Ecosystem & Stakeholder Mapping
AI ecosystem mapping for governments and regions
AI ecosystem mapping, listed on the AI Insider advisory services page as Ecosystem & Stakeholder Mapping, is a structured view of the companies, investors, research institutions, talent and infrastructure in a country or region, and of the stakeholders and connections between them. AI Insider builds the map from the Resonance Intelligence Engine, which reads thousands of sources including company filings, funding and deal records and regulatory dockets, and then tests it with practitioners.
Updated Q4 2026
What an AI ecosystem map shows
The advisory services page describes ecosystem and stakeholder mapping as visualizing the relationships between startups, investors, talent and technology providers. For a public body, five questions follow from it.
Who is here?
AI companies by segment and stage, and the larger firms and research labs that anchor them.
Who funds them?
Investors, funding rounds and public programs, and how much capital reaches each segment.
Who researches and trains?
Universities, labs, patents and talent flows into and out of the region.
Where are the gaps?
Missing anchor institutions, capital, infrastructure or demand compared with peer regions.
Who are the stakeholders, and what connects them?
Partnerships, investor networks and supply relationships between startups, investors, talent and technology providers, including connections that are not obvious from the outside.
AI ecosystem development: how a regional AI ecosystem is built
AI ecosystem development is the work of building the research institutions, talent, capital, compute and local demand that let AI companies start, scale and sell in one place. A map shows what exists; the documented programs show what governments add. The Brookings Institution’s Mapping the AI economy (July 16, 2025) scored 195 US metropolitan areas on talent, innovation and adoption, using 14 measures, and concluded that talent clusters are critical in generating self-reinforcing growth. The OECD found in Regional Development Paper 147 that capital regions such as Brussels, Vienna and Oslo had 26 to 32 percent of firms adopting AI in 2024, against 13.5 percent of EU27 enterprises overall.
Six parts, each with an official example
| Part | What it covers | Example from an official source |
|---|---|---|
| Research institutions | Institutes, chairs and university programs | Canada: three institutes (Amii, Mila, Vector), with C$125 million for phase one (2017 to 2022) and C$443.8 million for phase two (2021 to 2031) on the government strategy page. France: EUR 1.5 billion for phase one (2018 to 2022), financing AI institutes, 180 excellence chairs and the Jean Zay supercomputer, per the economy ministry |
| Talent | Training targets, fellowships and specialists | Singapore: aim to more than triple AI practitioners to 15,000, with no baseline given. Saudi Arabia: 10,898 local data and AI specialists against a 2025 target of about 8,000 (November 2025 scorecard) |
| Capital | Public budgets and investment attracted | Singapore: more than S$1 billion over five years (budget commitment). France: more than EUR 109 billion of investments announced during the February 2025 AI Action Summit (announced intentions, no horizon stated) |
| Compute and infrastructure | Supercomputers, data centers and shared access | Canada: C$2 billion over five years from 2024-25. Finland: the LUMI supercomputer, more than 375 petaflops and a EUR 144.5 million budget across 10 countries (EuroHPC, June 2022) |
| Adoption and demand | Local organizations that use AI | OECD: the gap between countries in firm-level AI adoption rose from 14 to 24 percentage points between 2021 and 2024. Singapore lists an Enterprise Compute Initiative of S$150 million |
| Strategy and governance | An owner, targets and a scorecard | Singapore: a National AI Council chaired by the prime minister, established in February 2026. Saudi Arabia: a strategy approved in July 2020 with a published scorecard |
Seven places compared
The table lists the main instrument and the scale as the source states it. Commitments, targets, announced intentions and projections are marked.
| Place | Anchor | Main instruments | Scale and status as stated |
|---|---|---|---|
| Canada | Three national AI institutes (Amii, Mila, Vector) | Pan-Canadian AI Strategy; Sovereign AI Compute Strategy | C$125M (2017 to 2022); C$443.8M (2021 to 2031) plus C$174M; C$2B over five years for compute (commitments, with “up to” amounts) |
| Singapore | Smart Nation program | National AI Strategy 2.0; Budget 2024 package; National AI Council (2026) | More than S$1B over five years (commitment); 15,000 practitioners (target) |
| France | Interdisciplinary AI institutes and chairs | National strategy within France 2030; Jean Zay supercomputer | EUR 1.5B (2018 to 2022) and EUR 1B (2021 to 2025) in public funding; EUR 109B of investment announced at the 2025 summit |
| Finland | Aalto, Helsinki, VTT through FCAI | Research flagship; shared LUMI supercomputer | LUMI: more than 375 petaflops, EUR 144.5M budget, 10 countries (2022) |
| United Kingdom | Public compute and growth zones | AI Opportunities Action Plan; AI Growth Zones | 20 times compute by 2030 (recommendation); 3,450 jobs in North Wales (projection, incl. temporary) |
| Saudi Arabia | National data and AI authority | National Strategy for Data and AI (2020) with a published scorecard | 10,898 specialists against a target of about 8,000; 221 startups against about 100 (2025 scorecard) |
| United States | Federal research agencies | NSF National AI Research Resource pilot | 600+ research projects and 6,000 students supported, with 13 federal and 28 nongovernmental partners (pilot, reported by NSF) |
Where programs stall
- Announced is not spent. France’s EUR 109 billion is described as announced during the summit, and the page does not state how much is committed.
- Projections include temporary work. The North Wales job figure covers temporary and construction roles.
- Compute without adoption. The OECD finds adoption concentrated in capital and high-innovation regions, so capacity alone does not spread use.
- Targets without a baseline. Singapore’s practitioner target has no stated baseline in the speech that announced it, so progress cannot be read from it.
- Strategies age. Saudi Arabia’s 2020 strategy is being refreshed and Singapore updated its strategy in 2026.
Who commissions AI ecosystem mapping
Economic development agencies
Regional and city agencies deciding where public money builds the most AI activity.
Ministries and national agencies
Departments that need a country-level baseline before writing or refreshing a strategy.
Universities, investors and industry bodies
Organizations planning an AI cluster, a fund or a program with public partners.
What you receive
The final structure is agreed when the work is scoped. An ecosystem mapping engagement typically builds these pieces.
| Deliverable | What it answers | Built from |
|---|---|---|
| Ecosystem map | Which companies, investors, institutions and talent pools exist and how they connect | Resonance Intelligence Engine |
| Segment and funding profile | Where the activity and capital sit, by segment and stage | Company and funding data |
| Research and talent view | How strong the research base and talent pipeline are | Patents, publications, talent flows |
| Gap analysis | What is missing against peer regions | Map, peer data, expert input |
| Program options | Which interventions could close the gaps and in what order | Gap analysis, peer practice |
| Data cuts and dashboards | The underlying data for your own team to explore | Custom data cuts |
How an engagement runs
Engagements follow the arc of the Resonance Intelligence Engine described on the AI Insider intelligence page: collect, structure, apply expert judgment, deliver.
Define the boundary
We agree what counts as the ecosystem, including the geography, the segments and the peer regions to compare.
Build the map from the intelligence engine
Data on companies, funding, patents and talent is collected, resolved to single entities and linked into a relationship map.
Expert input
We test the map and the gaps with AI practitioners, researchers and local stakeholders through interviews and workshops.
Decision-ready delivery
You receive the map, gap analysis and program options as a report, with data cuts and a briefing for leadership.
Ways to engage
Strategic workshop
Intensive sessions with your leadership team to test a position against live competitive data and ecosystem maps.
Project engagement
Defined-scope advisory projects of 4 to 12 weeks with clear deliverables, as described on the advisory services page.
Retainer advisory
Ongoing counsel with dedicated analyst support, including regular intelligence briefings.
Enterprise partnership
Advisory integrated into a large organization, with embedded analysts and access to senior advisers.
Published work on this topic
AI Insider publishes ecosystem material from the same data the advisory team uses: country strategy analyses, country scale-up lists and the Intelligence Platform on AI infrastructure and regulation.
10 Switzerland-Based AI Scale-Ups
A country-level view of the AI companies to watch in 2026.
Read the reportAI Insider Intelligence Platform
Infrastructure funding, capacity and regulatory intelligence, with every record linked to its source.
See the platformRelated government work from the Resonance network
These engagements are in quantum, not AI. They are published on The Quantum Insider consulting page, a sister platform in the Resonance network, and show the kind of government work the advisory method has been used for. Each is an ecosystem study or assessment.
Chattanooga Quantum Collaborative
Ecosystem and feasibility study supporting the Chattanooga quantum program.
North Carolina
Quantum ecosystem study assessing and strengthening the state’s position as a US quantum ecosystem.
MassTech (Massachusetts)
Updated quantum ecosystem assessment for the Innovation Institute at the MassTech Collaborative.
AI ecosystem mapping, answered
What is AI ecosystem mapping?
It is a structured view of the AI companies, investors, research institutions, talent and infrastructure in a country or region, and of the connections between them. Governments use it to see where the strengths and gaps are before they fund programs.
Who provides AI ecosystem mapping for public sector programs?
AI Insider provides it through its advisory team, using the Resonance Intelligence Engine. Public bodies also commission ecosystem work from management consultancies, university research centers and regional development consultancies. Ask any provider where its company and funding data comes from and how current it is.
What data goes into an AI ecosystem map?
Funding rounds, company records, patents, regulatory filings, job postings and news, resolved to single entities and linked to investors, institutions and talent flows. Expert interviews add what the data cannot show.
How is an ecosystem map different from a directory of AI companies?
A directory lists companies. A map also shows who funds them, who trains their talent, which institutions anchor them and where the connections are missing, and compares all of it with peer regions.
What do governments do with an ecosystem map?
They decide where to invest, which gaps to close first and which programs to design. The AI ecosystem development section gives official examples of programs for each part of an ecosystem.
What is AI ecosystem development?
It is the work of building the research institutions, talent, capital, compute and local demand that let AI firms start, scale and sell in one place, plus the organizations that adopt AI. The OECD and Brookings both treat talent, innovation and adoption as the core dimensions.
How do governments build a regional AI ecosystem?
The documented cases combine research funding, training targets, compute programs, adoption support and a coordinating strategy. Canada, Singapore and France each paired funding for people with funding for compute. A map of the assets comes first, so targets rest on a baseline.
How much do governments spend on AI ecosystem development?
Documented commitments include C$443.8 million for Canada’s second phase, more than S$1 billion over five years in Singapore and EUR 1.5 billion for France’s first phase. The scopes differ, so the amounts are not benchmarks for each other.
How long does an AI ecosystem mapping engagement take?
The advisory page describes defined-scope projects of 4 to 12 weeks, with ecosystem mapping named among them. The size of the region, the number of segments and the stakeholder consultation decide where an engagement falls, and the team confirms it when scoping.
Sources
- AI Insider, AI Advisory Services. Service areas, engagement models, 4 to 12 week project length and team description and the ecosystem and stakeholder mapping service area. As of Q4 2026.
- AI Insider, AI Market Intelligence & Data. The Resonance Intelligence Engine and its four steps. As of Q4 2026.
- The Quantum Insider, Quantum Computing Consulting & Advisory Services. Published engagements. As of Q4 2026.
- AI Insider, Singapore’s NAIS 2.0: How a City-State Builds an AI Hub, July 27, 2026.
- AI Insider, 10 Switzerland-Based AI Scale-Ups You Need to Know in 2026, September 24, 2026.
- Mapping the AI economy: which regions are ready for the next technology leap, Mark Muro and Shriya Methkupally, Brookings Institution, July 16, 2025.
- AI Index Report 2026, Chapter 4: Economy, Stanford Institute for Human-Centered AI, 2026.
- Emerging divides in the transition to artificial intelligence, OECD Regional Development Papers No. 147, Kergroach and Héritier, 2025. Working paper; not the official views of the OECD.
- Pan-Canadian Artificial Intelligence Strategy, Innovation, Science and Economic Development Canada.
- AI at CIFAR, CIFAR.
- Canadian Sovereign AI Compute Strategy, Innovation, Science and Economic Development Canada, page modified June 4, 2026.
- Stratégie nationale pour l’intelligence artificielle, Direction générale des Entreprises, September 2024, updated February 2025 (in French).
- Make France an AI powerhouse, Élysée, February 11, 2025.
- About FCAI, Finnish Center for Artificial Intelligence.
- Inauguration of LUMI, EuroHPC Joint Undertaking, June 13, 2022.
- Speech at the launch of the National AI Strategy 2.0, Ministry of Digital Development and Information, Singapore, December 4, 2023.
- AI initiatives launched to uplift Singapore’s economic potential, Ministry of Digital Development and Information, March 1, 2024.
- Update to Singapore’s National AI Strategy: refreshed priorities factsheet, Ministry of Digital Development and Information, May 20, 2026.
- National AI Strategy, Smart Nation Singapore.
- National Strategy for Data and AI, Saudi Data and AI Authority.
- National Strategy for Data and AI scorecard, Saudi Data and AI Authority, November 2025.
- AI Opportunities Action Plan, Department for Science, Innovation and Technology, January 13, 2025.
- AI Growth Zones, GOV.UK collection.
- AI Growth Zones to create thousands of jobs: new site confirmed for North Wales, GOV.UK, November 13, 2025.
- National AI Research Resource, National Science Foundation, page updated October 6, 2026.
Get started
Talk to the AI Insider advisory team
Tell us the region and the decision the map should support. The team will respond with how we can help and what the right engagement looks like.
The form is taking longer than usual to load. An ad or content blocker can stop it, so try turning it off for this site, or use this contact page instead
Protected by reCAPTCHA. The Google Privacy Policy and Terms of Service apply.