A research program · Technology Quotient

The capacity to
absorb technology
is the most
consequential
unmeasured variable
in organizations today.

Technology Quotient is a research framework for measuring how well individuals, organizations, and societies sense, adopt, and extract sustained value from technology — and why the gaps between them keep widening.

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Tech literacy
Adoption velocity
AI fluency
Leverage ratio
Resilience
Primary bottleneck Analysing…
500+ Assessments taken
3 TQ layers
5 Bottleneck types
Definition
Tech­nology Quo­tient
noun · abbrev. TQ /ˌteknˈɒlədʒi ˈkwəʊʃnt/

The multi-dimensional capacity of an individual, organization, or society to sense technological change early, absorb new technology effectively, adapt when the landscape shifts, and extract sustained, compounding value from technology over time. Capacity that can be measured, developed — and lost.

Sense Early radar
for change
Absorb Adopt with
depth + speed
Adapt Resilience when
landscapes shift
Extract Compounding
value over time
The three layers of TQ
Layer 01

Individual TQ

How a person relates to, learns from, and applies technology across their career. The most personal layer — and the most improvable with deliberate practice.

  • Tech literacy
  • Adoption velocity
  • Leverage ratio
  • Resilience
  • AI fluency
  • Teaching capacity
Layer 02

Organizational TQ

How well a company senses shifts, makes adoption decisions, and operationalizes technology at scale. Not the average of individual TQ — an emergent property of culture, structure, and leadership.

  • Tech sensing
  • Adoption infrastructure
  • Integration depth
  • ROI realization speed
  • Leadership TQ
  • AI readiness
Layer 03

Societal TQ

How nations, regulatory systems, and public institutions relate to technological change. Sets the ambient environment within which organizations and individuals operate.

  • Regulatory agility
  • Digital infrastructure
  • Talent pipeline
  • Public trust in technology
  • Equity of access
  • Innovation incentives

Technology adoption does not fail randomly.
It fails in five patterns.

After 15 years building AI solutions in the enterprise, the question stopped being "why do some investments work?" It became: why do identical investments produce radically different outcomes? The answer is always one of five bottleneck types.

01 Cognitive 31% most prevalent

Mental models for evaluating and using technology have not kept pace with the speed of change. Not a skill gap — a framework gap. Most acute with AI, where the conceptual distance between marketing and capability is historically large.

02 Cultural 26% frequency

Identity and established norms create friction at the moment of adoption. "We've always done it this way" at the organizational level. "I'm not a tech person" at the individual level. Both are adaptive responses to past environments that become liabilities when environments change faster than cultures.

03 Structural 22% frequency

The physical and organizational architecture of how work gets done prevents adoption regardless of intent. Siloed data ownership, absent integration budgets, and fragmented governance produce structural bottlenecks that kill adoption even when everyone wants it to succeed.

04 Economic 13% frequency

The return on technology investment is too slow, too uncertain, or too invisible to justify the commitment required. Organizations with short planning horizons systematically underinvest in TQ development — not from ignorance but from rational response to how ROI is measured and rewarded.

05 Trust 8% frequency

Insufficient trust in the technology, the vendor, or the institutions governing its use creates a ceiling on adoption depth. The most underappreciated bottleneck — and the most consequential in the AI era, where governance questions remain unsettled across every industry and jurisdiction.

TQ Assessment

Find out where you stand. In four minutes.

The TQ Navigator gives you a scored breakdown across five dimensions and identifies your dominant bottleneck. Free. No account required. Shareable output.

01 Answer 12 questions about how you relate to technology in your work
02 Receive a scored TQ report across five dimensions
03 Identify your primary bottleneck and what it means for you
04 Your data contributes anonymously to the Annual TQ Index
Individual assessment → Org assessment →
TQ Navigator — Question 5 of 12 AI Fluency

"How calibrated is your trust in AI-generated outputs in your domain?"

I either trust everything or nothing — it's hard to know when to rely on it
I verify important outputs but probably over- or under-trust in places
I have a good mental model for where AI is reliable vs unreliable in my domain
I can accurately predict failure modes and confidence levels for tasks I use AI on
Research

Original frameworks.
Original data.
No borrowed thinking.

All research →