Detailed Narrative
AI Adoption and Growth
AI revenue reached 30.7% of total revenue in Q2 FY26, growing 54.6% year-over-year, marking a sustained shift rather than a spike. The company is winning new programs and is on track to have 90% of its engineers trained on AI SDLC by the end of October. This strong performance is driven by wider enterprise adoption of GAIN platforms and clients transitioning AI workloads from pilots to production.
GAIN Platform Expansion
Grid Dynamics' GAIN platforms are central to its AI strategy, with Rosetta progressing to larger engagements and Allium moving into commercial banking. The company has expanded LLM partnerships with the top four frontier providers and made open-source contributions like SpecFlow to drive technical credibility. These platforms are enabling clients to accelerate work across the modernization lifecycle, particularly in code generation and testing.
Physical AI and Robotics
The company is significantly expanding its Physical AI capabilities, including a strategic partnership with Doosan Robotics and the acquisition of Ekumen, a robotics engineering team. This allows for full-stack solutions from foundational software (Robot Operating System) to simulation, hardware integration, and enterprise deployment. This initiative targets a market measured in trillions over the coming decade, with active programs spanning humanoid robotics, autonomous driving, and policy control platforms.
Client Engagement Evolution
Client relationships are evolving, with customers now requesting Grid Dynamics' involvement in advisory, execution, and ongoing operations beyond initial platform deployments. Partner influence revenue reached 19.1% of total revenue in Q2, driven by core hyperscaler relationships (Google Cloud, AWS, Microsoft Azure) and increasing AI engagements. The company aims for 25% to 30% partner influence revenue long-term.
Margin Expansion and Efficiency
Grid Dynamics is making solid progress towards its commitment of 300 basis points of margin expansion year-over-year by Q4. This improvement is attributed to revenue growth outpacing delivery costs, improved resource utilization, and efficiency gains from rationalizing non-engineering headcount. The adoption of fixed-price models and AI-driven productivity are also contributing to a more efficient and scalable delivery model.
Horizon-Based AI Strategy
The company's AI strategy is structured into two horizons. Horizon One, which is scaled, focuses on AI-first modernization and agentic platforms (Rosetta, Allium, SpecFlow) that are now in broader enterprise adoption. Horizon Two, which is scaling, covers agentic harness engineering and Physical AI, moving from research and internal validation towards repeatable client deployments and differentiated intellectual property.