Dragonfly Thinking
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Future of Work
in an AI-enabled World

Sue Brake · Dragonfly Thinking
i3 Strategy Forum · May 2026
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The visual essay

Future of Work visualisations

Full set of visualisations behind the QR.
01 · Pressure Verifiability →
Where AI-pressure lands and how fast
Head + verifiability (vs Head (unverifiable), Hand and Heart)
02 · Workers
Which workers win, and which don't
Diamond-complete vs classic I or T
03 · K-Shape Compound Erode
What determines K-shape compounding
for Workers, Organisations and Countries
04 · Countries
How does country-adoption cluster
we are all mid-tier laggards
The reframe

AI is a capability to compound
not a tool to deploy

Three things change.
Shift one
The work
Where AI bites first — and how the team pyramid restructures around what AI can't do.
Shift two
The shape
What shape of worker compounds with AI capability — and what shape erodes against it.
Shift three
The pipeline
How the next generation of senior judgment is made when AI is doing the apprentice's work.
The work

The team pyramid restructures around what AI can't do

Verifiability predicts whether AI substitutes or augments
Verifiable — the loss column
Cost-out, not edge
Analyst-weeks collapse to minutes. Already in production.
Analyst-weeks
weeks
Comp builds & screening Basic credit work ESG flags DD questionnaires Transactional legal & filings Standard valuation mechanics
Unverifiable — the gain column
Where alpha lives
AI doesn't substitute it. AI compounds it — for the right shape of worker.
Human judgment
baseline
× AI
compounds
Regime calls Illiquid sourcing Active stewardship & engagements Manager selection · trust over time Counter-cyclical allocation Mandate design under deep uncertainty
November 2025 — fully-verifiable code inflection · five independent witnesses (Willison · Cherny · Cat Wu · Vo · Schoening)
The worker

Diamond-complete is the new T-shape

Focus on hiring or building T-shape with AI fluency
AI DEPTH
I-shape
Deep specialist, no AI
AI DEPTH
Generalist
Breadth, no anchor
AI DEPTH
T-shape
What we used to hire for
AI DEPTH
Upside-down T
Generalist + AI, no anchor — useful catalysts
AI DEPTH
Diamond-complete
T-shape + AI fluency. What compounds.
The team

The team pyramid restructures into one of four shapes

The Diamond is the design target. The Barbell is the failure mode.
Traditional Pyramid
today's structure — juniors subsidise seniors
The Obelisk
same shape, dramatically narrower
The Barbell
missing generation in the middle
✗ failure mode
The Diamond
orchestrators in the widest band, working alongside AI
★ design target
The T
thin human layer over an automated stack
Roberts & Wilkins (2026), "The Pyramid Transformation" · adapted from the Harvard Law School project
The pipeline

Don't let the team become a barbell

Three answers — and one only this room can fund
01
Anchor depth is being redefined, not eliminated.
From “I can do this task better than the model”
to “I know where the model fails in my corner of the world, and I have the trained intuition to catch it before it costs us.”
Recap

Three messages. Three responses.

01
The question Where does AI bite first?
The response Verifiability — and it restructures the team pyramid. Verifiable work collapses to AI-minutes; unverifiable work is where alpha lives.
02
The question What shape compounds rather than erodes?
The response Diamond-complete at the worker level; the Diamond at the team level. Don't become a Barbell. Pair every upside-down-T hire with a senior specialist as a catalyst.
03
The question How do we develop the next generation when AI is doing the apprentice's work?
The response Preserve the apprenticeship architecture. A new credentialing standard would benefit the whole industry. Diamond-complete is currently undefined — no university, professional body, or vendor produces it.
Robustness Workflow
Dragonfly & Analyst
CTQ Framing
Context
Trigger — why now
Question to answer
Four Scenarios (A)
Finds drivers Prioritises drivers Chooses & builds most impactful scenarios
boundary
+ extract
Systems Mapping (B)
Determines network connections Finds loops & tipping points Finds synergies & trade-offs Synthesises emergent insights
boundary
+ extract
Robustness (C)
Stress-tests strategy across scenarios Designs signposts with triggers Determines scenario probabilities & final synthesis
boundary
On request
Committee Paper
draft · committee-ready
analyst
Results Explorer
Q&A on analysis & methodology Reports on demand
analyst
Interactive Dashboard
the analyst's window
{ }
JSON Manifest
source of truth · machine-readable · agent analysis preserved
Scenarios.json
Systems.json
Robustness.json
Audit Log
· · ·
boundary checks · clean-run record
Analyst
sign-off
Governance Committee
Governance
Reviews · approves
Decision
signed · defensible
Re-frame? Rerun the workflow.
What we tested against

Four future-of-work scenarios

Workers atomised Workers organised
Q2
Negotiated Displacement
Substitution still proceeds, but bargaining captures a share of the surplus and shapes deployment terms — guild, EU sectoral, and co-determination variants.
~12%
Q4
Co-Pilot Compact
Augmentation under co-determination and bargaining — AI funds shorter hours and care-sector wages. Only works if the metacognition gap is also addressed.
~14%
Q1
Hollowed Middle
Substitution at scale. Mid-skill knowledge work collapses, gains concentrate in capital and elite professions, populist backlash without binding response.
~8%
Q3
Productivity Without Power
AI augments rather than substitutes. Productivity rises, wages stagnate, gains accrue to capital. The 1990s decoupling pattern intensifies.
~16%
← AI substitutes AI augments →
As of May 2026 — both axes near midpoint. ~50% probability sits in the central zone. The corners are individually unlikely but collectively define the design space.
From the workflow

Three insights I haven't had time to land

01
Comprehension governance debt is accumulating silently.
The transformation paradox gap is its leading indicator. 2–4 year window before failure event. Measurable metric installable on Monday.
02
You hold both sides of the AI trade.
Capital owner of the disruption. Fiduciary for the disrupted. The first three peer funds to publish an AI-deployment stewardship policy will set the floor.
03
Q2 Negotiated Displacement is not the most likely scenario, but it's the right design case.
The only future where all four operating-model trade-offs stretch at once. Designing for it covers the others as a functional superset.
Ask Dragonfly-AI about any of them in the next ten minutes — it has loaded all of the robustness analysis as well as Dragonfly's broader Future of Work in an AI-Enabled World context.
Microsoft 2026 WTI · transformation paradox triplet: 65% fear falling behind · 13% rewarded for AI reinvention · 26% see leadership alignment.
Dashboard snapshot

The dashboard

Insert Dashboard Snapshot here
What we tested against

Scenario pathways — surplus, alternative view

Constructive ↑ Destructive ↓ 2026 2027 2028 2029 2030 2031 Today May 2026 Q4 Co-Pilot Compact ~14% Q2 Negotiated Displacement ~12% Q3 Productivity Without Power ~16% Q1 Hollowed Middle ~8%
As of May 2026 — both axes near midpoint. ~50% probability sits in the central zone. The four corners are individually unlikely but collectively define the design space.