CI&T Inc Q2 2026 Earnings Call Summary
Moby IntelligenceWed, August 12, 2026 at 4:55 AM GMT+3 3 min read
Strategic Performance Drivers
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Management attributes record revenue growth to a structural shift in client demand toward AI deployment, moving beyond experimentation to installing core operational capabilities.
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The company is deliberately transitioning its commercial model toward value-based pricing, which drove a sequential adjusted gross margin expansion to 32.4% as these models scale.
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Performance was broadly based across geographies and verticals, with Latin America serving as the primary growth engine at 32.1% year-over-year.
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Management characterizes 2026 as a transition year, prioritizing investments in the commercial engine and AI builder reskilling over near-term EBITDA margins.
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The 'Agentic Enterprise' framework is being used to bridge the 'process chasm,' moving clients from simple task automation to end-to-end business process reinvention.
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Strategic partnerships with Anthropic and Mistral are positioned as critical connective tissue, allowing CI&T to deploy frontier models within complex, regulated enterprise environments.
Outlook and Strategic Assumptions
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Full-year revenue guidance was raised to $566 million–$578 million, reflecting an improving demand environment and a 40% year-over-year expansion in the sales pipeline.
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Adjusted EBITDA margin guidance was revised to 15%–17% to account for deliberate commercial investments and foreign exchange headwinds from the Brazilian Real appreciation.
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Management expects sequential margin improvements through the second half of 2026 as one-time investments in the Agentic SDLC initiative moderate.
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The company projects that the transition of the existing book of business to new commercial models will take approximately 18 months to fully mature.
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Strategic focus remains on 'hyper-productivity,' aiming to decouple revenue growth from headcount expansion through AI-native delivery models.
Operational Risks and Structural Changes
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Foreign exchange volatility remains a significant headwind; on an FX-neutral basis, adjusted EBITDA margin would have been 2.3 percentage points higher at 15.6%.
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Consumer Goods was the sole vertical to contract, down 9% year-over-year, which management views as a temporary demand softening.
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Sales and marketing expenses rose to 12% of net revenue due to targeted 2026 initiatives, though management intends to stabilize this at roughly 10% long-term.
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The company successfully reskilled 100% of its workforce into 'AI builders,' reaching a revenue per builder of over $80,000 on a last 12-month basis.
Q&A Session Insights
Breakdown of margin guidance reduction and investment sustainability
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Management clarified that the 200-basis-point margin cut stems from a mix of FX pressure and discretionary spending on the Agentic SDLC launch.
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While some investments are structural, the peak spending seen in Q2 is expected to recede, with gross margin expansion from new pricing models providing a future offset.
Composition and deal size trends within the 40% pipeline growth
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Roughly 35% to 40% of current demand is specifically tied to Agentic SDLC engagements, which carry a higher margin profile than traditional digital services.
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Management noted that while recent deal sizes have been larger, they are not yet ready to label this a permanent trend versus a transitional effect of repricing.
Mitigating deflationary risks in consumption-based AI pricing models
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Management acknowledged falling token costs but argued that increased model capabilities lead to higher token usage, balancing the revenue impact.
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CI&T intends to maintain a portfolio of pricing models (fixed, throughput, and outcome-based) rather than relying solely on consumption to avoid revenue deflation.
Strategic rationale for maintaining a model-agnostic AI platform
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The CI&T Flow platform supports over 37 models to address diverse client needs regarding data privacy, compliance, and geographic availability.
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Being agnostic allows the company to provide 'FinOps' value by helping clients select the most cost-effective model for specific enterprise tasks.
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