Goldman Sachs comments on Meta layoffs, cost-cutting, and delayed model releases: this is "replacing the feathers to catch the bird"

Why does Goldman Sachs view Meta’s layoffs as a strategic restructuring rather than a contraction?

In response to widespread concerns about Meta’s layoffs, cuts to Reality Labs investment, and delays in the release of core models, Goldman Sachs offers a different interpretation: this is not a passive contraction under pressure from AI investment, but rather a strategic restructuring that actively reallocates resources from inefficient assets to high-value computing needs, thereby opening up space for long-term EPS revisions.

According to recent reports from multiple media outlets, Meta’s management may advance three significant initiatives: mass layoffs and personnel restructuring, cutting Reality Labs department expenses, and delaying the public release of the latest core model from its super-intelligent lab. As the news continues to develop, Meta’s stock price has fallen by approximately 20% since January 29, the day after its fourth-quarter earnings report was announced, while the S&P 500 index has only declined by about 7% during the same period.

Goldman Sachs analyst Eric Sheridan’s team noted in a research report on March 22 that the three initiatives mentioned above do not substantially exceed the forward guidance framework provided by management during the most recent earnings call.

A more critical judgment is that any cost-saving measures should be viewed as Meta’s efforts to seek efficiency and growth on a company-wide scale—resources freed up will primarily be used for AI growth investments centered on computing needs. The firm also stated that if the relevant initiatives are implemented, Meta is expected to return to the rhythm of “conservative guidance at the beginning of the year, with continuous upward revisions throughout the year” seen in previous years.

Goldman Sachs maintains a buy rating on Meta with a 12-month price target of $835. The firm quantifies the potential impact of cost optimization on EPS through three scenario analyses, concluding that: Meta’s existing cost structure possesses ample elasticity, and the rebalancing of efficiency and growth initiatives can continually propel positive EPS revisions.

Layoffs: Adjusting the personnel structure, not the overall scale

According to Reuters, Meta is planning massive layoffs.

Goldman Sachs quantified this in Scenario 1: assuming that by the end of 2026, the total number of employees decreases by 15% year-over-year, and then recovers by 5% each in 2027 and 2028, while per capita non-depreciation amortization expenses grow by about 6% annually. Under this assumption, compared to Goldman Sachs’ baseline forecast, Meta’s GAAP EBIT and earnings per share in 2026 would receive a boost of about over 10%, with increases exceeding 20% in 2027 and 2028.

Goldman Sachs emphasized that the essence of this scenario is not merely to reduce personnel numbers but reflects a significant structural transformation trend in the industry since mid-December 2025: companies are generally pursuing personnel adjustments alongside a shift toward AI and machine learning computing roles.

In other words, Meta’s layoffs are more akin to “changing personnel”—replacing existing positions with more technically skilled individuals with AI backgrounds—rather than shrinking the overall scale. Goldman Sachs thus characterizes it as a proactive talent structure reorganization rather than a passive response to cost pressures.

Reality Labs: Abandoning Horizon Worlds, not the entire spatial computing track

According to Bloomberg, Meta plans to adjust the core products of the Reality Labs department, which has been interpreted as Meta withdrawing entirely from this business segment.

Goldman Sachs believes this interpretation is misguided and cites multiple official statements from Meta pointing out that the core of this adjustment is to reduce investment in traditional VR legacy products represented by Horizon Worlds, while the company continues to maintain a high level of investment in the broader vision of spatial computing, and the strategic direction remains unchanged.

In the quantitative analysis of Scenario 2, Goldman Sachs assumes that annual expenditures for Reality Labs are reduced by a high single-digit to low double-digit percentage each year, with 10% of the savings reinvested into the business. The potential boost to GAAP earnings per share from 2026 to 2028 is in the low to mid single-digit percentage range, with relatively moderate elasticity but a clear direction.

Goldman Sachs’ judgment is that Meta’s action essentially lowers the priority of traditional VR within Reality Labs to allocate more resources toward AI integration and augmented reality (AR).

Delay of core models: The timeline has always been within expectations

The New York Times reported that the public release date for Meta’s latest core model from its super-intelligent lab may be delayed.

In response, Goldman Sachs stated that this timeline has never exceeded its expectations. Considering that the super-intelligent lab was established in mid-2025, it has been less than a year; compared to leading model institutions like Google DeepMind, OpenAI, and Anthropic that have been developing for many years, Meta will need at least 9 to 12 months to show initial results publicly.

Goldman Sachs reaffirms its anchoring of management’s public statements: the public release of core models and the implementation of AI strategic pillars (computing layout, intelligent product offerings, etc.) will primarily focus on the second half of 2026 to 2027, and the first batch of models is only a starting point, with continuous iterations and evolutions expected over many years.

The firm believes that using the establishment timeline and measuring the progress of Meta’s super-intelligent lab against market expectations for OpenAI and Anthropic introduces a benchmark bias.

Three scenario analyses: Different paths to unlock EPS elasticity

Goldman Sachs constructed three “blue-sky scenarios” in the report to quantify the potential impact of different cost optimization paths on profitability, explicitly stating that none are baseline predictions, and actual outcomes are influenced by multiple variables.

Scenario 1 (adjusting personnel and per capita costs) has the most significant boosting effect, with potential EPS increases of over 10% in 2026 and exceeding 20% in 2027 and 2028.

Scenario 2 (reducing Reality Labs expenses) has relatively limited elasticity, with boosts to EPS over the three years in the low to mid single-digit percentage range.

Scenario 3 (zero growth in non-D&A operating expenses over the next three years) has the theoretical maximum elasticity, potentially leading to a more than 30% boost in EPS for 2026, and about 40% to 50% upward potential for 2027 and 2028, but Goldman Sachs characterizes it as the scenario with the lowest probability of occurrence—core constraints include persistent wage inflation for AI and machine learning roles, as well as continued growth in the total number of employees over multiple years.

Goldman Sachs points out that Meta’s existing cost structure has ample profit elasticity, and any management initiative aimed at balancing efficiency and growth investments has the capacity to continually drive upward revisions of EPS expectations in the coming years, rather than facing downward pressure.