| Constellation Research

Nvidia outlines Google Quantum AI partnership, Foxconn deal

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Nvidia said that it is working with Google Quantum AI to design quantum computing AI processors. The quantum computing partnership with Google was part of a series of Nvidia announcements at the SC24 conference in Atlanta.

According to Nvidia, Google Quantum AI is using the Nvidia Cuda-Q platform to simulate designs. Google Quantum AI uses Cuda-Q, a hybrid quantum-classical computing platform and the Nvidia Eos supercomputer to simulate the physics of its quantum processors.

Hybrid quantum computing is moving to the forefront since there's the potential to solve complex commercial problems sooner. Specifically, Google Quantum AI generates simulations based on the 1,024 Nvidia H100 Tensor Core GPUs in the Nvidia Eos supercomputer.

The quantum partnership with Google was one of the main items outlined during Nvidia CEO Jensen Huang's keynote. Huang highlighted AI applications for science including drug discovery, climate forecasting and quantum computing.

"AI will accelerate scientific discovery, transforming industries and revolutionizing every one of the world’s $100 trillion markets," said Huang.

In addition, Nvidia said it is scaling production via a partnership with Foxconn. The company also announced the general availability of the Nvidia H200 NVL, a PCIe GPU based on the Nvidia Hopper architecture for low-power, air-cooled data centers.

Other Nvidia items at SC24 include:

CorrDiff NIM and FourCastNet NIM, two new microservices for climate change modeling and simulation on the Earth-2 platform. The Earth-2 platform is a digital twin for simulating weather and climate conditions.
cuPyNumeric library, which uses GPUs to accelerate NumPy for applications in data science, machine learning and numerical computing.
Nvidia launched the Nvidia Omniverse Blueprint for real-time development of digital twins.
Nvidia highlighted its open-source BioNeMo Framework, which is used for drug discovery. The company also launched DiffDock 2.0, which is a tool for predicting how drugs bind to target proteins.
The company also highlighted the Nvidia Alchemi NIM microservice which couples generative AI to chemistry.

More on Nvidia:

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GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

The gap between generative AI's "build it and they will come" folks and the enterprises looking for actual business value may be widening. The next year will be interesting for generative AI trickledown economics.

First, let's touch on the boom market.

Nvidia will report third quarter earnings Nov. 20 and rest assured it'll be the most important report of the year (again). Funny how we say that about Nvidia every quarter. Demand will remain off the charts and the hyperscalers and countries are begging to spend billions on Nvidia's AI accelerators. Analysts are looking for non-GAAP third quarter earnings 74 cents a share on revenue of $32.94 billion, up from $18.12 billion a year ago.
CoreWeave, the AI hyperscale cloud provider, just closed a minority investment round of $650 million led by Jane Street, Magnetar, Fidelity and Macquarie Capital, with additional participation from Cisco Investments, Pure Storage, BlackRock, Coatue, Neuberger Berman and others. CoreWeave is valued at about $23 billion, according to Reuters.
Softbank Corp. will be among the first to build out an AI supercomputer using Nvidia's Blackwell platform. Softbank will get Nvidia's first Nvidia DGX B200 systems with plans to build out a Nvidia DGX SuperPOD supercomputer. Softbank floated debt to be first in line.

And on it goes. You could round up the AI building boom weekly. All of the hyperscalers are spending big on AI factories. Microsoft, Amazon, Meta and Alphabet all said capital spending on AI will continue to surge.

Microsoft CFO Amy Hood said:

"Roughly half of our cloud and AI-related spend continues to be for long-lived assets that will support monetization over the next 15 years and beyond. The remaining cloud and AI spend is primarily for servers, both CPUs and GPUs, to serve customers based on demand signals.”

I couldn't help but think of what Oracle CTO Larry Ellison said on the company's most recent earnings call. Ellison said: "I went out to dinner with Jensen (Huang) and Elon (Musk) at Nobu in Palo Alto. I would describe the dinner as begging Jensen for GPUs. Please take our money. In fact, take more of it. You're not taking enough of it. It went well. The demand for GPUs and the desire to be first is a big deal."

We know the drill. The tech industry is betting that the real risk is not plowing billions (if not trillions) on the AI buildout. I'd recommend reading a contrarian argument about irrational AI data center exuberance. but your guess is as good as mine on the timing.

The disconnect between the AI buildout side and the business value side may be widening. 2025 is going to be a year of business value following 2024, which was about genAI production following proof of concepts in 2023. Yes, enterprises are going to need real gen-AI budgets in 2025, change management and returns.

The art, ROI and FOMO of 2025 AI budget planning

Bottom line: The trickledown economics of generative AI at the beginning of 2024 hasn’t exactly trickled down beyond the infrastructure layer.

Can vendors monetize genAI value?

For real genAI value to occur, the application layer will need to be built out. LLM players, think Anthropic and OpenAI, are going to need apps to go with their models. Vendor monetization models are a bit fuzzy now. ServiceNow is clearly benefiting, but other software companies are seeing mixed results. Here's a sampling of recent comments and there will be a bunch more as SaaS earnings season kicks off soon.

Monday CEO Eran Zinman:

"Total AI actions grew more than 250% in Q3 compared to Q2. And the AI blocks grew 150% from Q2. So overall, we see more and more customers adopt those blocks, people incorporate them into their automation. They create a lot of processes within the product that involves AI within that. And over time, we are planning to roll out the monetization tied with AI, where we're going to generate clear and efficient value for our customers."

Zinman was then asked whether 2025 will be the year for AI monetization. "We don't have a specific date, but it might be in 2025," said Zinman. "But we can't commit to that."

Translation: Monday needs to show value to get the money.

Hood danced around monetization, but did say that analysts need to think about the long game.

"We remain focused on strategically investing in the long-term opportunities that we believe drive shareholder value. Monetization from these investments continues to grow, and we're excited that only 2.5 years in, our AI business is on track to surpass $10 billion of annual revenue run rate in Q2. This will be the fastest business in our history to reach this milestone."

Infosys CEO Salil Parekh said:

"Any of the large deals that we’re looking at, there’s a generative AI component to it. Now, is it driving the large deals? Not in itself, but it’s very much a part of that large deal."

SAP CEO Christian Klein said Klein said about 30% of SAP's cloud orders included AI use cases.

Simply put, if you follow the money you'd trip once you got past the infrastructure layer and to the applications. Enterprise software vendors haven’t figured out what customers will pay for.

The beginning of genAI user fatigue?

What about the users? Well, that genAI love affair has become tiresome too.

A Slack survey found that generative AI adoption among desk workers went from 20% in September 2023 to 32% in March 2024 and then hit a wall. Today, 33% of desk workers are using generative AI, according to Slack. The survey also found that excitement around AI is cooling and drop from 47% to 41% from March to August. Slack cited uncertainty, hype and lack of AI training for the decreases. Another possible reason I'll throw in: There's a copilot sprawl that's adding to costs for the enterprise and distraction for the worker.

This genAI adoption from employees is a bit chicken or egg. If enterprises balk at spending on various copilots, they're going to limit access. Or there's just not enough value for employees yet. I can't tell you how many times I've tuned out Microsoft Copilot, Google Gemini and other overly helpful AI. Dear LLM, if you're useful I'll reach out. Until then don't annoy me.

It’s on you CxOs

These moving parts—genAI to agentic AI, FOMO, data strategies, vendor promises and change management—are going to be challenging to navigate for CxOs. I mined my recorded conversations in 2024 to surface common AI themes from CxOs. Here’s a look:

GenAI is a tool instead of a magic bullet. CxOs are looking to integrate AI into processes and workflows and use the technology as an excuse to revamp them. Agentic AI is promising, but full automation will require orchestration and process groundwork.

Change management is everything. Change management has turned up in multiple conversations throughout 2024. Implementing AI is really about transforming how people work and interact with the technology. GenAI also will create organizational challenges. CxOs also need strong change management approaches to address employee fears about job displacement.

Governance and control matters. Governance is becoming a key theme as genAI projects move to production.

Data strategy. Enterprises are still working on their ground games when it comes to data. That work will continue for many in 2025.

Costs. Enterprises will begin to focus more on cost of compute, open source models, small language models and the use cases that drive the most value for the money. There will be some hard conversations between enterprises and software vendors.

Training. Everyone is talking about upskilling and training, but it is unclear whether this education is happening.

Iterative implementation. The mantra with genAI has been to "just get started," but that approach has led to AI debt already with copilot sprawl, difficulty changing models and user dissatisfaction. Will 2025 be better for the slower movers that spent 2024 refining the data strategy?

Employee-AI collaboration. CxOs are trying to solve for human-in-the-loop approaches so employees feel more empowered working with AI.

This genAI cognitive dissonance is worth watching in 2025. Either the value reaches vendors and enterprises or we're going to have a massive AI buildout hangover.

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Alibaba's cloud unit shows AI traction in Q2

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Alibaba's cloud unit is now approaching a $17 billion annual revenue and the company said it will continue to invest in AI services.

The company's Cloud Intelligence Group reported fiscal second quarter revenue of $4.22 billion, up 7% from a year ago, due to "double-digit public cloud growth, including increasing adoption of AI-related products."

As for profits, Alibaba Cloud Intelligence Group reported second quarter EBITA of $379 million.

Alibaba's cloud division said AI services grew at a triple-digit pace. "We will continue to invest in anticipation of customer growth and in technology, particularly in AI infrastructure, to capture the increasing trend of cloud adoption for AI," the company said in a statement.

Constellation ShortList™ Global IaaS for Next-Gen Applications

Despite trade restrictions in China, Alibaba has been investing in generative AI. The company recently open sourced its Qwen 2.5 large language models and has been cutting prices for AI workloads. Alibaba's cloud division cut prices for API calls and upgraded infrastructure to boost efficiency.

Alibaba, best known for its e-commerce properties, reported second quarter net income of $6.25 billion on revenue of $33.7 billion, up 5% from a year ago.

In a statement, Alibaba CEO Eddie Wu said:

"We entered into long-term collaborations with industry peers to broaden payment and logistics services on Taobao and Tmall platforms, which we expect will accelerate our overall growth. Growth in our Cloud business accelerated from prior quarters, with revenues from public cloud products growing in double digits and AI-related product revenue delivering triple-digit growth. We are more confident in our core businesses than ever."

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Quantum computing all in on hybrid HPC with classical computing

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Quantum computing vendors are all bullish on hybrid supercomputing approaches that'll play well with the generative AI boom.

This hybrid mantra--with a heavy dose of commercial use cases today--started a year ago and has now become a common theme in the quantum computing industry. A few recent events include:

IBM launched a series of Qiskit software services to go with its IBM Quantum Heron systems. The aim is to integration classic supercomputers with quantum computers in an architecture that can allocate workloads based on the best platform available.
IonQ's recent earnings highlighted how its focus on commercial workloads that are enterprise relevant today is paying off nicely. At the SuperCompute24 conference in Atlanta, IonQ will highlight how its systems can integrate into hybrid quantum-classical infrastructure. SuperCompute24's agenda features a variety of quantum computing talks. More: IonQ’s bet on commercial quantum computing working, acquires Quibitekk | IonQ's quantum computing bets: Quantum for LLM training, chemistry and enterprise use cases
Rigetti Computing CEO Subodh Kulkarni said the company is working with Nvidia at the Israeli Quantum Computing Center to understand how a QPU interfaces with the CPU and GPU. "We are absolutely committed to doing that kind of work to understand how quantum computing fits into the broader datacenter hybrid computing ecosystem," said Kulkarni on Rigetti Computing’s earnings call. "We believe that our 9-qubit Nuvera QPU is ideal for experimentation across a variety of research areas, including qubit characterization and hybrid quantum algorithms." Rigetti Computing quantum systems are collocated with Nvidia Grace Hopper systems. More: Why your quantum computing vendors are going to look familiar
D-Wave Quantum CEO Alan Baratz said the company is focusing on using quantum computing to train foundational generative AI models. While Baratz didn't address hybrid architecture directly on the company’s earnings call, the door is open.
Quantinuum's partnership with Microsoft primarily revolves around hybrid architectures.

The catch with these hybrid HPC efforts is that the hardware is dramatically different. The good news, however, is that the software ecosystem around quantum computing is rapidly developing.

In recent research, Constellation Research analyst Holger Mueller noted that quantum networking and hardware advances have been critical. Mueller has argued that the industry would have seen the year of quantum computing if it weren't for the buzz around generative AI. The hardware side of quantum computing is reaching maturity, but software will be what bridges hybrid quantum-classical supercomputers. These quantum-classical supercomputers will likely be consumed as a service through cloud vendors.

He said:

"We are seeing the hardware side of quantum technology reaching stability and maturity through the quarters of 2024—so the focus switches to quantum software development kits (SDKs), the software libraries that map quantum problems to quantum hardware."

For now, CxOs should investigate use cases for quantum computing now and in the future, plan investments and realize how critical the software stack will be, said Mueller.

Data to Decisions Tech Optimization Innovation & Product-led Growth Quantum Computing Chief Information Officer

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Cisco Q1 shows better demand, networking struggles continue

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Cisco reported better-than-expected first quarter results and said it saw "acceleration in product orders reflecting normalizing demand."

But Cisco's first quarter networking revenue fell 23% from a year ago.

The company said it saw product orders jump 20% in the first quarter compared to a year ago and 9% excluding the Splunk acquisition.

Cisco reported first quarter earnings of 68 cents a share on revenue of $13.8 billion, down 6% from a year ago. Without Splunk, Cisco's first quarter revenue would have been down 14%. The first quarter earnings include a tax benefit of $720 million.

Non-GAAP first quarter earnings were 91 cents a share. Wall Street was expecting Cisco to report non-GAAP earnings of 87 cents a share on revenue of $13.77 billion.

As for the outlook, Cisco projected second quarter revenue of $13.75 billion to $13.95 billion with non-GAAP earnings of 89 cents a share to 91 cents a share. For fiscal 2025, Cisco projected revenue of $55.3 billion to $56.3 billion with non-GAAP earnings of $3.60 a share to $3.66 a share.

Cisco CEO Chuck Robbins said "our customers are investing in critical infrastructure to prepare for AI."

By the numbers:

Networking revenue in the first quarter was $6.75 billion, down 23% from a year ago.
Security revenue was $2.017 billion, up 100% from a year ago.
Collaboration revenue was $1.085 billion, down 3%.
Observability revenue was $258 million, up 36%.
Services revenue was $3.727 billion, up 6%.

On a conference call with analysts, Robbins said Cisco's portfolio is set up to capture demand for AI training infrastructure, AI networks and connectivity and observability.

He added that Cisco's new AI survey with Nvidia will ship in December and AI pods are available. Robbins said:

"As we look at what's occurring with AI, there are three key things. First, there is significant investment in back end AI networks with hyperscalers focused on training. Second, as enterprises look to adopt and deploy AI, they need to modernize and secure their infrastructure to prepare for pervasive deployment of AI applications. Finally, the combination of mature back end models with enterprise AI application deployment will lead to increased capacity requirements on both private and public front end cloud networks. Cisco is already playing a major role across all three of these significant opportunities."

Constellation Research analyst Holger Mueller said:

"Cisco can't catch growth for it's offerings. It was a struggle to grow in the cloud era and it seems to be one in the AI era as well. While 20% growth on product seems to be encouraging (unless you have not forgotten the previous focus on services) but half of it comes from the Splunk acquisition. Adjust for Splunk and Cisco is in medium single digit growth. When and where will Cisco grow again? Referring to government contracts as CFO Scott Herren did is not sustainable growth."

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Balancing AI, Innovation, and Resilience at Jewelers Mutual Group | BT150 Spotlight

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

In the latest BT150 Spotlight, Constellation Insights editor in chief Larry Dignan sits down with John Kreul, Chief Information Officer at Jewelers Mutual Group. They discuss how the insurance company is using #AI to enhance the #customerexperience for retail jewelers, personal line customers, agents, and employees. Kreul shares insights on Jewelers Mutual Group's approach to building vs. buying AI capabilities, the metrics they use to measure progress, and the importance of the human element in driving change. The conversation also covers future-proofing strategies and the role of AI in improving operational efficiency.

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IBM launches Qiskit services for quantum computing

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

IBM launched a series of Qiskit software services to go along with its IBM Quantum Heron-based systems. The effort comes as IBM aims to meld quantum computing and classical computing today while aiming for quantum advantage later.

At IBM's inaugural Quantum Developer Conference, the company said IBM Quantum Heron, which is available in Big Blue's quantum data center, can now use Qiskit to run certain classes of quantum circuits with up to 5,000 two-qubit gate operations.

Qiskit research:

This ability enables quantum computers to address scientific problems in materials, chemistry, life sciences and physics.

IBM's big theme at its developer conference revolved around integrating quantum computing and classical supercomputing. IBM is looking to leverage its Qiskit to enable supercomputers to split up problems and allow algorithms to use classical or quantum computing to solve them.

The IBM view was popularized by IonQ, which dropped talk of quantum advantage to focus on what quantum computing value can be delivered now. Most of quantum computing has come around to commercial benefits today, hybrid supercomputing and quantum advantage in the future.

IBM cited the RIKEN Center for Computational Science (R-CCS), Cleveland Clinic and Rensselaer Polytechnic Institute as companies bridging quantum computing with supercomputers with Qiskit.

New IBM Quantum Platform and Qiskit services include:

Qiskit Transpiler Service to optimize quantum circuits for quantum hardware with AI.
Qiskit Code Assistant to generate quantum code with IBM Granite generative AI models.
Qiskit Serverless to run quantum and classical supercomputing approaches.
IM Qiskit Functions Catalog, which will make services from IBM, Algorithmiq, Qedma, QunaSys, Q-CTRL, and Multiverse Computing available.

Constellation Research analyst Holger Mueller said:

"IBM is making good on it's promise of advancing its hardware progress, with Heron2 being 50x faster year over year. Now scientific use cases are suddenly feasible and the game changes from hardware to software. IBM is well positioned in software with the recent release of its Qiskit Functions Catalogue. The real milestone to watch will be the coupling of two Heron systems soon and that is what CxOs are looking for."

More quantum computing:

Data to Decisions Tech Optimization Innovation & Product-led Growth IBM Quantum Computing Chief Information Officer

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ServiceNow launches AI governance tools, contract management, Five9 partnership

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

ServiceNow launched a series of AI governance features across its Now Platform, generative AI contract management tools and an expanded Five9 partnership.

According to ServiceNow, the company is dropping more than 150 genAI features on its platform. A big part of the portfolio additions are governance capabilities. Jon Sigler, senior vice president of Platform and AI at ServiceNow, said the Now Platform has "governance at the core." ServiceNow has been forging various partnerships to help expand its reach.

The company said its governance and security tools will give customers guardrails for autonomous AI agents. Key items include:

ServiceNow AI Governance for Now Assist, which connects AI to security and compliance features across the Now Platform. AI Governance for Now Assist includes a unified AI inventory data model and a foundation designed to operate as an "AI control tower."
Now Assist Guardian, which monitors how genAI is used across the platform. Now Assist Guardian will include management and mitigation of offensive content, security vulnerabilities and exposure of sensitive information.
Now Assist Data Kit, which provides tools to manage data for AI use cases and benchmark accuracy. Data Kit will also evaluate the effectiveness of experiences built with Now Assist Skill Kit.

Now Assist Analytics, which provides a view of users and how they use Now Assist.

ServiceNow also said Now Assist will support English, French, Dutch, German, Spanish, Italian, Portuguese, and Japanese.

On the legal contract, health and safety front, ServiceNow added a bevy of tools to Now Assist. These tools include:

Now Assist for Configuration Management Database (CMDB), which uses AI to keep a clean and accurate CMDB while reducing duplicate data.
Now Assist for Legal Service Delivery, which is aimed at legal teams by auto-generating summaries of legal requests and use cases.
Now Assist in Contract Management, which flags terms and missing sections in contracts.
Now Assist for Health and Safety, a feature that simplifies incident tracking and uses genAI to summarize incidents and takeaways as well as suggested revisions for non-disclosure agreements.

In addition, ServiceNow's expanded partnership revolves around an AI joint effort that combines ServiceNow Customer Service Management (CSM) and the Five9 platform. The new capabilities will be available in the first half of 2025. Key parts include:

Five9 TranscriptStream will be integrated into ServiceNow Interaction Management to use genAI to take notes, generate summaries and reduce average handling times.
Five9's automated routing engine will be able to route ServiceNow digital channels and cases in Five9 channels to the right agents. Metadata from ServiceNow will be used to enrich data in Five9's platform.
ServiceNow's Native Call Controls in the company's Agent Workspace will integrate with Five9 in one inbox and work with other features.

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Softbank Corp. first to land Nvidia Blackwell systems in bid to be genAI provider in Japan

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Softbank Corp will be among the first to build out an AI supercomputer using Nvidia's Blackwell platform. Softbank will get Nvidia's first Nvidia DGX B200 systems with plans to build out a Nvidia DGX SuperPOD supercomputer.

At Nvidia's AI Summit Japan, Nvidia CEO Jensen Huang said Softbank will use multiple products including the Grace Blackwell platform, Nvidia AI Aerial accelerated computing and Nvidia AI Enterprise software.

"With SoftBank’s significant investment in Nvidia’s full-stack AI, Omniverse and 5G AI-RAN platforms, Japan is leaping into the AI industrial revolution," said Huang.

Softbank CEO Junichi Miyakawa said the supercomputer will look to reinvent networks for AI. Softbank recently floated a debt offering to pay for the Nvidia supercomputer and other growth investments.

Miyakawa tipped off the Nvidia news a few days before Huang spoke at Nvidia AI Summit.

Speaking on Softbank Corp.'s second quarter conference call, Miyakawa outlined the plans for the Nvidia supercomputer. Note that Softbank Corp. is the operating unit of Softbank. Softbank Group is the investment arm with the Vision Fund and equity stakes in OpenAI and others.

Miyakawa said:

"Since the end of October, our new AI computing platform, powered by Nvidia's 800, has been up and running. The number of GPUs on the platform increased to 6,000 to deliver five times better performance, which makes it one of the biggest AI platforms in Japan. We plan to increase the GPU count to 10,000 sometime in the first half of next fiscal year."

Softbank Corp. is aiming to be a leader in genAI in Japan. The company has built a large language model with 460 billion parameters focused on Japan research and development.

Miyakawa said the plan is to accelerate training for a commercial launch next fiscal year. Softbank Corp. has a consumer unit that offers mobile service with brands such as Y!Mobile, which is being converted to Softbank branding, enterprise services and integration, and fintech.

Ultimately, Softbank is investing to be Japan's genAI services provider.

More on Nvidia:

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Shopify increasingly becoming enterprise commerce OS, replaces incumbents

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Shopify is getting enough traction as an enterprise commerce platform that can deliver a real-time customer case study in two conference calls.

Speaking on Shopify's third quarter earnings call, Shopify President Harley Finkelstein cited On Running as a company that is betting on the company's platform. He said:

"Our platform's composability gives large brands the flexibility to choose modular components like On Running, who recently adopted our checkout commerce component. One of the best things about modular components is that integration can happen fast."

At roughly the same time, On Holding AG was reporting strong direct-to-consumer channel growth of 49.8% in the third quarter from a year ago.

As noted earlier in the year, Shopify was betting that it could expand its business into B2B commerce and larger retailers. So far, so good. The company reported third quarter net income of $344 million excluding the impact of equity investments on revenue of $2.16 billion, up 26% from a year ago. For the fourth quarter, Shopify is projecting revenue growth in the mid-to-high 20 percent range.

Shopify unveils Target partnership, new AI features

Finkelstein said larger brands and retailers are looking for a unified commerce system but are currently stuck with standalone single channel products. "This idea of having a modern future-proofed retail operating system that is unified across every channel like Shopify is very compelling," he said. Finkelstein added that Shopify's Commerce Components is enabling brands to expand on the company's platform. Sometimes it's the backend then checkout and other times its vice versa. With larger brands, enterprises are looking to consolidate checkout options.

"This idea that some of these large brands that are very sophisticated still don't have an optimized checkout like they would have on Shopify is becoming a competitive liability. And so, that's also driving things quite a bit," said Finkelstein.

Shopify is also pushing total cost of ownership and transparent pricing, which is often hard to find with large enterprise vendors. It's not clear what enterprises are replacing with Shopify, but you can check out our all-in-one commerce cloud Shortlist and figure it out.

Finkelstein said that brands, including B2B, are focusing more on direct-to-consumer sales.

He said:

"Once you're in the ecosystem, you begin to make that your retail operating system. Those gaps are getting closed pretty quickly. And we just think B2B, it is a huge -- I think there's like a $14 billion TAM. We're already seeing our B2B GMV doubled since last year. We think that's a great opportunity and we're able to close these future gaps quite quickly."

The game plan from here is for Shopify to replace commerce systems and shift "this narrative that Shopify is no longer just for small businesses," said Finkelstein. Shopify is adding data migration tools and working with systems integrators to expand its reach. "We're displacing the largest enterprise commerce companies in the planet, and that momentum is continuing. And the best part is we're winning these deals," he said.

And Shopify has plenty of runway. The company's US e-commerce market share is just above 10%.

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Nvidia outlines Google Quantum AI partnership, Foxconn deal

Nvidia outlines Google Quantum AI partnership, Foxconn deal

GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs