Economics and value: questions about AI

AnsweredHow long should we give an AI investment before deciding whether it worked?#

Answered 2 September 2026. Three questions are hiding inside this one and they run on three clocks. The J-curve supplies the reason an early read is biased downwards and a late one upwards, the Danish nulls supply the timing, and the page sets out a staged review with the baseline recorded before deployment rather than reconstructed after it.

AnsweredWhich AI investments should we stop?#

Answered through the escalation literature rather than through AI research, because there is no credible non-vendor base rate for AI programme failure and the page says so: the 80 per cent figure traces to a press article. What can be established is that between 30 and 40 per cent of information systems projects escalate, that the founding case study of that literature was itself an expert system, and that de-escalation has a four-phase shape whose second phase organisations skip. Three questions that do not require a counterfactual.

AnsweredIf every competitor has access to the same AI, where does our advantage come from?#

Answered 2 September 2026, and the premise turns out to be false before the argument even starts: US Census diffusion data puts firm use at 18 per cent with 57 per cent of adopters in three or fewer functions. The page runs a licence through Barney's four tests, where it passes one, and locates the durable positions in the intangible complements instead.

AnsweredWhat becomes more valuable in our business as AI becomes cheaper?#

Answered 3 September 2026 with the specific version rather than the textbook one. Three randomised trials, in customer support, professional writing and software, independently found the tool raising the floor far more than the ceiling, so the capability depreciating fastest is being unusually good at the work the model does well. Autor and Thompson decide the direction for a whole role: automation that removes the expert tasks lowers wages, and removing the less expert ones raises them.

AnsweredIf AI saves 20 per cent of someone's time, what should happen to that 20 per cent?#

Answered 26 September 2026. Two studies that actually tracked the destination, one Danish and one an eight-month US ethnography, found it reorganised into new oversight work or absorbed into a longer day, never banked and never a deliberate decision.

AnsweredWhat is digital labour?#

Digital labour has two senses. The older, academic one names the work, much of it unpaid or underpaid, that sustains the digital economy: content moderation, platform microwork, data labelling, and the ordinary use of social media that p...

AnsweredWho captures the productivity gains from AI?#

The distributional question, and almost nobody in this field asks it.

PartialWhere is AI actually creating economic value in our organisation?#

Partly answered, and the answered half is the uncomfortable one. Licences issued, hours saved and adoption rates measure procurement. Value requires a counterfactual, and almost nobody constructs one; the stopping page turns that into a usable test by sorting evidence of benefit into measured by a disinterested party, self-reported, and vendor-supplied, and treating an empty first pile after a year as the finding. Where the value actually sits in a particular business remains open, because it is a question about that business.

PartialWhat return should we expect from our AI investment?#

Partly answered, and deliberately not more than partly. The investment-horizon page gives the scale of the macro estimates and the reason the fast figures cannot carry weight, and it refuses a benchmark return because no dataset of AI programmes with a credible counterfactual exists in public. Firm-level returns could still be large where the macro number is small.

PartialWhere will AI change our competitive advantage?#

Partly answered. The advantage page gives the test for separating a cost floor from a position, and the evidence that identical tools produce non-identical results. Where inside a particular business model the advantage moves is sector-specific and this research holds no sector-level evidence on it, so the general logic is all that is offered.

PartialWhich parts of our business model does AI make obsolete?#

Partly. The test is now stated: revenue that prices a gap between your people and the market is exposed to compression, and revenue that prices accountability for a result is not. What remains open is the transition, since no firm has published what it did when it repriced, and the ones that have repriced have reasons not to.

PartialAre we using AI to reduce costs or to create new growth?#

Partly answered. The research argues the augmentation-or-replacement position must be declared by domain and in writing, and that the business cases reveal the real answer whatever the paper says. What is not answered is the sequencing: whether cost-first organisations can later become growth-first, or whether the first choice sets the culture.

PartialWhat should we do with the productivity gains from AI?#

Partly answered, and deliberately listed twice. The Career territory asks who captures the gains, which is a question about power. This asks what a leader should do with them, which is a decision. Reinvest, return to shareholders, reduce headcount, reduce hours, or fund the development time that AI removed from junior work.

PartialHow much smaller should our organisation become because of AI?#

Partly answered, and the answer is not the expected one. Three independent measurements find no general headcount effect yet. An organisation cutting today on the strength of AI is acting ahead of every measurement available, which may still be right, but is a bet rather than a deduction.

PartialWhat should our organisation look like in three years if AI keeps improving?#

Partly answered on shape. The pyramid becoming an inverted triangle or a diamond with little arriving at the bottom is the pattern in the field observation. What is not answered is the rate, because that depends on capability improvements nobody can forecast plainly.

PartialWhat happens if our biggest AI provider becomes unavailable?#

Partly answered. The research covers what happens when a vendor changes the model underneath a workflow. Outright unavailability is the sharper case, and the honest continuity answer depends on whether anybody can still do the work, which is a capability question rather than a procurement one.

PartialAre we becoming strategically dependent on one AI company?#

Partly answered as a capability question rather than a commercial one. Concentration risk is familiar to any board; what is new is that the dependency can be on a capability the organisation used to have, which no supplier register records.

PartialWhat capability are we transferring to our AI vendors without deciding to?#

Partly answered. This is capability debt with a counterparty. The transfer is rarely a decision and never a line item. Organisations find out at the end of the contract.

PartialWhat is tokenomics?#

Tokenomics is the economics of token cost, and specifically its fall. As the price per token drops, tasks not worth handing to a machine become worth handing over, so the boundary of what is automated moves without anyone deciding to mov...

PartialHas AI cut pay or working hours yet?#

Not measurably in Denmark to December 2024. Humlum and Vestergaard, writing at Brookings on 6 October 2026, report precise null effects of AI chatbots on earnings and hours for users and for adopting workplaces, ruling out average effects above 2 per cent. It is early evidence from one country. The page holds who receives the gains when there are some.

OpenHow much should we be investing in AI?#

Open, and unanswerable as posed. There is no defensible benchmark: the peer-spending figures in circulation are self-reported, definitionally inconsistent about what counts as AI spend, and published by people selling AI. A board asking this is usually asking a different question, which is whether it is behind.

OpenCould a competitor with far fewer people outperform us?#

Open, and the version of the threat that boards underrate because it does not appear in competitor headcount or revenue until late. A smaller organisation carries less legacy process and can make the augmentation-or-replacement call without a committee.

OpenWhat would we build differently if we were starting this company today with AI?#

Open, and useful precisely because it cannot be acted on directly. It surfaces which parts of the current shape are deliberate and which are inherited. The gap between the answer and the present organisation is the agenda.

OpenWhat are we doing today that we should stop doing because AI exists?#

Open, and rarer than it should be. Almost all AI effort is additive, layering tools onto existing processes. The subtractive question, which reports and reviews existed only because producing them was hard, is barely asked.