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Adobe’s AI Monetization Struggles Lead to Dull Forecast, Shares Drop

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Adobe (ADBE.O) has projected its second-quarter revenue to fall within Wall Street’s expectations, but it is facing challenges in the monetization of its artificial intelligence (AI) products, leading to concerns over its ability to capitalize on the growing demand for AI in creative tools. As a result, shares of the company dropped more than 4% in extended trading.

The company expects second-quarter revenue between $5.77 billion and $5.82 billion, in line with analysts’ estimates, according to data compiled by LSEG. Adobe reaffirmed its annual revenue forecast, and CEO Shantanu Narayen expressed confidence in the company’s ability to capitalize on the acceleration of the creative economy powered by AI.

Despite this optimism, analysts and investors are questioning the pace of monetization for Adobe’s generative AI products. As the company pours resources into differentiating itself from competitors, it aims to enhance its vast portfolio with more AI-driven editing tools. However, there is growing skepticism about whether Adobe can quickly turn its AI offerings into substantial revenue streams.

“I think guidance is rough, and I think people are questioning, is the AI monetization quick enough?” said Parker Snook, a senior research analyst at M Science.

In an effort to stay ahead of rivals, Adobe has been aggressively integrating AI into its software products, notably Photoshop, which is widely used by professionals in a variety of industries. However, its AI and add-on offerings generated $125 million in annual recurring revenue (ARR) at the end of the quarter, and the company expects to double that figure by the end of fiscal 2025, according to CFO Dan Durn.

Despite concerns over AI monetization, DA Davidson analyst Gil Luria is optimistic that new products will eventually ease investor worries: “As Adobe continues to deliver new products, we expect those concerns to be replaced by excitement over those products.”

For the first quarter, Adobe reported revenue of $5.71 billion, surpassing analysts’ estimates of $5.66 billion. The company also saw digital media revenue of $4.23 billion, which exceeded analyst expectations of $4.19 billion. On an adjusted basis, Adobe earned $5.08 per share, above the forecast of $4.97 per share.

SentinelOne Issues Lower Revenue Forecasts Amid Competition and Economic Uncertainty

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SentinelOne (S.N.) issued disappointing revenue forecasts for both the first quarter and the full year, citing challenges such as tough competition and reduced enterprise spending amid economic uncertainty. This led to a 16% drop in its shares after the market closed on Wednesday.

The cybersecurity company faces significant pricing pressure, particularly in the endpoint security market, where larger platform players like Palo Alto Networks (PANW.O) and CrowdStrike (CRWD.O) are offering deeper discounts. Analysts note that despite SentinelOne’s strong competitive positioning, the sector is feeling the strain of more aggressive pricing strategies. Additionally, economic challenges have led enterprises to curtail spending on cybersecurity solutions, focusing more on cost optimization.

Generative AI, while offering opportunities, has also opened the door for increased cyberattacks. The rise of malicious AI usage has made the cybersecurity industry more critical, with global cyberattacks becoming a significant threat. For example, X, the social media platform owned by Elon Musk, experienced intermittent outages earlier this week due to a powerful cyberattack. Similarly, a cyberattack on UnitedHealth Group‘s technology unit last year compromised the personal information of 190 million individuals, marking it as the largest healthcare data breach in the United States.

Despite these cybersecurity challenges, SentinelOne’s first-quarter revenue forecast was $228 million, below the Wall Street estimate of $235.1 million. For the full year, the company expects revenue between $1.01 billion and $1.012 billion, which is also below analysts’ average estimate of $1.03 billion.

In its most recent financial results for the fourth quarter ending January 31, SentinelOne reported $225.5 million in revenue, surpassing expectations of $222.3 million. The company’s adjusted profit per share for the quarter was 4 cents, exceeding the 1-cent estimate.

Meta Tests Its First In-House AI Training Chip

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Meta, the parent company of Facebook, has initiated testing of its first in-house chip designed specifically for training artificial intelligence (AI) systems. This development marks a significant step in Meta’s plan to reduce its reliance on external chip suppliers like Nvidia and move toward producing its own custom silicon. Sources told Reuters that Meta has begun a small deployment of the chip and plans to expand production if the test proves successful.

Meta’s push to develop in-house chips is part of a broader strategy to reduce the high infrastructure costs associated with its AI projects. The company has forecast total 2025 expenses between $114 billion and $119 billion, including up to $65 billion in capital expenditure largely driven by investments in AI infrastructure.

The new chip is a dedicated accelerator, meaning it is built specifically for AI tasks, making it more power-efficient compared to graphics processing units (GPUs) typically used for AI workloads. Meta is collaborating with Taiwan-based TSMC to produce the chip. The initial design, known as the “tape-out,” has been completed, a crucial milestone in chip development. While tape-out is expensive, costing tens of millions of dollars, it is an essential part of the process to test the chip’s functionality.

Meta has experienced setbacks in its Meta Training and Inference Accelerator (MTIA) series in the past, even scrapping one chip after its initial tests failed. However, last year, Meta began using a MTIA inference chip for content recommendation systems on platforms like Facebook and Instagram. This progress has encouraged Meta to pursue further development of custom chips, aiming to use them for both training and inference of AI models, including generative AI products like Meta AI.

Meta plans to start using its own chips by 2026 for training purposes, aiming to reduce costs associated with AI model training. Chris Cox, Meta’s Chief Product Officer, discussed the company’s phased approach, noting that while progress has been slow, the success of the first-generation inference chip for recommendations has been a significant achievement. Despite the setbacks in developing custom chips, Meta continues to rely heavily on Nvidia’s GPUs for its AI needs, making it one of Nvidia’s largest customers.

The broader AI industry has raised questions about the effectiveness of scaling up large language models with ever more data and computing power. Chinese startup DeepSeek has introduced new, more efficient AI models that rely more heavily on inference rather than the computationally expensive training process. This has sparked concerns about the future value of GPUs like those from Nvidia, which have faced significant market volatility this year.