Grid Dynamics (GDYN) Q2 FY26 earnings call: guidance and Q&A

How will AI efforts translate into growth and profitability for Grid Dynamics, addressing skepticism about AI being a net negative?

Leonard Livschitz explained that AI implementations, including forward-deployed engineers, Agentic AI, and GAIN platform adoption, are accretive. Increased growth in these areas substantially exceeds aged businesses. Physical AI is also driving adoption and partnerships, positioning Grid Dynamics as a leader.

“If you look at the increased growth in just these two areas, that substantially exceeds the -- some of the aged businesses, which would eventually drop out because the gloom and doom from many facets were about that engineering and consultancy is less relevant.”

asked by Mayank Tandon · answered by Leonard Livschitz

What is the current visibility for the Q3 guide and implied Q4 ramp, and does it indicate sustainable growth acceleration into FY27?

Anil Doradla cited seasonal patterns, increased billable headcount from new programs, and potential acquisitions for H2 FY26. For FY27, deeper relationships with technology and financial clients and an expanded addressable market suggest incremental positive growth.

“from my point of view, I see two things that are very interesting. Number one, the relationships that we're having with our technology customers, our financial customers, our top 10 and 20 customers is going deeper and deeper. Things that we've not done, we're doing.”

asked by Mayank Tandon · answered by Anil Doradla

How much of the 300 bps margin improvement comes from structural changes/automation versus cost control, and is the headcount reduction (7% revenue growth, 3% headcount down) indicative of a lasting change in the delivery model?

Anil Doradla attributed margin improvement to efficiency from organizational restructuring, embracing AI/fixed-price models, and non-engineering headcount rationalization. He stated that the headcount reduction was primarily non-billable staff. Leonard Livschitz added that AI adoption equalizes the field, allowing Grid Dynamics to compete at a higher level with better visibility and position.

“The movement that you've seen on the headcount right now was largely driven by efficiency improvements on non-engineering headcount. So people should not worry, it's not that we let go some billable headcount. No, it's just non-engineering, non-billable headcount, we cleaned it up.”

asked by Bryan Bergin · answered by Anil Doradla

How do new AI/robotics partnerships (e.g., NVIDIA, Doosan) differ from traditional hyperscaler relationships (Google, AWS, Microsoft Azure) in terms of revenue potential or client ownership?

Vasily Sizov explained that NVIDIA and robotics partnerships offer a pipeline of future opportunities, especially in transforming traditional manufacturing with Agentic AI and Physical AI. These engagements are seen as building new types of opportunities and transforming manufacturers on a bigger scale.

“we definitely value our relationships with NVIDIA and believe that's a great partnership to build a pipeline of future opportunities on. As you understand, right now, the industry, the manufacturing is going through a massive transformation and new tools like Agentic AI or Physical AI definitely brings new technology to more like a traditional manufacturing.”

asked by Puneet Jain · answered by Vasily Sizov

Is the shift towards higher U.S. headcount a continuing trend, and what are its implications for margins and employee base change management?

Leonard Livschitz confirmed a trend towards additional growth in U.S. onshore presence, driven by client demand for on-premise work on complex cases and rapid transformation. He clarified that non-engineering headcount reduction in offshore locations contributes to margin improvement. Margin expansion will be driven by fixed-bid projects, internal tools, and non-linear value.

“Now we're not saying that work is no longer relevant. But there are more and more demand presence on-premise with the clients to work together on these complex cases because the rapid change of transformation sometimes catches the clients a little bit through uncertainty, right?”

asked by Puneet Jain · answered by Leonard Livschitz

What does the revenue journey look like for AI projects moving from POC to full implementation, and what is the expected scale-up from a POC?

Leonard Livschitz noted that the definition of POC has changed; many are now substantial projects, especially those resulting from partnerships or GAIN productivity. Vasily Sizov added that customers start with smaller business cases to demonstrate value, which then convert into platform build-outs and longer-term, stickier engagements that grow like a snowball. Yury Gryzlov highlighted that POCs vary by industry and customer relationship depth, with Physical AI POCs being more traditional.

“The whole short-term engagement definition, which used to be followed or preceded by the proof of concept, become the proof of concept itself, and then it's a major rollout. So this has conceptually changed the definition of proof of concept and revenue associated with it.”

asked by Surinder Thind · answered by Leonard Livschitz

With AI revenue growing rapidly, what is happening in the remaining 70% of revenue (which appears to be declining), and is it due to cannibalization or pricing pressure?

Anil Doradla explained that the decline is due to volatility from significant customer changes (e.g., project completion, strategy shifts) in non-top-tier accounts, not cannibalization or pricing pressure. He stated that AI work is typically incremental. Leonard Livschitz added that the company is not defending legacy business by compressing margins.

“In our case, when you look at our business trends, from time to time, we might see a significant customer... have some changes. Maybe there's a change in strategy or a big project is completed or something changes, and we can have some volatility there.”

asked by Surinder Thind · answered by Anil Doradla