Role: Associate Professor, Wharton School (Management), University of Pennsylvania. Ralph J. Roberts Distinguished Faculty Scholar. Faculty Director, Wharton Generative AI Lab (GAIL). Co-directs with Dr. Lilach Mollick.
Platforms:
- Substack (“One Useful Thing”) — 424K+ subscribers, free, ~2 posts/month. Ranked #17 in Substack Business category.
- LinkedIn — large following (exact count undisclosed; routinely 500+ comments per post).
- X/Twitter (@emollick) — high-engagement academic AI account.
- Book — Co-Intelligence: Living and Working with AI (Penguin Portfolio, Apr 2024). NYT bestseller. Economist and Financial Times best book of the year.
- Speaker circuit — represented by Washington Speakers Bureau. Fee tier undisclosed but consistent with top-tier academic keynote ($50K–$100K+ range based on WSB positioning).
- moreusefulthings.com — free prompt library, teaching tools, Wharton Interactive resources.
Cadence: Approximately 2 posts/month on Substack. High-frequency LinkedIn micro-posts (screenshots, quick takes, research links). Book tour / keynote cycle.
Format Specs
- Length: 2,000–4,000 words per Substack post. Long-form essay, not listicle.
- Visual grammar: Text-first. Occasional screenshots of AI outputs. No custom graphics, no charts, no data visualizations, no video. Zero production investment beyond writing quality.
- Tone: Professorial but accessible. First-person (“I tried this…”). Exploratory, not prescriptive. Comfortable with ambiguity (“we don’t know yet”). Genuine intellectual curiosity — not performative.
- Distribution: Substack email → LinkedIn amplification → X amplification → book sales → Wharton exec-ed pipeline → speaking circuit.
Recurring Topics + Implicit Thesis
Core thesis: AI is a general-purpose technology that changes all knowledge work; the way to understand it is to use it yourself, not to read vendor marketing. The “jagged frontier” — AI is simultaneously superhuman at some tasks and terrible at adjacent ones — is the central analytical framework.
Recurring topics (from archive analysis, Sep 2025–Mar 2026):
- Model capability assessments (which AI to use, comparative evaluations)
- Agentic AI and what it means for work (“Claude Code and What Comes Next,” “Real AI Agents and Real Work”)
- Management as the key skill for AI era (“Management as AI superpower”)
- The shape/pattern of AI capabilities (“jaggedness,” “bottlenecks,” “salients”)
- Practical guides for individuals (“Opinionated Guide to Using AI Right Now”)
- AI verification and oversight (“Giving your AI a Job Interview,” “On Working with Wizards”)
- Education and pedagogy (less frequent on Substack, more on moreusefulthings.com)
What he consistently covers well:
- Individual productivity framing (“you + AI”)
- Academic rigor applied to capability claims
- Honest broker positioning — genuinely calls out limitations
- Intellectual framework-building (jagged frontier, co-intelligence)
- First-mover on new model releases with practical assessments
Audience Overlap with Brandon (Estimate: 40–60%)
Overlap zone: Senior leaders who read long-form, want evidence-based AI takes, distrust vendor marketing. The “smart skeptic” persona.
Divergence: Mollick’s core audience skews toward (a) individual knowledge workers figuring out personal AI use, (b) academics/educators, © tech-adjacent professionals. Brandon’s core audience is (a) C-suite decision-makers at mid-market companies ($50M–$2B), (b) people with budget authority and organizational responsibility, © people who need to decide for 500 people, not for themselves.
Mollick writes for the person asking “how should I use AI?” Brandon writes for the person asking “how should my organization deploy AI and what will it cost?”
Revenue Model / Funnel
Mollick’s monetization is indirect and institutional, not direct:
- Free Substack → builds massive audience and brand authority
- Brand authority → NYT bestselling book (Penguin advance + royalties)
- Brand authority → Wharton executive education enrollment (Wharton captures revenue; Mollick gets institutional positioning + likely course fees)
- “Digital Strategy in the Era of AI Certificate” — self-paced, multi-course
- “CEO Academy” — premium cohort
- “Strategies for Accountable AI” — live online
- “Advancing Digital Innovation” — in-person
- Brand authority → speaking circuit (Washington Speakers Bureau, $50K–$100K+ per keynote estimated)
- moreusefulthings.com — free resources, no paywall (builds goodwill, not revenue)
Key insight: Mollick does not need to monetize the Substack directly because Wharton’s institutional platform captures the downstream value. The free newsletter is the top-of-funnel for a $100K+ executive education product he doesn’t have to sell, market, or deliver logistics for.
Gap Brandon Can Own
What Mollick consistently does NOT cover — and mid-market CIOs care deeply about:
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Organizational deployment specifics. Mollick writes about individual use. He does not write about: change management programs, training architecture, adoption resistance, workforce communication, pilot-to-production timelines. Brandon’s entire corpus addresses the organizational layer Mollick flies over.
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Procurement and contracting. MSA timelines, BAA friction, DPA redlines, vendor security questionnaires, SOC 2 gaps, indemnity ceilings. Zero coverage from Mollick. This is Brandon’s Pillar 16 opportunity — defensible ground no academic will touch.
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Cost and ROI modeling. TCO per seat, training investment per employee, data remediation costs, license audit frameworks. Mollick never prices anything. Brandon’s CFO-facing tools (TCO one-pager, budget request template, license audit card) have no Mollick equivalent.
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Mid-market specificity. Mollick’s examples are either individual-scale or Fortune 100-scale (when he cites research). The 200–2,000 employee company — too large for one person to experiment, too small for a dedicated AI team — is invisible in his work. This is Brandon’s exact client profile.
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Industry-specific compliance and risk. SR 11-7 for banks, NAIC for insurers, HIPAA BAA requirements for healthcare, EU AI Act high-risk classification. Mollick stays at the capability layer; he never descends into the regulatory layer that blocks actual deployment.
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Actionable frameworks with Monday-morning specificity. Mollick’s advice is “try it yourself” and “be curious.” Brandon’s advice is “here is a 90-day pilot structure with success metrics, here is a shadow AI discovery worksheet, here is the vendor contract red-lines checklist.” The gap between “understand” and “execute” is where Brandon lives.
Format gap: Mollick is text-only. No video, no data visualization, no podcast. Brandon’s video-podcast format (kinetic typography, sourced stats on-screen, 3–5 min briefings) occupies an entirely different content surface. A CIO who reads Mollick’s essays can also watch Brandon’s briefings — they serve different consumption modes.
Anything Worth Borrowing
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“Jagged frontier” as a concept. Brandon should reference this framework (with attribution) when explaining why AI works brilliantly for some tasks and fails at adjacent ones. It’s become standard vocabulary among the exec audience.
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First-person experimentation. Mollick’s credibility comes partly from “I tried this and here’s what happened.” Brandon’s workshop format already does this live, but the written content could benefit from occasional “I tested this with a client’s actual workflow” case references (anonymized).
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Honest ambiguity. Mollick says “we don’t know yet” when the evidence is thin. Brandon’s corpus does this with temporal weighting and credibility ratings — but the willingness to say “the data isn’t there” is worth maintaining as a differentiator from vendor-funded research.
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Publication cadence discipline. 2 posts/month, every post substantial. Quality over volume. Brandon’s research corpus is 300+ documents — the challenge is surfacing the right 2–3 per month as public-facing content rather than publishing everything.