Meta Muse: The next wave of AI winners and disruption

Key points:

• AI is moving from answering questions to completing tasks, potentially creating new demand for memory, computing infrastructure, payments and cybersecurity as they take on more complex tasks.
• AI agents could also challenge established business models by making it easier for consumers to compare prices, switch providers and complete transactions without visiting individual websites or apps.
• The investment opportunity is broader than Meta, but adoption alone does not guarantee earnings growth. Investors need to distinguish between companies that could capture new revenue, those facing greater competition and those that could do both.

What is Meta Muse, and why does it matter?

Launched on 8 September 2026, Meta's Muse is a personal AI agent designed to perform tasks rather than simply answer questions. It can work across websites and applications, helping users manage emails, compare products, organise travel and complete purchases with their approval.

Imagine asking an AI agent to organise a family holiday within a budget, compare insurance renewal quotes or identify a more competitive savings account. Tasks that previously required multiple searches, phone calls and forms could become a single instruction.

For investors, this raises an important question: who benefits when AI starts doing the work, and whose existing business model could face disruption?

The benefits and the disruptions

The potential benefits extend beyond companies developing AI models. More sophisticated agents could support demand for memory, computing infrastructure, payments and cybersecurity. Businesses adopting AI could also improve productivity and reduce operating costs.

But the same technology could challenge established business models. AI agents may make it easier for consumers to compare prices, switch providers and complete transactions without visiting individual websites or apps.

Companies that rely on customer inertia, complex pricing or control over product discovery could face greater competition. Those with differentiated products, proprietary data and strong customer relationships may be better placed to adapt.

Eight investment themes from Muse

1. Memory: More AI activity, more memory demand

Stocks for reference: Micron, SanDisk, SK Hynix, Samsung Electronics

AI agents can perform multiple tasks, process larger amounts of information and operate continuously. Wider adoption could support demand for high-bandwidth memory (HBM), server DRAM and data storage.

Memory manufacturers could benefit from expanding AI inference workloads, with demand extending beyond HBM used in AI accelerators to broader data-centre memory requirements.

The risk is that memory remains cyclical. Expanding supply and improvements in computing efficiency could moderate pricing and earnings growth.

2. AI infrastructure: The computing power behind agents

Stocks for reference: Nvidia (NVDA), AMD (AMD), Broadcom (AVGO), TSMC (TSM), Intel (INTC), Arm (ARM), Vertiv (VRT)

AI agents require computing capacity to process information, coordinate tasks and interact with applications. Wider adoption could support demand for processors, networking, semiconductor manufacturing and data-centre infrastructure.

Nvidia and AMD provide exposure to AI accelerators, Broadcom to custom chips and networking, and TSMC to advanced manufacturing.

Intel offers exposure through server processors, AI inference hardware and advanced packaging, while Arm's power-efficient CPU technology could benefit from increasing AI workloads across cloud and personal devices. Both are developing products designed for agentic AI.

Vertiv provides exposure to supporting power and cooling infrastructure.

The risk is that more efficient AI models and slower infrastructure spending could moderate demand growth.

3. E-commerce: Who controls the shopping journey?

Stocks for reference: Shopify (SHOP), Amazon (AMZN)

AI agents could compare products, identify alternatives and complete purchases without consumers visiting individual retail websites.

Shopify could benefit by helping merchants make products accessible through AI platforms, creating additional sales channels.

Amazon faces a more complex equation. External agents could challenge its control over product discovery and customer relationships. However, its own AI capabilities, merchant network and fulfilment infrastructure could help protect its position.

The key question is whether AI generates incremental sales or shifts customer relationships and transaction economics towards external platforms.

4. Payment gateways: Enabling AI-driven transactions

Stocks for reference: PayPal (PYPL), Visa (V), Mastercard (MA)

AI agents may change how consumers initiate purchases, but transactions still require secure payments, authentication and fraud protection.

PayPal could benefit from its agentic commerce capabilities, while Visa and Mastercard provide established payment infrastructure that could support AI-initiated transactions.

However, AI platforms may choose different payment partners or develop alternative checkout solutions. Greater transaction volumes may therefore come with increased competition over fees and customer relationships.

5. Banks, brokers and insurers: Customer loyalty faces a test

Stocks for reference: Charles Schwab (SCHW), Wells Fargo (WFC), Bank of America (BAC), Progressive (PGR)

AI agents could make it easier to compare savings rates, investment fees, lending products and insurance premiums, potentially reducing the inconvenience of switching providers.

For banks, greater deposit-rate transparency could increase competition for customer balances. Brokerages may face pressure on fees and cash-management economics, while insurers could see customers comparing renewal quotes more frequently.

However, financial institutions could also use AI to lower operating costs and improve customer service.

Investors should monitor customer retention, pricing power and margins rather than assuming uniform disruption across the sector.

6. Travel and mobility: The battle for bookings

Stocks for reference: Booking Holdings (BKNG), Expedia (EXPE), Airbnb (ABNB), Uber (UBER), Lyft (LYFT)

AI agents could organise complete trips, comparing accommodation, flights and transport before making reservations.

This could reduce direct traffic to traditional booking platforms and weaken customer loyalty to individual travel or ride-hailing apps.

However, established platforms retain valuable supplier relationships, accommodation inventory, driver networks and fulfilment capabilities. They could also integrate with AI agents to generate additional transactions.

The key distinction is whether these businesses lose the customer interface, the underlying transaction or both.

7. Search and advertising: From clicks to transactions

Stocks for reference: Alphabet (GOOGL), Amazon (AMZN), Meta (META)

Traditional digital advertising relies heavily on attracting attention and directing consumers towards products or services. AI agents could compress that journey by completing research and facilitating purchases within a single interface.

Alphabet and Amazon could face changes in traditional search and product discovery, while Meta could gain opportunities to monetise AI-driven commerce alongside advertising.

All three are also developing their own AI capabilities.

The opportunity is a potential shift towards advertising based on completed transactions rather than clicks, although the revenue implications remain uncertain.

8. Cybersecurity: Securing the AI-agent economy

Stocks for reference: CrowdStrike (CRWD), Palo Alto Networks (PANW), Okta (OKTA)

As AI agents gain access to emails, financial accounts and business applications, security requirements could become more complex.

Businesses may need additional tools for identity verification, permission management, threat detection and protecting sensitive information.

Cybersecurity companies could benefit from these emerging requirements. However, competition and security features built directly into AI platforms could limit incremental revenue opportunities.

Disclaimer: The stocks mentioned are illustrative references and do not constitute investment recommendations. The potential benefits and disruptions discussed are scenarios rather than forecasts. Investors should consider company fundamentals, valuations, diversification and individual risk tolerance.

How should investors position for the AI-agent era?

Muse highlights why AI exposure need not be limited to semiconductor manufacturers and companies developing large AI models.

Investors may consider three complementary areas: the infrastructure supporting AI adoption, businesses enabling AI-driven transactions, and established companies that could use AI to improve efficiency even as competition increases.

The important distinction is between exposure to a growing technology and the ability to translate that growth into sustainable earnings.

Investors should assess revenue opportunities, competitive advantages, capital requirements and valuations rather than assuming every company associated with AI will benefit equally.

Risks to the view

• AI-agent adoption could be slower than expected, particularly if consumers remain reluctant to delegate sensitive financial or purchasing decisions. Privacy, security, reliability and regulatory concerns could also constrain usage.
• Businesses may restrict external agents from accessing their platforms, limiting the potential disruption to established distribution channels.
• Meanwhile, improvements in AI efficiency could moderate infrastructure demand, while competition could pressure monetisation across AI platforms, payments and commerce.
• Valuations are another important consideration. Strong growth expectations may already be reflected in share prices, leaving investors exposed if adoption or profitability falls short.

The bottom line

Muse brings the AI investment debate closer to the real economy. The next phase is not just about building more computing capacity, but about how AI could change consumer behaviour, business profitability and competitive advantages.

The investment opportunity lies in identifying who captures the economic value when AI starts doing the work and which established businesses can adapt as the rules of competition change.