AI, the journalist can now streamline parts of the process while increasing the depth and creativity of their work.

·Data Collect and summarize: AI tools like Avidnote and ChatGPT can sift through hundreds of research articles, extract key statistics and summarize complex findings. This allows the journalist to focus on the most important findings instead of getting bogged down in data collection.

·Idea Generation and structuring: AI can suggest angles or topics for the article, e.g. the impact of climate change on urban flooding, innovative solutions in flood-prone areas and personal stories of resilience. These suggestions stimulate creativity and provide a solid starting point.

·Human Creativity and storytelling: Using AI-generated insights, the journalist weaves emotional narratives, conducts interviews and contextualizes data in a way that resonates with readers. The AI can suggest wording or sentence structures, but the journalist refines the language to fit their unique voice.

·Final Polishing: AI-powered tools like Avidnote help with grammar and readability, while the journalist ensures the content is ethically sound and factually correct.

The result is a thoroughly researched, emotionally engaging article that neither the journalist nor the AI could have achieved alone.

In academia, AI can also increase productivity while maintaining the intellectual rigor of the researcher. For example, a historian studying pre-colonial corruption could use AI to summarize historical texts and identify recurring themes. However, the historian’s expertise interprets these nuances, highlights lesser-known perspectives, and contributes original insights to the field.

The recognition of human expertise

While AI automates routine tasks, the unique contributions of human writers and researchers are increasingly valued. Clients and employers are beginning to understand that quality comes at a price. Whether it's writing compelling narratives, conducting insightful analysis or producing innovative research, human expertise is a premium service in a world inundated with machine-generated content.

Those who combine their unique talents with mastery of AI are leading this change. By using AI as a tool rather than a replacement, they are increasing their productivity and regaining their value. These people are redefining their industries and positioning themselves as indispensable in the age of AI.

A balanced path to the future

The future is not about AI versus humans. It's a story of collaboration. In the polluted landscape of overproduced and overwhelming  AI content, those who master and combine AI with their human skills shine as green parks of excellence. They elevate their work, stand out for their quality, and lead the way to a new era of creativity and productivity.

The lesson of 2025 is profound: the pen — guided by a human mind and augmented by AI — is more powerful than ever before. By embracing AI as an ally, human writers and researchers can amplify their strengths, maintain their authenticity, and push the boundaries of what is possible.

However, it is important to recognize that generative AI is still in its infancy and has significant limitations. One of its biggest weaknesses is its short memory — a limitation that is rooted in the Transformer architecture that drives these systems. This short memory is not a flaw, but an intentional feature, as current AI systems are designed to mimic human intelligence, not surpass it in every way.

But the exciting future still lies ahead. Efforts are already underway to develop AI that not only mirrors human intelligence, but also enhances it in ways that preserve and amplify what makes human thinking unique: our creativity, our ability to learn and adapt, and our capacity for deep understanding. Such advances could mark the beginning of a new chapter in which AI becomes a true partner for human innovation, allowing us to push the boundaries of what we can achieve while remaining deeply rooted in the essence of our humanity.

As we move forward, let us cultivate this balance between human ingenuity and technological advancement. In doing so, we not only increase our productivity and creativity, but also preserve the authenticity and ethical standards that define being human. In this balance lies the promise of a thriving, collaborative world where human excellence flourishes amidst the power of AI.

The future of creativity is not about replacing humans, but enhancing them — our ability to think, adapt and create in a way that matches both our intelligence and the technology we are developing. That's the promise of human-AI collaboration: a partnership where humans are at the center, leading with wisdom and purpose.

From Knowledge to Allocation: How Generative AI is Reshaping the Economics of Work and Learning

In today’s world, where information flows freely and tools like ChatGPT, Avidnote and Gemini are at our fingertips, we are experiencing a seismic shift in the way we approach work, learning and even daily tasks. The Economics of Work and Learning explores this relationship, focusing on how education systems and labor markets interact to shape economic productivity and individual career opportunities. As we look at how this dynamic is being changed by technology, it is important to understand its fundamental impact on personal and economic growth. What once required a high level of expertise-be it analyzing data, interpreting it or composing a professional email- is now streamlined and simplified by generative AI. For researchers, professionals and students, AI has transformed time-consuming processes into quick, manageable tasks, fundamentally changing the landscape of our economy.

Generative AI not only increases productivity, it also signals the transition from a knowledge economy to what I call an allocation economy. In the knowledge economy, success depended on how much information you could acquire and apply. Today, the focus is on how well you use and manage AI-driven resources to accomplish work. This shift suggests that the future of business and professional growth will revolve around resource management rather than pure knowledge acquisition. This shift aligns with the views of AI advocates such as Dan Shipper, co-founder and CEO of Every, who writes the Chain of Thought column. Shipper argues that the future of work depends less on the depth of individual knowledge and more on how effectively we manage the resources available. In this context, the most valuable skills of today or the future include navigating, selecting and orchestrating AI tools to turn ideas into reality.

In an allocation economy, the value of knowledge is shifting from the mere possession of information to the knowledge of how to use that information effectively with the help of AI tools. The real economic advantage is no longer in being an expert on every topic, but in integrating and allocating AI resources to achieve results efficiently. However, this does not mean that knowledge has lost its importance. Rather, it means a recalibration of priorities, where fundamental understanding is complemented by agile, strategic allocation capabilities. Generative AI tools enable users to apply their knowledge more broadly, achieving unprecedented levels of productivity and precision.

Preparing for the allocation economy

Resource management capabilities

With the variety of generative AI tools available today, the ability to evaluate and select the right tool for specific tasks is critical. Students, professionals and educational institutions need to develop a keen eye for resource allocation, prioritizing adaptability over rote learning.

Ethical and responsible use of AI

As AI becomes increasingly integrated into life and work, it is crucial to understand the ethical implications and learn to use AI responsibly. This includes recognizing bias, addressing privacy concerns and promoting transparency in the use of AI. In addition, individuals and organizations need to create frameworks that promote ethical AI practices in their operations.

Collaborative intelligence

AI tools work best when combined with the human mind. Communication, collaboration and critical thinking remain essential as humans interpret, refine and implement AI-generated insights. Educational institutions should focus on fostering these collaborative skills in students and professionals alike.

Continuous learning and adaptation

Generative AI is evolving rapidly. Continuous learning and constant updating of AI advancements are essential to realize the full potential of these tools. It is not only the responsibility of individuals, but also of companies to create an environment that supports continuous learning and adaptation.

A look into the future

As we move into the sharing economy, generative AI holds the potential to democratize productivity by providing tools that promote innovation and efficiency for individuals and companies,organization and professional bodies alike. The challenge is not only to adapt to these tools, but also to orchestrate them skillfully, i.e. to manage resources smartly to maximize impact.

As we embrace this change, the focus shifts from what we know to how we use and manage the resources available to us to build, create and innovate. This techno-economic transition signals a new era in which strategic resource allocation becomes the cornerstone of economic success.

The transition to an allocation economy driven requires a comprehensive assessment of the knowledge production landscape. Educational institutions, as well as individuals and professional organizations, must adapt by prioritizing resource management skills, ethical AI practices, and interdisciplinary collaboration. This shift is essential to ensure that educational and research paradigms remain relevant and effective in addressing the complexities and challenges of an evolving knowledge economy.

To succeed in this new environment, educational institutions must not only incorporate these elements into their curricula, but also foster a culture of continuous learning and adaptability. Individual professionals and their organizations must also be proactive in responding to these changes. By equipping the next generation with the necessary skills to navigate this allocative economy, we can cultivate a workforce that is not only proficient in the use of AI-driven tools, but also able to harness them for sustainable innovation and societal benefit.