The AI sector has become incredibly skilled at selling visions of sunny futures. CEOs of tech companies, particularly those running major AI companies, frequently appear before Congress and offer the media interviews spinning rosy pictures of affluent futures driven by AI, job growth, and economic transformation. But behind all the high-gloss presentations and flawlessly scripted talking points is a darker and more ominous reality that needs to be explored openly.
The drift of arguments from AI heavies like Sam Altman is to be expected along the lines: AI generates more jobs than it destroys, technological change always in the end serves humankind, and the market will naturally distribute the dividends of AI to society. These reassurances, though soothing, need to be rigorously tested against hard evidence and alternative paradigms for understanding the contribution of technology to human thriving.
The Myth of Net Job Creation
Arguably the most pervasive AI supporter claim is that artificial intelligence will ultimately create more jobs than it replaces, following the template of past technological progress. That argument most typically invokes the Industrial Revolution and the computer revolution as models for how AI will ultimately increase employment opportunities.
Evidence currently shows that this optimism may not hold for AI, however. MIT reports provide some comfort with the observation that currently it is not economically feasible for machines to make most humans obsolete, but the implication is actually negative to industry claims. MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) study concludes that it is only approximately 23 percent of salaries paid for activities encompassing vision which are worth AI automating¹. This means that if AI displacement is happening, it’s only happening because it’s cheap for corporations, not because it’s technically necessary or universally preferable.
The manufacturing industry offers a bracing glimpse of AI’s real path. MIT studies indicate that AI is slated to displace 2 million factory workers by 2025². While that’s the future, recent statistics from Socius indicate 14% of the workforce has already seen their jobs displaced by automation or AI³. These aren’t predictions about the future—they’re reality for real families and communities right now.
The financial sector offers perhaps the most glaring case in point. IBM’s AskHR handles 11.5 million interactions annually with minimal human involvement⁴, demonstrating how easily AI can lop off entire classes of human work. Unlike previous technological revolutions, which generated new types of work alongside those they destroyed, AI’s course appears to be divergent—it’s eliminating human cognitive work without necessarily creating parallel possibilities for out-of-work humans to transition into.
Democratic Distribution Illusion
AI executives tend to argue that artificial intelligence will “democratize” economic profits, imparting advanced ability to everyone and creating new avenues of entrepreneurship and innovation. “We ought to get people to earn a lot of money and then also find ways to distribute the money widely and share the compounding advantage of capitalism,” Sam Altman has stated⁵.
This is a characteristic contradiction of Silicon Valley’s reaction to AI advancement. The same companies that advocate democratic allocation are likewise concentrating unparalleled computational ability and market power in the hands of a few technology titans. The money required to train leading-edge AI models now runs into hundreds of millions or even billions of dollars, putting up barriers to entry only the largest companies can clear.
Real-world evidence contradicts democratic access arguments. The companies developing the most sophisticated AI infrastructures—OpenAI, Google, Microsoft, Meta—are the same that own access to them through proprietary APIs and pay-for-play operations. It creates a new form of digital feudalism where small businesses and people become dependent on AI infrastructure owned by technological monopolies.
The International Monetary Fund has warned that AI will affect almost 40 percent of jobs worldwide, replacing some and complementing others⁶, but their report emphasizes the need for “careful balance of policies” and not allowing market forces self-assign benefits equally. New trends show the opposite: AI is consolidating instead of spreading economic power.
The White-Collar Recession Reality
Perhaps nowhere is the gap between AI industry hype and reality more evident than in white-collar work today. In January 2025, the United States Bureau of Labor Statistics (BLS) reported the lowest professional services job openings rate since 2013—a 20% drop from the prior year⁷. This is not an anomalous adjustment; it is a sea change in how businesses approach knowledge work.
The figures become more daunting when viewed up close. The American Staffing Association stepped forward and indicated that approximately 40% of white-collar positions lost in 2024 were entirely due to AI implementation⁸. These are not mere beginner positions—AI is taking over experienced professionals in fields such as legal research, financial analysis, content writing, and even coding.
Engineering, occasionally referred to as a field of business that will benefit from AI upgrade, is being radically upended. Detailed inspection of engineering job substitution in 2024-2025 indicates that AI automation is impacting engineering work in ways that challenge existing beliefs concerning human-AI collaboration⁹. Rather than merely supplementing human skills, AI is replacing full workflow and choice-making processes.
The promise that AI will set humans free to work on “higher-value” tasks rings hollow when higher-value tasks themselves are being mechanized. AI will eliminate between two million and three million factory workers by 2025, an MIT and Boston University report finds, and McKinsey Global Institute studies say at least 14% of the world’s workers could have to switch careers due to digitization by 2030¹⁰.
The Economic Feasibility Problem
One of the critical areas which are overlooked in the general discussion about AI is the problem of economic incentives to automation decisions. The MIT CSAIL research provides us with useful data: companies aren’t automating procedures because AI is theoretically superior to human beings at all things, but it’s more economical in some cases.
This is significant for social planning and policy. If adoption of AI were entirely an issue of technological capability, we would see incremental across-the-board change in all industries. Instead, what we are seeing is targeted displacement where cost savings are immediately apparent to corporate decision-makers regardless of broader societal costs.
The trend shows that AI deployment is on profit maximization lines and not on productivity optimization or social good. Companies are using AI not to expand human capabilities in a way that benefits employees, but to hold down labor costs in a way that benefits shareholders. This constructs a fundamentally different dynamic than existed in previous technological revolutions, when new technologies created new types of human work even as they eliminated others.
The Issue of Speed and Scale
Cross-historical comparisons of AI with past technological revolutions often forget important differences in speed and scale. The Industrial Revolution occurred over the span of decades, which gave societies time to reallocate education systems, set up new institutions, and develop policy responses. The computer revolution also occurred over the course of several decades, giving time for transitions in the workforce.
AI’s trajectory appears fundamentally divergent. Nearly 20% of all labor in the U.S. job market can potentially be replaced or supplemented by AI, and roughly a quarter of those activities — or 5% of all labor — are currently at risk of displacement¹¹. While 5% can potentially be contained, we’re talking about millions of jobs lost over a couple of years as opposed to decades.
The speed of AI advance worsens this problem. Unlike earlier technologies that required gigantic expenditures to put infrastructure in place and rollout over time, AI systems roll out quickly within entire organizations once developed. A single AI model can readily replace hundreds or thousands of individuals simultaneously, creating immediate gargantuan displacement without balancing job creation elsewhere in the economy.
International Competition and National Security Framing
Leaders in the AI industry have well learned how to frame their arguments in terms of global competition and national security. OpenAI and its rivals under Biden called for the government to regulate AI. Under Trump, they talk about moving faster to race with China¹². This approach of rhetoric serves corporate aims by presenting development in AI as a patriotic issue rather than a commercial strategy.
The “AI race” narrative hides important questions about whether the rapid rollout of AI ultimately serves American workers. The race to control the future of artificial intelligence is heating up between companies and countries, with Altman’s OpenAI in a frenzied battle to create the better artificial intelligence model versus technology rivals like Alphabet and Meta, and versus Chinese competitor models¹³.
But competition from China isn’t necessarily about domestic policies serving corporate interests ahead of workers’ well-being. Other countries are trying other ways of doing AI that bring more attention to social good and protection of workers in addition to technological progress. The premise that America needs to adopt Silicon Valley’s preferred model in order to stay competitive should be questioned.
The Regulation Reversal
One of the very educative aspects of present AI business practices is the shift in regulatory positions. Altman had earlier invited Congress to regulate AI and insisted on the point of risk if not contained, proposing an establishment of a federal agency that would license and audit AI models¹⁴. The same CEOs now argue for deregulation and urgency in the name of competition.
This reversal means demands for regulation were always a matter of genuine professional care for social welfare, but opportunistic positioning in the early stages of AI development. Having established firm positions in the marketplace, their regulatory palate shifted to maintaining those positions rather than diffuse social benefit.
The pattern is repeated in other efforts at regulatory capture in the tech industry, where companies initially welcome regulation as a barrier to entry for rivals and then resist deregulation once they have achieved market dominance. This pattern should inform policymakers in evaluating current AI industry claims to social value and job creation.
A Christian Theological Response: Technology in Service of Human Flourishing
The challenges posed by artificial intelligence require more than a shift in policy or market incentives—the call for an entire reprioritization of technology’s role in human society. Christian thought is full of paradigms for grappling with these questions, based on assumptions of human dignity, common good, and stewardship.
The Dignity of Work and Human Purpose
Christian theology believes that work is not merely an economic transaction but an expression of human dignity and co-participatory creation with God. Genesis describes humankind as being made in the image of God and tasked with the responsibility of stewards and guardians of creation (Genesis 2:15). This theological foundation establishes that technology can complement but never replace human initiative and creative capacity.
The trajectory of AI development, which is mainly driven by profit, gravely betrays this principle. When companies employ AI merely to cut back on labor, they turn human labor into a cost to be minimized rather than a representation of human dignity to be valued. A Christian alternative would instead ask: How can AI enhance human imagination, strengthen communities, and engage more persons meaningfully in productive work?
Stewardship and Common Good
Christian stewardship emphasizes good use of resources for the benefit of all of creation, not just the owners. Transferred to AI development, the principle resists the presumption that private institutions should own technologies that have as vast social consequences.
AI systems learned from human wisdom, constructed using public infrastructure, and based on societal information are a form of shared heritage available to all of humanity. The current paradigm of private profit-taking and ownership over these systems violates principles of stewardship and common good.
A Christian response might prefer models like AI infrastructure openly owned, community-driven priorities for development, or public benefit requirement for AI companies. These models would ensure AI is utilized for the sake of human flourishing and not for the sake of merely generating profit for shareholders.
Preferential Option for the Vulnerable
Christian social doctrine continuously reiterates God’s special concern for the poor, vulnerable, and marginalized. This teaching provides a basic paradigm for evaluating AI policies: In what manner do they affect society’s most vulnerable members?
Current AI deployment patterns consistently do injury to workers with lower economic and political power for the advantage of those who are already in possession of capital and influence. Factory laborers, administrative staff, and service workers are replaced, and tech business managers and stockholders enjoy the economic gains. The pattern is contrary to Christian doctrine concerning justice and compassion for the weak.
A Christian response would center on the protection of workers and communities against AI-driven displacement, ensuring technological benefits are made available to those who need it most, and creating new economic security which is not dependent on traditional employment relationships.
Community and Relationship
Christianity lays significant emphasis on the inherently communal nature of human existence and on ties of fellowship. Contemporary AI systems disrupt such ties by replacing human communication with algorithmic ones and eliminating the potential for collaborative labor.
Consider how AI-driven customer service solutions remove work while also waterin down the quality of human interaction in business life. Or how AI-generated content threatens to put at risk creative communities based on mutual development and artistic collaboration. This is change as loss that fails to register on economic analysis driven by efficiency and cost reduction.
A Christian response would gauge AI implementations in terms of their effect on individuals’ relationships and social connections, not solely economic metrics. This would favor AI applications that enhance human association and cooperative potential over others that only replace human exchange with mechanical processes.
Practical Solutions Based on Christian Principles
Beyond criticism to constructive alternatives, Christian theology has a number of practical solutions toward the goal of ensuring AI serves people’s flourishing:
Universal Basic Assets
Rather than Universal Basic Income, Christian stewardship instructs Universal Basic Assets—giving everyone access to productive assets like AI tools, education, and entrepreneurial capital. This framework does not view technology as merely owned heritage but also preserves human agency and dignity through meaningful work.
Community-Controlled AI Development
Organizations of workers and local communities should exercise some direct control over AI research and development priorities that affect them. This might include community ownership of AI facilities, worker membership on AI company boards, or technology deployment by democratic planning means.
Sabbath Principles in Technology Design
The Sabbath principle within the Bible—periodic rest from fruitful work—provides guidance for AI design. Instead of maximizing efficiency and productivity, AI systems could be designed to leave space for relaxation, reflection, and human connection. This might involve intentionally slowing down certain processes to make space for human interaction and community-building.
Vocational Discernment
Christianity believes that every person is endowed with unique gifts and a vocation to contribute positively towards the good of all. There is a need for AI systems to be designed to help humans discover and develop their vocational gifts rather than replacing human capabilities with automated counterparts.
Conclusion: Selecting Human Flourishing Over Profit Maximization
The direction in which AI development is currently headed is a choice—not an unavoidable technological destiny. We can continue to allow profit-hungry organizations to guide AI’s role in society in accordance with their bottom lines, or we can demand that such powerful technologies serve human flourishing.
Facts categorically establish that current AI deployment patterns are all narrowing wealth, replacing workers, and degrading community cohesion. Their overly optimistic forecasts have repeatedly proved to be false, while their threats against regulation and competition are primarily designed to protect corporate interests.
Christian theology offers critical prophecy of these trends and positive vision for alternatives grounded in human dignity, common good, and responsible stewardship. The question is not whether we can build more competent AI systems, but whether we will have the moral vision to see to it that they serve all of humanity and not just those who currently control them.
The stakes are as high as they can be. The choices we make about AI over the next several years will determine the nature of human society for centuries to come. We owe it to the future to act responsibly, driven by a commitment to justice, community, and human flourishing, and not merely to maximizing profits for tech firms in the short term.
The future involves both policy transformation and cultural transformation—new forms of economic organization devoted to human flourishing, democratic institutions capable of directing powerful technologies, and renewed commitment to the common good in preference to private accumulation of wealth and power. These are within our reach only if we renounce the fantasies of Silicon Valley utopianism and commit ourselves to forging a more just and human technological future.
Footnotes:
- MIT CSAIL – “Rethinking AI’s impact: MIT CSAIL study reveals economic limits to job automation” – https://www.csail.mit.edu/news/rethinking-ais-impact-mit-csail-study-reveals-economic-limits-job-automation
- Final Round AI – “AI Job Displacement 2025: Which Jobs Are At Risk?” – https://www.finalroundai.com/blog/ai-replacing-jobs-2025
- SEO.ai – “AI Replacing Jobs Statistics: The Impact on Employment in 2025” – https://seo.ai/blog/ai-replacing-jobs-statistics
- Final Round AI – “AI Job Displacement 2025: Which Jobs Are At Risk?” – https://www.finalroundai.com/blog/ai-replacing-jobs-2025
- CNBC – “OpenAI CEO Sam Altman says he’s ‘politically homeless’ in July 4 post bashing Democrats” – https://www.cnbc.com/2025/07/04/openai-altman-july-4-zohran-mamdani.html
- IMF Blog – “AI Will Transform the Global Economy. Let’s Make Sure It Benefits Humanity.” – https://www.imf.org/en/Blogs/Articles/2024/01/14/ai-will-transform-the-global-economy-lets-make-sure-it-benefits-humanity
- SalesforceDevops.net – “The White-Collar Recession of 2025: AI and the Great Professional Displacement” – https://salesforcedevops.net/index.php/2025/02/28/the-white-collar-recession-of-2025/
- SalesforceDevops.net – “The White-Collar Recession of 2025: AI and the Great Professional Displacement” – https://salesforcedevops.net/index.php/2025/02/28/the-white-collar-recession-of-2025/
- AI Critique – “AI-Driven Job Displacement in Engineering (2024–2025)” – https://www.aicritique.org/us/2025/05/24/ai-driven-job-displacement-in-engineering-2024-2025/
- Nexford University – “How Will Artificial Intelligence Affect Jobs 2025-2030” – https://www.nexford.edu/insights/how-will-ai-affect-jobs
- MIT Sloan – “A new look at the economics of AI” – https://mitsloan.mit.edu/ideas-made-to-matter/a-new-look-economics-ai
- The Washington Post – “OpenAI CEO Sam Altman’s Senate testimony shows industry shift on regulation” – https://www.washingtonpost.com/technology/2025/05/08/altman-congress-openai-regulation/
- PBS NewsHour – “WATCH: OpenAI co-founder Sam Altman testifies on AI competition in Senate hearing” – https://www.pbs.org/newshour/politics/watch-live-openai-co-founder-sam-altman-testifies-on-ai-competition-in-senate-hearing
- Fortune – “OpenAI’s Sam Altman goes to Washington to talk AI” – https://fortune.com/2025/05/09/openai-sam-altman-congress-ai-hearing/
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