SpaceX raises residential and Roam plans by $5-$10 and doubles Standby Mode to $10


TL;DR

SpaceX has raised prices on every consumer Starlink plan by $5 to $10 per month and doubled Standby Mode from $5 to $10, effective immediately for new customers and from 18 June for existing subscribers. The increases come as Starlink crosses 10 million users and SpaceX prepares for its IPO.

SpaceX has raised the price of every consumer Starlink plan in the United States, adding $5 to $10 per month across its residential and mobile tiers while doubling the cost of its budget Standby Mode from $5 to $10. The increases, which took effect immediately for new subscribers and will apply to existing customers from their next billing cycle on or after 18 June, come as SpaceX prepares for what would be the largest initial public offering in history and as its only serious competitor, Amazon’s satellite internet service, approaches commercial launch.

What changed

The new pricing touches every consumer tier except the recently introduced Roam 300GB plan, which remains at $80 per month. Residential plans, designed for fixed-location use at homes, rose across the board: the 100 Mbps tier went from $50 to $55, the 200 Mbps tier from $80 to $85, and the MAX tier, which offers the fastest available speeds, from $120 to $130. Roam plans, which allow mobile use at speeds of up to 100 mph and work across international borders, also increased: Roam 100GB moved from $50 to $55, and Roam Unlimited from $165 to $175.

The most notable change is to Standby Mode, a feature introduced in 2025 that allows subscribers to pause their active service while maintaining a minimal 500 Kbps connection for emergency use, firmware updates, and basic connectivity. At $5 per month, Standby was an attractive option for seasonal users, RV owners, and anyone who wanted to keep their Starlink hardware alive without paying for full service. At $10, the calculus shifts: the doubled price, combined with recent restrictions that removed in-motion use from Standby in March and eliminated the demand surcharge shield in April, makes the feature substantially less appealing than when it launched.

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SpaceX’s justification was terse. The company told customers in an email notification that the adjustment “supports ongoing improvements and investment in affordable, high-performance products and services as global operating costs continue to rise.”

The business context

The price increases arrive at a moment when SpaceX’s satellite internet business has never been stronger. Starlink crossed 10 million subscribers worldwide in February 2026, roughly doubling its user base in a single year. The constellation now consists of more than 10,000 satellites in low Earth orbit, representing approximately 65 per cent of all active satellites, and covers between 125 and 155 countries and territories. Revenue for 2025 reached $11.4 billion, with EBITDA margins of 63 per cent.

SpaceX’s public IPO filing targets a valuation of approximately $1.75 trillion and a raise of $75 billion, which would make it the largest public offering in history. A February 2026 all-stock merger with Elon Musk’s AI company xAI valued the combined entity at $1.25 trillion but also imported xAI’s cash burn onto SpaceX’s balance sheet for the first time, with the merged company posting a net loss of $4.94 billion in 2025 despite $18.67 billion in combined revenue.

The price increases, applied across more than 10 million accounts, could generate hundreds of millions of dollars in additional annual revenue, a meaningful contribution to the revenue growth story that SpaceX will need to tell public market investors. Notably, SpaceX actually reduced prices for its business-focused Local Priority plans earlier this month, suggesting a strategic decision to test consumer price elasticity while keeping enterprise rates competitive.

The competition question

For most of its existence, Starlink has operated without meaningful competition in the consumer satellite broadband market. That is about to change. Amazon’s satellite internet service, rebranded from Project Kuiper to Amazon Leo, entered enterprise beta in April 2026 with commercial availability targeted for mid-2026. Amazon has authorisation to launch more than 3,000 broadband satellites and has signed beta partnerships with Verizon, AT&T, Vodafone, JetBlue, and NASA.

European alternatives like Eutelsat are also building competing constellations, though none has yet reached the scale or coverage that Starlink offers. The timing of SpaceX’s price increases, just months before Amazon Leo’s commercial launch, suggests either confidence that its first-mover advantage is durable or a calculation that it needs to extract maximum revenue now before competitive pressure constrains pricing.

Early analysis of the satellite broadband market projected that low-earth-orbit internet could save American consumers $30 billion a year by introducing competition into markets dominated by a single terrestrial provider. That projection assumed competitive pricing among satellite operators. If Starlink raises prices in the absence of competition and Amazon matches those prices upon launch, the savings may never materialise.

What it means for users

The increases are modest in isolation, $5 to $10 per month, but they follow a pattern. SpaceX has changed Starlink’s pricing, plan structure, or feature availability at least five times in 2026 alone: the Standby in-motion removal in March, the demand surcharge shield removal in April, the new Roam 300GB plan introduction in May, the business plan price decreases in May, and now the consumer price increases. The company also introduced a new travel registration policy in May requiring passport and selfie verification for international roaming.

For residential customers in areas with no terrestrial broadband alternative, the increases are an unavoidable cost of being connected. For mobile users who rely on Starlink’s Roam plans for RV travel, maritime use, or remote work, the combination of price increases and feature restrictions makes the service incrementally less attractive at a time when cellular networks are expanding rural coverage through T-Mobile and SpaceX’s own direct-to-cell partnership.

The Standby Mode doubling is particularly significant for seasonal users. At $5 per month, keeping a Starlink dish alive during the off-season was effectively a rounding error. At $10, some users may choose to cancel entirely and reactivate when needed, a process that currently carries no additional fee. SpaceX may be betting that the friction of reactivation, or the risk that it introduces one, will keep enough subscribers on Standby to justify the higher price.

The broader picture is a company that has built an extraordinary product, satellite broadband that genuinely works, delivered to 10 million people in places that no terrestrial provider had any commercial interest in serving, and that is now monetising its monopoly position before competition arrives. Whether the pricing reflects the genuine cost of maintaining and expanding a 10,000-satellite constellation or simply the leverage of being the only option, the answer for most Starlink customers is the same: there is, for now, nowhere else to go.



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  • Scaling agentic AI starts with rethinking how work gets done. 

Gartner forecasts that worldwide AI spending will total $2.5 trillion in 2026, a 44% year-over-year increase. Spending on AI platforms for data science and machine learning will reach $31 billion, and spending on AI data will reach $3 billion.

The global agentic AI market will reach $8.5 billion by the end of 2026 and nearly $40 billion by 2030, per Deloitte Digital. Organizations are rapidly accelerating their adoption of AI agents, with the current average utilization standing at 12 agents per organization, according to MuleSoft 2026 research. This rate is projected to increase by 67% over the next two years, reaching an average of 20 AI agents. 

Also: How to build better AI agents for your business – without creating trust issues

According to IDC, by 2026, 40% of all Global 2000 job roles will involve working with AI agents, redefining long-held traditional entry, mid, and senior level positions. But the journey will not be smooth. By 2027, companies that do not prioritize high-quality, AI-ready data will struggle to scale generative AI and agentic solutions, resulting in a 15% loss in productivity. While 2025 was the year of pilot experiments and small production deployments of agentic AI, 2026 is shaping up to be the year of scaling agentic AI. And to scale agentic AI, according to IDC’s forecast, companies will need trustworthy, accessible, and quality data. 

Scaling agentic AI adoption in business requires a strong data foundation, according to McKinsey research. Businesses can create high-impact workflows by using agents, but to do so, they must modernize their data architecture, improve data quality, and advance their operating models. 

McKinsey found that nearly two-thirds of enterprises worldwide have experimented with agents, but fewer than 10% have scaled them to deliver measurable value. The biggest obstacle to scaling agent adoption is poor data — eight in ten companies cite data limitations as a roadblock to scaling agentic AI. 

Also: AI agents are fast, loose, and out of control, MIT study finds

McKinsey identified the top data limitations as primary constraints that companies face when scaling AI, including: operating model and talent constraints, data limitations, ineffective change management, and tech platform limitations. 

Data is the backbone of agentic AI

Research shows that agentic AI needs a steady flow of high-quality, trusted data to accurately automate complex business workflows. Successful agentic AI also depends on a data architecture that can support autonomy — executing tasks without human intervention. 

Two agentic usage models are emerging: single-agent workflows (one agent using multiple tools) and multi-agent workflows (specialized agents collaborate). In each case, agents will rely on access to high-quality data. Data silos and fragmented data would lead to errors and poor agentic decision-making. 

Four steps for preparing your data 

McKinsey identified four coordinated steps that connect strategy, technology, and people in order to build strong foundational data capabilities. 

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  1. Identify high-impact workflows to ‘agentify’. Focus on highly deterministic, repetitive tasks that deliver value as strong candidates for AI agents. 

  2. Modernize each layer of the data architecture for agents. The focus on modernization should support interoperability, easy access, and governance across systems. The vast majority of business applications do not share data across platforms. According to MuleSoft research, organizations are rapidly adopting autonomous systems. The average enterprise now manages 957 applications — rising to 1,057 for those furthest along in their agentic AI journey. Only 27% of these applications are currently connected, creating a significant challenge for IT leaders aiming to meet their near-term AI implementation goals. 

  3. Ensure that data quality is in place. Businesses must ensure that both structured and unstructured data, as well as agent-generated data, meet consistent standards for accuracy, lineage, and governance. Access to trusted data is a key obstacle. IT teams now spend an average of 36% of their time designing, building, and testing new custom integrations between systems and data. Custom work will not help scale AI adoption. The most significant obstacle to successful AI or AI agent deployment is data quality, cited as the top concern by 25% of organizations. Furthermore, almost all organizations (96%) struggle to use data from across the business for AI initiatives.  

  4. Build an operating and governance model for agentic AI. This is about rethinking how work gets done. Human roles will shift from execution to supervision and orchestration of agent-led workflows. In a hybrid work environment, governance will dictate how agents can operate autonomously in a trustworthy, transparent, and scaled manner. 

The work assigned to AI agents 

McKinsey highlighted the importance of identifying a few critical workflows that would be candidates for AI agents to own. To begin, an end-to-end workflow mapping would help identify opportunities for agentic use. McKinsey found that AI adoption is led by customer service, marketing, knowledge management, and IT. It is important to identify clear metrics that validate impact. Teams should identify the data that can be reused across tasks and workflows.

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McKinsey concludes that having access to high-quality data is a strategic differentiator in the agentic AI era. Because agents will generate enormous amounts of data, data quality, lineage, and standardization will be even more important in the agentic enterprise. And as agentic systems scale, governance becomes the primary level for control. The data foundation will be the competitive advantage in the agentic era. 





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