A real agent, or RPA in a new coat
A forecast reorganised the year: more than 40% of agentic projects will be cancelled by the end of 2027 — for runaway cost, diffuse value, or inadequate risk control — and the aggravating factor has a name, "agent washing", rebranding an assistant, a chatbot or an RPA bot as an "agent" with no real autonomy. For the board, what separates the project that survives from the write-off isn't the demo — it's measurable autonomy, ROI attributed per flow, and risk control proportional to blast radius. The autonomy test that breaks the happy path on purpose, ROI per flow as the continuity gate, controls sized to what the agent can touch, the total cost that includes the reasoning loop, the four ways a board ends up in the 40%, and why the document desk is the cleanest place to run the test.
13 minBuild the moat, partner for the plumbing
One figure from the last year cut through a lot of internal pride: programs run with a specialised partner reach production at roughly twice the rate of those built purely in-house — about two thirds versus one third. The naïve reading is "outsource it", and that's wrong; so is "we build everything". The build-vs-partner call decided layer by layer — rent the model, partner for orchestration and evaluation, own the domain data and the corrected flow — the portability clause that keeps a head-start from becoming lock-in, who should own the customer's correction, the four ways a partner program quietly fails, the honest trade-off between speed now and margin later, and why the board metric that predicts who ships isn't ML headcount.
13 minThe gap isn't the model. It's the instrumentation
Roughly 95% of GenAI pilots deliver no measurable P&L impact, almost everyone has a pilot and almost nobody has a fleet in production. The cause isn't model quality and it isn't regulation — it's the three layers underneath the technology that never got built: measurement that proves the task works, integration that wires it into the flow that creates value, and ownership that keeps the system learning after go-live. The three layers in detail, the build-vs-partner signal that roughly doubles the production rate, the four ways the evaluation layer quietly rots, the honest trade-off of instrumenting before you see a number, and why "which model" is the wrong opening question.
13 minTemplates or zero-shot, decided by the tail
Two honest ways to get fields out of a document, and most of the noise comes from pretending one has to lose. Template-based extraction is deterministic, fast and near-free per page — and breaks the instant a layout drifts. Zero-shot absorbs the long tail of formats you'll never template, at a per-call cost and with quiet, plausible failures. The eight dimensions a buyer actually weighs, where each genuinely wins, the hybrid that ships — route by class and confidence, zero-shot as cold-start and fallback, templates as a cache of what zero-shot learned — and the failure mode that bites each when nobody's watching.
12 minUpskilling at the speed of automation
In 12 months agentic-AI upskilling went from an optional internal program to a board investment — consultancies certifying tens of thousands of professionals in a single deal, banks certifying whole operations functions. The dual thesis (operating agentic AI needs a different skill stack; the firm that certifies at scale first captures the talent supply and builds a switching cost), the certification-as-moat case and exactly where it rots into paper, a competence matrix by role that survives an audit, the four ways an upskilling program quietly fails, and why the document desk is the cleanest place to make the certificate predict the work.
13 minIntelligence per worker, measured honestly
Frontier firms run ~3.5x more intelligence per worker than the median, and in 2026 the metric jumped from HR slide to board agenda — arriving in the same news cycle as the AI-restructuring layoffs. It is a real measurement and an easy euphemism, one keystroke apart. The four components that make it auditable instead of anecdotal — output per FTE-equivalent, delegable-task automation rate, time recovered with a destination, quality with vs without the agent — why measuring only the numerator books six months of gain against a year of cost, and where the document desk measures it honestly first.
13 minWhere the saved hour actually goes: the productivity capture gap
The 2026 research is settled at the desk — an individual saves 5 to 9 hours a week with AI — and unsettled everywhere above it: the hour is real on the timesheet and missing on the P&L. The four exits the saved hour takes before it reaches margin — recovered slack, low-value backfill, a downstream queue that stalls, and a premature headcount cut — why measuring the individual guarantees the leak, the capture architecture that plugs each one, and where the document desk fits.
12 minFrom executor to orchestrator, by design
The real AI gain of 2026 didn't come from a better model — it came from redesigning who does what. The worker moved from task executor to orchestrator of three to five parallel agents, validating output and calibrating thresholds. Why deploy time fell ~70% and underwriting went from 10 weeks to 10 days only after the operating model changed, the new unit of work, a persona-by-persona view of the redesign, and what it means for the document layer.
13 minThe Chief AI Officer the board now audits
In 12 months the CAIO went from trend to standard — surveys put one inside roughly three-quarters of large organisations, up from a quarter a year earlier. The four questions the board now asks every quarter (model utilisation, agent SLO, regulatory exposure, unit cost), where the CAIO line sits against the CTO and the Chief Data Officer, the governance playbook that separates a real mandate from a rebranded innovation title, and what all of it means for the document layer the CAIO is on the hook for.
13 minWhen the deal is the whole network: multi-tenant network deployments
In 2026 the unit of an IDP sale stopped being one company and became a whole network — an anchor that distributes document AI to its 30,000 professionals, its correspondent banks, its brokers, its 80,000 SMB sellers. The per-node isolation architecture, the opt-in cross-node data governance that becomes the differentiator, the anchor revenue split, the four anti-patterns that leak the network and the concentration trade-off the model invites.
13 minFrontier inference at $1.50/$9: the IDP unit-cost reset
Frontier-grade inference reached $1.50 per million input tokens and $9 per million output in May 2026 — and IDP cost per document can fall from $0.18 to $0.04–0.06 without touching quality. The four pricing levers, the router that reacts in hours not sprints, the price-pass-through clause that survives the next cut, and the four anti-patterns that decouple a vendor's unit margin from the market in 90 days.
14 minProvider risk moves to the cap table: AI due diligence in 2026
AI labs hit trillion-dollar scale, the first operationally profitable quarter and IPO prep in 2026 — and enterprise procurement turned provider selection into a cap-table line. The four contract clauses every IT shop is now writing, the eight-row provider risk register, three architectural moves that turn provider risk into a hedge, and the 90-day buyer plan.
13 minCapability contracts for the post-app era
The 2026 device-and-OS shift moved the buyer one layer up: the assistant in the operating system, the notebook and the phone decides which portal to call. The three consequences for SaaS in the next two quarters, the four-artefact capability contract buyers are asking for by name — capability manifest, intent registry, tool catalog with permission scope, per-agent telemetry — and the anti-patterns that quietly retire a portal.
12 minWhen inference owns your margin: compute as the 2026 moat for document AI
Record-breaking AI capital — an US$ 122B round at US$ 852B post-money, US$ 200B+ in committed compute, an OCR floor sliding to US$ 2/1,000 pages. The three decisions a CIO and a CFO have to make now, the five-line cost build-up procurement is asking vendors to show, and the two vendor profiles most likely to get squeezed in the next 12–18 months.
12 minAgent-as-user: the post-app B2B portal
A measurable share of B2B portal sessions in 2026 originate from an assistant acting for a logged-in buyer. Six surfaces an agent actually needs, four moves in the playbook that ships, and the anti-patterns that quietly disqualify a portal.
11 minThe AI ROI gap: what the 29% do differently
Enterprise AI budgets jumped 65% to US$11.6M, but only 29% report meaningful ROI and 42% have abandoned most of their initiatives. Four traits separate programs that pay back from those that quietly stalled.
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