What is TD Bank's AI strategy?
TD sets its AI strategy at group level and puts a number on it: at its September 29, 2025 investor day it targeted C$1 billion a year of AI value over the medium term, roughly half revenue uplift and half cost savings, from predictive, generative and agentic AI built mostly in-house by Layer 6, the lab it bought in 2018. The deck counted more than 2,500 AI-related roles in house and set a goal of moving from 20% of colleagues enabled with AI agents to 100%. Three quarters into fiscal 2026 TD said it had 'essentially hit' the year's C$200 million target (C$195 million). For TD Bank (U.S.), which operates under the asset limit from the 2024 anti-money-laundering settlement, the investor-day plan was to 'deploy ~10 AI use cases to automate routine operations' and take about $200 million of cost out through AI-led process change, alongside machine learning in AML transaction monitoring. The first agentic model (May 2026) cut mortgage pre-adjudication from 15 hours to under three minutes, and the CEO says the capability can transfer to US lines. TD ranked among the top 10 of the 2026 Evident AI Index. Enterprise AI moved under Paul Whitehead in September 2026.[1][2][3][4][5][6][7][8][9][10]
Data as of Oct 16, 2026 · TD profile updated Oct 13, 2026 · 24 sources cited on this page · 140 banks profiled on this site · Markdown
What AI targets has TD set, and what has it delivered?
Group figures in Canadian dollars unless stated. US-segment figures as presented for U.S. Retail.
| Item | Target or result | Scope | Date |
|---|---|---|---|
| AI value | C$1 billion a year medium term: about C$500 million annualised revenue uplift and C$500 million annualised cost savings | Group | September 29, 2025[1][4] |
| AI value delivered | About 75 use cases, $170 million in fiscal 2025; C$195 million in the first three quarters of fiscal 2026 against C$200 million | Group | August 27, 2026[11][5] |
| Colleagues enabled with AI agents | 0% (2022), 20% (2025), 100% medium-term target | Group | September 29, 2025[1] |
| AI talent | More than 2,500 AI-related roles in house (data design and engineering, data science, advanced analytics) | Group | September 29, 2025[1] |
| Canadian Personal Bank AI value | About $300 million: ~$200 million revenue and ~$100 million cost; agentic RESL processes +40% capacity | Canada | September 29, 2025[1] |
| US AI use cases | Deploy ~10 AI use cases to automate routine operations; core process transformation via AI worth ~$200 million of cost takeout | U.S. Retail | September 29, 2025[1][2][12] |
| US developers on GitHub Copilot | 1,800, with 30-40% technology-capacity gains; voice AI agent aimed at ~50% of calls | U.S. Retail | September 17, 2026[13] |
| Claims costs | $150 million reduction targeted with AI; 15-minute auto-claim settlement and 90% shorter home-claims cycle cited | Insurance (Canada) | 2025-2026[14][1] |
How does AI fit TD Bank's US strategy?
At the 2025 investor day the U.S. Retail segment listed 'modernize technology and harness AI for productivity' among its priorities and set out four AI themes: automating operational and analytical processes, knowledge-management solutions, a real-time data activation and insights engine, and a cloud-native, modular core architecture.[1]
Salom told investors the US bank would 'purposely invest in digital, data, AI and technology infrastructure', move to 'a scalable, cloud-native, modular environment', and prioritise AI in three areas: automating operational processes, knowledge management for stores and call centers, and real-time data insights across sales and service channels. He said AI-enabled underwriting models in Bankcards let TD extend credit to more clients than traditional methods.[2]
AML remediation is the US bank's first priority, and AI sits inside it. The deck reported 'first phases of specialized AI and Machine Learning capabilities' and a new transaction-monitoring platform; US CEO Leo Salom said in May 2026 that the AML programme now runs on a monitoring system with embedded machine learning and AI enhancements.[1][6]
Layer 6 opened a New York office in April 2025 to bring generative-AI expertise in-house for the US bank, and the US analytics and AI head, Ted Paris, has said agents can 'truly transform operations' if fitted to the bank's environment.[15][16]
The CEO's five AI 'big rocks' (September 2026) are the contact centre, end-to-end retail credit, fraud, AML and KYC, and advisor productivity; he said the agentic mortgage capability is transferable to the US.[8]
What have TD's executives said about AI, and when?
| Date | Who | What was said |
|---|---|---|
| September 29, 2025 | Leo Salom, CEO, TD Bank (U.S.) | AML remediation has 'implemented the first phase of our AI and machine learning solutions'; AI priorities are operations automation, knowledge management for stores and call centers, and real-time data insights, worth US$200 million of cost reduction[2] |
| February 26, 2026 | Leo Salom, CEO, TD Bank (U.S.) | 'We implemented machine learning models in our transaction monitoring system last year, and additional models will be deployed'[4] |
| August 27, 2026 | Raymond Chun, Group CEO | 'Three-quarters into the year, we have essentially hit our fiscal 2026 target of 200 million [Canadian dollars] in value from AI'[5] |
| September 9, 2026 | Raymond Chun, Group CEO | With agentic AI 'you can finally truly go end to end and reimagine entire processes'[8] |
| September 22, 2026 | Kiran Vuppu, US CIO | 'It really comes down to ensuring you have the right guardrails and observability in place'[17] |
| October 6, 2026 | Sumee Seetharaman, Head of AI and ML Practice | 'At TD, AI innovation and responsible AI are not separate conversations'[9] |
What does the TD profile record on this topic?
The rows below are the entries of the TD AI strategy profile that bear on this page, as of Oct 13, 2026; the profile holds the full record of 39 dated moves, 18 use cases and 55 sources.
| Date | Move | Detail | Source |
|---|---|---|---|
| Sep 9, 2026 | Chun at the Scotiabank summit: five AI 'big rocks' and a collections agent | Contact centre, end-to-end retail credit, fraud, AML and KYC, and advisor productivity; mortgage funding cost to fall from about C$187 to about C$47; collections agent lifts connect rates from 6-7% to 20-25%; he said the capability can move to the US. | [8] |
| Sep 4, 2026 | Enterprise AI moves under Paul Whitehead; Taylan Turan leaves | Whitehead takes enterprise AI and global corporate affairs on top of client experience and transformation; the Fintech Futures account says Shpilsky now owns AI strategy, data, fraud operations and cyber resilience within technology. | [10][18] |
| Aug 27, 2026 | Q3 fiscal 2026 call: first wave of end-to-end AI in credit, software and contact centres | The CEO names retail end-to-end credit, the software development life cycle and contact centres as the first wave; AML remediation expense of about $550 million for the year. | [19][20] |
| Aug 27, 2026 | Fiscal 2026 AI value target essentially hit | C$195 million (about US$141 million) against a C$200 million target three quarters in; the CEO said the target was 'essentially' hit. | [5][21] |
| May 28, 2026 | Q2 fiscal 2026 call: US AML runs on AI-enhanced transaction monitoring | Salom: new monitoring system with embedded ML and AI, new KYC platform and improved customer risk rating model; group: over 40,000 colleagues using Copilot (the call did not name the product's vendor), over 7,000 engineers using AI, mortgage pre-adjudication cut from about 15 hours to 3 minutes. | [6] |
| Feb 26, 2026 | Q1 fiscal 2026 call: US ML models in transaction monitoring, new KYC platform live | Salom: the new KYC platform went live to business users that month and more ML models follow in coming quarters; Chun: first scaling of agentic AI in real-estate lending, C$1 billion AI target split C$500 million revenue and C$500 million expense, with upside beyond it. | [4][22] |
| Dec 4, 2025 | Q4 fiscal 2025 call: majority of US AML remediation actions complete | Salom: remediation includes machine learning enhancements to transaction monitoring and advanced risk detection; fiscal 2025 cost $507 million; Chun cited about 75 AI use cases and $170 million of value in 2025. | [23][11] |
| Sep 29, 2025 | US investor day: $750 million of structural cost cuts, about $200 million from innovation | Salom's plan for the US business includes data management and AI development as a source of about $200 million of the savings, alongside branch pruning and lower governance spending. | [12] |
| Sep 29, 2025 | Investor day: C$1 billion a year of AI value targeted | Alongside C$2–2.5 billion of annualised savings and reinstated financial targets. | [3][24] |
| Apr 22, 2025 | Layer 6 opens a New York office | To bring gen-AI expertise and delivery in-house for the US bank, per Leo Salom. | [15] |
How much value does TD expect from AI?
C$1 billion a year over the medium term, set at the September 2025 investor day and split roughly C$500 million of revenue uplift and C$500 million of cost savings. For fiscal 2026 the target was C$200 million; CEO Raymond Chun said in August 2026 that TD had essentially hit it, with C$195 million after three quarters.
What is TD Bank (U.S.) doing with AI?
The US bank planned about 10 AI use cases to automate routine operations and around $200 million of cost takeout from AI-led process change. It runs machine learning and AI in AML transaction monitoring, has 1,800 developers on GitHub Copilot, a contact-centre knowledge assistant, and a vendor voice AI agent aimed at about half of incoming calls.
Who leads AI at TD?
Paul Whitehead took responsibility for enterprise AI on September 4, 2026. Vlad Shpilsky heads Global Technology and Solutions; Maksims Volkovs is chief AI scientist at Layer 6. In the US, Ted Paris heads analytics, intelligence and AI and Kiran Vuppu is US CIO. Luke Gee is chief analytics and AI officer.
How does TD rank on AI?
TD said in October 2026 that it ranked among the top 10 banks globally and No. 2 in Canada in the 2026 Evident AI Index, which ranks 50 large banks, and No. 4 for responsible AI and No. 5 for AI transparency. Banking Dive reported in 2025 that TD produced 4% of bank AI research publications in 2024.
Does the US asset cap affect TD's AI plans?
TD presents AI as a growth and efficiency lever that does not need a bigger balance sheet. The 2025 annual report put headroom to the US asset limitation at about US$52 billion; the US plan relies on cost takeout, AML automation and productivity rather than balance-sheet growth.
- TD Investor Day 2025: full presentation
- TD Bank Group Investor Day 2025 conference call transcript: Leo Salom, U.S. Retail
- TD wants to get 'back to winning'
- TD Bank Group Q1 2026 Earnings Conference Call transcript
- TD Bank Unlocks $141 Million in AI Value Months Ahead of Schedule
- TD (TD) Q2 2026 Earnings Call Transcript
- TD expands agentic AI across mortgage operations to make banking faster, simpler and more human
- TD Bank at Scotiabank summit: profit gains, AI push lift outlook (transcript)
- What's behind AI you can trust?
- TD Bank Group announces senior leadership appointments to further accelerate strategy
- TD Bank US head of AI weighs in on agents
- TD touts 'unparalleled opportunity' after major AML scandal
- TD Bank Targets 100 U.S. Branches as AML Remediation Continues
- TD eyes $150M in cost reductions – with help from AI
- TD Announces Opening of New Layer 6 Office in New York City
- TD's US head of AI weighs in on agents
- Banks batten down the hatches for rogue AI agent swarms
- TD Bank Group shakes up leadership to consolidate tech, AI, and commercial strategy
- TD (TD) Q3 2026 Earnings Call Transcript
- TD Bank Group Third Quarter 2026 Report to Shareholders (Form 6-K, Exhibit 99.1)
- TD Bank Group Reports Third Quarter 2026 Results
- TD Bank Group First Quarter 2026 Report to Shareholders (Form 6-K, Exhibit 99.1)
- TD has completed 'majority' of US AML remediation
- TD Bank Brings Back Financial Targets, Looks to Return Billions to Shareholders
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