# Civico Ventures

> Civico Ventures is a venture academy for AI leadership. Experiential programmes for business leaders transforming their companies with AI: bring a real problem, solve it with AI as a partner, leave with a decision that holds up. Not a study tour. Not an AI course.

Key facts:
- Promise: "Bring a real problem. Leave with a decision that holds up."
- Who it is for: business leaders transforming their companies with AI. The Venture Residential is for executives on EMBA and executive-education programmes (sold through business schools); the Civico AI Academy is for leadership teams (CEOs, COOs and owner-successors).
- Programme 1: Vietnam Speed (Civico Venture Residential). Vietnam Speed is our Venture Residential in Vietnam. For four days, EMBA and executive cohorts build, test and pitch a real venture or AI initiative in one of Asia's fastest-moving markets. Each run is its own edition: Hanoi in July 2026, Ho Chi Minh City in January 2027. Editions: delivered: Hanoi edition, July 2026 (Sasin Connect+ Executive MBA); now running: Ho Chi Minh City edition, January 2027 (Sasin Connect+ Executive MBA); your cohort: Ho Chi Minh City, dates set with you.
- Programme 2: Civico AI Academy. For CEOs whose AI pilots never reach the P&L, the Civico AI Academy is an eight-week AI transformation programme that takes leaders' own projects to a board-ready case. Each team brings one live AI project, redesigns the work and the decisions around it, and pitches a board-ready case at graduation. A two-day residency in Vietnam starts it; weekly coaching carries it.
- Track record: Hanoi edition, July 2026: about 40 executives in four venture teams. Participants rated the build sessions above the company visits, and scored the week 8.95 out of 10 on whether they would recommend it. Sasin asked us back for the Ho Chi Minh City edition in January 2027.
- What it replaces: A study tour → A venture residential; An AI literacy course → AI as a partner on your own problem; Completion certificates → Judged on decisions that held up; A transformation consultancy → Your programme, run with you.
- Faculty: Jakub Wachocki, Managing Partner · Faculty. Masterclass: The Autonomous Organisation, on how agentic AI redesigns operating models, decision rights and roles; CEO of vitX and Nessoris, technology companies that build and run engineering teams working with AI; Former Global Director, Bentley Systems; MBA, Imperial College Business School.
- Faculty: Alvin Ng, Venture Partner · Faculty. Adjunct Associate Professor, Nanyang Business School (NTU); Visiting faculty at Sasin; programme faculty with Duke Corporate Education and Emeritus; Teaches AI transformation to executive teams at companies including Linde, ASML and PETRONAS; Thirty years as an operator at Cisco, GE Digital, Johnson Controls, Wincor Nixdorf and Aboitiz Data Innovation; ICF Professional Certified Coach.
- Research library: an open, sourced AI library for business leaders, with 494 sourced facts from 371 organisations across 16 themes and 15 frameworks. Every row links to its source; the CSV files are public (see Data).
- Weekly Insight: a short note on what the evidence shows, linking to the rows behind each claim.
- Prices are not published. Programmes are scoped on a call.
- Contact: hello@civicoventures.com, or book a 45-minute call at https://www.civicoventures.com/contact/
- LinkedIn: https://www.linkedin.com/company/civicoventures/

## Pages

- [Home](https://www.civicoventures.com/): what Civico does, the two programmes and the track record
- [Vietnam Speed · Venture Residential](https://www.civicoventures.com/residential/): the four-day venture residential in Vietnam for EMBA and executive-education cohorts: the week, the editions, what the school gets, who does what, and straight answers to common questions
- [Civico AI Academy](https://www.civicoventures.com/academy/): the eight-week AI transformation programme for a leadership team with one live AI project: residency (two days, in Vietnam), weekly coaching (across the eight weeks), graduation pitch (week eight), who it is for and what the team leaves with
- [About](https://www.civicoventures.com/about/): The people who design every programme teach it, and the people you meet on the first call are the people in the room. Civico Ventures runs experiential AI programmes for business leaders transforming their companies: the Venture Residential for executive-education cohorts and the Civico AI Academy, an AI transformation programme for leadership teams.
- [Contact / book a call](https://www.civicoventures.com/contact/): enquiry form and call booking
- [Insights](https://www.civicoventures.com/insights/): the weekly Insight, each linked to the data behind it
- [Start here](https://www.civicoventures.com/insights/start-here/): why the research library exists and how to use it

## Research library

- [Research hub](https://www.civicoventures.com/research/): what leaders should know about AI, as patterns in the evidence, each with its sources; visitors can ask the library their own challenge
- [Use cases](https://www.civicoventures.com/research/use-cases/): named AI deployments, surveys, filings and case studies by industry, function and region, each with its source
- [Funding Map](https://www.civicoventures.com/research/funding/): which AI startups are being funded: company, round, amount, date, investors, workflow, industry and source
- [AI Radar](https://www.civicoventures.com/research/radar/): AI technologies and application layers, scored for maturity and momentum from sourced rounds and use cases
- [Workflow Map](https://www.civicoventures.com/research/workflows/): business workflows and what AI is disrupting in each, with the startups and use cases behind every score
- [Industry heatmap](https://www.civicoventures.com/research/industries/): which industries AI and agents disrupt most, by business function, with the evidence behind each cell
- [Agentic tracker](https://www.civicoventures.com/research/agentic/): what AI agents can reliably do, from dated benchmark results with primary sources
- [AI transformation frameworks](https://www.civicoventures.com/research/frameworks/): the named AI adoption and transformation frameworks, what each says, and what evidence exists that using one reaches the P&L
- [Knowledge graph](https://www.civicoventures.com/research/graph/): how the research connects: themes, frameworks, technologies, industries, workflows, companies and evidence
- [Method](https://www.civicoventures.com/method/): how the library works: sources, tagging, scoring, judgements and limits

## What the evidence says

Patterns in the research library, each with the sourced fact it leads with. Figures come from the cited source, not from Civico.

- Self-reported benefit outruns measured P&L impact: Most firms say AI helps; few measure it against a baseline. Example: Atlanta Fed et al.: over 80% of firms report no AI impact on employment or productivity (Federal Reserve Bank of Atlanta with Bank of England Bundesbank and Stanford (Yotzov Bloom et al.), 2026-03; https://atlantafed.org/research-and-data/publications/working-papers/2026/03/24/03-firm-data-on-ai). 14 sourced rows on this theme.
- The pilot-to-production funnel narrows hard: Evaluation is common; production and scale are rare. Example: Deloitte State of AI 2026: 25% moved 40%+ of experiments to production (Deloitte AI Institute, 2026-01; https://www.deloitte.com/content/dam/assets-shared/docs/about/2025/state-of-ai-2026-global.pdf). 10 sourced rows on this theme.
- Winners redesign the work; they do not just add a tool: High performers are more likely to have redesigned workflows and jobs; most firms have not. Example: Deloitte 2026: skills are top barrier; 84% have not redesigned jobs (Deloitte AI Institute, 2026-01; https://www.deloitte.com/content/dam/assets-shared/docs/about/2025/state-of-ai-2026-global.pdf). 8 sourced rows on this theme.
- Skills and training are the binding constraint: Skills are the top cited barrier, executives themselves use AI little, and where employers pair tools with training use rises sharply. Example: Vietnam skills gap constrains AI scale-up (AWS / Strand Partners (Vietnam), 2026-10; https://vietnamnews.vn/economy/1801071/viet-nam-turns-ai-ambitions-into-business-impact.html). 8 sourced rows on this theme.
- Time saved is not money saved: Controlled trials and government pilots show real but modest time savings, mostly self-reported, and an experienced-developer trial found a slowdown. Example: Stanford AI Index 2026: studies report productivity gains of 14-15% in support and 26% in software (Stanford HAI (AI Index Report 2026), 2026-04; https://hai.stanford.edu/assets/files/ai_index_report_2026_chapter_4_economy.pdf). 7 sourced rows on this theme.
- Headcount cuts attributed to AI are being reversed: Klarna, Commonwealth Bank and employer surveys show firms rehiring after AI-attributed cuts, and Gartner expects half of such firms to rehire by 2027. Example: Careerminds survey: 35.6% of employers rehired over half of roles cut for AI (Careerminds, 2026-02; https://careerminds.com/blog/cost-of-ai-layoffs). 7 sourced rows on this theme.
- Small and founder-led firms adopt later and see less: Adoption rises with firm size in the US, UK and OECD data; micro firms start high but grow slowly, and most small-firm users report no revenue change. Example: UK DSIT AI adoption research: 16% of businesses use AI, micro 14% vs large 36% (UK DSIT and DBT (IFF Research and Technopolis), 2026-01; https://gov.uk/government/publications/ai-adoption-research/ai-adoption-research/). 6 sourced rows on this theme.
- Agents can do more than firms have deployed: Benchmark task success has risen sharply while enterprise deployment of agents stays in single digits by function, and governance and data readiness lag. Example: Deloitte 2026: only 21% have mature governance for autonomous agents (Deloitte AI Institute, 2026-01; https://www.deloitte.com/content/dam/assets-shared/docs/about/2025/state-of-ai-2026-global.pdf). 6 sourced rows on this theme.
- Southeast Asia: adoption is rising faster than ROI measurement: In Vietnam and ASEAN, adoption and self-reported gains are high, but most adopters are still experimenting and few have a consistent ROI framework. Example: Vietnam AI adopters: 13% have a consistent ROI framework, 46% cannot measure returns (AWS / Strand Partners (Vietnam), 2026-10; https://vietnamnews.vn/economy/1801071/viet-nam-turns-ai-ambitions-into-business-impact.html). 8 sourced rows on this theme.
- Governance and liability catch up with deployment: Courts, regulators and insurers are now acting on AI use: fake citations, chatbot liability, insurer exclusions and board oversight lag. Example: Deloitte Australia partially refunds A$440,000 government report with AI-fabricated citations (Deloitte Australia / Department of Employment and Workplace Relations, 2025-10; https://babl.ai/deloitte-to-refund-part-of-290000-government-contract-after-ai-errors-found-in-report/). 7 sourced rows on this theme.
- Cheaper tokens, bigger bills: Price per unit of capability keeps falling while enterprise AI budgets overrun and software and services pricing is repriced. Example: IDC: 61% of organisations exceeded their cloud AI budget (IDC (Smith and Villars blog), 2026-08; https://www.idc.com/?p=119289). 2 sourced rows on this theme.
- IT services and outsourcing are repricing: IT services, BPO and contact-centre firms report revenue pressure and repricing attributed to AI, while some regional players report growth in AI work. Example: Accenture FY26: revenue $74.2B, bookings $84.5B, 814,000 people (Accenture, 2026-10; https://www.sec.gov/Archives/edgar/data/0001467373/000146737326000037/q4fy26earnings8-kexhibit.htm). 13 sourced rows on this theme.
- Healthcare: modest measured gains, large claims: Measured clinical-documentation savings are small and financial payoff is unproven, while vendor and payer claims are large and regulators and recall data show real risk. Example: JAMA Network Open quality study: scribe use cuts burnout from 51.9% to 38.8% in 30 days (Six US health systems, JAMA Network Open (Olson et al.), 2025-10; https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2839542). 6 sourced rows on this theme.
- Manufacturing: measured value lags, early adopters can lose productivity first: Plant-level data show a productivity J-curve for early AI adopters, and most manufacturers report value without scaling it across sites. Example: Rockwell survey: 34% of manufacturing operations AI-augmented, only 18% still in pilot (Rockwell Automation / Sapio Research (2026 State of Smart Manufacturing), 2026-05; https://www.rockwellautomation.com/en-be/company/news/press-releases/90-of-Manufacturers-Say-Digital-Transformation-Is-Now-Essential-According-to-New-Global-Study.html). 6 sourced rows on this theme.
- Evidence on training leaders in AI is thin: No AI executive programme has independently measured P&L outcomes. Example: AACSB: 65% of business schools bolt AI modules onto existing courses; 18% build non-degree AI programmes (AACSB International, 2025-02; https://www.aacsb.edu/insights/reports/2025/genai-adoption-in-business-schools-deans-and-faculty-respond). 9 sourced rows on this theme.
- Regulators are putting AI on named executives and boards: Financial regulators and lawmakers now expect a named senior manager or the board to answer for AI use: UK MPs want FCA guidance on senior-manager accountability for AI, and Singapore's AI risk guidelines make boards oversee AI risk from October 2027. Example: MAS finalises AI risk management guidelines: boards must oversee AI risk from October 2027 (Monetary Authority of Singapore (reported by Blockhead), 2026-10; https://www.blockhead.co/2026/10/08/mas-finalises-ai-risk-rules-for-financial-institutions-with-agentic-ai-guidance-to-follow-in-2027/). 4 sourced rows on this theme.

## Insights (latest first)

- [Banks are starting to put AI on the P&L. Few name the line.](https://www.civicoventures.com/insights/2026-10-17-few-firms-name-the-line/) (2026-10-17): In this month's results, Citi named the costs AI moved while several peers gave no figure. What the few with a number do differently, and who answers for it.
- [AI is in the survey. It is not yet in the P&L.](https://www.civicoventures.com/insights/2026-10-14-ai-in-the-survey-not-in-the-pnl/) (2026-10-14): Most firms now use AI and most say it helps. Far fewer can show it in a revenue or cost line, and the gap is a measurement problem before it is a technology problem.

## Data

Open CSV files behind the research library, rebuilt with the site. Every evidence row carries a source_url.

- [ai-agentic-results.csv](https://www.civicoventures.com/data/ai-agentic-results.csv): dated benchmark results (benchmark, model, date, score, source_url) (42 rows)
- [ai-benchmarks.csv](https://www.civicoventures.com/data/ai-benchmarks.csv): agentic benchmark series tracked (5 rows)
- [ai-frameworks.csv](https://www.civicoventures.com/data/ai-frameworks.csv): AI adoption and transformation frameworks, with the evidence basis and limits of each (15 rows)
- [ai-funding.csv](https://www.civicoventures.com/data/ai-funding.csv): AI funding rounds (company, round, amount in USD millions, date, investors, country, workflow, industry, source_url) (16 rows)
- [ai-industries.csv](https://www.civicoventures.com/data/ai-industries.csv): the fixed list of industries (14 rows)
- [ai-tech.csv](https://www.civicoventures.com/data/ai-tech.csv): AI technologies and application layers with maturity, horizon and the reason for each judgement (23 rows)
- [ai-usecases.csv](https://www.civicoventures.com/data/ai-usecases.csv): named deployments, surveys, filings and case studies (industry, workflow, metric, summary, source_url) (503 rows)
- [ai-workflows.csv](https://www.civicoventures.com/data/ai-workflows.csv): the fixed list of business workflows, grouped by function (36 rows)
- [graph-concepts.csv](https://www.civicoventures.com/data/graph-concepts.csv): research themes and the evidence rows that support each (16 rows)
- [graph-edges.csv](https://www.civicoventures.com/data/graph-edges.csv): knowledge-graph links between nodes, with the basis for each link (1771 rows)
- [graph-nodes.csv](https://www.civicoventures.com/data/graph-nodes.csv): knowledge-graph nodes (themes, frameworks, technologies, industries, workflows, companies, evidence) (607 rows)

## Questions the library is researching next

- Where do AI pilots stall before they reach the P&L? Why so many pilots stall between demo and budget, and what the ones that cross have in common.
- Which functions are adopting agents first, and how deep? Which functions are putting agents into daily work first, and how far they have gone.
- How does AI capital spending compare with AI revenue? How much of today's AI market is paid for by customers rather than investors.
- What is shifting in workforce and skills? Which roles, tasks and skills change first, and what employers say they will pay for.
- How do AI rules differ by region? How rules on AI, data and procurement differ across Asia, the US and Europe.
- Where does Asian AI funding differ from the US and EU? Which workflows and industries attract capital in Asia, and who funds them.
- Which evals should leaders ask vendors for? A short list of tests and evidence a leadership team can ask for before funding a project.
- What do board-ready AI decisions look like in practice? Projects that were funded, parked or stopped, and the evidence that decided each.
- Which AI startups are replacing software seats with finished work? Whether AI-native products are priced and bought differently from software seats.
- How reliable are agents on long tasks? Where agents stay reliable on long tasks, and where they still break.

## Optional

- [Full text for AI assistants](https://www.civicoventures.com/llms-full.txt): programme details, FAQs, the principles and the full text of every Insight
- [Sitemap](https://www.civicoventures.com/sitemap.xml)
- [Civico Ventures on LinkedIn](https://www.linkedin.com/company/civicoventures/)
- [Privacy](https://www.civicoventures.com/privacy/)