AI Was Supposed to Save Time. Why Are We Working More?

AI was supposed to save time. So why does it feel like everyone is working more?

In this episode of Tales of Abundance, Randy Lorensen, Dr. John Oberg, and Anthony Marino explore the Jevons Paradox and why efficiency gains often lead to more work, not less. From coal in the Industrial Revolution to washing machines, manufacturing, and now artificial intelligence, the pattern keeps repeating: when something gets dramatically more efficient, demand expands right along with it. And that raises a bigger question—if AI makes us more productive, what are we supposed to do with the time it gives back?

The conversation gets practical fast. The guys unpack how AI is changing expectations in business, why tiny teams can now do the work of much larger organizations, and why “more productive” does not automatically mean more freedom, more happiness, or a better life. They also bring it back to the Five F’s—family, friends, fun, fitness, and finance—and challenge listeners to think harder about whether they are using new tools to build abundance or simply to cram even more work into the same 24 hours.

In the Abundance Briefing, they shift to relationships, forgiveness, and the politics of AI infrastructure. They discuss the long-running Harvard research on happiness and relationships, why forgiveness may matter for longevity, and the growing debate around AI safety, data centers, energy, water, and fear-driven narratives around technological progress.

If you want to understand AI and productivity, the future of work, why better tools do not automatically create a better life, and how to stay intentional in an age of accelerating leverage, this episode is for you.

Show Notes

00:03 – The Jevons Paradox: why better engines led to more coal use, not less
01:35 – From agriculture to industry: how technology keeps reshaping work
03:14 – China, manufacturing, and the rise of the middle class through technology
04:51 – AI, efficiency, and why almost nobody seems to be working less
06:12 – Revenue per employee, tiny teams, and the new leverage economy
07:21 – Better tools raise expectations, not just productivity
08:26 – Continuous improvement, Six Sigma, and why AI pressure feels familiar
11:36 – More opportunity, more abundance, and the risk of working even harder
12:54 – The real messiness in AI may be human resistance to change
14:07 – Infinite analysis: when AI creates too much data and not enough clarity
18:11 – What should we actually optimize for with AI?
20:36 – The danger of solving the wrong problem with better tools
22:35 – The five whys, sovereignty, and what all this productivity is really for
24:30 – Broken money, lifestyle inflation, and why people still feel squeezed
28:51 – The Five F’s: family, friends, fun, fitness, and finance
30:57 – Health, supplements, and why AI still needs skepticism and filtering
34:40 – Time theft: when AI productivity quietly steals from sleep, fitness, and family
36:31 – The case for balance and using AI with intention
39:15 – Harvard’s long-running happiness study and the power of relationships
42:43 – Forgiveness, stress, cortisol, and why letting go may help you live longer
52:02 – AI safety, data centers, fear, and the politics of abundance
57:09 – Why energy, infrastructure, and innovation matter more than fear narratives