Innodata rides $1.1 trillion AI wave as hyperscaler spending surges

Innodata is capturing a growing share of the AI infrastructure buildout as the five largest US hyperscalers are expected to spend as much as $1.1 trillion on AI capital expenditures by 2027, creating demand for the data engineering and model evaluation services the company provides.

"Industry estimates suggest AI capital expenditures by the five largest US hyperscalers could exceed $800 billion in 2026 and reach $1.1 trillion in 2027," Innodata management said on the company's first-quarter earnings call, citing third-party industry projections.

First-quarter 2026 revenue rose 54% year over year to a record $90.1 million, while adjusted EBITDA nearly doubled to $25 million. Adjusted gross margin expanded to 47%, reflecting growing operating leverage as higher-value AI services gained traction. Following the quarter, management raised its full-year 2026 revenue growth outlook to approximately 40% or more, up from a prior target of 35% or more.

The opportunity extends beyond data engineering. Innodata is expanding into AI evaluation, trust and safety, agent observability platforms and enterprise AI, broadening its addressable market. A newly signed Big Tech customer is expected to generate roughly $51 million in revenue this year after contributing nothing a year ago, while revenue from the company's other Big Tech customers jumped 453% in the first quarter.

A Specialized Play in a Crowded Field

Innodata competes with Concentrix and TaskUs in delivering AI data services, model training and content operations. But it has differentiated itself by focusing on frontier AI labs, hyperscalers and high-value services such as model evaluation, trust and safety, and agentic AI infrastructure. The company is also developing proprietary platforms, including its Evaluation and Observability Platform, which could generate recurring software-driven revenue.

Concentrix benefits from a large global delivery network and long-standing enterprise relationships, but AI data services remain one part of its diversified business. TaskUs is strengthening its AI capabilities through trust and safety and AI support services, though it remains more focused on outsourcing and customer operations. Compared with both, Innodata offers a more specialized exposure to the accelerating AI infrastructure spending cycle.

The company's profile is also gaining attention beyond traditional equity markets. On July 8, crypto exchange MEXC listed Innodata as one of nine tokenized stock pairs through Ondo Finance's infrastructure, giving crypto-native investors on-chain exposure to the AI data services provider. The listing reflects broadening investor interest in companies tied to the physical backbone of AI.

Valuation Reflects the Growth Premium

Innodata shares have gained 35.5% year to date, outperforming the industry's 28.6% advance. The stock trades at a forward price-to-earnings ratio of 45.88, above the industry average, reflecting the premium investors are placing on pure-play AI infrastructure exposure.

The Zacks Consensus Estimate calls for 2026 sales growth of 40.6% and earnings growth of 23.9%. The 2026 earnings per share estimate stands at $1.14, unchanged over the past 30 days, while the 2027 estimate has risen to $1.84 from $1.78, suggesting analysts see the growth trajectory extending.

For investors, the key question is whether Innodata can sustain its growth trajectory as competition intensifies. The company's expanding customer base, growing portfolio of AI infrastructure solutions and improving profitability suggest it is well placed to capture a meaningful share of the long-term AI spending wave. Risks include project timing, customer concentration and the competitive AI services environment. Innodata currently holds a Zacks Rank #1 (Strong Buy).

This article is for informational purposes only and does not constitute investment advice.