Canada

Like a river with still pockets, flowing eddies and rushing currents, the still phase is giving way. Recent PYMNTS survey data shows a sharp shift from sideline interest to real-world action — and it’s happening fast. On Wednesday, enterprise planning platform Board said it was launching tools and services for finance, supply chain and merchandising planning that were developed with Microsoft Foundry using Microsoft Azure’s agentic AI.

For the most recent edition of the CAIO Report, PYMNTS Intelligence surveyed 60 chief product officers at U.S. businesses bringing in at least $1 billion a year. The study, completed last November, explored how they’re thinking about and using agentic AI.

Last August, more than half of companies (52%) said they were just “considering” or “exploring” agentic AI. By November, that number had plunged to 30%. In other words, a big chunk of the enterprise market moved out of the window-shopping phase.

What replaced the passive interest is hands-on implementation. In November, nearly 1 in 4 CPOs reported that they were either piloting agentic AI or fully using it in production processes, up from just 3% in August. Actual usage and piloting were evenly split: Just over 1 in 8, or 12%, are testing agents out, and another 12% have already made them part of their daily operations.

The upshot is that in just three months, the number of enterprises using or testing agentic AI spiked sevenfold.

But while some companies are sprinting ahead, others remain harder to sway. About half of companies seem totally uninterested in agentic AI, which can autonomously make real-world decisions and perform tasks with minimal human oversight.

In November, 45% of CPOs said they didn’t have any plans to adopt the technology any time soon. That portion might be a steep drop-off from June, when 90% said the same, but it’s entirely unchanged from August. As with polarizing foods like broccoli, there’s not a lot of middle ground: Companies are either racing toward autonomous systems or sitting agentic AI out — for now — altogether.

It’s not just one or two industries embracing the technology. Adoption is rising across every sector. Goods and manufacturing enterprises saw one of the biggest jumps in implementation, going from almost no usage last August to nearly 1 in 5 firms using or piloting the technology by November. Services companies followed a similar path, with adoption jumping fivefold, from 4.3% in August to 25% three months later. Technology companies lead the pack, with 31% piloting or using AI agents.

One the one hand, the agentic AI digital divide between industries is shrinking quickly. On the other hand, the divide between enthusiasts and skeptics remains entrenched.

Some companies are showing off their agentic AI ventures.

Earlier this month, grocery giant Kroger said it would introduce Google’s Gemini agent tools to allow shoppers to convert a “I want to prepare vegan tomato soup” request into a shopping cart of ingredients through a single click. Walmart announced an agentic commerce partnership with Google that will take consumers from online shopping to purchase to delivery.

Rideshare and delivery firm Uber is using agentic tools it developed internally to improve employees’ workplace communications in Slack. The tool has reduced what it called “incorrect advice” in Slack messages by 60%.

BMW is using a multi-agent system to boost efficiency across its manufacturing plants, where specialized autonomous actors collaborate. Paper goods manufacturing giant Georgia-Pacific is doing the same to modernize operations across its plants.

In financial services, JPMorgan Chase has started deploying agents internally to automate labor-intensive tasks, with one agent able to produce an investment banking deck in 30 seconds.

“The broad vision that we’re working towards is one where the JPMorgan Chase of the future is going to be a fully AI-connected enterprise,” Chief Data Analytics Officer Derek Waldron told CNBC during a demonstration.

Capital One is using AI agents as “digital concierges” for car buyers and dealerships that allows them to compare vehicles and schedule appointments with sales representatives. No allowing an agentic bot to buy a car for you just yet.

Instead of running isolated pilots, the company, whose brands include Lysol and Mucinex, rebuilt its data infrastructure first, then deployed AI agents and analytics tools that now support marketing, sustainability and enterprise decision-making.

Data First: Building an AI-Ready Decision Layer

Reckitt’s AI strategy rests on a centralized data platform built on Microsoft Azure, which unified consumer, sales, media and operational data that had previously been fragmented across brands and regions. Leadership concluded early that deploying generative AI on top of inconsistent data would amplify errors rather than improve decisions.

Reckitt embedded Power BI and Copilot capabilities into its analytics stack, allowing marketers and insights teams to query enterprise data using natural language rather than relying on static dashboards or centralized reporting teams.

According to Microsoft’s customer case study, Reckitt saw a 60% improvement in marketing efficiency after deploying these tools, while cutting time spent on routine analytical tasks by up to 90%. Internal testing showed that AI-generated insights performed as well as or better than traditional research outputs when evaluated against historical benchmarks.

Elaine Rodrigo, Reckitt’s chief insights and analytics officer at Reckitt, told Microsoft that the goal was to let teams move from data to decisions faster, while keeping humans accountable for final judgment. The company deliberately avoided using AI to make autonomous decisions, instead using it to surface correlations, anomalies and performance signals that teams could act on.

“The insights generator development journey has been nothing short of remarkable,” she said. “The purpose is to empower our marketers; to ensure that every idea they develop starts from insight.”

Reckitt extended this data-first approach into marketing operations through its partnership with TTEC Digital, integrating AI-driven insight generation into campaign planning, execution and measurement workflows across global teams.

Scaling AI Across Global Marketing

With its data foundation in place, Reckitt moved to agentic AI. By 2025, the company had rolled out AI agents to more than 500 marketers globally, embedding them into daily workflows rather than isolating them in innovation teams.

According to Digiday, Reckitt measured 20% to 40% time savings in brand tracking and performance analysis after deploying these tools.

What differentiates Reckitt’s rollout is how narrowly it targeted use cases. Teams conducted time-and-motion studies to identify where marketers spent the most time on low-value tasks, then deployed AI specifically to eliminate those steps. Executives told Digiday that repeated pilots often become a dead end, creating organizational fatigue without delivering scale. Reckitt instead designed systems with governance, training and deployment in mind from the start.

Internally, the company framed AI as a capacity multiplier rather than a headcount reducer. By automating analysis and reporting, the company pushed marketers to spend more time on interpretation, creative strategy and consumer understanding.

Applying AI to Emissions and Product-Level Data

Reckitt’s most technically demanding AI deployment sits outside marketing. Scope 3 emissions account for the majority of the company’s carbon footprint, but traditional measurement relied on representative averages that limited actionable insight.

Working with CO2 AI and Quantis, Reckitt applied AI-driven automation to calculate product-level emissions for approximately 25,000 individual products. The system matches activity data with emissions factors at scale, increasing accuracy by an estimated 75x compared with prior approaches.

What once required months of manual modeling now takes minutes. More granular data allows Reckitt to identify which ingredients, suppliers and packaging choices drive emissions, enabling targeted interventions aligned with its 2030 and 2040 net-zero targets.

Together, these deployments mean Reckitt now runs AI across more than 500 marketers, draws from roughly 35 integrated data sources and analyzes 25,000 products at the SKU level.

Canada’s payments landscape is being recast at high speed, and the once-predictable routines of corporate treasurers are being pushed into the digital fast lane.

The change is as much cultural as technological for the practitioners who sit at the center of cash management.

“I have been on the ground here in Canada … for over 25 years,” Lyndsay Langford, Bank of America’s head of Global Payment Solutions for Canada, told PYMNTS. “In the past, we had wires, EFT and checks. Today, clients demand faster payments, less friction and richer remittance data.”

Those demands have forced treasury teams to abandon manual processes and build real-time visibility into positions and forecasts. The pandemic “shifted us toward a more digital mindset,” accelerating projects that once sat on multiyear road maps, she said.

That shift is playing out against a sweeping upgrade of Canada’s underlying rails. Payments Canada began its modernization plan in 2016, replacing the legacy wire system with Lynx and preparing the country’s first real-time rail (RTR).

“We’re heavily focused right now as a country on the buildout and the launch of real-time payments,” Langford said.

Once live, RTR will settle payments in seconds, carry data-rich messages and eventually enable QR-code requests for payment and cross-border links to other real-time payment methods. Interac — once a person-to-person tool — now supports near-instant business-to-consumer disbursements. Two years ago, Bank of America folded the channel into its global digital disbursements platform alongside Zelle and PayPal.

The glue that makes many of those ambitions useful to a treasurer is ISO 20022, a global messaging standard that expands the amount of information that can travel with each transaction. Bank of America has been running a formal ISO migration program since 2019 and has already completed “over 10 clearing migrations around the world,” Langford said.

Early Canadian adopters are exploiting the richer data to “remove a lot of manual work from the reconciliation process,” she said because ERP systems can auto-match invoices to payments the moment funds hit. The bank is building direct ISO feeds into corporate accounting platforms to maximize straight-through processing.

Risk Mitigation

Yet data alone does not erase the uncertainty of sending money across borders. Pandemic shocks, geopolitical tension and exchange rate swings have only amplified that uncertainty.

“Risk mitigation for cross-border payments is rising to the top of the priority list,” Langford said.

Bank of America’s answer includes a guaranteed foreign exchange (FX) rate solution that allows clients to lock in an FX rate for up to a year — “market leading” in tenor, she said — and CashPro Forecasting, a machine learning tool that predicts liquidity needs so companies can “make more intelligent working capital decisions” and pivot when volatility strikes.

Speed, meanwhile, is not always paramount.

“We want to make sure the options we put in front of clients are cost‑effective and fast where speed is important,” Langford said.

Still, the bank also aims for a globally consistent user experience so a Canadian treasurer responsible for Asia or Europe sees the same interface and controls.

Much of that experience is delivered through CashPro, Bank of America’s digital treasury suite used by more than 40,000 corporate clients worldwide. When the bank combined its Global Transaction Services and Enterprise Payments teams under the banner of Global Payment Solutions in 2023, it created a pipeline for ideas developed in the retail bank to flow into the commercial platform. The most visible import is CashPro Chat, built on the artificial intelligence backbone that powers Erica, Bank of America’s consumer virtual assistant. The tool lets treasurers ask questions and receive 24/7 answers from an “intelligent virtual service advisor,” escalating more complex issues to human specialists, Langford said.

“The more we collectively use it, the more it learns and grows,” she said.

Integration has also sped product rollouts. A U.S. electronic payments collections service that lets businesses accept card and ACH payments will soon debut in Canada after clients “raved about it for years,” she said, illustrating how the new structure “allows us to consider how investments can be leveraged more broadly.”

Listening to the Pros

Listening to clients is as important as engineering. CashPro advisory boards meet regularly “with clients around the world, and that includes right here on the ground in Canada,” ensuring new features target the highest priority wishes, Langford said.

The next inflection point is already on the horizon. The Retail Payment Activities Act will allow nonbank providers to participate directly in the RTR, intensifying competition and giving corporates more ways to customize how they pay and get paid.

“With this complexity, … the goal is to make things easier as they become more complex,” Langford said.

She said she expects that competitive pressure — and the data fabric of ISO 20022 — will trigger a wave of innovation in financing, supply‑chain optimization and value-added analytics.

“The real-time rail will be the platform for future innovation in Canada,” Langford said. “It’s going to increase competition, and when you have increased competition that benefits all Canadians — consumers and commercial entities alike.”

For treasurers, the tools are arriving quickly, and those who master them will turn liquidity management from a back-office chore into a source of strategic advantage.

“We need to be at the table — and we are at the table — to ensure our clients’ voices drive the next three- to five-year journey,” Langford said.

The pay later company and the travel search engine have offered services to travelers in the United States since 2023 and are now bringing their collaboration to Canada, Kayak said in a Thursday (May 22) press release.

“Consumers are increasingly turning to Affirm when booking their flights, hotels, rides and more as flexible payment options remain a top priority for travelers across Canada,” Affirm Chief Revenue Officer Wayne Pommen said in the release. “This expansion with Kayak is a natural next step for our long-standing partnership as we look to offer even more travelers peace of mind when paying for their next trip using Affirm.”

By choosing Affirm at checkout on Kayak’s Canadian website, approved travelers can split the cost of flights, accommodations, and car rentals or car sharing into monthly payments, according to the release.

Affirm already works with several other travel companies, including Booking Holdings brands Agoda, Booking.com and Priceline, which itself owns Kayak.

Kayak Chief Product Officer Matthias Keller discussed with PYMNTS Thursday the company’s launch of Kayak.ai, a conversational travel booking assistant powered by generative artificial intelligence.

“This is not just a chatbot,” Keller said. “It’s a ChatGPT just built for travel. You can ask any travel question, and in a conversation, you get real-life rates that are also bookable on Kayak.”

Kayak.ai was created to emulate natural human conversation and the kind of planning a traveler might do with a knowledgeable agent or friend. It isn’t fully automated, but future versions of the assistant will allow for seamless and even semi-autonomous bookings within the chat itself, Keller said.

“Right now, it’s more like an attended booking within the chat,” he said. “You’ll still see what you’re booking, confirm the price, and maybe enter your credit card. But over time, this could get more and more semi-automated. Maybe you leave your details, and the booking happens in the background.”

Meanwhile, Kayak’s integrations with major airlines, hotel chains and global distribution systems (GDS) offer it a competitive edge, Keller said.