Dr. Kjell Carlsson serves as a VP Analyst on the Analytics & AI team, where he specializes in guiding leaders to achieve transformative impact through the large-scale application of AI, machine learning, data science, and advanced analytics. He offers advice on Analytics & AI: strategy, governance, innovation, literacy and upskilling, organizational design, best practices, case studies and market trends – across technologies ranging from MLOps and AI engineering to GenAI and Agentic AI.
Prior to joining Gartner, Dr. Carlsson was the Head of AI Strategy at Domino Data Lab where he advised executives in FSI, biopharma and public sector, and hosted the Data Science Leaders podcast. He was a Principal Analyst at Forrester Research for many years covering AI, data science, computer vision and conversational intelligence, and has a background that spans managing AI teams, management consulting, and strategy research.
athenahealth, Senior Manager, Market Analystics, 2 years
Domino Data Lab, Head of AI Strategy, 3 years
EMC, Manager, Corporate Strategy Consulting, 2 years
Forrester Research, Principal Analyst, 4 years
Institute for Strategy and Competitiveness, Research Associate, 3 years
Wilson Perumal & Company, Consultant, 2 years
Analytics and Artificial Intelligence
PhD, Business Economics, Harvard University
MA, Economics, Harvard University
BA, Economics & Computer Science (minor), Columbia University
Strategy: developing and implementing impactful strategies for Analytics & AI, GenAI, agentic AI, data science, and advanced analytics
Impact: best practices for driving scalable results with AI technologies, including governance, risk management, product management, organizational design, and literacy and upskilling initiatives
Leadership: advice for surviving and thriving as an AI, data science and/or analytics leader and growing AI-related organizations
Market understanding: understanding the market landscape of AI and data science technologies, tools and platforms
Emerging trends: getting ahead of the latest developments in enterprise AI adoption