CI&T Joins Claude Partner Network to Scale Claude Across the World's Largest Enterprises, with 1,000+ Certified AI Engineers Jun 08, 2026 CI&T Joins Claude Partner Network to Scale Claude Across the World's Largest Enterprises, with 1,000+ Certified AI Engineers. Learn more
CI&T Releases 2025 ESG Report Focused on Social Impact, Clean Energy, and Innovation Mar 31, 2026 CI&T Releases 2025 ESG Report Focused on Social Impact, Clean Energy, and Innovation Learn more
CI&T Report Shows That Over 60% of UK Consumers Already Use AI When Shopping, But Few Are Impressed by Retailers’ Efforts Nov 30, 2025 The Retail Tech Reality Check examines how artificial intelligence (AI) is impacting the way consumers shop. From where journeys begin to how people pay, what channels they trust, and the prices they expect, retail is undergoing a significant transformation. Learn more
CI&T and Valleys to Coast Modernise Housing Systems to Improve Services for 18,000 South Wales Residents Mar 24, 2026 New unified platform removes administrative hurdles, allowing teams to focus on residents and the quality of their homes. Learn more
Solving CPG and Retailer Demand Forecasting Dilemmas Download The retailer-supplier relationship isn’t arranged in the way most conducive to confident demand forecasting. In this new report CI&T examines the demand forecasting relationship between retailers and suppliers. The report highlights pain points and opportunities for both parties, revealing a misalignment of data strategies causing ineffective forecasting. DOWNLOAD THE FULL REPORT Key findings from the report include: Suppliers’ highest ranking challenge related to forecasting demand was visibility and access to data. Retailers’ highest ranking challenge related to demand forecasting was scaling the data platformSuppliers reported they were most likely to break demand forecasting down by geography, while retailers were most likely to report breaking down demand forecasting by channel The majority of suppliers reported looking at sales data from the same month over years prior as their predictive approach, while the majority of retailers reported referencing the previous month’s sales to predict the following monthBoth suppliers and retailers overwhelmingly reported that consumer-level data (gender, age, household size) is the most likely type of data leveraged for demand forecasting