Sam Ransbotham

Confidence 0.80 · 2 sources · last confirmed 2026-06-02

Professor of analytics at the Carroll School of Management, Boston College, and guest editor of MIT Sloan Management Review’s Artificial Intelligence and Business Strategy Big Ideas initiative. Lead author of the eighth annual MIT SMR × BCG global AI research report (Nov 2024), the longest-running comparable annual survey on AI in business strategy in the wiki’s source set.

Role and remit

• Boston College / Carroll School of Management: professor of analytics; recurring teaching and research focus on AI in business.
• MIT SMR Big Ideas: guest editor of the Artificial Intelligence and Business Strategy track. The 8-year panel of comparable annual surveys has produced research reports on AI strategy, organizational learning with AI, and AI value capture.
• Podcast: co-hosts (with Shervin Khodabandeh of BCG) “Me, Myself, and AI” — the MIT SMR × BCG AI podcast cited in the Augmented Learners report’s references.

Wiki contributions

• Lead author, Learning to Manage Uncertainty, With AI (Nov 2024, with David Kiron, Shervin Khodabandeh, Michael Chu, Leonid Zhukov) — 3,467-respondent global survey + 9 executive interviews; introduces Augmented Learners (15% of orgs combining high organizational + high AI-specific learning); 1.6× uncertainty-management advantage; explicit appendix on the State of AI in Business 2024 including the year-over-year adoption series back to 2017.
• Host (with Shervin Khodabandeh of BCG), [[2026-05-31-peron-mit-smr-me-myself-and-ai-philips-interoperability-health-care|Me, Myself, and AI — Season 13 episode with Carla Goulart Peron (Philips CMO)]] (31 May 2026) — long-form interview on AI-for-interoperability in health care. Ransbotham’s interviewing turn surfaces the radiologist-trained-on-normal-images deskilling-pipeline question (raised by an audience member at a recent radiologist-society meeting) and extends Peron’s nine-German-women postpartum-blood-loss anecdote with the prompt that “a very simple job for agents would be to go through all of our clinical practices in every area and find the root study for that and assess how that plays out” — making the AI-as-clinical-protocol-bias-auditor prescription explicit at host-vantage altitude. The wiki’s first podcast-format Ransbotham source, alongside his 2024 written-research authorship.

Cross-source positioning

The MIT SMR × BCG annual research instrument (8 years of comparable methodology) is one of the wiki’s longest panels; the Augmented Learners report is the first ingest from this stream. Earlier reports (2017–2023) are cited indirectly — first-party ingestion of any prior edition would strengthen longitudinal analysis.

Direct co-authorship with David Kiron connects this entity to the operational follow-up How to Reap Compound Benefits From Generative AI (2026) which extends the Ransbotham et al. 2024 framework with the verification → evaluation → learning capture flywheel.

Open questions

• The Ransbotham team has co-authored at least 8 annual MIT SMR × BCG AI reports (2017–2024) cited via reference in the 8th. Earlier reports likely contain longitudinal trajectory data on Augmented Learner cohort sustainability — first-party ingestion would clarify the durability question.