AI Generation Cost Nears Zero: Digital Economy's Value Anchor Shifts Towards Verification and Trust

In the traditional industrial and information ages, value systems were rooted in a series of implicit axioms: value was believed to be embodied in product output, with functionality and exchange value dominated by the production side; scarcity stemmed from the supply side, where high replication costs formed barriers in capacity, copyright, and channels; verification was considered a cheap auxiliary activity, with brands and authoritative channels implicitly trusted; distribution was a secondary step performed only after product completion; and measurement was based on human inputs such as man-hours and headcount. However, as AI technology has broken through physical production and replication bottlenecks, these core assumptions are being systematically dismantled. As the cost of creation and supply infinitely approaches zero, old value anchors will inevitably become invalid, forcing us to re-examine the essence of value.

Against this backdrop, a new chain of mechanisms is gradually taking shape: plummeting generation costs lead to an explosive growth in supply, which in turn drives marginal product prices towards zero. This prompts the value anchor to shift from products to 'complementary scarce elements,' with pricing power consequently transferring to the holders of these bottleneck elements. Crucially, while generation is low-cost forward sampling, verification often requires inverse reasoning, combinatorial search, or external anchoring, leading to **verification costs being significantly higher than generation costs (Cv≫Cg)** as a structural norm ([arXiv 2608.08709, 2026](https://arxiv.org/html/2608.08709)). Therefore, generation approaching zero does not imply verification also approaches zero; verification itself is being elevated into a new scarce commodity. Simultaneously, autonomous agents bypass traditional presentation layers to make direct decisions, rendering the value of 'attention' ineffective in the B2A (Business-to-Algorithm) market, thus driving value further from the interface layer towards the trust layer ([Zhao & Tang, CMR 2026](https://cmr.berkeley.edu/2026/06/competing-in-the-trust-economy-how-ai-agents-are-rewriting-the-rules-of-digital-strategy/)).

The collapse in generation costs brought about by artificial intelligence is an undeniable fact. For instance, the unit price for large model inference is decreasing at an astonishing rate; as of September 1, 2026, the effective market price has dropped to $0.97 per million tokens, a decrease of over 50% from its summer peak. GPT-3.5 level capabilities have fallen from approximately $20 per million tokens in late 2022 to about $0.07 in October 2024 ([KuCoin, 2026-09-03](https://www.kucoin.com/blog/why-ai-token-costs-are-falling)). The cost of producing AI short dramas has plummeted by over 90% in six months, from 5,000 yuan/minute to a few hundred yuan; digital human customization fees have dropped from 300,000-600,000 yuan to tens of thousands or even a few thousand yuan. In the first half of 2026, China launched 221,900 AI short dramas, but only about 0.47% achieved over 100 million views, while traffic promotion still accounted for 70% of the entire chain cost, highlighting the reality that 'whoever controls traffic entry points controls allocation' ([Sing Tao Daily/Jiemian/CCTV Finance, 2026-09-07](http://www.stnn.cc/detail/6a9e2b7ab4b06b3f17064acd.html)). In content creation, Graphite's analysis of 65,000 English articles shows that AI-generated articles first surpassed human-generated ones in November 2024, reaching 52% by May 2025 ([Kuaikeji, 2025-10-28](https://www.163.com/dy/article/KCVT0K260511CPVM.html)). To address the challenges of content proliferation and the difficulty of discerning authenticity, institutional layers are also responding; for example, TikTok has labeled over 3 billion AI-generated content items and joined the C2PA steering committee ([C2PA, 2026-07-28](https://c2pa.org/c2pa-welcomes-tiktok-to-steering-committee/)).

However, accompanying the plummeting generation costs is the stubbornness and complexity of verification costs. Although some tools claim to provide information 'without hallucinations,' RAG legal tools, for instance, still exhibit a hallucination rate of 17%–33%, indicating that verification is not a simple task. METR's randomized controlled trials found that senior open-source developers using AI experienced a 19% slowdown in tasks (July 2025); although an update in February 2026 showed an approximate 18% acceleration, significant selection bias remained, suggesting that AI assistance does not universally improve efficacy. Concurrently, agent tasks consume 5–30 times more tokens than ordinary conversations, illustrating Jevons' paradox, where increased efficiency leads to an overall increase in consumption. In the human market, attention remains an expensive cost item, and the attention economy and trust economy will coexist for the long term. Only when outputs come with machine-verifiable certificates (e.g., schema-constrained extraction, certificate-backed generation) might verification costs (Cv) be lower than generation costs (Cg), allowing the product side to retain value (arXiv, same paper, Table 1). This clearly demonstrates that 'verification approaching zero' is only a localized, not a universal, truth.

The anchor of value is undergoing a profound systematic migration. In the past, products/services focused on functionality and deliverables; today, they are shifting towards certifiable outcomes and success. Processes are transforming from tacit experience into auditable, reproducible workflows. System value is evolving from single-point tools to platforms and API interfaces. In the B2A market, attention is giving way to effective bandwidth in 'human-in-the-loop scenarios.' Trust is no longer merely a brand premium but verifiability and traceability. Responsibility is shifting from corporate backstopping to clearly accountable entities. Observable criteria for this shift include the emergence of outcome-based billing models, versioned and replayable processes, value moving from 'frontend interfaces' to 'backend APIs,' paying a premium for 'verifiable' rather than 'aesthetically pleasing' services, and the clear formalization of liability contracts. Together, these indicators depict the evolution of value from physical output to intangible management and risk control dimensions.

To determine whether a true 'revolution' has occurred, rather than mere 'refinement,' we propose four actionable criteria: ① an irreversible migration of scarcity sources; ② a fundamental change in the unit of account or pricing basis; ③ the emergence of new protocols or institutional layers (e.g., C2PA, AEO, audit APIs) that alter transaction rules; and ④ a reconstruction of the measurement system. Among these, criterion ② is a prerequisite. If only a cost reduction within the same pricing basis occurs, it should be considered a 'refinement' driven by efficiency improvements. If three or more of the above criteria are met simultaneously, it constitutes a **paradigm revolution**. According to these criteria, the generation side, by virtue of its precipitous cost drops and explosive supply growth, has already completed a paradigm revolution. However, on the verification and trust side, despite their increasing scarcity, institutional, technological, and pricing systems have not yet fully converged, thus remaining in a 'semi-revolutionary' state, awaiting further evolution and solidification.

This value paradigm shift has profound implications for the business world. Enterprise pricing models are transitioning from traditional 'pay-per-item' to 'pay-per-outcome, pay-per-subscription, pay-per-certification.' Key Performance Indicators (KPIs) may also shift from focusing on click-through rates (CTR) or daily active users (DAU) to emphasizing a 'Success-to-Interaction Ratio,' measuring the efficiency of true value creation. An API-first strategy and source credibility will become new competitive barriers, but it is important to note that platforms may still capture most of the value, and many innovative One-Person Companies (OPCs) might face challenges in pricing power. If businesses can grasp these trends and shift their core capabilities from 'what to produce' to 'how to ensure trustworthy outputs,' they are likely to gain an advantageous position in the new market.

At the organizational level, production scale is no longer simply equivalent to organizational size. The 'control plane,' comprising verification, authorization, auditing, and rollback, is replacing traditional execution departments as the core capability of organizations, signaling a shift in management focus from production efficiency to risk control and quality assurance. For individuals, the foundation of value judgment is also undergoing a fundamental transformation: from traditionally 'what can be produced' to 'ability to judge, bear responsibility, define intent, and build trust.' This shift implies that the human brain is no longer a mere executor but serves as the core judge, decision-maker, and bearer of responsibility. However, the accompanying risks should not be overlooked; over-reliance on AI could lead to the outsourcing of judgment capabilities and cognitive degradation, warning individuals to continuously enhance critical thinking and independent decision-making skills to adapt to this new value ecosystem.