Grid Dynamics Q1 Earnings Call Highlights

Key Points

• Grid Dynamics reported Q1 revenue of $104.1 million (up 3.7% YoY) and non‑GAAP EBITDA of $12.5 million; it guided Q2 revenue of $106–108 million and maintained full‑year revenue outlook of $435–465 million.
• AI is now core to the business, with AI revenue reaching 29.3% of total and growing nearly 60% YoY, and the company saying AI projects can deliver materially higher contribution margins (some >60% in cases) including new "physical AI" engagements.
• Management is shifting away from time‑and‑materials toward productized, outcome‑oriented work via its GAIN platforms and partner‑led GTM; partner‑influenced revenue rose to 19.1% with a long‑term target of 25–30%.

Grid Dynamics NASDAQ: GDYN opened 2026 with first-quarter results that management said reflect accelerating adoption of its AI-led offerings and a shifting customer mix toward technology and financial services. Executives also emphasized a growing role for partner-led go-to-market efforts and a business model transition away from time-and-materials work toward more platform-driven, outcome-oriented engagements.

Q1 results and guidance

Management reported first-quarter revenue of $104.1 million, which was above the high end of the company’s prior guidance range of $103 million to $104 million. Revenue grew 3.7% year over year. Non-GAAP EBITDA was $12.5 million, or 12% of revenue, at the midpoint of the company’s $12 million to $13 million guidance range.

Anil, who reviewed the quarter’s financial performance, said foreign exchange was a headwind. The net impact on EBITDA from currency movements was approximately $1.2 million year over year, despite the company using “both natural hedges and an active hedging program.”

For the second quarter, Grid Dynamics guided to revenue of $106 million to $108 million and non-GAAP EBITDA of $14 million to $15 million. For full-year 2026, the company maintained its revenue outlook of $435 million to $465 million.

AI revenue becomes a larger share of the business

CEO Leonard said “three trends stood out” in the quarter, including “a meaningful and growing contribution from AI revenue.” He reported that AI revenue reached 29.3% of total company revenue in Q1, growing “nearly 60% year-over-year.” Leonard described the AI practice as having “become the core of our business,” reshaping offerings, talent development, and client relationships.

Leonard also said AI is expanding the company’s addressable market by changing delivery economics and enabling new modernization work. As an example, he cited a “leading home improvement retailer” where global operations ran on legacy mainframe platforms. He said Grid Dynamics used AI agents to deliver “a full modernization program within the timeline and budget.”

The company also highlighted “physical AI” initiatives. Leonard said Grid Dynamics’ GAIN platform for physical AI is aimed at making “intelligent robotics more accessible and economically viable,” and that in Q1 the company closed its “first commercial engagement in physical AI with a heavy equipment manufacturer,” enabling mining equipment with “intelligent autonomous capabilities.”

Customer mix shifts toward TMT and finance

Executives said Grid Dynamics is benefiting from a structural shift in vertical mix. Leonard noted that for the first time, the company’s top five accounts were “entirely outside of retail,” including two global technology companies and multiple financial services clients. He also said each of those customers has undergone “meaningful vendor consolidation,” with Grid Dynamics emerging “as a clear beneficiary.”

Anil provided detailed vertical results for the quarter:

• TMT became the largest vertical at 29.5% of revenue, growing 30.3% year over year.
• Retail represented 28.4% of revenue.
• Finance represented 23.5% of revenue, with Anil citing strong demand from banking and fintech customers.
• CPG and manufacturing represented 9.4% of revenue.
• Other was 7.1% of revenue.
• Healthcare and pharma was 2.1% of revenue.

Customer concentration increased year over year, with revenue from the top five and top 10 customers at 40.8% and 59.7%, respectively, compared with 35.6% and 56.6% a year earlier.

GAIN platforms and a shift away from time-and-materials

A recurring theme in prepared remarks and Q&A was the company’s push to productize repeatable IP under its GAIN platforms and pair them with “forward-deployed engineers.” Leonard said the transformation rests on four pillars: AI-native delivery, productized engineering, AI consulting, and internal AI automation.

In response to JPMorgan’s Puneet Jain, Leonard said a “big shift toward not T&Ms” is underway and that “the number of non-T&M projects” has “significantly increased.” He also said most forward-deployed engineers are trained internally, supported by the company’s R&D organization, while external hires still need to be structured around the GAIN approach.

CTO Eugene Steinberg addressed risk in fixed-price work, saying the main risks come from uncertainty in requirements. He said Grid Dynamics uses AI agents and its “GAIN Rosetta framework” during presales to uncover gaps and clarify requirements, then uses AI coding assistance during delivery to accelerate execution and “build the buffer for any unknown unknowns.” Anil added that Grid Dynamics has prior fixed-price experience “pre-AI,” and said those learnings are being applied as the model expands.

On margin dynamics, Anil said AI work generally carries higher margins than the blended services average, and cited having “seen the contribution margins when we get to some of our AI work somewhere in the 60+% range” in certain cases, while emphasizing that not every project achieves that level.

Partnership influence rises, with a target of 25%-30%

Rahul Bindlish, Global Head of Partnerships and Marketing, said partner influence revenue grew to 19.1% of total company revenue in Q1, driven largely by Google Cloud, AWS, and Microsoft Azure. He said the company’s strategy includes deploying GAIN platforms on hyperscaler marketplaces, noting the GAIN platform for risk and compliance is listed on both Google Cloud Marketplace and AWS Marketplace.

Bindlish told William Blair’s Maggie Nolan that Grid Dynamics has a long-term goal for 25% to 30% of revenue to be influenced by partnerships, and said the company is “tracking slightly ahead” of its internal goals. He also said that when the company “leads with a vertical specific platform,” sales cycles can compress and conversion rates improve because the platform’s value is visible to both business buyers and technical evaluators.

Beyond hyperscalers, Bindlish said the company is expanding work with NVIDIA by porting solutions onto its software stack, and is also building relationships with specialized firms in process mining and organizational change management for AI consulting engagements. In Q&A, he also pointed to potential partnerships with specialized AI firms and LLM providers, as well as interest from large business consulting companies seeking technology implementation partners.

On capital allocation, Anil said cash and cash equivalents totaled $327.5 million at March 31, down from $342.1 million at year-end. The company repurchased approximately 1.8 million shares for $11.5 million since its prior earnings call, and about 2 million shares for $13.5 million since authorization of a $50 million program. He added that M&A remains a priority, focused on tuck-in acquisitions that enhance capabilities and align with “data, AI, and certain end markets.”

In closing remarks, Leonard said the quarter was “proof that our AI transformation is working,” citing AI revenue at 29.3% of total revenue and stating that agentic AI solutions are now in production across multiple verticals with “measurable ROI at commercial scale.” He added that the pipeline entering Q2 is “the strongest it has ever been.”

About Grid Dynamics NASDAQ: GDYN

Grid Dynamics NASDAQ: GDYN is a digital engineering and technology services company that helps enterprises accelerate their digital transformation initiatives. The company specializes in designing and implementing scalable, cloud-native solutions that leverage advanced analytics, machine learning and artificial intelligence to optimize operations, enhance customer experiences and drive revenue growth. Its technology expertise spans e-commerce platforms, modern data architectures, DevOps and automation, as well as custom application development across a range of industries including retail, financial services, high tech and automotive.

Key service offerings include cloud migration and modernization, data engineering and analytics, AI/ML-driven insights, digital commerce and omnichannel solutions.

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