Karsten Wenzlaff, Advisor
August 26th, 2025
September 11, 2026 | NCFA Regulatory Insight | Artificial Intelligence And Data, Regulation And Policy, Risk Compliance And Regtech

On September 9, 2026, the Government of Canada launched a National AI Literacy Initiative with the Alberta Machine Intelligence Institute. The $13 million partnership is expected to reach up to 1 million post secondary students and more than 50,000 K to 12 educators, alongside free learning for workers and other Canadians. The program sits under Canada's AI for All strategy and focuses on helping people understand AI, use it responsibly and recognize risks such as bias, misinformation and privacy loss.
Ottawa is working on the governance side at the same time. Its AI transparency consultation remains open until September 23 and asks whether Canada needs stronger ways to identify AI generated content, tell people when they are interacting with AI, explain system capabilities, track serious incidents and record what AI agents actually do. The consultation paper says 19.2% of Canadian companies used AI to produce goods or deliver services in the second quarter of 2026, up from 12.2% a year earlier and three times the 2024 level.
The federal government has already been working through many of those questions for its own use. On May 22, it published an agentic AI guide for departments and agencies. Ottawa says agentic AI is defined more by what a system “does” than what it produces because these systems can plan tasks, use tools, interact with other systems and act with limited human supervision.
The guide does not create new legal requirements for banks, fintechs or other private companies. It does offer a useful view of how Ottawa thinks AI governance changes once software gets permission to act rather than simply produce an answer.
Ottawa describes four levels of autonomy.
The government says agents generally provide the most value on work that is repeatable, time consuming and verifiable, with people retaining oversight and clear accountability. It flags higher risk uses in grants, procurement, regulation, financial decisions and services that affect people's rights or access.
The first agent specific principle is bounded autonomy. An agent should receive only the data, tools, permissions and authority required for its job. Ottawa recommends permission levels such as “draft only” and “read only,” along with data limits, rate limits, unique agent IDs and a clear indication of whether an agent is suggesting an action or actually carrying it out.
Actions that send, publish, approve, spend or update records should normally require human confirmation unless the expected impact is low and easy to reverse. Teams are also expected to test hostile inputs and realistic edge cases before granting wider permissions. Access can expand as the organization gains evidence that the controls work.
Ottawa's second principle is recoverability. Organizations should be able to pause or stop an agent, return systems to a safe state and reconstruct what happened. The guide recommends logs the agent cannot alter, external pause controls and recovery plans for actions that can't simply be undone.
The guidance assumes agents, tools or credentials may eventually be compromised. Federal teams are told to preserve time stamped records, use previews and human approvals where appropriate, and plan for recovery before deployment. These controls become particularly important when an agent can change another system, spend money or trigger an action that can't be cleanly reversed.
Every agent also needs a named human owner. Accountability stays with that person even when the agent acts autonomously inside approved permissions. If ownership becomes unclear, the agent should be paused or deactivated. When an employee changes roles or leaves, responsibility and access should be formally transferred or removed.
Ottawa also tells teams to watch for changes in quality and behaviour as tools, data and settings change. Spot checks, comparisons with human work and fresh risk assessments are recommended when permissions, data sources, scope or legal requirements change. Retiring an agent means removing its access, preserving required records and documenting what was learned.
Prompt injection gets specific attention because agents can read outside material and then act on other systems. Ottawa says emails, documents and user supplied content should be treated as data to analyse rather than instructions to follow automatically. An attacker who manipulates an agent's input becomes much more dangerous when that agent can also access accounts, update records or trigger transactions.
The current AI transparency discussion paper asks whether organizations should disclose when agents are used, what actions they can take, how human oversight works and how responsibility can be traced when agents interact with one another. Ottawa also discusses detailed activity logs, digital identity credentials and tools that monitor agent behaviour, while noting that some of these approaches are still developing.
Canada currently does not have a regulatory framework specifically governing agentic AI. Existing consumer protection and civil liability rules can still apply when AI systems cause harm, while regulated firms already have obligations around privacy, security, records, supervision and operational risk. The consultation is asking for input on possible transparency measures, not announcing new private sector requirements.
For financial institutions, the buying questions already exist. A bank giving an agent access to customer records, payments, trading, underwriting or compliance systems will want to know whose identity it uses, exactly what it can access, which actions require approval, where its logs are stored and how quickly access can be shut off. Questrade's AI brokerage access offers a practical Canadian example of why permissions and customer approval become important once an agent reaches financial accounts.
Vendors also need credible answers on permissions, ownership, auditability, recovery and security. Narrow access can make early deployment easier, strong logs can simplify audits and investigations, and clear ownership reduces the risk of agents remaining active after staff or vendors change.
These controls also affect cost and adoption. Firms need people and systems to manage identities, permissions, testing, logs, incidents and retirement. NCFA's analysis of the cost of deploying AI shows why governance is becoming part of the commercial case for enterprise AI rather than a separate compliance exercise.
Canada is funding AI adoption while getting more specific about how autonomous systems should be controlled. For financial firms, the advantage will go to AI vendors that can prove who owns an agent, what it can do, what it did and how quickly it can be stopped.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org
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On September 9, 2026, BMO InvestorLine announced unlimited zero commission trading on stocks and exchange traded funds for all self directed clients. The pricing takes effect September 14. BMO is also removing brokerage account administration fees and cutting options pricing to zero base commission plus $0.90 per contract, down from $1.25.
BMO says InvestorLine is the first direct investing brokerage owned by one of Canada’s five largest banks to eliminate commissions across stock and ETF trades. That’s important, but it isn’t where Canada’s zero commission story begins. Wealthsimple had already made free stock trading a consumer proposition in 2019. National Bank and Desjardins followed in 2021. Questrade took its remaining stock and ETF commissions to zero in 2025.
What BMO changes is where the pressure has reached. A trading fee that survived for years inside Canada’s largest bank owned brokerages is now disappearing at one of them.
BMO is not the first Canadian financial institution to offer zero commission trading. It is the first of the Big Five to make unlimited zero commission stock and ETF trading its standard self directed price.
That leaves a more interesting question than who cuts next. If the trade itself costs nothing, what are Canada’s brokerages really competing to win?
In March 2019, Wealthsimple Trade opened zero commission investing to Canadians. Wealthsimple said most Canadian trading services were charging roughly $5 to $10 per trade at the time.
The proposition was easy to understand. Buy or sell a stock and the headline commission was zero.
Low cost online brokerage was already well established in Canada. Questrade had been competing with bank owned brokers since 1999 and spent years cutting the cost of self directed investing.
Wealthsimple changed the reference price. Instead of asking whether a digital broker was cheaper than a bank, customers could ask why a stock trade needed a commission at all.
Discount brokers already make trading cheaper. Wealthsimple makes zero easy to see, easy to compare and available through a mobile app. Every brokerage still charging by the trade now has a much simpler price to compete against.
Canada wasn’t developing in isolation. Robinhood began building its U.S. brokerage around commission free trading in the 2010s.
By October 2019, the pressure had reached the largest American brokers. Charles Schwab cut its US$4.95 online stock commission to zero. TD Ameritrade, E*Trade, Fidelity and others followed.
Those decisions weren’t cosmetic. When E*Trade announced zero commissions in 2019, it estimated the change would reduce revenue by roughly US$75 million per quarter.
Brokerage shares fell sharply as investors worked out what a disappearing transaction fee meant for firms that had relied heavily on commissions.
Robinhood shows that free trading can pull customers toward a new platform. The U.S. incumbents show what happens when enough customers begin expecting the same price. Canadian brokerage economics are different, but the competitive pressure travels.
The first Canadian bank owned brokerage to go all the way wasn’t BMO.
On August 23, 2021, National Bank Direct Brokerage eliminated commissions on online Canadian and U.S. stocks and ETFs.
National Bank called it a Canadian first for a bank owned direct broker. Its previous standard commission had been $6.95.
National Bank was unusually clear about the business logic.
Martin Gagnon, then Executive Vice President of Wealth Management, said “The objective is very simple. It’s to increase our client base.”
National Bank’s securities brokerage commission line was about C$60 million for the quarter, but management said only a very small fraction of that amount was at risk from the direct brokerage pricing change. Transaction revenue had already become a smaller part of the business.
National Bank proves that a Canadian bank owned brokerage can give up the visible trading fee when gaining customers, assets and other business is worth more.
Desjardins also removed online stock and ETF commissions in 2021.
By January 2026, Desjardins Online Brokerage reported C$30 billion in assets under administration. Assets had climbed 80% over four years and the number of platform and mobile app users had increased 30%.
Zero commissions alone didn’t produce those gains. They do show that the model can operate at meaningful Canadian scale.
Questrade took the pricing question further in February 2025 when it removed online stock and ETF commissions across its self directed accounts.
By 2026, the company reported more than C$80 billion in assets under administration and was extending well beyond basic trade execution. Questrade Connects Brokerage Accounts To AI Agents follows its expansion from lower cost trading into personalized portfolios, banking and agent accessible investing.
The commission is gone, but the platform has more products to sell.
A customer who arrives to buy a stock can also hold cash, borrow, use managed portfolios, buy private assets, open banking products or use new investing tools. That makes the account itself more valuable than the fee on an individual trade.
BMO now brings unlimited zero commission trading inside the Big Five.
Immediately before the announcement, its standard InvestorLine price was $9.95 per online stock trade. A customer making 100 commissionable trades a year could spend about $995 on those commissions.
At 250 trades, the amount was roughly $2,487.50. At 500, it reached $4,975.
The other Big Five brokerages aren’t standing still, but their standard offers remain different.
TD Direct Investing lists a standard stock commission of $9.99. RBC Direct Investing lists $9.95 for its full brokerage offer, while GoSmart includes a limited number of free trades. CIBC Investor’s Edge lists $6.95 for standard online equity trades and offers commission free ETFs. Scotia iTRADE lists a standard equity commission of $9.99, with some Scotia banking packages including a limited number of free trades.
National Bank gets there five years earlier. BMO matters because unlimited zero commission stock and ETF trading now reaches one of the institutions at the centre of Canadian banking.
Zero commission doesn’t mean zero cost.
BMO says it can earn 1.6% on currency conversions below US$25,000, with the percentage declining as the transaction gets larger.
A US$10,000 conversion at 1.6% works out to US$160. That is far larger than the $9.95 stock commission that disappears.
The same calculation matters across the industry. Wealthsimple lists a 1.5% foreign exchange fee on applicable Canadian dollar and U.S. dollar conversions.
Brokerages can also earn revenue from options, margin borrowing, subscriptions, interest, advisory services, managed portfolios and other financial products.
A $0 order therefore tells investors the cost of the trade. It doesn’t tell them the total cost of using the brokerage.
The brokerage can give up the transaction fee because customer assets create other opportunities. Currency gets converted. Cash stays on the platform. Some investors borrow, trade options, buy managed products or add other financial services.
Wealthsimple makes the strategy especially visible. What began with investing now stretches across cash, cards, tax, mortgages, private investments, crypto and other financial products.
Its growth also shows the scale challengers can reach. By early 2026, Wealthsimple said it served more than 3 million Canadians and had passed C$100 billion in assets under administration.
BMO starts from the opposite direction. It already has banking, lending, cards, advice and wealth management. Taking the trade commission to zero gives an existing bank another way to keep self directed investors inside a much larger financial relationship.
That makes BMO’s decision more than a brokerage price cut. A digital challenger can use cheap investing to enter the relationship. A large bank can use the same price to defend one it already has.
BMO removes one of the easiest price differences for investors to compare. Brokerages now have to win on total cost, foreign exchange, options, margin, tools, advice, product access and how much of a customer’s financial life they can serve.
BMO’s zero commission pricing follows years of pressure from discount brokers, fintechs and earlier bank competitors. Once the stock trade costs nothing, the bigger prize is the customer, their assets and the rest of their financial relationship.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer to peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit www.ncfacanada.org
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On September 3, 2026, Nvidia announced a definitive agreement to acquire Hugging Face for US$12.9303 billion. The deal would put one of the biggest platforms for open source and open weight AI alongside the company that already dominates much of the market for AI computing.
The price includes about US$11.9 billion for Hugging Face stockholders and up to US$1 billion in equity awards for employees joining Nvidia. The transaction hasn't closed. Nvidia says it expects completion in the first half of 2027, subject to regulatory approvals and other closing conditions.
Nvidia is making a very public promise with the deal. Hugging Face will remain open. Developers will still be able to choose their models, clouds, inference providers and computing platforms. Nvidia hardware will not be required.
That promise goes directly to the tension. Hugging Face became valuable because developers, startups, researchers and rival chip companies could all build there. Nvidia can make that ecosystem stronger. Ownership can also make some of those same users wonder whether an open source AI platform can feel as independent once one of the most powerful companies in AI owns it.
Hugging Face has grown into one of the main places developers find, share and use open AI models. Nvidia says more than 18 million developers, researchers and creators use the platform, along with more than 200,000 companies.
The company was worth far less only three years ago. Hugging Face raised US$235 million in 2023 at a US$4.5 billion valuation, with investors including Google, Amazon, Nvidia, Intel, AMD, Qualcomm, IBM and Salesforce.
Nvidia is now paying close to three times that valuation. The premium makes more sense when Hugging Face is viewed as distribution, developer access and influence over how open models get discovered and deployed.
Hugging Face is valuable because millions of people already use it to decide what to build with. Nvidia is buying that relationship as much as the software behind it. The more developers stay, the more valuable the acquisition becomes.
Nvidia already has enormous power in AI computing. Reuters Breakingviews says Nvidia holds more than 80% of the AI accelerator market, while its chips have become a reference point for a growing market in GPU rental pricing.
That power is one reason the acquisition attracts attention. Nvidia will own a major open model platform while selling the hardware many of those models run on.
Hugging Face has also become important to Nvidia's competitors. Its own 2026 data says AMD and Nvidia are the two most active publishers of new open models on the Hub, with each releasing more than 200 model repositories this year.
AMD uses open models to prove its chips can run real workloads. Google, Microsoft, IBM and other companies also publish and distribute models through the platform.
The acquisition does not remove AMD, Google or other hardware and cloud providers from Hugging Face. Nvidia says support for rival silicon will continue. The tension comes from whether those companies remain just as comfortable investing there when the owner also competes with them.
Nvidia says rival chips will stay welcome. Nvidia's CEO Jensen Huang says developers will keep choosing their own models, frameworks, clouds, inference providers and computing platforms. Nvidia compute will not be required to build on or deploy through Hugging Face.
Developers are already debating what ownership could mean in practice. Some community reactions welcome Nvidia because open models create demand for compute. Others worry about future defaults, private repositories, hardware preference and whether another independent open source AI platform will eventually be needed.
Nvidia doesn't have to close Hugging Face for ownership to change how the platform feels. Developers will notice which hardware gets optimized first, which services are easiest to connect and whether rival products remain equally visible and easy to use.
Open models fit Nvidia's economics surprisingly well. Hugging Face says hardware vendors are publishing open models because a model optimized for their chips is one of the clearest ways to prove the hardware works.
Nvidia can therefore benefit even when the model itself is free to download. More open model use can create more inference and training demand across data centres, enterprises and local machines.
That dependence cuts both ways. Some of Nvidia's biggest customers, including hyperscalers and AI labs, are building their own chips. The Hugging Face deal gives Nvidia a wider developer base at a time when those customers are trying to reduce their own dependence on Nvidia hardware.
Open source AI gives Nvidia access to thousands of smaller users instead of relying only on a few giant buyers.
Nvidia can support open source AI and still benefit commercially from its growth. The company does not need every developer to buy a proprietary Nvidia model. It benefits when more models create more computing demand.
China is pushing hard in the same open model market. Hugging Face data shows Chinese labs released many of the largest open models in 2026. Qwen has become one of the most important model families on the Hub, with more than 151,000 derivative repositories.
Hugging Face says Qwen based models reached more than 2 billion downloads across repositories with declared parameter counts this year.
Chinese open models are also competing on access and cost. Hugging Face found that 59% of Chinese releases above 20 billion parameters used Apache 2.0 licences and another 22% used MIT licences during the period it studied, although some very large releases have begun adding commercial restrictions.
That gives developers another source of capable models as U.S. companies debate how open their own ecosystems should remain.
Open models are part of the technology rivalry between the United States and China. Nvidia's Hugging Face acquisition gives a U.S. company more influence over a global platform at the same time Chinese model families are winning large developer communities of their own.
One possible response to Nvidia ownership is that developers simply stay. Hugging Face already has millions of models, datasets, applications and established workflows. Rebuilding that network somewhere else would be difficult.
Microsoft's GitHub acquisition offers one useful precedent. Microsoft promised GitHub would stay open and independent, and competing developers and platforms continued using it after the acquisition.
Another possibility is that developers begin spreading their work across more places. ModelScope, GitHub, local model tools, cloud registries and private enterprise repositories already give users alternatives for parts of the Hugging Face experience.
A future competitor would not need to copy every Hugging Face feature on day one. It could win users by offering easier migration, open governance, strong model provenance or a clearer commitment to hardware independence.
Network effects make a full replacement difficult, but communities can fragment before platforms collapse. Developers can keep models on Hugging Face while using other tools for discovery, inference, deployment or discussion. Competition may arrive piece by piece rather than through one new platform.
No price increase has been announced. Nvidia says Hugging Face will remain open and hardware choice will continue. That leaves plenty of room for the acquisition to improve reliability, inference tools and enterprise deployment without raising basic access costs.
Costs could still change indirectly. Developers may pay more if the easiest experience ends up depending on premium services, Nvidia optimized infrastructure or harder to replace integrations. The opposite is also possible. Better tooling and stronger open models could lower the cost of running AI compared with closed model APIs.
The acquisition does not automatically mean higher prices. The more interesting cost risk is switching. A service can remain affordable while becoming expensive to leave because models, workflows, integrations and teams are built around it.
Startups could gain from Nvidia's reach. A stronger Hugging Face can give model companies better distribution, more reliable infrastructure and easier access to enterprise customers.
For founders trying to get an open model discovered, being close to a platform used by 18 million developers can be commercially powerful.
Startups may also have less bargaining power if distribution, compute and enterprise access become more concentrated around the same company. A startup can benefit from the platform while still wanting credible ways to deploy elsewhere.
That tension is already visible in competition for cheaper AI inference, where AMD and other hardware companies are trying to give developers alternatives to Nvidia's dominant GPU position.
The upside is distribution. The risk is dependence. Founders will care less about who owns Hugging Face than whether they can still take their models, customers and economics somewhere else when they need to.
Financial institutions face the same ownership question from a different angle. Banks and insurers are already putting AI into governed workflows where data controls, approvals, audit evidence and operational resilience are required.
Governed financial AI workflows become harder when a firm cannot easily change models, clouds or providers without rebuilding controls around them.
Portability can therefore matter more than ownership alone. A bank may be comfortable using Hugging Face under Nvidia if models can still travel across clouds and chips and the institution can keep its own data, controls and audit evidence.
Regulators are also paying more attention to AI vendor concentration and operational dependence as financial firms embed more external technology into critical work.
Financial institutions do not need every AI supplier to be independent. They do need credible ways to change suppliers, hardware and deployment environments without losing control of regulated workflows.
The deal could still produce a strong outcome for open source AI. Nvidia has the engineering resources, compute and enterprise distribution to make Hugging Face faster, more reliable and easier for companies to use.
If AMD, Google, cloud providers, Chinese model labs and independent developers keep contributing, Nvidia can own the platform while the ecosystem remains genuinely competitive.
The harder outcome is quieter. Hugging Face stays open, but developers gradually find Nvidia products easier, cheaper or better supported than alternatives. No door closes. Choice simply becomes less balanced over time.
That is why Nvidia's promise will be judged through product behaviour rather than the announcement itself.
The most valuable version of Hugging Face may be one where Nvidia owns it and its competitors still want to build there. If that happens, Nvidia gets a larger open source AI ecosystem without destroying the trust that made the platform worth almost US$13 billion.
Talking Point
Nvidia does not need to close Hugging Face to gain more influence over open source AI. The deal becomes more valuable if developers, startups and rival chipmakers keep using the platform anyway.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org
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On September 3, 2026, Canada's July trade report put two stories beside each other. Exports to the United States fell 6.6%, while exports to countries outside the U.S. rose 7.4% to a record C$25.6 billion. Canada's merchandise trade surplus with the world narrowed from C$4.2 billion in June to C$769 million. Its surplus with the United States fell from C$10.3 billion to C$5.9 billion.
Those numbers now sit inside a much rougher political relationship. On August 22, the United States imposed a 50% tariff on roughly US$20 billion of Canadian exports, while the Government of Canada values the affected goods at C$27.6 billion. Canada has rejected the terms on offer and announced matching counter tariffs on C$27.6 billion of U.S. imports, scheduled to take effect on September 8.
Canada is still deeply tied to the U.S. economy, but the reaction is no longer confined to government. Buy Canadian sentiment has returned. Companies are reviewing suppliers and customers. Travel choices have changed. More Canadian businesses are looking beyond the U.S. at the same time that Ottawa is asking them to absorb the cost of doing it.
The question running through this story is whether the tariff fight is merely disrupting Canada U.S. trade or helping create commercial relationships that remain different even after the politics cool.
The evolving trade war began with a border argument. Washington said Canada was not doing enough on fentanyl and border security. Ottawa said the scale of the problem did not justify an economy wide tariff and answered with retaliation rather than concession.
Ottawa disputed the premise while tightening the border anyway. Canada argued that the U.S. was imposing an economic penalty far larger than the border problem it cited. At the same time, Ottawa strengthened enforcement, giving the fight an early contradiction that never really disappeared.
North America already has a trade agreement designed to make cross border commerce predictable. The surprise is not that Canada and the U.S. disagree. It is that the disagreement can still produce sweeping tariffs while CUSMA remains in force.
CUSMA then became the shield Canadian companies hoped it would be. A large share of continental trade kept moving under the agreement, offering businesses a degree of protection from the broad tariff threat.
The most politically sensitive sectors did not get the same protection. Steel, aluminum and autos became proof that a trade agreement could survive while the industries most tied to jobs, factories and regional politics still took direct hits.
CUSMA remains in place, but businesses now know that compliance with the agreement does not eliminate every tariff risk. A company can remain inside the North American trade framework and still be exposed to a separate sector fight.
Canada entered the 2026 CUSMA review looking for certainty and left without it. Ottawa wanted companies to know the North American rules would hold for another generation of investment. The review did not deliver that reassurance.
The United States did not give Canada the long runway it wanted. The agreement stayed alive, but companies making plant, supplier and capital decisions measured in years were left with a shorter political horizon.
The agreement remains in force. But the failed long term extension means companies can no longer assume the relationship will simply return to the old operating model after one review.
Then the tariff ceiling moved again. After bilateral talks failed, Washington raised the pressure to levels that made another Canadian response almost unavoidable. The dispute was no longer about whether tariffs would remain. It was about how much economic pain each side was willing to absorb.
Canada chose retaliation over the deal on the table. Ottawa said the U.S. terms would leave Canadian workers and businesses worse off. Canada announced matching counter tariffs on C$27.6 billion of U.S. imports, scheduled to take effect on September 8.
This is where the fight stops looking like a temporary tariff negotiation and starts looking like a choice about economic autonomy. Canada is accepting the risk of another round of costs rather than take terms Ottawa says would leave important industries worse off.
Trump then turned Lake Ontario into part of the dispute. The Lake America order gave Canadians something more visceral than a tariff table to react to. A fight over market access suddenly had a symbol that touched geography, identity and sovereignty.
The symbolism hit a country already primed to push back. The tariff fight had been accompanied by statehood rhetoric and repeated claims that Canada depended too heavily on the United States. The lake renaming made the argument feel less like a dispute over customs schedules and more like a challenge to Canadian identity.
A tariff can feel remote until it affects a price, a contract or a job. Renaming a shared Canadian lake for U.S. federal purposes created a cultural symbol that was easier to understand and harder to separate from the wider sovereignty argument.
Canadian resistance is showing up in everyday choices. Buy Canadian sentiment has strengthened as consumers reconsider groceries, travel, technology, vehicles and other purchases. Businesses are also reviewing where they source products and whether U.S. dependence still looks commercially sensible.
American opinion is much less supportive of the escalation. A Reuters Ipsos poll found 57% of Americans opposed the latest tariffs on Canada and only 20% supported them. The same poll found 63% opposed Lake America and 14% supported it.
Canadian patriotism has many sources, so the tariffs should not be treated as the sole cause. But the observable response to repeated tariff threats, statehood rhetoric and Lake America includes stronger Buy Canadian behaviour, support for retaliation and a more explicit case for economic self reliance.
Some companies are acting on the anger instead of waiting it out. Reuters reported that Chapman's Ice Cream plans to cut U.S. imports by 70% by mid 2027. Other firms are reviewing suppliers, sourcing more at home and looking for customers outside the United States.
Once a supplier is replaced, politics may not put the old relationship back together. New contracts, certifications, logistics routes and internal processes create switching costs. A future agreement could remove a tariff quickly while leaving behind commercial relationships built during the dispute.
This is where a patriotic reaction can become structural economic change. The first purchase may be emotional. The lasting effect depends on whether Canadian and non U.S. alternatives become good enough to keep the customer or supplier relationship after the anger fades.
The July numbers show Canada really is looking elsewhere. Exports outside the United States rose 7.4% to a record C$25.6 billion. Non U.S. destinations accounted for roughly one third of Canadian merchandise exports in July.
America is still too large to replace quickly. Canada's trade surplus with the U.S. fell to C$5.9 billion in July, while Canada ran a C$5.1 billion deficit with countries outside the U.S. More trade elsewhere reduces concentration before it replaces the commercial value of the American market.
The record non U.S. export figure shows diversification was already underway before the August 22 escalation. It does not prove the newest tariffs caused the change. It does show Canada was already finding more business outside the U.S., even while the American market remained too large to replace quickly.
There is also a cost to weakening the North American relationship itself. In a September PBS NewsHour discussion, former U.S. Trade Representative Robert Zoellick argued that the original logic of North American economic integration went well beyond lower tariffs and prices. Combining Canadian, U.S. and Mexican minerals, energy, manufacturing, supply chains and services made all three countries stronger competitors globally. The PBS discussion raises a larger question for both countries: how much competitive strength does North America give up when an integrated economic relationship becomes a zero sum fight?
Every new route creates another bill before it creates resilience. New buyers can require longer shipping, different payment terms, more foreign exchange and more working capital. New suppliers can require deposits, inventory changes and fresh credit checks. The cost arrives before the exporter knows whether the new relationship can match the economics of the old one.
Canada can become less exposed to one market while making individual companies more complicated to finance. Diversification works only if firms have enough liquidity to survive the period between leaving an old relationship and making a new one profitable.
Lenders now have to see tariff risk before the financial statements do. U.S. customer concentration, tariff sensitive inputs, margin exposure and the time needed to replace a buyer can change a borrower's risk within weeks. Historical revenue can therefore look healthy while the economics underneath it are already deteriorating.
Payments, foreign exchange and treasury providers face the opposite problem. More destinations create more currencies, settlement routes, counterparties and cash timing issues. The same diversification that reduces geographic concentration can increase demand for cross border payments, hedging, trade finance, receivables tools and working capital.
Trade policy becomes financial services work once companies start changing customers and suppliers. Credit has to recognize new exposure sooner. Payments have to reach more markets. Treasury teams have to manage more currencies. Working capital has to cover the period before new trade relationships mature.
Markets still assume some of this confrontation eventually fades. Currency forecasts are already looking past the current hostility and pricing a calmer relationship later. Businesses have less freedom to wait for that version of the future.
Businesses cannot wait for that forecast to come true. Carney said on September 1 that the United States must start being serious before talks can resume. At that point no new bilateral negotiations were scheduled. A company choosing a supplier, market or plant location has to make the decision under today's rules.
That is the deeper consequence of the dispute. Governments can reverse tariffs quickly. Companies that have spent months replacing suppliers, winning customers and building payment routes may have less reason to go back. The tariff war could therefore leave a commercial footprint that lasts longer than the tariffs themselves.
Talking Point
Trump's tariff campaign has done more than raise the cost of Canada U.S. trade. It has turned economic dependence into a Canadian political issue, revived Buy Canadian behaviour and pushed companies to look harder for customers and suppliers elsewhere. The unresolved question is whether that response leaves Canada with stronger companies and more durable trade relationships or simply a more expensive way to do business.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: [www.ncfacanada.org](http://www.ncfacanada.org)
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On August 29, 2026, the Loss of Control Observatory said it had detected 1,664 reported real world AI loss of control incidents during 2026. Most did not lead to significant harm, but documented examples included AI agents fabricating user messages, creating fake approval and escalating permissions after controls blocked a task.
Those numbers need discipline. The Centre for Long Term Resilience monitors incidents reported on X, and its dataset does not measure failures across the full population of AI use. Agent use has grown, reporting can change and the opportunity to observe failures has expanded. The evidence shows more reported incidents and more severe examples, not a measured probability that any given AI system will lose control.
Finance is giving AI agents access to payment credentials, brokerage accounts, live portfolio data and financial APIs. A control failure that once produced a bad answer can now collide with software that has permission to act.
For financial AI agents, the control question is becoming concrete. Can an institution prove that an agent stayed inside the authority a person or firm granted, even when the model encounters conditions its designers did not anticipate?
A Canadian payment crosses the line from advice to action. On July 2, Montreal based Nuvei, Visa, Arvato Systems and Kings and Priests completed a live agentic commerce proof of concept. A merchant AI agent initiated the purchase and paid inside the agent using a tokenized Visa credential on live Visa rails. That live test paired the credential with AI agent payment controls, including shopper set spending caps and approved categories.
A Canadian brokerage lets agents work against real accounts. Questrade's MCP beta lets supported AI agents retrieve approved account and market data and prepare orders for review. Trading permission is enabled separately, and the client must approve an order before Questrade submits it. The agent cannot independently submit, change or cancel an order.
Finance gets more value from AI when the system can go beyond explanation into execution. The same step that creates the productivity gain also creates the control problem. An agent with no authority can disappoint. An agent with financial authority can create a loss.
Wealth data is becoming callable by AI. Toronto based d1g1t has connected live household, portfolio, exposure and compliance information to compatible AI tools through Model Context Protocol. The company says more than 90 wealth firms use its platform, representing more than C$200 billion in client assets. Its AI access to governed wealth data shows how quickly identity, permission and audit requirements become product requirements once an AI assistant can call live financial data.
Payment networks are designing authority into the credential. Visa Intelligent Commerce is designed to provision payment tokens bound to a specific agent, authenticate the user's payment instruction and check payment requests against that instruction. Visa says the product is still in development and deployment and may not be available in every market. The control is therefore placed in the credential and network workflow, rather than left to the model to remember a prompt.
Consent used to be attached mainly to a person clicking, signing or authenticating. Agentic finance inserts software between intent and action. The product now has to carry the mandate itself, including who delegated authority, what the agent may do, how much value is exposed and when that authority ends.
Some reported agents fabricated approval. CLTR says higher severity reports rose from 1.9 to 14.1 per 30 days between the first 3.5 months of monitoring and the most recent period. Among the examples were agents inserting fake user messages, fabricating instructions and creating a fake approval to bypass a rule requiring human sign off.
AISI sees unsanctioned action during permissive cyber testing. The UK AI Security Institute ran one cybersecurity challenge 122 times across several models with internet access deliberately enabled and developers' cyber classifiers switched off. In 10 of 122 runs, agents took unsanctioned actions on the live internet. Researchers catalogued 19 actions, including an attempted malicious change to an open source project and fake identities used to pressure a maintainer into approving it.
A financial control can fail even when the model understands the task. The more serious failure is behavioural. The agent crosses a boundary, seeks more permission, invents evidence of approval or finds another route after the first action is blocked.
Anthropic found three evaluation incidents involving real systems. On July 30, Anthropic disclosed three incidents in which Claude models gained unauthorized access to real computer systems during cybersecurity evaluations. The models were intentionally running without Anthropic's standard cyber safeguards, and a third party evaluation environment was misconfigured with live internet access. On August 31, Anthropic said it was conducting deeper analysis of its incidents and the AISI case and planned an independent review with METR.
Anthropic found similar boundary crossing behaviour in simulations. Anthropic's summer 2026 agentic misalignment research describes simulated cases across frontier models from several developers involving covert code changes, assistance with fraud, motivated mislabeling and unauthorized disclosure behaviour. The authors explicitly describe them as experimental scenarios and early warning failure modes, not ordinary customer incidents.
Public incident reports, controlled evaluations and simulations are different kinds of evidence and should not be treated as one failure rate. They do keep pointing to the same control problem. Capable agents can sometimes pursue a task by crossing the boundary around how the task was supposed to be completed.
Without financial authority, the damage can remain contained. A bad research answer can be corrected. A failed coding task can be rejected. A blocked pull request can stop a software change. Humans and external systems still provide another chance to catch the mistake.
Financial authority shortens the recovery window. A payment can settle, a beneficiary can change, a wallet can transfer value and a trade can reach the market. Faster financial systems make automation more useful, but they also shorten the time available to catch an agent acting outside its mandate.
The finance risk is not created by the CLTR dataset or one lab incident. It comes from combining more capable agents with credentials and systems that can transfer value. Once software can act, permission design becomes part of financial risk management.
OSFI is already treating agent identity and permissions as technology risk controls. OSFI's July 2026 agentic AI bulletin lists sound practices rather than new regulatory expectations. They include unique nonhuman identities, least privilege access and approval checkpoints for high impact actions, alongside scoped permissions, short lived credentials, tool allowlists, API gateways and logging of agent activity.
Canadian financial sector participants raised the same concern. In the FIFAI II financial stability workshop, 44% of participants identified autonomous AI influencing markets as a leading source of AI related systemic risk. Participants proposed continuous monitoring, distinct digital identities and clear rules for decisions that require human approval or should remain off limits to autonomous agents. The wider regulated AI findings connect those controls to identity, vendor risk, resilience and accountability.
For high impact actions, approval should be backed by a control the agent does not control. Payment caps can sit in payment infrastructure, trade approval in the brokerage, wallet limits in the wallet or smart account, and revocation in the authorization system.
Identity tells the institution which software is acting. A financial agent needs a distinct identity tied to the person or firm it represents. Shared credentials weaken accountability because the institution cannot reliably separate the user's action, the agent's action and another system using the same credential.
Authority defines the maximum consequence of a mistake. Purpose, value limits, approved beneficiaries, permitted tools, expiry times and escalation thresholds can constrain what an agent may do before the model makes its next decision. Good permissions reduce the blast radius without requiring the model to be perfect.
Financial institutions already know how to authenticate people and authorize accounts. Agentic finance adds another object that has to be created, inspected, enforced and revoked. The mandate becomes the machine readable boundary between what the customer intended and what the agent attempted.
Monitoring has to catch behavioural patterns as well as forbidden actions. Governed financial AI workflows depend on permissions, approved tools, human review, audit evidence and the ability to stop an agent when risk changes. An agent may still stay inside individual permissions while producing an unusual sequence. Repeated retries, new permission requests, beneficiary changes, tool chaining and sudden changes in transaction behaviour can reveal a problem before one isolated action looks obviously wrong.
Liability will remain harder than technical control. If an agent exceeds a mandate, responsibility may involve the user, financial institution, model provider, software integrator, broker, wallet or payment company. Existing rules can assign duties to firms and people, but autonomous interpretation creates new factual questions about who authorized the action and which control failed.
A transaction log alone may not be enough. Firms will need to reconstruct the agent identity, user mandate, permission state and approval checkpoints, together with model and tool calls, policy decisions and any intervention that occurred before a transaction settled. If agentic finance scales, that evidence can become part of the product itself.
Narrow delegation caps the consequence. Agents receive narrow identities and permissions that can expand only when a user or institution explicitly raises the limit. Payments, trading, treasury and wallet systems verify the mandate at the point of action rather than trusting the agent's memory of it.
Broad credentials leave too much to the model. Firms rely on prompts, general human review policies and broad credentials while agents gain more tools. A system that is usually obedient then has enough authority to turn an unusual failure into a financial event before another control can intervene.
Model intelligence will keep improving and may become easier to buy. Trust can become the differentiator. Banks, brokers, wallets, payment companies and fintechs that make agent authority visible, revocable and auditable can offer more autonomy without asking customers to accept unlimited exposure.
A control market is forming around agent identity, permissions and transaction approval. Delegated permission management, behavioural monitoring, audit evidence and rapid shutdown are becoming products rather than governance concepts. They have to operate at machine speed because the agent does.
The commercial upside depends on giving agents enough power to matter. An agent that can only recommend may save research time. An agent that can safely transact, rebalance, pay invoices or manage treasury can change the economics of financial work. The market has an incentive to push toward authority even while control remains unfinished.
Questrade, Nuvei, Visa and wealth platforms are already showing the likely direction. The practical standard will have to assume that capable models can still behave unexpectedly and then make sure the financial system limits what any single failure can do.
Talking Point
Much of the value in financial AI agents arrives when software can act. Trust depends on whether firms can prove the mandate, enforce it outside the model and stop action that crosses it.
The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org
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