---
title: "The Great Remaking"
date: 2026-07-12
description: AI is restructuring how organisations think, decide, create, and deliver, and the gap between those that redesign work and those that wait compounds.
author: Mario Thomas
canonical: https://mariothomas.com/briefings/the-great-remaking/
---

## Start here

Two short reads that orient you: what The Great Remaking actually is, and the order in which to work through this briefing.

### What The Great Remaking Is, and Why It Is a Race

I have worked through five technology revolutions: desktop,
internet, web, mobile, and cloud. Each changed how organisations
accessed, connected, distributed, and scaled, and each felt
transformative at the time. None of them restructured the
essence of how organisations actually work. AI does. It is
remaking how organisations think, decide, create, and deliver,
across the cognitive and the physical domains at once, and that
is why I treat it as [The Great Remaking](/blog/the-great-remaking/)
rather than the sixth wave in a familiar sequence.

The mistake I see most often is not denial but familiarity.
Most of the Boards I meet reach for the playbook that served
them through every previous wave: run pilots, watch the early
movers, buy or build what works, and measure progress in spend
and project counts. Those measures capture the technology
layer, and the technology layer is the smallest part of what is
at stake. BCG's January 2026 research, AI Transformation Is a
Workforce Transformation, puts roughly 10% of AI value in the
algorithms, 20% in the technology required to implement them,
and 70% in redesigning how people and machines work together.
The standard Board conversation measures the replicable 30% and
misses the 70% where advantage accumulates.

The position this briefing takes is that The Great Remaking is
a race with compounding consequences. Organisations that
redesign work around AI, rather than bolting AI onto existing
processes, build advantage through three self-reinforcing
loops: proprietary data shaped by AI-integrated workflows,
human capability developed through sustained practice, and
institutional knowledge of redesign itself. None of that can be
purchased, and all of it compounds. The roughly 5% of
organisations that BCG finds have achieved substantial
financial gains from AI are already showing three-year
shareholder returns around four times those of the laggards
(BCG 2026), and fast-follower logic, which worked in every
previous wave, fails when the source of advantage has no
product to copy.

The judgement a director should come away able to make is a
precise one: whether their organisation is redesigning how work
is structured around AI or merely augmenting the status quo,
and what every month of deferral adds to the cost of catching
up. Everything in this briefing is built to make that judgement
possible, and to make it honestly.

### One Argument in Four Parts

The core sequence in [the articles](#core-reading) is one
argument in four parts, and it rewards being read in order. The
[opening article](/blog/the-great-remaking/) makes the claim
and assembles the evidence that AI is restructuring the essence
of work. [Four Dimensions](/blog/the-great-remaking-four-dimensions/)
works through thinking, deciding, creating, and delivering one
at a time, because they are not moving at the same speed or
through the same mechanisms. [Fast Following](/blog/the-great-remaking-fast-following/)
explains why the gap between redesigners and augmenters
compounds and cannot be closed by procurement, and
[the diagnostic](/blog/the-great-remaking-board-diagnostic/)
turns the whole argument into questions a Board can put to
management, with a guide to what credible answers look like.

Around the core sit the pieces that follow the remaking to
where it lands hardest. [Dawn of the three-hour work week](/blog/dawn-of-the-three-hour-work-week/)
is the earliest statement of the thesis, written in 2024.
[The Redeployment Dividend](/blog/ai-redeployment-dividend/)
argues that the right success metric for AI is redeployment,
not headcount. [The Personal Agent Economy](/blog/personal-agent-economy/)
follows knowledge ownership to its inversion point, and
[AI and the Chair](/blog/ai-board-director-chair/) brings the
remaking into the boardroom, where the Board itself is one of
the things being remade. [AI and the CEO](/blog/ai-board-director-ceo/)
carries the remaking into the executive, where the chief
executive chooses the bets that matter and answers for them,
and [The AI Accountability Gap](/blog/ai-agency-accountability/)
sets out the principle beneath the deciding dimension: agency
transfers to the machine and accountability does not.
Later pieces extend the argument: [Not Everything Needs AI](/blog/not-everything-needs-ai/)
sets out the questions that come before any decision to stop,
keep, or change a piece of work, and [Governing the Redeployment Dividend](/blog/governing-the-redeployment-dividend/)
turns the dividend into something a Board can govern and measure.

When the argument has landed, [Remake](#remake-assets) holds
the mechanisms I use to turn the thinking into Board-level
apparatus, and [the questions](#faqs) answer the ones directors
put to me most often on this subject. The references at the
end gather the external evidence the articles draw on, so the
claims can be tested against the sources themselves.

Take the core sequence in one sitting if you can, because the
compounding argument in the third article changes how you read
the fourth, and then bring the diagnostic questions to your
next AI agenda item and see how the answers hold up.

## Core reading

The core sequence builds one argument from claim to diagnostic; the pieces alongside follow the remaking into the workforce and the boardroom.

1. [The Great Remaking: AI and the Race to Transform the Very Essence of Work](https://mariothomas.com/blog/the-great-remaking/) (10 minute read, 22 February 2026): Five technology revolutions changed organisations; none restructured the essence of work. AI does, and redesign beats bolt-on by four times in shareholder returns. Podcast edition: 16 minute listen.
2. [The Great Remaking: How the Four Dimensions of Work Are Transforming](https://mariothomas.com/blog/the-great-remaking-four-dimensions/) (15 minute read, 8 March 2026): AI is remaking thinking, deciding, creating and delivering at different speeds and towards different ends. Treating them as one question is most organisations' mistake. Podcast edition: 20 minute listen.
3. [The Great Remaking: Why Fast Following Does Not Work When the Gap Compounds](https://mariothomas.com/blog/the-great-remaking-fast-following/) (13 minute read, 15 March 2026): Every previous technology wave rewarded fast followers. The Great Remaking does not: the advantage is operational accumulation that cannot be bought and compounds with time. Podcast edition: 16 minute listen.
4. [The Great Remaking: The Questions Boards Should Be Asking About Their AI Position](https://mariothomas.com/blog/the-great-remaking-board-diagnostic/) (10 minute read, 22 March 2026): Pilot counts and budget lines cannot tell a Board whether work is being remade. These questions, built on the data, talent and process loops, can. Podcast edition: 14 minute listen.

## Video

- [The Great Remaking](https://mariothomas.com/videos/the-great-remaking/) (22 min): What AI is doing to the essence of work, why the gap between the organisations that redesign the work and those that wait compounds, and the questions a Board should ask about its own position.

## Further reading

- [Dawn of the three-hour work week: AI's impact on employment and compensation](https://mariothomas.com/blog/dawn-of-the-three-hour-work-week/) (10 minute read, 9 June 2024): If machines do routine work faster and cheaper, what happens to us? The outcome is negotiated, not predetermined.
- [The Redeployment Dividend: Why AI Will Unleash Your People, Not Replace Them](https://mariothomas.com/blog/ai-redeployment-dividend/) (9 minute read, 11 January 2026): AI's primary value is not headcount reduction but the intellectual capital it releases from undifferentiated work. Measure only the former and the dividend goes unclaimed. Podcast edition: 12 minute listen.
- [The Personal Agent Economy: When Your Best AI Isn't On Your Balance Sheet](https://mariothomas.com/blog/personal-agent-economy/) (8 minute read, 15 February 2026): Individuals now own AI agents that encode their judgement and expertise, capability that belongs to them rather than their employer. The assumption has inverted. Podcast edition: 10 minute listen.
- [AI and the Chair: Governing the Board Through The Great Remaking](https://mariothomas.com/blog/ai-board-director-chair/) (14 minute read, 26 April 2026): Existing chair responsibilities now require different execution as AI remakes both the Board's own work and the work the Board governs. Podcast edition: 16 minute listen.
- [Not Everything Needs AI: The Questions That Come Before the Decision](https://mariothomas.com/blog/not-everything-needs-ai/) (8 minute read, 12 July 2026): Boards keep being told to remake the business around AI. The real question is not which tool, but whether the work needs doing at all. Podcast edition: 8 minute listen.
- [Governing the Redeployment Dividend: Turning Saved Hours Into Value](https://mariothomas.com/blog/governing-the-redeployment-dividend/) (10 minute read, 19 July 2026): AI is saving time almost everywhere. The organisations that gain from it are the ones whose Boards decide what the recovered capacity becomes. Podcast edition: 12 minute listen.
- [AI and the CEO: Choosing the Bets That Matter](https://mariothomas.com/blog/ai-board-director-ceo/) (12 minute read, 21 June 2026): AI can build, deliver, and draft, yet the chief executive still chooses and still answers. Accountability for the bets does not move. Podcast edition: 12 minute listen.
- [The Accountability Gap: When AI Delegation Meets Human Responsibility](https://mariothomas.com/blog/ai-agency-accountability/) (15 minute read, 16 November 2025): Organisations are transferring decision-making agency to AI while accountability stays with people, and approving deployments without the verification capability that accountability needs.

## Remake

The mechanisms beneath the thinking: the model, diagnostic, methodology, and principle from the Remake Library that turn this briefing into apparatus a Board can use.

- **Model: Stop Keep Change Model**. The verdict set of the Remake framework: for the work under examination the framework returns one of three verdicts, Stop, Keep, or Change, and all three are governed. [Remake Library](https://mariothomas.com/remake/library/#stop-keep-change)
- **Diagnostic: Process Audit**. The per-process evaluation applied one process at a time: what the work is for, how it is done today and whether it is still needed, and why it needs the technology at all, returning a verdict on the Stop, Keep, Remake scale with every reading graded by indicator type. [Remake Library](https://mariothomas.com/remake/library/#process-audit)
- **Methodology: AI Business Case**. The integrated decision framework that crystallises across an ADAPT engagement rather than at a single stage: strategic alignment established at Align, cost and readiness evidenced at Diagnose, value shaped at Advise, and execution designed at Plan. [Remake Library](https://mariothomas.com/remake/library/#ai-business-case)
- **Principle: Well-Advised**. The framework of five strategic priorities, Innovation, Customer Value, Operational Excellence, Responsible Transformation, and Revenue, used to ensure AI investments create balanced value rather than narrow cost reduction. [Remake Library](https://mariothomas.com/remake/library/well-advised/)

## Questions

The questions directors put to me most often about The Great Remaking, answered from the articles in this briefing.

### Is AI not simply the sixth technology wave, to be managed like the previous five?

The previous five waves changed how organisations accessed, connected, distributed, and scaled, and each rewarded a measured, follow-the-leader response. None of them restructured how organisations think, decide, create, and deliver, which is precisely what AI is doing across both the cognitive and the physical domains. [The Great Remaking](/blog/the-great-remaking/) sets out the evidence for why this is a difference in kind, not just scale, and why that changes the strategic response it demands.

### Why can we not wait, watch the early movers, and follow fast?

Because the source of advantage this time is not a product that can be studied and replicated. It is operational accumulation: proprietary data shaped by AI-integrated workflows, capability developed through sustained practice, and institutional knowledge of redesign itself. BCG's 2026 research attributes roughly 70% of AI value to redesigning the people component, which is the part no procurement decision can buy. [Fast Following](/blog/the-great-remaking-fast-following/) works through the three loops that make the gap compound rather than close.

### Management reports strong AI progress. How do we test whether it is real?

Pilot counts, budget lines, and strategy documents measure activity, not compounding advantage, and self-assessments of AI maturity are systematically inflated. Ask instead whether a specific workflow has been redesigned rather than augmented in the past 18 months, what data it now generates that it did not before, and what the organisation has learned about redesign itself. [The Diagnostic](/blog/the-great-remaking-board-diagnostic/) gives the full set of probing questions, with a guide to what credible answers look like.

### Does The Great Remaking mean large-scale workforce reduction?

Not if the Board chooses otherwise. Headcount reduction is the default success metric for AI initiatives in many boardrooms, and I think it is the wrong one: the larger value lies in releasing the intellectual capital trapped in undifferentiated work and redirecting it towards work AI cannot do. [The Redeployment Dividend](/blog/ai-redeployment-dividend/) makes that case, and [Dawn of the three-hour work week](/blog/dawn-of-the-three-hour-work-week/) asks what an equitable settlement with the workforce might look like.

### Is the Board itself part of what is being remade?

Yes, and in two states at once: AI in the preparation of board materials invites the quiet substitution of director judgement, while AI in the operations of the business produces decisions most directors cannot yet interrogate. Agency can be transferred to machines; accountability cannot, and the chair polices that boundary. [AI and the Chair](/blog/ai-board-director-chair/) works through what existing chair responsibilities now require, and [The Personal Agent Economy](/blog/personal-agent-economy/) previews the ownership questions coming behind them.

### How small a redesign can we start with?

One piece of work, not a programme. The three loops that make the gap compound start from a single decision: restructure one workflow around what AI can do rather than bolting AI onto it. Name the work precisely (a redesigned credit decision is a piece of work, an AI programme is not), with someone able to restructure it and someone answerable for it all the way up to the Board. The value compounds from the moment the decision is made and depreciates with every month it is deferred. [Fast Following](/blog/the-great-remaking-fast-following/) explains why, and the Process Audit diagnostic takes one process at a time from evidence to verdict.

### Which of the four kinds of work is moving fastest in our sector?

That varies by sector, which is why the question matters: the four are not moving at the same speed. In most organisations I see, thinking and creating are furthest along. AI as a faster research assistant is already commoditised, and a restructured creative function runs a different ratio of human direction to machine execution. Deciding moves more carefully, because AI can take the agency in a decision but not the accountability. Delivering is furthest from substitution but accelerating as the cost of embodied AI falls, and its pace differs most by sector. [Four Dimensions](/blog/the-great-remaking-four-dimensions/) works through each in turn, with the human residual that survives in every case.

### Does a remaking mean putting AI into everything?

No. The remaking is the mandate; putting a model into everything is fashion with a budget. Examine any single piece of work honestly and there are only three verdicts: stop it, keep it, or change it. Only the last reaches a tool decision, and a model suits judgement; it is the wrong instrument for a question with one right answer. The most valuable answer is often that the work should stop, and nobody below the Board has the standing to say so. [Not Everything Needs AI](/blog/not-everything-needs-ai/) sets out the three questions that come first, and the Stop Keep Change model is how the verdicts are governed.

## Gallery

The slides the video's argument is built on: the essence of work, the pace of the remaking, the two sides of every remaking, and why the gap compounds.

- [The essence of work: four kinds of work, what AI is doing to each, the moat, and the human residual](https://mariothomas.com/briefings/the-great-remaking/gallery/the-great-remaking-essence.jpg)
- [The remaking is not uniform: where agency sits across the four essences today](https://mariothomas.com/briefings/the-great-remaking/gallery/the-great-remaking-pace.jpg)
- [Agency and accountability: the two groups in every remaking](https://mariothomas.com/briefings/the-great-remaking/gallery/the-great-remaking-agency-accountability.jpg)
- [Three compounding loops: redesign, data, and talent, each feeding the next](https://mariothomas.com/briefings/the-great-remaking/gallery/the-great-remaking-compounding.jpg)

Four slides from The Great Remaking video (select any image to enlarge)

## References

The external research and primary sources the articles in this briefing draw on.

- **BCG** (4 February 2026): [AI Transformation Is a Workforce Transformation](https://www.bcg.com/publications/2026/ai-transformation-is-a-workforce-transformation). The February 2026 research behind the 10/20/70 value split and the four-times shareholder return gap between AI leaders and laggards.
- **McKinsey & Company** (5 November 2025): [The State of AI](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai). The State of AI global survey: adoption at 88% of organisations, with workflow redesign among the strongest predictors of EBIT impact.
- **Stanford HAI** (April 2025): [The 2025 AI Index Report](https://hai.stanford.edu/ai-index/2025-ai-index-report). The AI Index 2025: model performance converging and inference costs falling 280-fold, shifting advantage to what organisations build around AI.
- **PwC** (2025): [The Fearless Future: 2025 Global AI Jobs Barometer](https://www.pwc.com/gx/en/issues/artificial-intelligence/job-barometer/2025/report.pdf). The 2025 Global AI Jobs Barometer: a 56% wage premium for AI skills and three times the revenue growth per employee in the most AI-exposed industries.
- **White House CEA** (January 2026): [Artificial Intelligence and the Great Divergence](https://www.whitehouse.gov/wp-content/uploads/2026/01/Artificial-Intelligence-and-the-Great-Divergence-5.pdf). Artificial Intelligence and the Great Divergence: the national-level parallel to the organisational gap this briefing describes.
- **Deloitte** (3 March 2026): [AI and the future of human decision-making](https://www.deloitte.com/us/en/insights/topics/talent/human-capital-trends/2026/decision-making-with-ai.html). 2026 Global Human Capital Trends: 60% of executives use AI to support decisions while only 5% of organisations rate their decision maturity as leading.
- **Harvard Business Review** (12 January 2026): [Survey: How Executives Are Thinking About AI in 2026](https://hbr.org/2026/01/hb-how-executives-are-thinking-about-ai-heading-into-2026). The January 2026 executive survey: 39% of organisations with AI in production at scale, and culture named the biggest barrier by 93% of data and AI leaders.
- **Goldman Sachs Research** (2024): [The global market for humanoid robots could reach $38 billion by 2035](https://www.goldmansachs.com/insights/articles/the-global-market-for-robots-could-reach-38-billion-by-2035). Humanoid robot costs falling 40% year on year: the economics accelerating the remaking of physical delivery work.
- **Protiviti & BoardProspects** (18 March 2026): [How Boards Drive AI ROI: 2026 Governance Survey](https://www.protiviti.com/us-en/survey/global-board-governance-survey). The 2026 Global Board Governance Survey: boards that discuss AI at every meeting correlate strongly with high AI returns.
- **Institute of Directors** (January 2026): [NEDs Reimagined](https://www.iod.com/app/uploads/2026/01/FINAL-IoD-Business-Paper-NEDs-reimagined-14.01-6ca5096ee6348f2301347e942a1ffe29.pdf). NEDs Reimagined (January 2026): the Commission naming technical literacy gaps and the limits of AI judgement as challenges for directors.
- **BCG** (September 2025): [The Widening AI Value Gap](https://media-publications.bcg.com/The-Widening-AI-Value-Gap-October-2025.pdf). The Widening AI Value Gap, 2025: the 5% of future-built organisations show 1.7 times the revenue growth and 3.6 times the three-year shareholder return of AI laggards.
- **BCG** (26 June 2025): [AI at Work: Momentum Builds, but Gaps Remain](https://www.bcg.com/publications/2025/ai-at-work-momentum-builds-but-gaps-remain). AI at Work 2025: 67% of people in redesigned processes report an hour a day saved against 49% in augmented ones, the pace gap the film turns on.
- **PwC** (13 April 2026): [Three-quarters of AI’s economic gains are being captured by just 20% of companies – with the leading companies focused on growth, not just productivity](https://www.pwc.com/gx/en/news-room/press-releases/2026/pwc-2026-ai-performance-study.html). PwC's 2026 AI Performance Study of 1,217 executives: around three quarters of AI's economic gains captured by 20% of companies, which are twice as likely to redesign workflows.
- **McKinsey & Company** (2026): [The State of Organizations](https://www.mckinsey.com/~/media/mckinsey/business%20functions/people%20and%20organizational%20performance/our%20insights/the%20state%20of%20organizations/2026/the-state-of-organizations-2026.pdf). The State of Organizations 2026: 88% of organisations experimenting with AI and 81% reporting no meaningful bottom-line gains, the two figures the video sets against each other.

## The ideas beneath this briefing

Ideas I've named and matured writing about The Great Remaking: what each one means, and where it started.

- **The Essence of Work**: The four irreducible dimensions of work every organisation performs: thinking, deciding, creating, and delivering. AI is restructuring each at a different speed along a trajectory from augmentation to substitution. [Read more](https://mariothomas.com/blog/the-great-remaking/)
- **The Great Remaking**: AI changing the essence of work rather than merely its tools: the redistribution of judgement, the bifurcation of the workforce, and what organisations owe the people whose roles are remade. The frame that lets a Board govern workforce transition as a strategic programme, not an HR afterthought. [Read more](https://mariothomas.com/blog/the-great-remaking/)
- **Human Residual**: The durable human contribution that survives in each dimension of work as AI advances: judgement in thinking, accountability in deciding, taste and originality in creating, and adaptability and trust in delivering. [Read more](https://mariothomas.com/blog/the-great-remaking-four-dimensions/)
- **Data Loop**: A compounding cycle in which AI-integrated workflows generate higher-quality, better-structured operational data that feeds back into an organisation's AI systems, improving their performance and, in turn, producing still better data over time. [Read more](https://mariothomas.com/blog/the-great-remaking-fast-following/)
- **Process Redesign Loop**: The institutional capability for redesign itself: accumulated knowledge, cross-functional relationships, and governance that make each successive restructuring of work around AI faster, compounding organisational learning capacity rather than just productivity. [Read more](https://mariothomas.com/blog/the-great-remaking-fast-following/)

All concepts: https://mariothomas.com/glossary/concepts/

## More Board Briefings

More complete resources on AI and emerging technology for the Boards that need the full picture.

- [AI & the Workforce](https://mariothomas.com/briefings/ai-and-the-workforce/): The workforce question is not how many roles AI removes, but whether people build capability that earns premiums or credentials that incur penalties.
- [AI Transformation](https://mariothomas.com/briefings/ai-transformation/): Most organisations are stuck at the pilot stage; crossing the divide is a Board judgement about delegation, architecture, and governance, not a technology purchase.
- [AI Strategy](https://mariothomas.com/briefings/ai-strategy/): Approving good AI projects is not a strategy, and the Board's move is from accumulating pilots to a strategy it owns.
- [AI & the Board](https://mariothomas.com/briefings/ai-and-the-board/): AI changes how every Board duty is discharged, from director to Company Secretary, and moves none of the accountability.