Jev Fever: Predictive AI Is Superhot Again

A new breed of models has rejuvenated predictive AI. But successful deployment demands a new business-value playbook.

... and then Eric summarizes his follow-on article:

Jev AI Will Make You Money – But Exactly How Much?

AI users are pouncing on the new predictive capabilities of Jev and its competitors. But to make money with Jev, you must also "valuate" it for your project.

Predictive AI Thrives, Despite Generative AI Stealing the Spotlight

This is the new preface to the paperback edition of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment.

Special offer: Pre-order the paperback of The AI Playbook now and receive free, immediate access to the audiobook.

This was also published as an adapted article in:

CDO Magazine: GenAI May Own the Hype, but Predictive AI Also Delivers Value

The Machine Learning Times: GenAI Owns the Hype, but Predictive AI Is Thriving

Listen to Luba and Eric unpack, explore, and expound. #noAGI

- Why predictive AI and generative AI are destined to remain inherently distinct

- Why comparing them is unavoidable, even though they solve different problems

- How they compare

- How companies should balance investments between the two

The paper endeavors to "address what’s wrong with our conception of AGI, and why, even in its most coherent formulation, it is a flawed concept to describe the future of AI."

That aligns so well with our episode just two days ago that one of the paper's authors, Philippe Wyder, tweeted us about the paper, bringing it to our attention!

The paper presents the new term "Superhuman Adaptable Intelligence," which is defined as "intelligence that can learn to exceed humans at anything important that we can do, and that can fill in the skill gaps where humans are incapable."

Listen to our break-down and take, and access the full paper here: https://arxiv.org/abs/2602.23643

Predictive AI Thrives, Despite GenAI Stealing The Spotlight

GenAI and predictive AI battle for resources, but even as the overwhelming attention focuses on genAI, enterprises are still adopting predictive AI just as much.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2026/02/11/predictive-ai-thrives-despite-genai-stealing-the-spotlight/

You can access an overview of HYBRID AI 2026 and a description of each enterprise presentation here: https://machinelearningweek.com/

Hybrid AI: Industry Event Signals Emerging Hot Trend

AI is not yet the success that it should be, so two dozen enterprises will disclose their move toward a crucial new paradigm – hybrid AI – at a 2026 conference.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2026/02/09/hybrid-ai-industry-event-signals-emerging-hot-trend/

It's about shifting the conversation from abstract metrics to tangible ROI. 

Henry Castellanos is a data scientist extraordinaire. He goes beyond establishing a strong technical performance for his ML models to also maximizing their business value. Let this sink in: Most data scientists don't do that – most ML projects don't plan and sell predictive AI deployment according to the the explicit business value.

Interestingly, Henry points out that using Gooder AI (www.gooder.ai) to do this even bucks up his own confidence in his models and their business value.

Listen to Henry's presentation to see exactly how to bridge the gap from ML to real-world value.

To view this presentation as a video, go to: https://youtu.be/BT-GnnuN3jA

Predictive AI Usually Fails Because It’s Not Usually Valuated

Most predictive AI deployments are scrubbed. Why? They didn't forecast the potential value in business terms like profit or savings.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/11/18/predictive-ai-usually-fails-because-its-not-usually-valuated/

AI Drives Alphabet’s Moonshot To Save The World’s Electrical Grid

AI is pivotal as global utilities tackle a looming crisis with the electrical grid. Here's how Alphabet uses AI to help the world keep the lights on.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/10/07/why-we-need-ai-alphabets-moonshot-to-save-the-worlds-electrical-grid/

To Deploy Predictive AI, You Must Navigate These Tradeoffs

Before deploying predictive AI, you must strike a balance between competing business factors. Here's how.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/08/27/to-deploy-predictive-ai-you-must-navigate-these-tradeoffs/

Excuse my furious typing noises (as I absorbed Michael’s compelling input) and I hope you find his insights as exciting as I did!

How Generative AI Helps Predictive AI

Large language models can act as predictive models. Here's an example for misinformation detection—and an introduction to savings curves.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/08/21/how-generative-ai-helps-predictive-ai/

The Quant's Dilemma: Subjectivity In Predictive AI's Value

When machine learning fails to detect misinformation, medical conditions or spam, the cost of each error is subjective. Here’s how to apply predictive AI nonetheless.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/09/30/the-quants-dilemma-subjectivity-in-predictive-ais-value/

The Great AI Myth: These 3 Misconceptions Fuel It

The impending arrival of artificial general intelligence is a story of wish fulfillment that lacks concrete evidence.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/07/29/the-great-ai-myth-these-3-misconceptions-fuel-it/

The 3 Things You Need To Know About Predictive AI

Stakeholders involved with predictive AI must ramp up on a semi-technical understanding that comes down to 1) what's predicted, 2) how well and 3) what's done about it.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/06/29/the-3-things-you-need-to-know-about-predictive-ai/

Why You Must Twist Your Data Scientist's Arm To Estimate AI's Value

For every machine learning model that you consider deploying, make sure that your data scientists provide you with a full view of its potential business value.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/06/11/why-you-must-twist-your-data-scientists-arm-to-estimate-ais-value/

The Rise Of Large Database Models

Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2025/01/13/the-rise-of-large-database-models/

In this episode, listen to a narration of Eric Siegel's article in Forbes:

3 Predictions For Predictive AI In 2025

1) GenAI hybrids, 2) ML valuation, 3) bizML—these advances will bring predictive AI back into the spotlight and further amplify its value.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2025/01/06/3-predictions-for-predictive-ai-in-2025/

Alphabet Uses AI To Rush First Responders To Wildfires — Takeaways For Businesses

An initiative from Google’s parent company that rushes the National Guard to climate disasters stands ready to review aerial images from the LA wildfires.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2025/01/13/alphabet-uses-ai-to-rush-first-responders-to-disasters-takeaways-for-businesses/

Listen to this uncanny chat to hear an overview of the book and some specific highlights...

... or listen to it to see if you can identify any tricks behind NotebookLM that make this such an uncanny, real-sounding chat.

I did no work or customization here -- I just uploaded the book manuscript, pushed "go", and waited a few minutes (yes, fewer than the actually length of this artificial podcast episode).

Listen to this uncanny chat to hear an overview of the book and some specific highlights...

... or listen to it to see if you can identify any tricks behind NotebookLM that make this such an uncanny, real-sounding chat.

I did no work or customization here -- I just uploaded the book manuscript, pushed "go", and waited a few minutes (yes, fewer than the actually length of this artificial podcast episode).

Concern about a generative AI bubble is growing. To defend against disillusionment, measure its concrete value.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/04/21/metas-new-genai-is-theatrical-heres-how-to-make-it-valuable/

See/listen also to Eric Siegel's Harvard Business Review article: HBR Article: The AI Hype Cycle Is Distracting Companies

Also see/listen to his Forbes article: Artificial General Intelligence Is Pure Hype

The belief that we’re gaining ground on AGI is misguided—reports of the human mind's looming obsolescence have been greatly exaggerated.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/04/10/artificial-general-intelligence-is-pure-hype/

See/listen also to Eric Siegel's Harvard Business Review article: HBR Article: The AI Hype Cycle Is Distracting Companies

AI can drive millions of operational decisions, but first the business must strategically select a single number that differentiates the yeses from the nos.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/03/25/ai-success-depends-on-how-you-choose-this-one-number/

Links from the article:

3 Ways Predictive AI Delivers More Value Than Generative AI (or read the original non-narrated article)

What Leaders Should Know About Measuring AI Project Value – why predictive AI needs – but usually doesn't have – business metrics (or read the original non-narrated article in MIT Sloan Management Review).

The AI Playbook: Mastering the Rare Art of Machine Learning Deployment by Eric Siegel

The detection of fraudulent credit card transactions is an ideal candidate for the application of machine learning technology. However, in order to learn how to spot attempted fraud, such a system needs someone to tell it which historic transactions were OK, and which were not.

Access the original article here: https://www.europeanbusinessreview.com/where-fico-gets-its-data-for-screening-two-thirds-of-all-card-transactions/

This article is excerpted from the book, The AI Playbook: Mastering the Rare Art of Machine Learning Deployment, with permission from the publisher, MIT Press. It is a product of the author’s work while he held a one-year position as the Bodily Bicentennial Professor in Analytics at the UVA Darden School of Business.

Other links from the article:

What Leaders Should Know About Measuring AI Project Value – why predictive AI needs – but usually doesn't have – business metrics (MIT Sloan Management Review).

Citations and other notes (PDF)

Generative AI attracts headlines, but predictive AI delivers greater value. This article covers three ways predictive AI eclipses generative AI.

Access the original article here: https://www.forbes.com/sites/ericsiegel/2024/03/04/3-ways-predictive-ai-delivers-more-value-than-generative-ai/

Also listen to narrations of two of Eric Siegel's other recent, related articles on predictive AI:

1) What it takes to capitalize on predictive AI:

Getting Machine Learning Projects from Idea to Execution

Harvard Business Review (print article)

2) Why predictive AI needs – but usually doesn't have – business metrics:

What Leaders Should Know About Measuring AI Project Value

MIT Sloan Management Review (print article)

Both of these articles are adapted from Eric Siegel's new book, The AI Playbook.

Most AI/machine learning projects report only on technical metrics that don’t tell leaders how much business value could be delivered. To prevent project failures, press for business metrics instead.

Access the original article here: https://sloanreview.mit.edu/article/what-leaders-should-know-about-measuring-ai-project-value/

This article is excerpted from Eric's new book, The AI Playbook: http://www.bizML.com

The full details of the article's central example are within a sidebar of the original article (not read through in detail within this podcast episode). You can also access this spreadsheet with the same calculations if you would like to try out different scenarios — such as varying the model lift, the number of transactions held, or the cost of each FP and FN.

On a related note, the book has been included as a Next Big Idea Club Must Read.

Also, here is the book's recent Bloomberg Businessweek Radio segment, which was mentioned herein.

For more about The AI Playbook, see the details, endorsements, and ordering options at www.bizML.com.

The AI Playbook: Mastering the Rare Art of Machine Learning Deployment

Info at: http://www.bizML.com

In my first book, Predictive Analytics, I explained how machine learning works. Now, in The AI Playbook, I show how to capitalize on ML. The book presents a greatly-needed business framework that I call bizML.

See all the details, recommendations from the likes of Scott Galloway, Charles Duhigg, Mustafa Suleyman, the CEO of FICO, and DJ Patil, the first Chief Data Scientist of the US – and order the book at: www.bizML.com

It's available there as a hardcover, ebook, and audiobook.

This podcast episode includes the book's "FAQ: What This Book Is about and Who It’s For," which can also be read here: https://www.predictiveanalyticsworld.com/machinelearningtimes/faq-for-eric-siegels-new-book-the-ai-playbook/13205/

Here is some early media coverage:

Fast Company called the book, "An antidote to overheated rhetoric of all-powerful AI." https://www.fastcompany.com/91005340/eric-siegel-ai-playbook-interview

It is a Next Big Idea Club Must Read: https://nextbigideaclub.com/magazine/next-big-idea-clubs-february-2024-must-read-books/46393/

Also read or listen to my Next Big Idea Club five-insights overview: https://nextbigideaclub.com/magazine/5-guidelines-successfully-launching-machine-learning-business-bookbite/47774/

Harvard Business Review: https://hbr.org/2024/01/getting-machine-learning-projects-from-idea-to-execution

Book review from Barbara Oakley – co-instructor of the world's most popular course, Coursera’s Learning How to Learn. She writes, “Siegel is a master story-teller... We LOVED this book and cannot recommend it more highly!” https://barbaraoakley.com/recommendation/the-ai-playbook/

Even before its release, the book hit the #1 slot on Amazon’s top 100 Hot New Releases in Technology.

Here’s to accelerating progress as the world improves business with science — thanks and happy reading!

Access the original article here: https://hbr.org/2023/06/the-ai-hype-cycle-is-distracting-companies

Learn more about and order Eric's new book, The AI Playbook: http://www.bizML.com

Machine learning has an “AI” problem. With new breathtaking capabilities from generative AI released every several months — and AI hype escalating at an even higher rate — it’s high time we differentiate most of today’s practical ML projects from those research advances. This begins by correctly naming such projects: Call them “ML,” not “AI.” Including all ML initiatives under the “AI” umbrella oversells and misleads, contributing to a high failure rate for ML business deployments. For most ML projects, the term “AI” goes entirely too far — it alludes to human-level capabilities. In fact, when you unpack the meaning of “AI,” you discover just how overblown a buzzword it is: If it doesn’t mean artificial general intelligence, a grandiose goal for technology, then it just doesn’t mean anything at all.

Access the article: https://hbr.org/2024/01/getting-machine-learning-projects-from-idea-to-execution

Learn more about and order The AI Playbook: http://www.bizML.com

The AI Playbook: Mastering the Rare Art of Machine Learning Deployment

Info: www.bizML.com

This podcast episode includes a book overview, book sample – the opening of the book's Introduction – and a free audiobook offer.

In his bestselling first book, Eric Siegel explained how machine learning works. Now, in The AI Playbook, he shows how to capitalize on it.

SPECIAL OFFER: FREE AUDIOBOOK

Pre-order The AI Playbook as a hardcover or e-book on Amazon – shipping February 6, 2024 – and receive a free advanced copy of the audiobook version now.

You'll also receive a copy of the audiobook for Eric Siegel's other book, Predictive Analytics, and free access to the first three modules of his online course, "Machine Learning Leadership and Practice: End-to-End Mastery" (a total of 39 instructional videos).

This offer ends January 12, 2024. Click here for details: https://www.machinelearningkeynote.com/the-ai-playbook-free-audiobook-offer

Join him in Las Vegas June 19-24 for Machine Learning Week 2022, with seven tracks of sessions covering the commercial deployment of machine learning. Register to attend one or more of MLW’s five co-located conferences: PAW Business, PAW Financial, PAW Industry 4.0, PAW Healthcare, and Deep Learning World.

MLW Vegas 2022: http://www.machinelearningweek.com

Predictive Analytics World for Climate Tech: https://predictiveanalyticsworldclimate.com/

Predictive Analytics World for Industry 4.0 Munich: https://predictiveanalyticsworldindustry40.eu/

Predictive Analytics World for Healthcare Munich: https://predictiveanalyticsworldhealthcare.eu/

Deep Learning World Munich: https://deeplearningworld.de/

The history of these conferences -- from spawning the Target-predicting-pregnancy publicity debacle to getting dinged by the Hollywood action movie star Chuck Norris: https://www.predictiveanalyticsworld.com/machinelearningtimes/a-brief-history-of-paw-on-its-10-year-anniversary/9936/

"Are Orange Cars Really not Lemons?" by John Elder and Ben Bullard, Elder Research, Inc.: www.elderresearch.com/orange-car

The good news is that you probably already have the hardware to handle this endeavor: the same system currently running your high-volume transactions – oftentimes a mainframe. But getting this done requires a specialized leadership practice and strong-willed change management.

For further details, see the article: https://www.predictiveanalyticsworld.com/machinelearningtimes/real-time-machine-learning-why-its-vital-and-how-to-do-it/12166/

See also this webinar on real-time machine learning: https://event.on24.com/wcc/r/3285703/7B596BEFB9D70F8AFF812858C322E5C0?partnerref=ESLI

See my Scientific American blog article to dig in further and access many links: https://blogs.scientificamerican.com/observations/the-medias-coverage-of-ai-is-bogus/

Watch my two-part video coverage of the accuracy fallacy:

https://www.youtube.com/watch?v=81Vv0J2Vw-Y

https://www.youtube.com/watch?v=ui3VkecTX3Y

Links:

https://www.kdnuggets.com/2022/01/models-rarely-deployed-industrywide-failure-machine-learning-leadership.html

https://www.kdnuggets.com/2020/10/machine-learning-omission-business-leadership.html

http://www.machinelearning.courses

http://www.theAIparadox.com