Analysis of the market opportunity for AI software from 2022 to 2029. Includes market sizing, segmentation, and forecasts for generative AI (GenAI) and predictive AI across 150 use cases, 20 industries, eight regions, and four workloads.
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Artificial Intelligence Software Market Forecasts – 2H24 Data
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The Analyst Team
Neil Dunay
Follow AnalystPrincipal Market Forecaster
Neil Dunay is Principal Market Forecaster, forecasting on enterprise technology, particularly for AI and other emerging technologies. His focus is on leveraging statistical tools to discover interrelationships among technological, economic, demographic, and sales trends that drive market evolution.
Neil joined Omdia in March 2020, following more than 20 years of experience researching ICT markets. Before joining Omdia, he was an engagement manager at International Planning and Research in Waltham, Massachusetts, where he assisted leading global technology companies in their strategic planning decisions by estimating their technology product market positions and forecasting market opportunities. Before IPR, Neil was a telecommunications industry analyst for KMI/PennWell in Newport and Providence, Rhode Island, where he estimated and forecast markets for fiber-optic cable and optoelectronic equipment for telecom clients. Neil holds a Master of Arts in international economics from The Johns Hopkins School of Advanced International Studies in Washington, D.C.
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Natalia Modjeska
Follow AnalystResearch Director, AI and Intelligent Automation
Natalia Modjeska leads the AI & IA research team at Omdia. She has 15+ years of experience in developing and deploying analytics and AI. Her diverse career includes R&D, product and program management, sales, consulting, and client advisory. She has worked with organizations of all sizes and levels of maturity across many industries and geographies helping clients to harness the power of data, advanced analytics and AI for transformative change. She has advised 200+ organizations around the globe on topics ranging from AI strategy and use cases, to execution, best practices, governance, ethics, emerging trends, and vendor due diligence.
Natalia is passionate about helping clients to demystify AI/ML and to deploy these technologies responsibly. As part of that effort, she serves as an expert on the ISO/IEC JTC 1/SC 42 - AI Standards working group and she volunteers with several non-profits to develop responsible AI certification; increase AI literacy and improve government through innovative technologies. Natalia holds a PhD in AI (NLP) from the University of Edinburgh in Scotland and an Executive MBA from the Ivey School of Business (Western University).
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