Introduction

On March 5th, 2025, Manus AI (an Autonomous Agent from a Chinese startup) demonstrated its new product on X. Within a day, there were 200,000 views and in less than a week, more than 1 million requests to join the waitlist for its private beta¹.

Autonomous AI agents are emerging as a transformative force in finance and the broader economy. Unlike traditional software or even advanced chatbots, these agents can make decisions and execute tasks independently – from analyzing stock portfolios to managing complex workflows – with minimal human input. For institutional investors, the advent of AI agents like Manus.im signals a new era in which artificial intelligence not only augments decision-making but can act on its own directives in real time. This paper explores how such AI agents will impact capital markets, drive productivity and GDP growth, create new investment opportunities, and how investors should position their portfolios to benefit from this revolution.

AI Agents in Capital Markets: Automating Decisions and Execution

AI agents are poised to automate decision-making and trade execution in capital markets. Today’s quantitative funds and algorithmic traders already rely on preset algorithms, but AI agents take this further by dynamically learning, reasoning, and acting across a range of tasks without explicit instructions at each step. For example, Manus.im – a newly launched AI agent – can autonomously analyze financial transactions and market trends, then optimize decisions and execute trades or other actions that traditionally required human analysts or traders. In practical terms, an AI agent could:

• Digest news and data 24/7: Scour financial news, earnings calls, and social media in real time, gauging sentiment or detecting market-moving information faster than any human.
• Adapt trading strategies on the fly: Continually adjust portfolio positions or algorithmic strategies in response to new data (e.g. adjusting equity exposure if an economic indicator surprises, or rebalancing assets during volatility).
• Execute with precision and speed: Place orders across markets in milliseconds when conditions meet predefined risk/return criteria, or even derive those criteria through self-learning.

By automating these processes, AI agents could make markets more efficient but also potentially more volatile in the short term, as machine-driven strategies react at lightning speed. The emerging role of AI agents is thus twofold: they offer the promise of better-informed, unbiased decisions and cost savings, but also create an arms race where investment firms must deploy advanced AI to keep up with competitors. Early evidence of this shift is visible – for instance, the excitement around autonomous agents has already triggered significant capital flows into AI-driven funds (the launch of Manus reportedly led to billions of dollars moving into AI-focused ETFs within days². Going forward, trading floors may evolve into “human+AI” hybrid operations, and firms that successfully integrate autonomous decision-making AI could gain an edge in alpha generation and risk management.

Manus.im vs. OpenAI’s Operator

Manus.im has quickly positioned itself as a leading AI agent platform delivering tangible results, standing out against competitors like OpenAI’s “Operator.” Developed by Chinese startup Monica, Manus is described as a platform that “bridges minds and actions: it doesn’t just think, it delivers results.” In early demos, Manus tackled tasks ranging from planning a detailed travel itinerary to offering in-depth stock analysis and even comparing insurance policies – each from a single user prompt. Unlike large language models (LLMs) that might output a written answer or require step-by-step guidance, Manus executes multi-step tasks autonomously. For example, when asked to create a research report, Manus will independently research data, draft a report, generate charts, and produce a final document without further human direction. This hands-free execution is a significant leap in functionality, delivering end-to-end solutions rather than just information.

OpenAI introduced its first AI agent, "Operator," as a research preview on January 23, 2025.  Operator is designed to autonomously perform web-based tasks – early use cases include filling out online forms, booking travel, or handling e-commerce purchases on behalf of users³. It launched with consumer-facing partners (like Uber and DoorDash) to showcase how a user could delegate everyday online tasks to an AI. While this was groundbreaking, Operator’s current focus is narrower (mostly on consumer and browser tasks) compared to Manus’s wide-ranging ambitions across industries. Manus is pitched as a general-purpose agent that can handle business and finance tasks as readily as personal errands, and its creators claim it even outperforms OpenAI’s own agent on certain benchmarks. Indeed, early demos suggest Manus is showcasing multi-domain expertise and the ability to manage dozens of applications simultaneously.

For institutional investors, Manus’s rapid strides highlight that the competitive landscape of AI agents is global – and that disruptive innovation may come from unexpected players. A key takeaway is that AI agents are moving from concept to reality quickly; the winners will be those that can demonstrate reliability and value in executing complex tasks. Manus’s early momentum (backed by notable funding and investors) suggests it is one to watch, as it validates that an AI agent can directly drive business outcomes rather than just provide recommendations.

Productivity Gains and GDP Growth

The rise of AI agents portends a significant boost to productivity, with ripple effects on economic growth and labor markets. By automating tasks that were previously labor-intensive or time-consuming, AI agents allow firms to produce more with less human input, effectively raising output per worker (or per unit of capital). Historically, general-purpose technologies (e.g. steam power, electricity, the internet), have driven productivity surges and higher GDP growth; AI agents could be another such catalyst. In fact, economists are already projecting sizable impacts: according to PwC, global GDP could be up to 14% higher in 2030 thanks to AI adoption, equivalent to an additional $15.7 trillion in output⁴. Over half of these economic gains are expected to come from productivity improvements, as intelligent systems automate workflows and augment human efficiency.

AI agents amplify these gains by extending automation into knowledge-based and service sectors. In finance, an AI agent can handle tasks like compliance checks or portfolio monitoring overnight; in healthcare, it might automate medical data analysis; in corporate settings, it could manage scheduling, procurement, or customer service inquiries with minimal human oversight. This widespread deployment of “digital workers” has a compounding effect on productivity – potentially lifting the long-run GDP growth trajectory of advanced economies and accelerating development in emerging ones that leverage the tech. Higher productivity can also be disinflationary (lowering costs of goods and services), which might influence central bank policies and interest rates in the long term.

However, these gains will come with a reshaping of global labor markets. AI agents performing decision-making and execution tasks will inevitably displace certain job functions. Roles that involve repetitive information processing or routine decisions (for example, junior analyst work, basic accounting, customer support) are most vulnerable even as it frees them up for higher-level work. We can expect substantial workforce disruption: some jobs will be eliminated, many will evolve, and new roles (like AI system oversight, strategy, or data curation) will emerge. Global labor markets may bifurcate between those who can work effectively with AI and those who compete with AI. On a macro level, countries investing heavily in AI (such as the U.S. and China) could see outsized economic benefits. Others may risk falling behind if they cannot adapt their workforce skills and economic policies to the new AI-driven paradigm.

For investors, these economic shifts imply a need to reconsider assumptions about growth and corporate performance. Corporate earnings could swell for companies that harness AI agents to slash costs or create better products, while wage pressures might ease in some sectors due to automation (potentially increasing profit margins). At the same time, if AI-driven productivity surges, it could raise the natural rate of GDP growth and potentially investment returns across the board – but it might also increase inequality between firms (the AI haves and have-nots) and between workers of different skill levels. Prudent investors will watch metrics like productivity growth, unit labor costs, and AI adoption rates as key indicators of which economies and industries are set to outperform.

AI Investment Opportunities and Market Impact

The advent of powerful AI agents opens a wide spectrum of investment opportunities. As AI-driven efficiency gains filter through to corporate earnings and economic trends, capital allocators should view this not just as a tech fad, but as a fundamental shift in how value is created. Key areas of opportunity include:

• AI Solution Providers: The companies building the “picks and shovels” of the AI agent revolution – from semiconductor firms (supplying the GPUs and chips for AI computing) to cloud infrastructure providers and AI software platforms – stand to benefit immensely. For example, the surge in demand for AI capabilities has already driven extraordinary gains for chipmakers. As businesses race to adopt AI agents, those enabling the technology (model developers, enterprise software firms integrating AI, etc.) are poised for strong growth.
  
• Companies Leveraging AI for Efficiency: Many established companies are now incorporating AI agents or automation into their operations. Investors should look for firms that demonstrably use AI to improve productivity or enhance products/services. This could mean a bank using AI agents to handle back-office processes (reducing costs), a retail chain using AI for supply chain optimization, or a media company using AI to personalize content at scale. These efficiency gains can lead to margin expansion and higher profitability. Corporate leaders often highlight AI initiatives in earnings calls; tracking such developments can reveal who is ahead in the adoption curve. Over time, we may see a performance gap between AI-savvy firms and those sticking to traditional methods, similar to how early IT adopters outpaced others in past decades.
  
• AI in Investment Management: The financial industry itself is an investment opportunity as it embraces AI. Asset managers deploying AI agents for research or trading might achieve better risk-adjusted returns, attracting more assets. Venture capital and private equity funds are pouring money into AI startups, which could lead to lucrative exits or public offerings. Moreover, new investment products are emerging – from AI-driven ETFs to algorithmic funds – allowing investors to ride the AI wave. Institutional investors could allocate a portion of portfolios to specialized AI funds or thematic ETFs focused on AI and automation, which provide diversified exposure to this trend. The key is selectivity: not every AI promise will translate to profits, so due diligence on the real economic value created by a given AI application is crucial.
  
• Macroeconomic and Thematic Plays: On a macro level, if AI agents indeed boost global growth, it could support a bullish case for equities in general (higher growth often lifts corporate earnings broadly). Certain sectors might structurally benefit: technology and communications, but also industries like healthcare, education, and finance that could be transformed by autonomous AI services. Investors might also consider country allocation – for instance, increasing exposure to countries leading in AI adoption (like the USA) which may enjoy higher productivity and growth, while being cautious with regions slow to adapt. Additionally, as AI drives changes in labor markets, consumer spending patterns could shift (if, say, unemployment rises in some sectors or if wages stagnate, that affects consumer goods sectors). Thus, macro-focused investors will incorporate AI trends into their analyses of inflation, interest rates, and fiscal policies. A surge in productivity could keep inflation moderate even in growth periods, influencing bond yields and equity risk premiums.
  

It’s also worth noting that market sentiment is increasingly tied to AI developments. Breakthroughs or setbacks in AI can move markets. The frenzy around generative AI in 2024-2025, for example, saw large inflows into AI-related stocks and sharp rallies in tech indices, reminiscent of past tech booms. While long-term investors should avoid chasing hype, they should recognize that AI is a real paradigm shift – positioning for it early can be rewarding, but it requires staying grounded in fundamental analysis of which AI applications truly drive value.

Portfolio Strategy: Positioning for the AI Agent Era

For institutional investors, the rise of AI agents is a call to action to recalibrate portfolio strategies. Here are several ways investors can adjust portfolios to benefit from (and protect against) the growing influence of AI agents:

• Overweight AI Beneficiaries: Increase exposure to sectors and companies that are clear beneficiaries of AI-driven efficiency. This includes technology firms (AI software, cloud services, chipmakers), but also companies in any industry with a credible strategy for AI adoption. An insurer using AI agents to automate claims processing or a manufacturing firm using AI for predictive maintenance could see improved earnings – those belong in a forward-looking portfolio. Active managers should evaluate how each holding is leveraging AI; a company that aggressively and wisely deploys AI may deserve a premium, whereas one that ignores the trend could become a laggard.
  
• Underweight or Hedge AI Disruptors: Conversely, identify industries or business models at high risk of disruption from AI. For example, firms reliant on large workforces performing routine data tasks, or outsourced service providers doing back-office processing, might face margin pressure as AI can perform similar work at lower cost. If an AI agent can handle basic legal contract reviews, might it reduce the need for junior lawyers or outsourcing firms? Investors should be cautious with companies that have not articulated an AI strategy in sectors where the technology could render traditional methods obsolete. This doesn’t necessarily mean divesting entirely – but hedging those exposures or underweighting them relative to benchmarks could be prudent.
  
• Invest in Human Capital and Transition Winners: A nuanced angle is considering companies that will help facilitate the AI-driven labor transition. For instance, firms in education, training, or human capital management that re-skill workers for an AI-centric workplace could see rising demand. Similarly, companies developing AI ethics, security, and compliance solutions might become essential, given the concerns around autonomous decision systems. These are more indirect plays but could be part of a holistic strategy to capture value around AI adoption.
  
• Balance Growth with Quality: While AI agents promise growth, investors should also focus on quality and robustness. Not every company touting AI will succeed – some may over-invest in wrong initiatives or face execution challenges. Maintain a balanced portfolio where AI-exposure is coupled with strong balance sheets and cash flows. This balance will help weather any volatility if the “AI boom” experiences pauses or shakeouts (for example, if regulation of AI tightens or if a high-profile failure sours sentiment temporarily).
  
• Engage with Asset Managers on AI Integration: Institutional allocators (pension funds, endowments, etc.) should ensure the asset managers they employ are themselves integrating AI into their investment process. Many hedge funds and quant funds are already using AI for signal generation and risk management. Traditional managers are starting to use AI tools for research (like parsing financial statements or transcripts faster). When selecting external managers or funds, due diligence can include questions about how they leverage technology and AI. Those who use AI thoughtfully might gain an edge, which in turn benefits the allocators entrusting them with capital.

In summary, the rise of AI agents should influence both where you invest and how you invest. Portfolio construction in this era means capturing the upside of AI-driven innovation while managing the transition risk in disrupted industries. It also means being agile – the AI field is evolving quickly, so investors must remain informed about technological advances and be ready to adjust exposures as the landscape changes.

Conclusion

The ascendance of AI agents will mark a pivotal shift in capital markets and the global economy. These agents are automating decision-making and execution in ways that promise significant productivity gains and potentially faster GDP growth, albeit with disruptive effects on labor markets and competitive dynamics. For institutional investors, the message is clear: AI applications are no longer niche considerations but core drivers of future returns and risks. Understanding AI agents’ capabilities and implications will be as essential as tracking interest rates or earnings reports. Investors should embrace this change by repositioning portfolios to favor AI-powered value creation, supporting companies and technologies leading the charge, and guarding against the pitfalls for those left behind. Much like previous technological revolutions, those who recognize the trend early and adapt will reap the rewards. In the coming years, capital markets themselves may be partially run by AI agents collaborating with humans, productivity across sectors could surge, and new winners and losers will emerge based on AI proficiency. A proactive, informed investment approach will ensure that as AI agents transform our economic landscape, portfolio performance is enhanced rather than hindered by this historic shift. The bottom line for institutional investors: position for the AI agent era, or risk playing catch-up in a market that’s moving at machine speed.

¹Economic Times - “Manus AI: China's new AI agent can plan your Japan trip and offer analysis of stocks. 10-point explainer”)

²Medium Blog Post - “Manus AI: How China's Fully Autonomous AI Agent Is Redefining …”

³Bain Capital Ventures - “OpenAI Operator Signals the Agentic Era of Commerce is Here”

⁴World Economic Forum - “The global economy will be $16 trillion bigger by 2030 thanks to AI”