Podcast Summary: How I Invest with David Weisburd

Episode E247: Why Wall Street Is Wrong About AI w/ Dan Ives

Date: November 21, 2025
Guest: Dan Ives, Managing Director and Head of Technology Research at Wedbush Securities
Host: David Weisburd

Episode Overview

This episode dives into why Wall Street’s consensus view on AI is lagging behind true market dynamics—and how Dan Ives, one of the most prominent and distinctive tech analysts on Wall Street, approaches tech investing differently. Ives dissects the long-term, disruptive potential of AI across hardware and software (especially as embodied by Tesla and Nvidia), the importance of non-quantitative analysis (“not in the spreadsheets”), the underestimated value of founder-led companies, and the personal philosophy behind his conviction-driven, often contrarian investment style.

Key Discussion Points and Insights

A Long-Term Vision for Valuation

• Valuing Beyond the Next Quarter:
  Dan Ives makes the case for projecting three, five, even seven years ahead to capture the real potential of disruptive tech companies rather than being bogged down by short-term multiples.

  "If you focus just on one year PE or one year valuation, you missed every transformational tech stock the last 20 years."
  — Dan Ives (03:36)

AI, Tesla, and the Power of Narrative

• Tesla as “Physical AI”:
  Ives sees Tesla not as a car company but the "best physical AI disruptive player" after Nvidia, predicting dominance in autonomous vehicles and robotics.

  "I don't think there's a better play outside Nvidia... when thinking about the longer-term AI vision, physical AI in terms of autonomous robotics, than Tesla."
  — Dan Ives (01:36)

• Narrative Drives Value:
  The market’s focus on narrative is critical, especially for stocks like Tesla, where the story about future potential matters more than present-day numbers.

  "The focus on Tesla is about the future... We view ourselves as very important in a lot of these games in terms of measure the narratives. Right. Because I believe that's where the growth is."
  — Dan Ives (35:16)

Separating from the Herd

• Getting Comfortable with Being Different:
  Ives embraces being a nonconformist, from his attire to his research process, leveraging global conversations and on-the-ground feedback.

  "I've never dressed like that. I've never analyzed stocks like that. And that's been part of our framework, right? Part of our DNA."
  — Dan Ives (11:25)

• Retail and Sentiment:
  He highlights the gap between institutional echo chambers and retail/meme dynamics—often spotting value others miss by engaging with all market participants.

  "They've been caught up in their echo chambers... and they've missed some of the underlying trends that are happening in memes... You have to have a good understanding of sentiment."
  — Dan Ives (09:26)

Information Beyond the Spreadsheets

• Non-Quantitative Signals:
  Ives’s edge comes from tracking qualitative customer sentiment, leadership quality, and operational momentum—factors often “not in the spreadsheets.”

  "My alpha is are things that are not in the spreadsheets, which is very surprising for public companies."
  — Dave (10:52)
  "Like leadership—there's no line item, right?"
  — Dan Ives (39:19)

• Customers Drive Theses:
  When customers’ attitudes and priorities change—like moving from AI skepticism to all-in adoption—that signals major potential before it shows up in financials.

Dealing with Turbulence, Failure, and Conviction

• Surviving the Ups and Downs:
  Ives talks about the importance of conviction during rough patches and how insights from global travels counterbalance negative market sentiment.

  "It's easier to go with the pack, not fight sometimes the trends, stocks are selling off against you. But I've traveled 3 million air miles 25 years... that's helped build confidence."
  — Dan Ives (06:35)

• Learning from Mistakes:
  Career-defining failures taught him the value of perseverance and conviction even when stocks underperform temporarily.

  "The thing that I would tell myself... would be embrace the failures, let them make you better. And it's belief in yourself."
  — Dan Ives (44:54)

Recognizing When You’re Wrong

• Thesis-Driven Corrections:
  Admitting mistakes when the underlying story changes, not just because of temporary volatility, is key.

  "You know when you're wrong more from when the thesis changes... that was a good example of recognizing we are wrong, admitting we are wrong and then ultimately taken out of our core AI index."
  — Dan Ives (16:14)

Portfolio Construction and Sizing

• Sizing by Conviction:
  Ives recommends scaling up only as conviction moves from 8.5 out of 10 to the 9+ range, rather than blindly following early bullishness.

  "When it inflects from like an 8.5 to like in the nines, that's where you scale up."
  — Dan Ives (23:52)

Power Laws and Outliers

• Are Public Markets Still Power Law Driven?
  Despite debates, Ives sees ongoing power law opportunities in public equities—in both obvious (AI chips, big tech) and overlooked segments.

  "My whole view is it's not just about big tech... It's about who in software, who else in chips, the grid infrastructure. And a lot of times I'm looking for names, like okay, could this stock outperform?"
  — Dan Ives (30:05)

Leadership, Founder-Led Companies, and EQ

• Leadership Rarely in Models:
  The ability to “bet on the pilot” (great founders/CEOs) is key, yet under-modeled by Wall Street.

  "Leadership is essential. There's no line item, right? ... I do think that's something that you have to have a very good sense for, like which management teams to bet on."
  — Dan Ives (39:19)

• Founder Control and Long-Term Vision:
  Super-voting structures enable founders to take bold, long-term bets that standard governance might block.

  "You're betting on that pilot to fly the plane... I do think you need that because it's very easy to get caught up in gyration boards and other investors."
  — Dan Ives (42:34)

• EQ vs. IQ:
  The most successful investors are not just analytical, but have extraordinary emotional intelligence (EQ) for qualitative assessment.

Notable Quotes & Memorable Moments

• On Why Wall Street Gets AI Wrong:

  "Wall Street could not spell AI, David. A year ago, it was like, let’s see it in the numbers. But when you talk to engineers, CIOs, customers? The AI revolution had already begun."
  — Dan Ives (02:28, paraphrased for clarity from sentiment throughout the episode)

• On Palantir and Non-Consensus Bets:

  “The haters hated it at 12, despised at 50, yelling from the mountaintops at 100. I always say: bears, when they're in hibernation mode—can't see AI in spreadsheets.”
  — Dan Ives (03:36)

• On the Role of Narrative:

  “It's about the narrative... We view ourselves as very important in a lot of these games in terms of making sure the narratives are right.”
  — Dan Ives (35:16)

• On Embracing Eccentricity:

  “I've always dressed funky... it's a little symbolism too. I'm not gonna go to the beat of a typical drone and I could care what others think.”
  — Dan Ives (13:39)

• On Failure and Resilience:

  "Embrace the failures, let them make you better. And it's belief in yourself."
  — Dan Ives (44:54)

• On Being a Conduit for Information:

  “We view ourselves as almost like very intertwined globally with investor feedback. … I think cognitive information is a big role you play as an analyst.”
  — Dan Ives (28:08)

Timestamps for Key Segments

• Valuing AI and Tesla’s Disruption: 01:28 – 03:36
• How to Value Transformative Tech Companies: 03:36 – 05:10
• On Surviving Market Turbulence: 06:21 – 07:53
• The Importance of On-the-Ground Sentiment: 07:53 – 10:52
• Beyond Spreadsheets—‘Alpha’ from Qualitative Insights: 10:52 – 13:29
• Navigating Against the Herd: 13:29 – 14:49
• Admitting When You’re Wrong: 16:13 – 18:53
• Sizing Positions and Portfolio Construction: 23:29 – 25:52
• Finding Power Law Outliers in Public Markets: 29:28 – 31:32
• Leadership, Founder-Led Companies, and EQ: 39:19 – 43:29
• Advice to Younger Self on Conviction and Failure: 44:39 – 47:31

Closing Thoughts

Dan Ives’s approach—combining global qualitative research, deep conviction, a contrarian mindset, and a keen sense for leadership and narrative—sets him apart in interpreting and investing in disruptive technology. For investors willing to think beyond models, embrace uncertainty, and play the long game, his strategies and lessons offer rich, actionable insights into the future of tech and AI investing.