Meta Platforms is expanding its monetization strategy with Meta One, a subscription product designed to generate revenue from the company’s growing artificial intelligence ecosystem. Pricing reportedly begins at $2.99 per month and rises to $14.99 for creator and business-oriented bundles.

The initiative represents a potentially important evolution for Meta. Advertising remains the company’s core revenue engine, but the introduction of paid AI services could create additional monetization channels as the company invests heavily in computing infrastructure, AI models, agents and hardware.

Muse and Wearables Expand the AI Ecosystem

The subscription launch follows Meta’s introduction of Muse, a personal AI agent designed to assist users with everyday tasks. The company is also developing its AI-powered wearables strategy, although its latest smart glasses have faced scrutiny over recording capabilities.

Meta is reportedly preparing a camera-free version of its smart glasses, internally known as Luna, for release in the fall. Together with AI agents and subscription services, the wearable strategy suggests Meta is attempting to extend AI beyond social-media applications and into everyday consumer interactions.

Revenue Growth Remains Strong Despite Rising Costs

Meta’s second-quarter fiscal 2026 results demonstrate the scale of the underlying business. Revenue increased 28% year over year to $60.80 billion, while Family of Apps revenue rose 28% to $60.37 billion. Average Family Daily Active People reached 3.6 billion in June, a 3% increase, while advertising impressions increased 14%.

However, the cost of pursuing the company’s AI strategy has become increasingly visible. Costs and expenses jumped 55% to $42.03 billion, while capital expenditures, including principal payments on finance leases, reached $31.08 billion during the quarter. Quarterly EPS consequently declined 13% to $6.18.

AI Spending Could Reshape Meta’s Financial Profile

The spending trajectory is expected to remain substantial. JPMorgan analysts cited in the source project Meta’s capital expenditures could reach $243 billion in 2027, a 70% increase, followed by $284 billion in 2028. The bank also expects free cash flow to turn negative by approximately $65 billion to $70 billion in each of those years.

These projections highlight the central financial question surrounding Meta’s AI strategy: whether new products can eventually generate enough incremental revenue and profitability to justify the scale of infrastructure investment.

Analyst Views Reflect Different Expectations

Analyst opinions on META remain varied. Wedbush maintained a $650 price target and Hold rating, while JPMorgan upgraded the stock from Neutral to Overweight and increased its target from $640 to $820. The latter cited Meta’s early-stage rollout of advanced AI models and new products outside its traditional advertising business, including Muse and access to its Meta Model API.

The source cites a consensus Strong Buy rating among 54 analysts, with 45 Strong Buy ratings, two Moderate Buy ratings and seven Holds. The consensus price target is $758.26, while the highest cited target is $1,000.

Valuation and Technical Signals Need Attention

META stock has fallen 13% over the past year but remains 2.5% higher year to date and approximately 30% above its March 27 low of $520.26. Its 14-day RSI of 72.60 places the shares in technically overbought territory.

At the same time, the forward-adjusted non-GAAP PEG ratio of 1.07x is below the cited industry average of 1.33x. This creates a mixed picture in which valuation metrics remain relatively moderate while the stock’s recent momentum has become stretched.

What Could Investors Watch Next?

The success of Meta One will depend on adoption, pricing and the company’s ability to turn AI engagement into recurring revenue. Investors will also be watching advertising growth, capital expenditures, free cash flow and the rollout of AI agents and wearables.

Meta’s next phase is increasingly defined by the balance between its highly profitable advertising business and the enormous investment required to build an AI platform. The key financial question is whether these new AI products eventually become meaningful contributors to revenue rather than simply increasing the company’s cost base.