"Which assets will benefit or be negatively impacted by the Agentic economy of Openclaw?"

Author: Changan I Biteye Content Team

In the past, AI was like an intern that could only talk; now, OpenClaw is a seasoned pro that can get things done directly.

Previously, if you asked AI how to book a ticket, it would give you a guide; now, when you say "I want to go to Shanghai," it directly helps you compare prices, place orders, and select seats. Just like the automatic food ordering feature demonstrated by Qianwen, AI has begun to deliver execution results across apps.

This shift is quietly stealing the wallets of many companies, leading to a decline in valuations.

This article will analyze the asset repricing logic triggered by this productivity transformation from the following dimensions:

• Value Collapse: Analyzing which old assets that rely on human premiums and information asymmetry are losing their moats.

• Value Migration: Exploring how capital flows towards computing power, energy, crypto settlement protocols, and embodied intelligent hardware.

• Practical Guide: Providing individuals with coping strategies based on cutting-edge product experiences.

I. Value Collapse: Which Old Assets Are Losing Their Moats?

1. Stocks of SaaS Companies

The software industry is undergoing a transformation from function-oriented to execution-oriented. In the past, users paid for software primarily to leverage its UI to reduce operational difficulty, completing tasks with mouse clicks.

However, when AI Agents gained the ability to directly drive underlying logic and deliver results, the value of traditional software as an operational entry point began to crumble. Users no longer need complex software interfaces; they just need to issue commands, and the Agent can complete tasks at the underlying level.

Editor’s practical experience: The photo editing feature of Gemini's Nano Banana is more user-friendly than Meitu.

This shift in logic has already triggered panic in the capital markets. Recently, the U.S. software sector has been experiencing a significant valuation correction:

• Sector Plunge: At the end of January 2026, the S&P North American Software Index plummeted about 15% in a single month, marking the largest monthly decline since the 2008 financial crisis.

• Giant Shrinkage: In just a few recent trading days, the market capitalization of the U.S. software sector evaporated by over $800 billion.

Investors have realized that those SaaS companies that only provide simple functions and lack core data moats are being hit hard by AI. Currently, 89% of publicly listed software companies globally have valuations below 10 times earnings, with an average stock price decline of up to 33%.

(Source: @afc)

2. Stocks of Basic Intermediary Platforms

In traditional business models, aggregation platforms profit by integrating dispersed information, leveraging information asymmetry and controlling traffic entry points. They charge commissions to merchants and display ads to users, essentially acting as intermediaries.

However, platforms like OpenClaw have completely disrupted this pattern:

• Bypassing the Middle Layer: When Agents possess the ability to automatically negotiate and place orders, they no longer need to operate through intermediary platform interfaces. Agents connect directly with the underlying service providers (such as airline websites, hotel websites), thus bypassing the commissions of intermediary platforms.

• Advertising Model Failure: Merchants used to buy traffic to get visibility, but Agents do not view ads. Those spammy listings that relied on paid placements will completely lose their audience.

Case Comparison: Currently, the phenomenon of different prices for the same product across e-commerce platforms is severe. For the same item, Xiaohongshu or Douyin often have higher prices due to video ad premiums compared to Pinduoduo. But in the AI era, Agents will directly lock in the lowest price across the internet with absolute rationality, causing the premium space for platforms that rely on information asymmetry to rapidly shrink to zero.

As Goldman Sachs stated in its "2026 Global Internet Revaluation Report": 2026 will be a turning point for intermediary platforms to degrade from aggregation to data providers.

Goldman Sachs Chief Information Officer Marco Argenti pointed out that as AI Agents can directly penetrate traditional traffic to make decisions, platforms that rely on paid placements for customer acquisition are losing their Take Rate moats.

3. Real Estate-Related Funds and Stocks (Especially Commercial Real Estate)

The carrier of productivity is shifting from people to code. While humans need physical office spaces and residences, Agents only require data centers, electricity, and hardware. This reconstruction of production relations is causing a displacement in the value logic of traditional real estate assets.

1. Shrinking Demand for Office Space

In the past, the primary purpose of large enterprises renting office buildings in prime locations was to accommodate employees. As AI Agents enter the large-scale commercial application phase in 2026, the demand for physical workstations is beginning to plummet dramatically.

Goldman Sachs predicts that due to the impact of AI, the U.S. will lose about 20,000 traditional administrative and professional service jobs each month by 2026.

2. Capital Shift: From Commercial Locations to Energy and Computing Power

Capital is flowing from properties in bustling locations to data center assets that offer low electricity costs, stable power grids, and high cooling efficiency.

Morgan Stanley noted in a report at the beginning of 2026 that energy supply has replaced chips as the primary bottleneck for AI expansion. This means that the value of land is no longer determined by its distance from business centers, but by its ability to access cheap electricity and fiber optic backbone networks.

As of early 2026, the average price of office buildings in U.S. cities has dropped by about 50% from previous peaks. This decline reflects the market's final pricing in response to the dual impact of remote work and AI automation.

The overall vacancy rate for office space in the U.S. had already risen to over 20% by the end of 2024, breaking historical records from 1986 and 1991. In areas where tech and administrative job losses are most severe, this figure is approaching the 35% warning line.

4. Human Resource Service Companies (Outsourcing and Consulting Assets)

The valuation logic of these companies was once based on the premise that employee scale equals productivity. However, as Agents can replace junior analysts, programmers, and legal assistants at a very low cost, the large number of employees is shifting from being an asset to a heavy operational liability.

Capital is rapidly withdrawing from those labor-intensive professional service sectors: such as Accenture (ACN) and Infosys (INFY). These companies rely on a large number of junior programmers to support their business, but now AI can complete the vast majority of standardized coding tasks.

The film industry has conducted on-site research in Kenya on the local paper-writing outsourcing industry. This labor outsourcing sector, which once supported hundreds of thousands of locals, is experiencing a devastating blow in the face of AI:

• Sharp Decline in Orders: Local practitioners stated in a video that due to students turning to AI for generating papers, the volume of writing orders has plummeted. Tasks that used to cost hundreds of dollars to hire African writers can now be completed at almost zero cost through AI.

• Skill Value Approaching Zero: Being good at English and writing papers was once a core competitive advantage, but in the face of AI, the value of this kind of basic intellectual labor has rapidly diminished. This is not only a crisis for individual writers but also a common negative for platforms like Upwork and Fiverr that rely on individual labor to extract commissions.

The capital market no longer views employee scale as a competitive barrier. If a company still relies on increasing manpower as its core growth engine, it will face the risk of productivity efficiency being completely covered by AI. In the future, high-value assets will concentrate on lightweight entities capable of driving large-scale Agent operations through code.

II. Where Is the Money Flowing?

1. Restructuring of Production Factors: Demand for Computing Power and Energy Certainty

When the moats of old assets collapse, wealth does not disappear but flows to the underlying infrastructure that supports Agent operations.

The operation of Agents essentially involves the continuous consumption of electricity and computing power. Companies are reallocating the physical office costs (such as office rent) that were originally used to accommodate employees to computing power subscriptions and energy security expenditures.

Token fees have become a core burden for business operations. Current top models (such as Claude Code/Seedance 2.0) have high inference costs, with complex tasks costing thousands of dollars per instance. The high costs are forcing the industry into a competition over inference costs.

With the application of dedicated inference chips and open-source models (such as DeepSeek, Kimi), the cost of inference per instance will continue to decline, making electricity quotas an irreplaceable scarce production factor.

In this wave of value transfer, hardware and energy assets with certainty of supply attributes have become the biggest beneficiaries:

• Core Computing Hardware: NVIDIA, AMD. They provide the computing power foundation required for Agent operations and are core suppliers of AI productivity.

• Energy and Utilities: Vistra Corp, Constellation Energy. Companies that control stable electricity have been revalued from traditional defensive sectors to premium assets in the AI supply chain.

• Digital Infrastructure REITs: Equinix, Digital Realty. The IDC data centers they operate are now receiving capital that previously flowed to traditional office buildings.

In summary, the pricing power of assets is shifting from landlords providing office space to suppliers providing computing energy.

2. AI's Automated Payment System: From Manual Confirmation to Code-Driven Settlement

As mentioned earlier, Agents have made traditional intermediary platforms obsolete through price comparison, but price comparison is just the first step. Once Agents lock in the optimal price, they must have the ability to autonomously complete transactions. The limitations of the current traditional payment system prevent it from closing the loop, driving capital towards code-driven crypto protocols.

For example, the recent demonstration of the "automatic bubble tea ordering" feature by Qianwen shows that AI can now perform cross-app purchasing and ordering operations, proving the maturity of Agents in decision-making and interaction. However, in practical implementation, automated processes often break down at the final payment stage because traditional banking systems still require manual face scans, SMS verification codes, or physical identity checks.

This gap where decisions can be made but payments cannot be completed is where programmable trading protocols like X402 find their value.

Beneficial Assets:

• Programmable Trading Protocols (such as X402): Provide Agents with private key management and fund invocation capabilities, allowing them to bypass traditional payment interfaces and execute financial interactions directly through code.

• Stablecoins (such as USDT, USDC): Provide a 24/7 online, no human review clearing environment, serving as the settlement benchmark for Agent commercial activities.

• High-Performance Public Chains (such as Kite AI): A Layer 1 blockchain tailored for Agents, providing a low-latency execution environment. Through programmable governance and identity, it offers Agents legitimate identity and permission control, allowing them to evolve from isolated tools into economic entities capable of autonomous decision-making, collaboration, and profit generation. With the explosive growth of Agent transaction volumes, Kite AI, as a core collaborative infrastructure, has shown strong price performance in recent markets.

The current situation where Agents can compare prices but cannot make payments is driving the rise of crypto settlement systems. Protocols that master automated payment interfaces will take over the business flow lost by traditional financial intermediaries.

3. Evolution of Productivity Forms: Embodied Intelligence and Physical Execution Hardware

Once AI solves the problems of logical decision-making and software interaction, capital begins to flow towards physical entities that can carry this intelligence. Budgets originally allocated for purchasing "basic intellectual labor" are being reallocated to hardware assets with physical execution capabilities.

As Agent intelligence reaches a critical point, the only bottleneck limiting its performance is its physical form. Capital is flowing towards robotic hardware to fill the execution gaps of AI in the real world.

• Extension of Work Scenarios: The application of Agents is expanding from computer screens to physical spaces. By utilizing OpenClaw for logical control, AI can intervene in home management (such as cleaning supervision and homework assistance) and industrial production.

• Capital Expenditure Replacement: Companies and households are shifting costs. Expenses that were originally paid to human assistants and junior outsourced workers are being converted into fixed asset expenditures for purchasing embodied intelligent devices (such as home service robots and industrial robots).

Asset Categories with Certainty of Benefit:

• Core Components of Embodied Intelligence: At the beginning of 2026, there was a significant increase in the prices of robotic joints (reducers, servo motors), tactile sensors, and other sectors. These components are the hardware foundation for Agents transitioning from code to physical execution.

• Programmable Automation Devices: Intelligent factory equipment and smart home terminals that can open underlying interfaces, allowing Agents to connect and directly control them.

Goldman Sachs pointed out that the combination of Agents and robots is triggering a generational shift in capital expenditure. As Agents significantly enhance the return on investment for hardware, budgets that were originally directed towards labor outsourcing are being transformed into procurement orders for robotic assets at an annual rate of 25%.

Agents endow hardware with the ability to think, while hardware provides Agents with a means to monetize. This complementarity determines that the evolution of Agents will inevitably lead to a reevaluation of the value of physical execution assets.

III. Summary of KOL Perspectives

Teddy@DeFiTeddy2020 (XHunt Ranking: 1742)
Viewpoint: The agency economy driven by OpenClaw will significantly lower the valuations of SaaS software stocks, intermediary platform stocks, and commercial real estate-related assets, as AI agents directly call APIs, autonomously search for bargains, and do not require physical offices. Traditional assets that rely on human behavior will face systemic revaluation.

https://x.com/DeFiTeddy2020/status/2020762007625248925?s=20

Haotian@tmel0211 (XHunt Ranking: 1202)

Viewpoint: AI + Crypto will be a grand track that crosses the boundaries of web2 and web3, which is an inevitable result of the development of the Agentic Economy track. Once AI moves towards decentralization, the trusted payments, identities, contracts, etc., it requires are all strengths of Crypto, which is worth looking forward to.

https://x.com/tmel0211/status/2020319970908074021?s=20

Dov@dov_wo (XHunt Ranking: 1843)

Viewpoint: The era of major turning points has arrived, with SaaS and software company stock prices collapsing, such as Chegg being crushed by GPT-4; ClaudeCode and OpenClaw will lead to unemployment for high-paying positions like Wall Street analysts and lawyers, with layoffs exceeding 50% within three years. Traditional education will become useless, and students will be replaced by AI with 10 times the efficiency and double the effectiveness. This is a plunder of wealth and meaning from the old generation by the new generation. Humans need rest, but AI continues cheaply; everything will end. People should avoid documents like Notion and turn to AI to connect the old and new worlds.

https://x.com/dov_wo/status/2020045763330601007?s=20

BuccoCapital Bloke@buccocapital (XHunt Ranking: 3935)

Viewpoint: Although "internal building" is no longer the main reason for the current SaaS bear market (as many companies still rely on ready-made SaaS), the AI agent economy will still bring multiple structural pressures, leading to long-term pressure on SaaS companies and even valuation revaluation: platform differentiation is approaching zero (customer acquisition costs are rising sharply), value is migrating to the agent layer, AI-native startups are providing better outcome-based solutions that erode LTV, seat revenue models are collapsing, transitioning from "charging by seat" to "charging by outcome" is difficult, pricing power and gross margins are deteriorating, organic traffic is decreasing, further raising CAC, and competition for AI talent is increasing operational costs. Investors must have a clear judgment on the intensity and time window of these bear market factors.

https://x.com/buccocapital/status/2015603777420607967?s=20

Alex Clayton@afc (XHunt Ranking: 31467)

Viewpoint: The current situation of public software company valuation multiples is bleak, with 89% of over 100 companies trading below 10 times NTM revenue, and only 3 exceeding 20 times; most companies have stagnant revenue growth, with a median ARR annual growth of only 15%, far inferior to AI newcomers like Anthropic. Although AI may replace some budgets, it is not the root cause; the real problem is that most SaaS vendors have not developed AI products that customers are willing to pay for. If they cannot innovate and prove AI traction, these traditional companies will continue to experience low growth, low valuations, and gradual decline. Now is a critical period for them to transform with AI.

https://x.com/afc/status/2014133417538130351?s=20

IV. Conclusion: What Should Ordinary People Do?

In the face of asset repricing, the most effective way for ordinary people to participate is to deeply experience cutting-edge products and perceive the changes in productivity boundaries.

1. Master Vibe Coding: Achieving Iteration of Development Paradigms

Tools represented by Claude Code 2.0 have changed the underlying logic of software development.

The focus of development has shifted from writing code line by line to optimizing macro architecture. If a function that originally required a week of team collaboration can now be completed by an individual with AI assistance in a few hours, this means that the valuation logic of traditional software outsourcing assets, which profit from human scale, is facing a major overhaul.

By attempting to convert the time saved by AI into excess personal productivity gains.

2. Identify the Cost Inflection Point in Video Production: Taking Seedance 2.0 as an Example

The popularity of video generation models like Seedance 2.0 marks a structural decrease in the cost of producing visual content.

• Assessing Physical Asset Risks: By generating complex advertising storyboards, it can be observed that when the fidelity of AI-generated images approaches that of real shooting, the asset values of rental companies with expensive filming equipment and traditional film studios will shrink.

• Identifying Track Changes: By experiencing highly integrated generation tools, one can discern which tracks are in the clearing stage and which tracks are gaining increments due to technological empowerment.

3. Find Missing Points in Business Closed Loops: Looking at Transaction Protocols from Payment Bottlenecks

The performance of Qianwen in scenarios like automatic bubble tea ordering reveals the gap between decision-making and execution for Agents.

• Positioning Growth Opportunities: In daily operations, look for those points where AI can make decisions but cannot complete transactions; these links will be the core growth areas of the future.

• Verifying On-Chain Settlement Logic: When Agents cannot complete payments through traditional banking systems, capital will inevitably flow to programmable on-chain protocols. This proves that X402 and its related infrastructure are not speculative assets but necessary links to complete the commercial closed loop of Agents.

Core Advice: By continuously applying advanced tools in work and life, maintain sensitivity to changes in productivity. In 2026, the most robust asset will be an individual's ability to integrate across fields and a deep understanding of the core nodes of the AI supply chain (energy, computing power, settlement, execution).