What the NGen AI4M Challenge Funds: Eligible Costs, Rates, and Examples
The NGen — AI For Manufacturing Challenge (AI4M) provides non-repayable funding to collaborative, business-led projects that commercialize artificial intelligence and machine learning in Canadian manufacturing. This guide explains what AI4M can fund: eligible expenses, excluded costs, funding percentages, documentation, examples, and how claims are reimbursed.
As part of the Pan‑Canadian AI Strategy, AI4M supports advanced manufacturing projects that integrate AI/ML technologies to build capability across Canada. According to current program guidance (as of December 3, 2025), total project costs should be between $1.5M and $8M, with eligible costs reimbursed at 40%. Projects must be collaborative and include at least two industry partners: one manufacturing company and one AI company, with at least one SME in the consortium.
Program Funding Overview
AI4M is a contribution program administered by Next Generation Manufacturing Canada (NGen), Canada’s Global Innovation Cluster for Advanced Manufacturing. It funds the commercialization of AI/ML solutions in manufacturing, such as systems optimization, robotics and automation, rapid prototyping, and testing of materials, products, and processes.
Key features:
Funding model: non‑repayable contribution (reimbursement of eligible costs)
Coverage: up to 40% of total eligible project costs
Project size: total costs typically between $1.5M and $8M
Structure: industry‑led, collaborative consortiums
Scope: commercial adoption and deployment of AI/ML in manufacturing environments
AI4M focuses on practical deployment and scale-up of AI/ML in real manufacturing settings across sectors such as automotive, aerospace, food and beverage processing, metals, electronics, chemicals, plastics, machinery, medical devices, and more.
Funding Amounts & Rates
AI4M uses a cost-sharing model. NGen reimburses a portion of eligible expenses incurred by approved partners.
What to expect:
Funding percentage: 40% of eligible project costs reimbursed by NGen
Co-investment: at least 60% of eligible costs contributed by project partners (cash and, where applicable, approved in‑kind)
Claims-based: funding flows after eligible costs are incurred and claimed
Category rules: certain cost categories may include caps, rate limits, or special documentation requirements under NGen’s budgeting eligibility guidance
Partner eligibility: each funded partner must incur eligible costs directly related to approved work packages and milestones
Important notes:
The 40% rate applies to eligible costs only; non‑eligible costs cannot be claimed and must be covered by partners.
Consortium members should align budgets to approved work packages and milestones with clear labour, materials, services, and equipment usage allocations.
All other government funding must be disclosed and counted against stacking limits set by NGen; double‑claiming the same expense across programs is not permitted.
Eligible Expenses
Below is a comprehensive list of cost types that are typically eligible under AI4M when they are reasonable, directly related to the approved project, and supported by documentation. Specific caps and conditions may apply. Always align budgets with NGen’s budgeting guidance and the approved statement of work.
1) Wages and Salaries
Project personnel salaries and wages directly performing project tasks (engineering, data science, software development, manufacturing process specialists, quality, and validation).
Employer costs proportionate to eligible wages (e.g., statutory benefits).
Timesheets with task‑level coding are commonly required.
2) Contractors and Subcontractors
Fees for specialized services required for project execution (e.g., AI/ML consulting, robotics integrators, safety certification, specialized testing labs).
Statements of work must specify deliverables, rates, and timelines.
Competitive procurement is recommended for larger subcontracts.
3) Equipment and Specialized Infrastructure (Usage-Based)
Short‑term rental, lease, or usage of specialized manufacturing or AI testing equipment required for the project.
Depreciation or usage charges for project‑specific equipment time in line with NGen rules.
Commissioning or integration costs necessary to deploy equipment into the project environment.
Note: General‑purpose capital purchases for ongoing operations are typically ineligible; usage or depreciation related to the project is more common.
4) Materials, Components, and Consumables
Raw materials, components, test coupons, consumables, and prototyping supplies used in experiments, pilots, and demonstrations.
Scrap and rework materials directly tied to approved work packages.
5) Software, Licensing, and Tooling
Project‑specific software licenses (AI/ML frameworks, MLOps, computer vision, simulation, digital twin platforms).
Seat licenses or enterprise modules where the cost attributable to the project can be clearly allocated.
Temporary licenses or incremental modules tied to project milestones.
6) Data Acquisition and Preparation
Procurement or access fees for training datasets, sensor packages, industrial data feeds, or metrology datasets.
Data cleaning, annotation, labeling, and augmentation services required to train or validate models.
Secure data storage and transfer associated with the project.
7) Cloud Computing and Digital Infrastructure
Cloud compute and storage required for training, inference, simulation, and data pipelines during the project.
Container orchestration, monitoring, and logging services necessary for the project’s AI workloads.
Costs must be metered, attributable, and project‑bounded.
8) Integration, Deployment, Pilots, and Demonstrations
Systems integration, commissioning, configuration, and validation in manufacturing environments.
Pilot lines, limited‑scale production runs, or multi‑site demonstrations to prove performance and scalability.
Site preparation work that is minor and directly tied to project deployment.
9) Training and Upskilling
Training needed for operating AI‑enabled manufacturing systems, safety protocols, and SOP updates.
Train‑the‑trainer models to build internal capability for sustainable adoption.
10) Cybersecurity, Compliance, and Safety
Cybersecurity measures directly required to deploy AI systems in production (access controls, secure networking for OT/IT convergence, monitoring).
Compliance testing and certification (e.g., machinery safety, data privacy compliance) tied to project deployment.
11) Intellectual Property (IP) and Legal (Project-Limited)
Legal services directly related to project IP strategy, project‑bound freedom‑to‑operate assessments, consortium IP tables, and data‑sharing agreements.
Registration fees and limited drafting related to project outputs, subject to program limits.
12) Project Management and Reporting
Project management time and tools directly tied to executing and reporting on approved work packages, milestones, and deliverables.
Preparation of claims, technical reports, and results dissemination required by NGen.
Note: Indirect or overhead costs may be limited or only partially eligible. Follow NGen’s budgeting eligibility guidance for definitions, caps, and allocation methods.
Ineligible Expenses
The following costs are commonly ineligible. When in doubt, budget conservatively and confirm against NGen’s guidance.
General corporate overhead not directly linked to project tasks (e.g., rent, utilities, office supplies, routine IT).
Sales, marketing, and business development activities (trade shows, advertising, lead generation).
Stand‑alone research without a clear commercialization pathway in manufacturing.
Land and building purchases; major capital expansion unrelated to the project; facility renovations for general use.
Routine production costs, regular maintenance, and normal operating expenses unrelated to the project.
Entertainment, hospitality, gifts, and lobbying.
Fines, penalties, interest charges, debt service, exchange losses.
Employee bonuses not tied to project deliverables and unsupported by timesheets.
Patent portfolios and legal costs not directly linked to project outputs and IP strategy for this project.
Travel for sales or unrelated business purposes; luxury travel arrangements.
Contingency allowances and unsubstantiated reserves.
Costs already reimbursed by another program or double‑claimed for the same expense period.
Expense Documentation Requirements
Strong documentation is essential for reimbursement and audit readiness:
Timesheets and payroll records: show employee name, role, hours by task/work package, hourly cost, and approvals.
Invoices and contracts: detail scope of work, deliverables, rates, and dates; include proof of vendor selection where required.
Proof of payment: bank statements, cancelled cheques, or payment confirmations matching invoice amounts and dates.
Equipment usage logs: utilization records or depreciation schedules showing project‑specific usage and allocation method.
Materials and consumables: itemized invoices, receiving records, and evidence of consumption within project tasks.
Software and cloud: license agreements, usage meters, billing statements with project tagging or cost‑centre allocation.
Data acquisition: purchase records, licensing terms, and data provenance documentation.
Travel: itineraries, receipts, per‑diem calculations aligned with eligible limits and project activities.
IP/legal: statements of work, time logs, and deliverables tied to project IP/data governance.
Reporting: milestone reports, technical deliverables, and outcome evidence required by NGen.
Keep records organized and retained for post‑project audits for the period specified by program rules. Establish internal controls before costs are incurred to ensure traceability.
Examples of Funded Projects
These illustrative examples show how AI4M‑aligned projects can map eligible costs.
Automotive predictive maintenance
Objective: deploy ML models on production equipment to predict failures and reduce downtime across two Ontario plants.
Eligible costs: data engineers and maintenance specialists, vibration sensors and gateways (usage), cloud compute for model training, subcontracted vibration analytics, pilot line integration, operator training, cybersecurity hardening, project management.
Food and beverage computer vision quality control
Objective: implement AI vision to detect defects on a high‑speed packaging line in Quebec.
Eligible costs: cameras and lighting (rental/usage), custom model training and labeling services, edge compute devices, integrator fees for line integration, trial materials, SOP updates and training, safety certification, milestone reporting.
Aerospace digital twin for composite manufacturing
Objective: create a digital twin to optimize cure cycles and minimize scrap in a BC facility.
Eligible costs: simulation software licenses, HPC cloud time, materials for test coupons, specialist subcontractors in model calibration, cyber and access controls for OT/IT, engineering labour, IP strategy specific to project outputs.
Robotics cell with reinforcement learning for metals
Objective: deploy a robotic cell to optimize welding parameters using RL in Alberta.
Eligible costs: robot cell usage or depreciation, sensors and tooling for experiments, integrator services, training curricula for technicians, safety compliance testing, labour for commissioning and validation, demonstration runs at two sites.
Electronics assembly yield optimization
Objective: ML‑driven yield improvement in a multi‑site pilot across Ontario and the Montreal region.
Eligible costs: multi‑site data acquisition, cloud analytics, data labeling, site‑to‑site deployment and validation, travel between sites for project tasks, cross‑site training, technical dissemination.
These examples are indicative. Each consortium’s budget must be justified against its approved work plan and NGen’s eligibility rules.
Funding Disbursement & Claiming Process
AI4M funding is typically reimbursed against approved milestones:
Milestone‑based: work packages and deliverables define the claim cadence.
Claim submission: partners compile eligible costs with supporting documents and submit consolidated claims for the consortium.
Review and verification: NGen validates eligibility, deliverable completion, and documentation completeness before releasing reimbursement.
Frequency: claims are commonly submitted periodically (e.g., quarterly) or upon milestone completion; timelines can vary by agreement.
Change management: scope or budget changes require prior approval; maintain alignment with the statement of work.
Final report and close‑out: a comprehensive technical and financial report wraps up results, IP outcomes, and performance metrics.
Plan cash flow to cover the consortium’s cost share and the timing gap between cost incurrence and reimbursement.
Stacking Rules
Combining funding sources (stacking) is often permitted within limits:
Disclose all public funding: federal, provincial, territorial, and municipal.
Maximum government assistance: NGen sets stacking limits; AI4M’s 40% contribution counts toward the total. Ensure the cumulative public share does not exceed program thresholds.
No double‑counting: the same expense cannot be reimbursed by multiple programs.
Private match: partners must maintain the required industry co‑investment (at least 60% of eligible costs for AI4M).
In‑kind vs cash: in‑kind contributions may be eligible in certain categories when valued and documented per NGen rules; confirm category‑specific limits.
When stacking with programs such as provincial manufacturing grants or R&D incentives, align timelines and expense attribution to stay compliant.
Real-World Budgeting Tips
Build from the work plan: define tasks, milestones, and deliverables first; then map costs to each task.
Separate eligible vs ineligible: tag each budget line with its eligibility status to prevent errors during claims.
Justify every line: include a short rationale and the evidence you will use at claim time (invoice, timesheet, usage log).
Meter cloud and software: enable tagging and cost centres so usage aligns to the project period and partners.
Control subcontracting: develop clear statements of work and compare quotes to demonstrate value for money.
Track labour consistently: use standardized timesheets with work‑package codes and approvals.
Manage equipment use: choose rental, lease, or depreciation models that fit project timelines and maximize eligibility.
Watch caps: some categories may have limits; design budgets to stay within them and avoid rework.
Plan for cash flow: schedule milestones to minimize reimbursement lag and ensure partner liquidity.
Align IP and data costs: keep IP/legal/data governance focused narrowly on project outputs to stay eligible.
Conclusion
AI4M funds the commercialization of AI/ML in Canadian manufacturing by reimbursing up to 40% of eligible, project‑specific costs across labour, subcontractors, equipment usage, materials, software, data, cloud, integration, training, cybersecurity, IP/legal (limited), and project management. Exclusions generally cover general overhead, sales and marketing, unrelated capex, and routine operations. Build a clear, well‑documented budget tied to milestones, disclose all stacking, and follow NGen’s budgeting and financial guidance to maximize eligible expenses and streamline claims.
