Abstract
The rapid development of artificial intelligence (AI) has sparked a global competition among corporations and governments, but this “AI race” is leaving the interests of people behind. The current model of AI development is primarily driven by the pursuit of profit and market dominance by tech companies and the geopolitical ambitions of power and national security by leading states such as the US and China. This paper argues that a people-centered approach is essential to steer AI toward a more equitable and sustainable future. Corporations, led by a handful of tech giants, are focused on maximizing cost-efficiency and building foundational platforms, often sidestepping societal concerns about job displacement, algorithmic bias, and data privacy. Their “responsible AI” frameworks are frequently used as a tool to manage public image and preempt meaningful regulation, rather than as a genuine commitment to the public good. Similarly, governments are competing for AI dominance as a strategic resource, leading to a concentration of power and the adoption of security-focused AI systems that can erode individual freedoms and democratic norms. To counter these trends, the paper advocates for a middle ground that prioritizes human rights, fairness, and the well-being of communities. This involves a collaborative effort between governments and the private sector to establish an “AI transition” plan, which includes reskilling programs to help populations adapt to job automation. It also calls for greater global cooperation and multilateral partnerships to liberalize AI development, ensure equitable access, and create ethical frameworks that protect human rights, promote transparency, and restore the balance between security and individual freedoms.
Key Words: AI Race, Corporations, Governments, People, AI Transition Plan, Partnerships
Introduction
Artificial Intelligence (AI), refers to the ability of computer systems to perform tasks that require human intelligence like learning, problem-solving and decision-making; it involves building machines which operate on limited intelligence as opposed to the general-purpose intelligence humans possess. AI operates using narrow or specialized intelligence designed to perform specific functions with remarkable speed and accuracy. It adapts human algorithms and can recognize patterns in large datasets, predict outcomes and even engage conversationally through natural language processing as seen in virtual assistants and chatbots (Russell & Norvig, 2022).
AI was initially conceptualized in the mid-20th century and evolved from simple rule-based systems to advanced machine learning algorithms and neural networks that power everything from digital assistants to autonomous vehicles (Russell & Norvig, 2021). Over time, AI has witnessed transformative changes driven by intelligent automation and data analytics. AI technologies are active across a wide array of sectors, including healthcare, finance, agriculture, transportation, education, and defense systems, boosting economic productivity, scientific advancement, and growth in military power. Given the impact of AI on societies, the technology has attracted strategic competition from global powers seeking AI dominance, especially the United States of America (US) and China, and by extension the European Union (EU) and Russia, among others. Governments and private sector players – particularly tech companies and corporate firms are increasingly competing to shape AI development and governance.
This paper makes the central argument that in the wake of the scramble for AI development and governance, the people have been left behind. AI development models are currently exclusive to the interests of tech companies and governments, but the net effects of AI on populations are likely to be harmful even as governments and companies are focused on maximizing strategic and operational goals. The paper thus argues for a middle ground based on a people-centered approach for AI development and governance to transform the current “AI race”, which is majorly dominated by government and corporate interests.
Corporations, Profits and AI
The current era of AI is defined by a frantic and high-stakes corporate scramble. This race, fueled by unprecedented levels of private investment, is not primarily a scientific pursuit of knowledge but a strategic competition for market dominance. It is driven by two core objectives: the maximization of profit and the construction of dominant technology platforms. In this frenetic pursuit, this section argues, broader societal interests and the well-being of people are not merely secondary considerations; they are systematically sidestepped. Corporate actors treat public concerns less as a moral compass and more as operational hurdles to be managed, mitigated, or circumvented in the relentless drive for competitive advantage (Naisho, 2025).
The foundational driver of the corporate AI scramble is the pursuit of cost-efficiency and profit. AI is viewed as a revolutionary tool for achieving core business objectives, increasing operational efficiency and securing market-beating returns. The assignment of tasks to AI through automation of jobs, optimization of supply chains, or personalization of marketing is evaluated on a single primary metric, its contribution to the bottom-line (Davenport & Ronanki, 2018). This relentless focus on profit inherently necessitates sidestepping complex societal questions. Concerns about technological unemployment, the ethics of algorithmic decision-making, or the quality of AI-mediated work are often framed as an externality cost to be borne by society rather than the corporation. As argued by Brynjolfsson and McAfee (2014), while the technologies may create immense wealth, there is no inherent economic law ensuring this wealth is distributed equitably. The logic of profit maximization, therefore, puts corporate interests on a direct collision course with a people-centered agenda, prioritizing speed and shareholder value over deliberation and social welfare. According to the World Economic Forum, around 85 million jobs are expected to be displaced by AI by 2025, particularly those involving repetitive and routine tasks. McKinsey estimates that 45% of current tasks could already be automated using existing AI technologies, placing jobs with predictable workflows at higher risk. However, this shift is also creating new avenues for employment, with 97 million new roles projected to emerge in areas such as AI development, data analysis, and technology management. As companies seek greater efficiency and profitability, 35% have adopted AI specifically to reduce labor costs. Reflecting this momentum, global spending on AI technologies soared to $300 billion in 2025, underscoring a continued rise in investment and integration of automation across the global economy.
The strategic battlefield for the AI scramble is the creation of foundational platforms. Corporations such as Google, Baidu, Zhipu AI, Microsoft, and OpenAI among many others, are not just building products; they are constructing the essential infrastructure upon which future innovation will depend. By developing massive foundation models and controlling access through APIs and cloud services, these firms aim to win the scramble not just for one application but for the entire ecosystem. This strategy of “platform capitalism” (Srnicek, 2017) is designed to create powerful network effects and technological lock-in, ensuring long-term market control.
The battle for platform dominance is perhaps the most significant way in which the people are sidestepped. The architecture of these platforms, their inherent biases, their data privacy policies, and their very capabilities are determined by a small, homogenous group of engineers and executives within a handful of corporations. Once built and widely adopted, these foundational systems become deeply embedded in the fabric of society, yet there is no formal mechanism for public input or democratic governance in their design or deployment (Autor, 2015). The platform model centralizes power and decision-making, effectively sidestepping the principles of public accountability and co-creation from the outset.
Faced with growing criticism, corporate actors in the AI scramble have developed a sophisticated apparatus for managing their public image: the corporate “Responsible AI” framework. These frameworks, with their published principles of fairness, accountability, and transparency, present a facade of ethical diligence. However, they function less as a genuine commitment to the public good and more as a strategic tool for sidestepping meaningful accountability.
These initiatives are a form of “ethics washing” (Metcalf, Moss & Boyd, 2019), designed to placate public concern and pre-empt binding government regulation, thereby allowing the profit- and platform-driven scramble to continue unabated. They allow corporations to control the narrative around AI ethics while avoiding substantive changes to their core business models. For example, a company might promote a principle of “fairness” while continuing to profit from data-gathering practices that perpetuate societal inequality (Zuboff, 2019). Critical issues such as the planetary costs of computation or exploitative labor in the AI supply chain are neatly sidestepped in these polished corporate pronouncements (Crawford, 2021). Large technology companies such as Google, Amazon, Meta and Microsoft dominate AI. They have immense access to data and computational power that has allowed them to advance. AI tools are often optimized to promote user engagement and advertising rather than social well-being. Such developments are primarily driven by the pursuit of profit and market share (Zuboff, 2019).
Governments, Power and AI
AI has joined the category of strategic resources. The effects of AI on economic growth, national security capabilities and military power have transformed the strategic relevance of AI from an output of scientific progress, to an input of national power. The development and governance of AI has thus become a sphere for scramble and geopolitical competition among the leading global powers—the US and China, and by extension EU and Russia with each power keen on becoming the global leader in AI, as a pathway to geopolitical dominance. The Russian President Vladimir Putin has described AI as “… the future not only for Russia, but for all humankind. Whoever becomes the leader in this sphere will become the ruler of the world” (Lindsay, 2023). Putin’s words accurately capture the global powers’ AI ambitions, especially dominance and control, but gloss over the inadvertent effects of the AI race on global populations. This concentration of power undermines democracy and increases the risk of social manipulation through AI-driven misinformation and political interference.
The AI race has exposed the leading powers as focused on blocking each other’s ascension to AI dominance, while blind to the harmful gatekeeping and protectionist policies and measures they adopt for AI development and governance. Primarily, such policies are limiting the spread of AI across the world for the benefit of all of humanity. As AI technologies increasingly continue to shape critical aspects of the economy, governance and also daily life, there is a dire need to liberalize AI to ensure that it is inclusive, ethical and globally beneficial.
Currently, the trajectory of AI advancement is mostly dependent on a few dominant corporations and powerful states like the United States and China. These countries possess the required capital and technological infrastructure and the vast datasets to lead the field. This centralization brings about many risks, especially the monopolization of innovation, unequal access to AI’s benefits and the reinforcement of geopolitical tensions (Floridi, 2020). A liberalized AI ecosystem ensures a diversity of thought and encourages the development of AI systems that reflect a broader range of cultural, economic and social contexts. It also alleviates the dangers of technological dependency.
The AI race is also changing the nature of democracies and transforming governance systems across the world by blurring the lines between security on the one hand, and freedoms, rights and the sovereignty of the individual on the other (Csernatoni, 2024). The current AI models seem mostly built to achieve security goals as opposed to expanding freedoms, rights and the sovereignty of the individual. As democracies increasingly deploy AI-enabled facial, voice and gait recognition tools and inter-operationalize them with geolocation data, they achieve significantly enhanced surveillance and security outcomes, but undemocratically breach individual spaces and de-personify and disempower their populations. An overbearing state emerges, and previously people-focused power relations into a “state versus the people” relationship, which is now replacing democratic policing models.
The integration of AI particularly into social media platforms, has increasingly been exploited to disseminate misinformation, disinformation and propaganda, which is spiralling beyond governmental oversight and societal ability to manage the consequences on social cohesion and political stability (Csernationi, 2024). While such use of AI is destabilizing, the lack of a middle ground is a constant risk to the long-term stability of affected countries. This is because governments are responding by increasingly adopting laws and norms which limit freedoms online and promote suppression in local jurisdictions (Shahbaz & Vesteinsson, 2022). The United Kingdom (UK), France, Germany and the European Union (EU) are among the leading democracies which have adopted stricter regulations and laws to govern speech online (Accardo, 2025). Algorithms at the core of AI technology have been programmed in these jurisdictions in cooperation with tech companies, to identify “harmful” speech—mostly considered “hate speech”—and the “perpetrators”. Digital censorship has increased, with democratic governments heavily deploying AI technologies to limit public access to certain information and public debate around certain issues of national importance (Shahbaz & Vesteinsson, 2022). Unlike the control of speech, the effect of digital censorship can be at the global scale, given the global reach of social media platforms such as X (formerly Twitter), Facebook and TikTok.
The Middle Ground: A People-Centered AI Development
Currently, tech corporations are the leading actors in AI development, with a keen focus on developing technologies that maximize their revenue, often at the expense of developing technologies that are people-centered. In principle, a people-centered approach in the development of AI should prioritize human rights, fairness, inclusivity and the well-being of communities (Frank et al., 2019). At its core, a people-centered approach puts people before profits and power, ensuring that developed technologies serve human needs; this is especially important in a contemporary world that is increasingly embracing the use of AI across multiple sectors, with job automation increasingly becoming the trend across sectors. There is thus the need for the world, or at least the leading AI economies, to adopt an “AI transition” plan which allows for populations to acquire “future resilient” skills, in a manner which is sustainably paced with the automation of jobs, as a middle ground.
Without prioritizing human values, AI would risk harming the very society it is meant to help. It may reinforce existing inequalities by embedding racial, gender, and economic biases into decision-making processes and may lead to widespread surveillance, data exploitation, and loss of individual autonomy especially when controlled by powerful corporations or authoritarian governments. A recent assessment of AI development, precisely by technological corporations, reveals a trend of leveraging on global consumer trends to maximize profits. Technological corporations have especially leveraged on the rising internet and social media penetration rates. According to Davenport (2025), the global social media penetration rate stood at 5.24 billion, accounting for 63.9 per cent of the world’s population. As of July 2025, the leading platforms that recorded active social media usage were Facebook (3.07 billion), YouTube (2.50 billion), Instagram and WhatsApp (2.0 billion). Recognizing the potential of AI in growing their user base, the aforementioned have been keen to set up their private AI research labs, primarily with the intention of enhancing user engagement. The latter has further contributed to an “AI race” among the various social media platforms.
Social media corporations such as Meta for instance, deploy AI-algorithms across its Facebook and Instagram platforms to recommend users and groups, personalize content feeds, moderate harmful content and target users with advertisements. According to the Meta Annual report (2022), the firm generated over USD 113 billion from advertisements alone, which were largely driven by AI-algorithms. According to the same report, the revenue generated from advertisements accounted for 97 per cent of Meta’s total revenue. TikTok, which has its own AI research Lab as well (“the Seed team”), runs a “For You” feed, which heavily relies on machine learning to monitor users’ real-time engagement and curate customized feeds. As a result, TikTok with 1.6 billion users globally records one of the highest average global social media usages per person per day, recording an average of 52 minutes. YouTube on the other hand, which is operated by Google, attributed 70 per cent of its watch time to algorithm-recommended content (Google, 2021). These separate incidents of different technology corporations highlight the role of corporate-led AI development in enhancing social media user interaction. The latter is often done at the expense of fostering addictive user behavior and deepening information echo chambers, a sharp contrast to what a people-centered AI-development model should look like.
Equally, there is a need for governments to partner with the private sector players, particularly the tech corporations and other industry players, to establish mechanisms to transition their populations into the AI era, for instance, through re-modelling the job training systems to mainstream “future resilient skills” (Jyotishi, 2020). Such a step would mitigate the immediate effects of AI on employment and livelihoods across various sectors, particularly manufacturing, agriculture and healthcare. In 2016, having spearheaded automation of the American industry, for example, to allay anxiety among American workers, the US President Barack Obama’s AI transition vision, whereby he urged for the “retraining of populations for the jobs of the future” (Jyotishi, 2020). President Obama’s vision for future resilient jobs accurately captures the urgency with which global AI development should be “peopled” to balance between the interests of the corporations and the societies. Essentially, the people-centered AI development approach provides a transition ramp for populations in the most vulnerable sectors and allows for re-skilling, which expands the human role in future economies and societies.
The geopolitical competition for AI dominance, particularly between the US and China, is limiting the global spread of AI for global development through protectionist measures and intellectual property regimes at the national level. This is creating two centers or capitals of AI (the US and China), which the rest of the world is virtually cut off from perhaps until one AI pole gains dominance over the other, to be able to determine the future development and spread of AI. Global and multilateral partnerships and cooperation for AI development and governance are necessary for global AI diffusion. Such efforts will provide a formidable people-centered AI development approach, being inclusive and allowing global participation and equitable access to AI technologies. Global cooperation and multilateral partnerships are also critical for establishing global models for AI governance, co-created between AI powerhouses and the rest of the world.
Conclusion
The current model of AI development which is dominated by the leading tech corporations such as Google, Meta, Microsoft, OpenAI, Baidu, and Zhipu AI among others, has marginalized the interests of the people from the design stage to operationalization. In consequence, AI innovations are mostly serving the interests of the capitalistic corporate world, mainly productivity, profit and cost-efficiency, while undercutting the livelihood and income outcomes for populations being rendered redundant by AI. Aggressive AI-enabled personalized marketing, mostly deployed through social media and popular search engines, is also trampling over societal values by driving up consumerism and commodifying human networks.
Global powers, especially the US and China should provide global leadership in the space of AI development to enable globalized participation and spread of AI technologies across the world for global development. Similarly, in charting AI governance through global and multilateral partnerships, reviewing the use of extreme versions of intrusive security-focused AI which have personified populations and adversely changed the nature of democracies and power relations in the affected countries is necessary to restore individual freedoms and democratic policing.
Given the current gap in governance of AI globally, there is an urgent need for leading actors in AI, corporates and governments, to partner and include the people in AI development, to liberalize and humanize AI innovations. Global partnerships should steer the development of ethical frameworks for the development and deployment of AI to protect human rights, protect livelihoods and incomes, ensure transparency, and promote accountability. Embracing the middle ground will create a future of technology where humans are not isolated targets of scientific advancement and their livelihoods are not vulnerable to the ever-changing technologies.
AI as a threat or Asset to Kenya democracy:
Current situation. How Kenya was ranked as a leading country in CGAT gpt and how many Kenyans use social media the with. A recent trend among Kenyan youth in using AI has been seen in civic education e.g. in educating the masses on government policies in a digestible way a way in which the common mwananchi can understand and we have also seen the use of bots to troll and …… citizen participation, affects how issues are discussed and use of fake news by some media outlets and how government representatives have often used the term fake news to discredit actual citizens grievances which has leaving social issues unrest. It sees the increased use of social media to advance a civic populated youth road map to good governance due to accountability or misuse
Recent research shows that AI-generated propaganda is just as believable as propaganda written by humans. To train and deploy the same machine-learning models that generate AI to detect AI-generated content, generally, some of the digital-literacy techniques that have already gained currency will likely apply in a world of proliferating AI-generated texts, videos, and images
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The topics and key points for reference are as follows:
1.Bridge the digital divide to share digital dividends
2.Jointly build Digital Silk Road and promote global digital cooperation
3.Adhere to a people-centered approach in developing AI for good and for all
4.Promote development and governance of global digital economy and digital trade
5.Prevent cyber risks and safeguard peace and security of cyberspace
6.Improve data governance rules and promote data security
7.Intensify international cooperation on combating cyber crimes and cyber -terrorism
8.Build a fairer and more equitable cyberspace governance system
9.Improve law-based cyberspace governance
10.Enhance online culture exchanges and mutual learning among Internet
civilizations
For government officials, this undermines efforts to understand constituent sentiment, threatening the quality of democratic representation
