Sunday, October 25, 2026
Source trace. Via News points to the documents behind its reporting and shows what we drew from each — so you can check any claim. How we source
Source document· July 24, 2026

Why Most AI Projects Will Fail — And How to Find the Companies That Won't

View original at nasdaq.com
Why Most AI Projects Will Fail — And How to Find the Companies That Won't In this episode of Motley Fool Hidden Gems Investing, Motley Fool contributor Rachel Warren sits down with Steve Lucas, chairman and CEO of Boomi, to unpack what Wall Street is missing: Why the next wave of AI winners won't be the flashy model ma…
Opening lines of the source · short snapshot — read the full document at the original

What we drew from this source

The claims Via News extracted from this document. We point to the source; we don't replace it.

  • Stock Advisor's total average return is 908%, compared to 208% for the S&P 500

    60% confidence
  • OpenAI is burning $3 billion a month, which is a reported and reliable figure

    60% confidence
  • Claims that AI will take away human jobs are largely nonsense and fraud designed to scare people into buying a product

    60% confidence
  • Nvidia is the one company unequivocally making a ton of money from AI, while many other companies build amazing models but lose extraordinary amounts of money

    60% confidence
  • A $1,000 investment in Nvidia at the time of its Stock Advisor recommendation on April 15, 2005 would be worth $1,301,557

    60% confidence
  • The cost to train frontier AI models in 2026 exceeds $1 billion

    60% confidence
  • A $1,000 investment in Netflix at the time of its Stock Advisor recommendation on December 17, 2004 would be worth $369,577

    60% confidence
  • AI is meaningless without data, and unique proprietary data is what investors should look for

    60% confidence
  • Companies citing AI efficiency as the reason for layoffs are often engaging in spin without real data to back up productivity claims

    60% confidence
  • Gartner forecasts that a number of agentic AI projects will fail or fail to return results and will be shut down by the end of 2027

    60% confidence
  • New customer/logo acquisition is the number one indicator of a sufficiently transformative technology

    60% confidence
  • Steve Lucas previously turned Marketo into a $4.75 billion acquisition by Adobe

    60% confidence
  • The four major U.S. hyperscalers spent around $400-410 billion on AI capex last year, rising to over $700 billion this year

    60% confidence
  • Elon Musk put a cap on what his employees can spend at Tesla and SpaceX, per a recently reported news item

    60% confidence
  • If humans don't trust something, it will never be used, and this applies to AI just as it did to prior data and analytics projects

    60% confidence
  • As many as 40% of enterprise AI projects could ultimately be abandoned

    60% confidence
  • ROI now supersedes AI as the priority for boards and executives evaluating AI investments

    60% confidence
  • Within the next two decades, AI will largely manage or solve the major health challenges humans currently face, including curing type 1 diabetes

    60% confidence
  • The cost to train GPT-2 was just shy of $50,000

    60% confidence

Data points we hold from this source

OpenAI · cash burn rate3 billion_USD_per_month
What we know · the intelligence behind this page
Live from the substrate
What we're seeing
Enterprise Software Races to Govern and Consolidate Around Agentic AI
Enterprise software vendors are repositioning around autonomous AI agents. Salesforce is acquiring Braze, ServiceNow is launching agent governance tools (AI Passport, Super Intelligence Control Tower), SAP is pushing its 'Autonomous Enterprise', and Zeta is launching AthenaOS and its own inference model. Palantir is embedding itself in banking, aviation and sovereign AI infrastructure through partnerships with Customers Bank, Surf Air, Ondas and Armada. Governance, data sovereignty and enforced policy are emerging as preconditions for regulated sectors like finance. Investors such as Norwest see room to disrupt ERP and finance software, and they caution that AI should not be trusted with financial calculations. Consolidation and shareholder disputes (Salesforce/Braze, Tiny/Oso Cloud, ZenaTech/Boardwalktech) show the market reshaping.
Our read on the data ›
Signals we're tracking
EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
Patterns we're watching ›
Where sources disagree
Ford Motor Company
Both facts give cash for Ford Motor Company at the same point in time (2025-12-31; FY 2025 year-end and Q4 2025 year-end are the same date). Both are labelled USD, but the values are 23,356,000,000 and 23.356, which cannot both be true in USD. The two numbers agree once the second is read as billions (23.356 bn = 23,356,000,000), so the economic content is consistent and the conflict is a unit/scale error in the Q4 2025 record. The period is not the reason for the conflict: a Q4 and an FY figure at the same year-end date should match.
We flag conflicts openly ›
Recently verified
✓ Checked against the original source
4,994
facts traced to their source — and we flag the ones that don't hold up.
101 entities tracked4,994 facts checked against source5,500 source documents archived
Query this data → isubstrate.com
Why Most AI Projects Will Fail — And How to Find the Companies That Won't — Source | Via News | ViaNews Market