About
Principal Analyst Mike Leone draws upon his enthusiasm for bleeding-edge technology and his engineering and marketing background to provide a unique perspective to enterprise technology vendors.
At Enterprise Strategy Group, Mike focuses on all things data, analytics, and AI. His passion shines through in helping organizations improve everything from go-to-market strategies and messaging to product development and content creation.
Mike has a strong technical background, with early roles in software and hardware engineering focused on future product feasibility, modeling, and performance. He gradually moved into roles that interfaced with marketing by helping translate deep technical concepts into understandable business benefits.
Mike has appeared in The Wall Street Journal, Forbes, AIthority, Fox News, eWeek, BizTech, SDXcentral, Computerworld, DevOps, Datanami, Data Center Knowledge, CBR, and T_HQ, among others. He holds a BS in Computer Science from Stonehill College in Easton, Massachusetts.
While data has the power to transform the business in radical ways, achieving data excellence requires an equal balance of tightly integrated technology, well-defined processes, and the empowerment of all stakeholders to confidently bring the right data to every decision.”
Mike Leone
Principal Analyst, Data Analytics & AI
Research Report
Beyond the GenAI Hype: Real-world Investments, Use Cases, and Concerns
While AI in general was already assimilating into the everyday business and IT lexicon thanks to ongoing AI and analytics strategies and initiatives, GenAI recently stormed the market and mindshare of decision makers across industries and major geographic markets. Business leaders see a massive opportunity to positively impact operations and customer strategies with GenAI, but its adoption and use across all business units carry a fair share of trepidation.
Mike Has Appeared In
Latest Insights from Mike
Blog | March 6, 2024
Cohesity Launches GAIA: There’s More Than Meets the AI
Infographic | February 13, 2024
Decoding the Data Universe: The State of Data Science and Machine Learning
Research Report | February 9, 2024
Decoding the Data Universe: The State of Data Science and Machine Learning
Research Brief | January 5, 2024