A group-level AI programme run from Toronto around Layer 6, its in-house AI lab, with a C$1 billion annual AI value target (half revenue, half cost), a first agentic AI model in mortgages, a C$25 million Cohere collaboration and an Evident AI Index rank that slipped from ninth to 13th in 2025.
How is TD Bank using AI?
The Toronto-Dominion Bank, which reported C$2,111.9 billion of total assets at 31 July 2026, runs its AI programme from the group centre in Toronto and measures it in dollars: CEO Raymond Chun set a target of C$1 billion a year of value from AI over the medium term, half revenue and half cost, at the September 2025 Investor Day, and said on 27 August 2026 the bank had 'essentially hit' its fiscal 2026 target of C$200 million three quarters into the year, with C$195 million delivered by then. The build is centred on Layer 6, the AI lab TD bought in 2018, which produced the TD AI Prism foundation model (June 2025) and the bank's first agentic AI model (May 2026), which cut mortgage pre-adjudication from about 15 hours to under three minutes. TD's AI rank fell to 13th from ninth in the 2025 Evident AI Index, which also noted a 35% rise in AI-focused staff. On 22 September 2026 it announced up to C$25 million over three years for a Layer 6 and Cohere collaboration, and on 3 September 2026 it gave enterprise AI responsibility to Paul Whitehead. TD's US banking arm, under an asset cap after its 2024 anti-money-laundering settlement, is covered separately at /banks/td-bank-us.
Lead bank
The Toronto-Dominion Bank
Total assets (group, as reported, Jul 31, 2026)
C$2,111.9 billion total assets[1]
Charter
Canadian Schedule I bank; federally regulated financial institution supervised by the Office of the Superintendent of Financial Institutions (OSFI), with US banking subsidiaries supervised by the OCC and the Federal Reserve
Headquarters
Toronto, Canada
Flagship platform
Layer 6, TD AI Prism and the agentic RESL model
AI leadership
Raymond Chun · Luke Gee · Maksims Volkovs · Paul Whitehead · Vlad Shpilsky · Sumee Seetharaman · Ajai Bambawale · Kelvin Tran · Rizwan Khalfan · Mohit Veoli · Taylan Turan
- Value target: C$1 billion a year from AI over the medium term, half from cost savings and half from revenue; about C$170 million of AI value was extracted in 2025, C$195 million in the first three quarters of fiscal 2026 against a C$200 million target, and Chun told investors on 9 September 2026 he saw 'sizeable upside' to the C$1 billion.
- Layer 6 (acquired 2018) is the engine: TD AI Prism (June 2025), a causal foundation model, the agentic mortgage model (May 2026) and, from September 2026, a funded collaboration with Cohere at the MaRS Discovery District.
- First wave of scaled AI, as named on the Q3 2026 call: retail end-to-end credit, the software development life cycle and contact centres; TD Insurance leads Canada in AI vehicle-damage estimation and targets C$150 million of claims-cost savings.
- Scale of use: more than 40,000 colleagues on Copilot, more than 7,000 engineers using AI (the most active with a 29% increase in throughput), a generative knowledge-management assistant in more than 1,000 Canadian branches and supporting 20,000-plus client-facing colleagues.
- Benchmark: Evident ranked TD 13th of 50 banks in October 2025, down from ninth, citing competition in innovation and talent; Evident said the dollar targets 'suggest that the bank could well regain ground'.
- Governance: Responsible AI Principles (seven commitments, 30 July 2026) sit inside an AI Risk framework overseen by an AI Risk Management team and a Trustworthy AI team that tests models for fairness and explainability before launch and monitors them after.
- Organisation: Paul Whitehead takes enterprise AI from 4 September 2026; Vlad Shpilsky leads Global Technology and Solutions; Luke Gee is Chief Analytics and AI Officer; COO Taylan Turan is leaving.
- US bank: TD Bank, N.A. and its AML remediation are covered at /banks/td-bank-us; this page covers the group's Canadian and enterprise AI record. The Canadian peer with a similar AI value target is covered at /banks/rbc.
What is Layer 6, TD AI Prism and the agentic RESL model?
Layer 6, the Toronto AI start-up TD acquired in 2018, is the bank's AI research and development centre; its Toronto and New York offices act as TD's AI centre of excellence. Its team of more than 130 built TD AI Prism, a predictive foundation model launched in June 2025 that replaces many single-purpose models and, according to Chief AI Scientist Maksims Volkovs, improved predictive accuracy by 20% to 30%, lead quality by 53% and campaign response rates by more than 40%. In May 2026 Layer 6 and the bank's technology, data, lending and risk teams launched TD's first agentic AI model, which generates application summary memos for mortgage and home equity underwriters and cut pre-adjudication from an average of 15 hours to under three minutes. Around these sit generative knowledge-management assistants for client-facing colleagues (20,000-plus by August 2026), Copilot for more than 40,000 colleagues and AI-assisted coding for more than 7,000 engineers.[6][11][7][3][4]
What has TD Bank Group done on AI, and when?
- Sep 22, 2026
Layer 6 and Cohere: up to C$25 million over three years[10]
A strategic collaboration on knowledge management, security and responsible adoption, with a dedicated Cohere team working alongside Layer 6 at MaRS in Toronto.
- Sep 9, 2026
Chun: 'sizeable upside' to the C$1 billion target[13]
At the Scotiabank Financials Summit the CEO says an AI agent for collections lifted the customer connect rate to between 20% and 25% from 7% and that the mortgage agent is transferable to small business banking and auto finance.
- Sep 3, 2026
Enterprise AI moves under Paul Whitehead[9]
A senior-leadership reshuffle gives Whitehead responsibility for enterprise AI from 4 September, keeps Vlad Shpilsky at the head of Global Technology and Solutions and has COO Taylan Turan leave.
- Aug 27, 2026
- Jul 30, 2026
Responsible AI Principles introduced[8]
Seven enterprise-wide commitments embedded in the AI Risk framework, with model risk and privacy impact assessments and independent oversight reviews; the Trustworthy AI team monitors deployed models.
- Jul 16, 2026
OSFI bulletin on generative and agentic AI[18]
OSFI sets out sound practices for generative and agentic AI under its technology, operational-resilience and third-party guidelines (B-13, E-21, B-10), pointing to E-23 for model risk.
- May 28, 2026
Q2 2026 call: almost C$145 million of value; Copilot for 40,000[4]
Chun reports almost $145 million of AI value at the half-year, over 40,000 colleagues on Copilot, over 7,000 engineers using AI and, in insurance, Canada's first client-facing generative AI assistant from a home and auto insurer.
- May 21, 2026
First agentic AI model launched in mortgages and HELOCs[7]
Layer 6's model classifies documents, calculates income and checks policy before writing an underwriter memo, cutting pre-adjudication from an average of 15 hours to under three minutes; the Trustworthy AI team oversees it.
- Feb 26, 2026
Q1 2026 call: about C$170 million of AI value in 2025[15][11]
The bank says AI delivered about $170 million in 2025; Chun says the generative knowledge-management tool has reached more than 1,000 Canadian branches and the agentic mortgage project is scaling; the CFO targets $150 million of insurance claims-cost savings.
- Dec 4, 2025
2025 annual report: 'Simpler & Faster' technology leveraging AI[2]
The MD&A makes AI a pillar of the strategy, names AI-driven automatic adjudication in TD Auto Finance and Small Business Banking, and records the opening of a Layer 6 GenAI centre in New York and further machine learning and specialised AI in US AML remediation.
- Oct 8, 2025
Evident AI Index: TD falls to 13th[12]
TD drops from ninth to 13th and out of the top ten on competition in innovation and talent, while adding 35% more AI-focused staff year over year.
- Sep 29, 2025
- Sep 11, 2025
OSFI publishes Guideline E-23 on model risk[17]
Canada's prudential supervisor finalises its model-risk guideline, effective 1 May 2027 for federally regulated institutions, with added clarity for AI and machine-learning models.
- Jun 11, 2025
Where does TD Bank Group use AI today?
| System | What it does | Status | Use case |
|---|---|---|---|
| Agentic pre-adjudication for mortgages and HELOCs[7][3][13] | Autonomous agents classify documents, calculate income, check policy and consent and write an underwriter summary; the Q3 2026 call said the first RESL agentic capability was fully scaled and speeding decisions, with the same approach planned for small business and auto finance. | In production | Credit scoring & underwriting |
| Automated adjudication in auto finance and small business[2][3] | The 2025 annual report plans AI to raise automatic-adjudication rates in TD Auto Finance and Small Business Banking; by August 2026 TD Auto Finance Canada had automated about a third of manual funding processes and launched digital income verification. | Rolling out | Credit scoring & underwriting |
| Generative knowledge management for frontline colleagues[15][3][14] | Introduced in contact centres in 2025, deployed across more than 1,000 Canadian branches by February 2026 and supporting over 20,000 client-facing colleagues by August 2026; answers that previously sent colleagues through multiple screens now come in seconds, per the CEO. | In production | Generative & agentic AI |
| TD AI Prism predictive foundation model[6][11] | One model in place of dozens of predictive models, used to personalise marketing; Volkovs reports 20% to 30% better predictive accuracy, 53% better lead quality and a more than 40% lift in campaign response rates. | In production | Generative & agentic AI |
| Copilot and AI-assisted engineering[4][3] | More than 40,000 colleagues use Copilot and more than 7,000 engineers use AI for software development, the most active with a 29% increase in throughput; the software development life cycle is one of three first-wave priorities. | In production | AI-generated code & coding agents |
| Contact-centre AI and collections agent[3][13] | Contact centres are a first-wave priority to simplify routine interactions; a first collections agent lifted the connect rate to 20% to 25% from 7%, per the CEO in September 2026. | Rolling out | Customer-facing chatbots |
| AI in TD Insurance claims[3][15][4] | AI-powered vehicle damage estimation is deployed at scale in Canada and the bank targets $150 million of claims-cost reductions in the medium term through AI, vendor optimisation, fraud detection and process reengineering; a client-facing generative AI virtual assistant launched in insurance in 2026. | In production | Fraud detection |
| Cohere collaboration with Layer 6[10] | Up to C$25 million over three years to apply Cohere's secure enterprise models with Layer 6 research to knowledge management, security and responsible adoption. | Announced | Third-party & vendor AI |
| Responsible AI Principles and Trustworthy AI team[8][7] | Seven commitments, model risk and privacy impact assessments, independent oversight reviews and post-deployment monitoring of fairness, performance and explainability; controls such as retrieval grounding and human oversight apply to colleague-facing assistants. | In production | AI governance (general) |
Use-case links open the tracker's rules-by-use-case matrix: which documents govern each system type.
What has TD Bank Group disclosed in numbers?
| Metric | Value | As of |
|---|---|---|
| Total assets | C$2,111.9 billion[1] | Jul 31, 2026 |
| Medium-term AI value target | C$1 billion a year (C$500 million revenue uplift, C$500 million cost savings)[5][14] | Aug 27, 2026 |
| AI value delivered, fiscal 2026 to date | C$195 million against a C$200 million full-year target[5] | Jul 31, 2026 |
| AI value delivered in 2025 | About $170 million[11][15] | Dec 31, 2025 |
| Evident AI Index 2025 rank | 13th of 50 (ninth in 2024); AI-focused staff up 35% year over year[12] | Oct 8, 2025 |
| Colleagues using Copilot | Over 40,000[4] | May 28, 2026 |
| Engineers using AI for development | Over 7,000; most active up 29% in throughput[4] | May 28, 2026 |
| Client-facing colleagues on generative knowledge management | Over 20,000[3] | Aug 27, 2026 |
| Mortgage pre-adjudication time | From an average of 15 hours to under three minutes[7] | May 21, 2026 |
| People working on AI development | Roughly 2,500[14] | Feb 20, 2026 |
| TD Insurance claims-cost target | $150 million in the medium term[15] | Feb 26, 2026 |
| Layer 6 and Cohere commitment | Up to C$25 million over three years[10] | Sep 22, 2026 |
“Three quarters into the year, we have essentially hit our fiscal 2026 target of $200 million in value from AI.”[3]
Raymond Chun · Group President and CEO · Aug 27, 2026
“I believe AI will transform our operations, make our colleagues more efficient, our processes faster and our products and services better.”[4]
Raymond Chun · Group President and CEO · May 28, 2026
“What I am seeing with agentic AI capabilities is something that I have not seen with automation, I have not seen in digital”[13]
Raymond Chun · Group President and CEO · Sep 9, 2026
“We're building a hybrid future where our colleagues and AI work together to help our clients get to a 'yes' faster on some of their most important decisions.”[7]
Luke Gee · Chief Analytics and AI Officer · May 21, 2026
“Operating one foundation model instead of dozens of individual predictive models allows us to more efficiently implement the standards and guardrails set by our 'Trustworthy AI' team”[11]
Maksims Volkovs · SVP and Chief AI Scientist, TD · Jun 1, 2026
“suggest that the bank could well regain ground”[12]
Alexandra Mousavizadeh · Co-founder and CEO, Evident Insights · Oct 8, 2025
Who runs AI at TD Bank Group?
Luke Gee
Chief Analytics and AI Officer[7]
Paul Whitehead
Senior Executive Vice President, Global Corporate Services; responsible for enterprise AI (from 2026-09-04)[9]
Sumee Seetharaman
Head of Artificial Intelligence and Machine Learning Practice[8]
Ajai Bambawale
Chief Risk Officer[8]
Kelvin Tran
Chief Financial Officer[15]
Rizwan Khalfan
Executive Vice President and Vice Chair, Strategic Growth, Innovation and Partnerships[10]
Mohit Veoli
Senior Vice President, Real Estate Secured Lending[7]
Which regulators govern TD Bank Group's AI?
| Authority | Why it matters here | Documents |
|---|---|---|
| OSFI | TD's home prudential supervisor. Guideline E-23 on model risk management takes effect for federally regulated institutions on 1 May 2027 and adds clarity for AI and machine-learning models; OSFI's July 2026 bulletin sets sound practices for generative and agentic AI, directly relevant to TD's agentic lending model. | |
| OCC | TD Bank, N.A., the group's US bank, is a national bank under an OCC consent order; group AI platforms used there are examined inside that remediation (covered at /banks/td-bank-us). | OCC Bulletin 2026-13 OCC Bulletin 2023-17 |
| Federal Reserve | TD's US holding company is Federal Reserve supervised, so model-risk guidance such as SR 26-2 reaches AI models built in Toronto and used by US entities. | SR 26-2 SR 23-4 |
What does the public record suggest about TD Bank Group's AI strategy?
Analysis by BankingNewsAI from the sources cited on this page. Observations, not advice.
01
A dollar target reported every quarter
Few banks give a running figure for AI value. TD reports it against a fiscal-year target (C$195 million of C$200 million by Q3 2026) and a medium-term C$1 billion goal, which makes slippage or upside visible, and Chun has already said he may have underestimated the upside.
02
A lab-first bank that dropped in the rankings
TD has had Layer 6 since 2018 and still fell from ninth to 13th on Evident's index as peers moved faster on innovation and talent. Evident's own reading is that the dollar targets could let TD regain ground; the next index will test that.
03
Agents that can be reused
The mortgage agent is being extended to small business and auto finance, and the CEO's 'build once and use many times' principle points to a platform pattern rather than a series of one-off tools. Reuse also concentrates model risk in the shared components.
04
Accountability moved to a corporate-services executive
Placing enterprise AI under Global Corporate Services in September 2026, alongside transformation and marketing, while technology stays with Global Technology and Solutions, splits delivery from enterprise direction.
What is TD's AI value target?
TD aims to generate C$1 billion a year of value from AI over the medium term, half from cost savings and half from revenue, a target Chun set at the September 2025 Investor Day. By the third quarter of fiscal 2026 it had delivered C$195 million against a C$200 million target for the year.
What is Layer 6?
Layer 6 is the Toronto AI company TD acquired in 2018. It is the bank's AI research and development centre, with offices in Toronto and New York, and built TD AI Prism, a causal foundation model and the bank's first agentic AI model.
How does TD rank for AI?
TD ranked 13th of 50 banks in the 2025 Evident AI Index, down from ninth in 2024, according to the Financial Post's report of the index. Royal Bank of Canada ranked third; its record is at /banks/rbc.
Does TD use AI in the United States?
Yes. TD Bank, N.A. is covered separately at /banks/td-bank-us, including AI in anti-money-laundering monitoring under the OCC consent order. The group's Layer 6 opened a New York office to support US demand.
Who is responsible for AI at TD?
Luke Gee is Chief Analytics and AI Officer and Maksims Volkovs is Chief AI Scientist at Layer 6. From 4 September 2026 Paul Whitehead, Senior Executive Vice President, Global Corporate Services, is responsible for enterprise AI.
- TD Bank Group Third Quarter 2026 Report to Shareholders (Form 6-K, Exhibit 99.1)
- TD Bank Group 2025 Annual Report: Management's Discussion and Analysis (Form 40-F, Exhibit 99.2)
- TD (TD) Q3 2026 Earnings Call Transcript
- TD (TD) Q2 2026 Earnings Call Transcript
- TD Bank Unlocks $141 Million in AI Value Months Ahead of Schedule
- TD Announces Launch of Groundbreaking Predictive Foundation Model
- TD Launches Agentic AI to Transform Real Estate Secured Lending from End to End
- TD strengthens Its Responsible AI Principles to support trust in AI innovation
- TD Bank Group announces senior leadership appointments to further accelerate strategy
- TD announces $25 million strategic relationship with Cohere to support AI adoption
- #4 Maksims Volkovs drives TD Bank's AI transformation
- RBC retains top spot, TD stumbles as AI race in banking intensifies
- Banks say AI is allowing them to recover unpaid loans, cut call centre volumes and save workdays
- How AI is Permeating Work Throughout TD Bank, and Lessons Learned
- TD eyes $150M in cost reductions – with help from AI
- TD wants to get 'back to winning'
- Guideline E-23 – Model Risk Management (2027) - Letter
- Generative and Agentic Artificial Intelligence: Implications for Technology, Cyber Security, and Operational Resilience
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