Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Enterprises are pursuing AI agents as part of a broader transformation and automation push. Here’s a look at the projects we’re watching for May.

Paypal: Building agentic commerce

Paypal has big dreams of being an agentic commerce platform that can connect consumers, merchants, and decision support into one AI-driven loop. It's a promising vision.

But first the company has to get down its tech debt.

The company must collapse its data silos to create one customer platform. Then it has to get to cloud native capabilities across its platform. From there, PayPal is expecting to rock its AI strategy at full speed.

• PayPal eyes agentic commerce platform, but first has to retire tech debt

Here's a look at the timeline.

Bank of America scales its AI agent plays

Bank of America was early in the AI assistant game with Erica way back before generative AI took off.

Today use newer models, Erica is getting an overhaul that will be aimed at not only customer support but internal employee experience.

• Bank of America's AI investments boost digital engagement, customer satisfaction

Citigroup: AI enablement

Citigroup outlined how it is using Google Cloud as an AI enabler across the company. Now it is ready to scale its use of AI to drive efficiencies.

Like PayPal, Citigroup has had to collapse a bevy of systems, refine its data strategy and do a lot of blocking and tackling to rev its AI strategy.

• 9 Google Cloud customers on AI implementations, best practices

Citigroup has been under transformation for years, but now looks like it's ready to actually move on its AI dreams.

Walmart: Continuous optimization

Walmart has more projects than you can mention, but its ability to use AI for experience and supply chain optimization is going to be critical in the current environment. Some items being rolled out. A look at Walmart’s platform approach to data, AI, optimization

• Sparky, an AI shopping assistant.
• Trend-to-Product, a tool to speed up fashion design.
• Just Go AI Checkout, a computer vision checkout system that will be rolled out to all Sam's Club locations.
• Wally, an AI assistant for merchants that will evolve into an inventory AI agent.

Bank of New York Mellon: A bet on OpenAI

With a partnership with OpenAI, BNY is building a platform that will leverage AI agents through the enterprise. The effort is a work in progress, but BNY is making good progress. I'm watching this project because it’s one of the large enterprises betting on OpenAI innovation.

• Financial services firms: The only certainty is investing in AI transformation

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Classiq, a quantum computing software company, said it raised $110 million in Series C funding. The company is looking to build the software stack for quantum computing.

The funding, led by Entrée Capital and a bevy of other investors, will be used to build Classiq's go-to-market, customer success and R&D teams globally.

Classiq's software has been used for multiple projects and has the promise of being the software layer across the various types of quantum computing systems. Classiq has raised $173 million in total funding.

Nir Minerbi, CEO of Classiq, said the goal is to build "the essential software stack to empower the development of real-world quantum applications."

Constellation Insights caught up with Minerbi recently to talk strategy and its hardware agnostic approach. Classiq, based in Israel, was founded in 2020. The company said it has tripled its customer base and revenue in compared to a year ago.

• Classiq CEO Minerbi on the intersection of quantum computing, HPC and use cases
• Constellation ShortList™ Quantum Computing Software Platforms

Classiq counts BMW, Citi, Deloitte and Toshiba as customers.

Constellation Research analyst Holger Mueller said:

"Classiq's funding is another sign of the quick maturation of the quantum computing industry. The funding for software highlights what really matters in quantum computer after the hardware.

Funding for Classiq is the proof point here, and the good news for CxOs is that Classiq is providing the abstraction layer between different quantum computing platforms. Classiq's claim to be for the quantum industry what Microsoft has been for the PC is a valid one, but needs to materialize."

Key items about Classiq:

• The company's software can be deployed on multiple quantum hardware systems via AWS Braket, Microsoft Azure Quantum, Google Cloud.
• Classiq has direct integration with IBM, IonQ, QuEra, Quantinuum, OQC, AQT, Alice & Bob, Rigetti and most leading simulators including NVIDIA and Intel.
• Classiq has more than 60 filed patents on core quantum modeling and compilation technologies.
• The company has about 70 employees, up from 40 in 2022.
• Classiq covers multiple industries including finance, healthcare, pharma, manufacturing, logistics, automotive, aerospace and defense and automotive.

More quantum:

• IBM sees quantum advantage 2026, fault tolerant quantum in 2029
• 2025 is the year of quantum computing (already)
• CxOs need to focus on quantum computing readiness, not the noise
• IonQ’s plan: Quantum networks extending into space

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

The race is on to parent your soon-to-be sprawling set of AI agents with orchestration layers, AI studios and a bevy of tools to build, deploy, manage and optimize this digital workforce. Being in the pole position as an agentic AI platform is going to be lucrative for a few enterprise vendors, but choose wisely.

A set of announcements in recent days featured how the race to be the platform of AI agents is ramping.

ServiceNow outlined plans for CRM, a data partner network, an AI control tower, AI agent management tools and other key features to extend the company's workflow and automation platform to AI agents. ServiceNow CEO Bill McDermott said: "We're going to bring AI agents to every corner of your business."

IBM at its Think 2025 conference outlined its AI agent orchestration platform. IBM is looking to build, deploy and manage AI agents for multiple use cases that create a "system of intelligence."

Ritika Gunnar, GM of Data & AI Software at IBM, said: "We built systems of records. These things are like our digital vaults. We connected them through systems of engagement. We gained understanding of them with our systems of insight and our analytical dashboards, which were grounded with our warehouses and our data lakes. But knowing isn't enough. The next big step is systems of intelligence powered by AI agents. These aren't just dashboards. They're doers. They act autonomously orchestrating workflows across your enterprise."

Gunnar noted that "the explosion of AI agents across the enterprise holds immense promise, but let's be real for a minute, it also creates significant complexity."

UiPath launched its automation platform, which includes AI agents as part of a holistic approach that includes RPA, applications and the enterprise estate.

These are just a few examples of how enterprise vendors are looking to manage AI agents--their own as well as third parties. Boomi, which has its Boomi World conference this week, is also a key player in the AI agent orchestration race. Obviously, Salesforce with its Agentforce effort has another platform play for AI agents as does SAP. And of course, all the hyperscale cloud providers--Amazon Web Services, Microsoft Azure and Google Cloud--have platforms and the ambition to manage agents across enterprises.

With that backdrop, it's worth thinking through what you want in an AI agent orchestration layer. Here are some of the requirements that are bubbling up from CxOs.

Horizontal approach

Enterprise AI buyers don't want a portfolio of platforms managing their AI agents. Yes, you're likely to have agents defined by software categories such as CRM, HCM and ERP, but the aim is for enterprises to have an orchestration to manage them.

It's no secret that system integrators have done their best so far at building AI agents. These integrators are accustomed to working across systems, data silos and vendors. The base requirement for any agentic AI platform is the ability to work across systems, data stores and functions.

PepsiCo has more than 1,500 bots, agents and assistants across the company. Magesh Bagavathi, SVP, Chief Data and AI Officer a PepsiCo, said at IBM Think that the company has "a platform centric approach."

Bagavathi looks at two kinds of platforms. First, PepsiCo has built an agent orchestration platform on IBM's watsonx platform. "We're really looking at platforms for our business end to end," he said. PepsiCo started with proof of concepts and then moved to production by processes including accounts receivable and accounts payable with the aim of moving throughout the company's value chain.

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PepsiCo is also building its own internal abstraction layers for agents, AI and data with IBM Consulting.

Cindy Hoots, Chief Digital Officer and CIO at AstraZeneca, said during the ServiceNow Knowledge 2025 keynote that the company used ServiceNow to create a unified platform to save time and money across everything from HR to R&D. Like PepsiCo, AstraZeneca looked to automate workflows and processes with AI.

"We're finding agents are really embedded in every part of our company and using them to transform patient care as well as drive healthcare innovation," said Hoots. "It's just something that we've kind of built into every aspect of the company for research and development all the way down, and it's helping us have much more autonomous ways of working. They're helping the team to really focus on those higher value activities."

IBM and ServiceNow historically work across systems, but there are a bevy of others. Horizontal characteristics can be found in hyperscale cloud vendors (think Amazon Q), integrators and platforms that historically connect systems (Boomi, UiPath, process mining vendors and other firms).

Enterprises may choose to build their own platforms too.

Neutrality

Neutrality is a tricky topic because a vendor that has historically worked across systems naturally wants you to consume as much of its platform as possible.

Vendors that are coming from a SaaS orientation and working to become more of a broad platform have a lot to prove. Salesforce's Agentforce makes the company's various clouds more of a platform, but perceptions will take time to change. SAP can launch Datasphere and partner with Databricks to connect third party data sources, but there's little doubt that it wants enterprises on its cloud and data stores (all connected by its Joule agent).

The big vendors can be seen as neutral players that ultimately drive costs down, but CxOs will remain skeptical.

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Now enterprises can opt for smaller vendors that are good at integrating platforms--think Boomi or UiPath--and get neutrality. But these smaller players could always simply be acquired by larger vendors. MuleSoft, an API platform that was acquired by Salesforce, is an example. A neutral vendor today may not be neutral tomorrow.

ServiceNow's Amit Zavery, Chief Product and Chief Operating Officer, drove home the neutral platform argument. ServiceNow provides model, infrastructure and data neutrality. IBM's CEO Arvind Krishna had a similar riff.

Connectors, data integration

It's not hard to find CxOs who note that AI agents are largely glorified souped up APIs. As a result, you'll want vendors that have an API heritage as your AI agent control plane.

For instance, Boomi has evolved from being a pure play iPaaS vendor to a broader platform covering AI, AI agents, data app integration and automation.

Connectors are the base layer for any AI agent orchestration effort. If a vendor isn't supporting Model Context Protocol (MCP) or Google Cloud's Agent2Agent standards they aren't likely to be a good choice. Microsoft recently became the latest to support Agent2Agent and noted that AI agent interoperability is critical.

• ServiceNow, UKG integrate AI agents across platforms

This same approach applies to data integration. Yes, it would be swell if all your data were in one lakehouse and organized. It is also fantasy. As a result, the ability to connect and access data wherever it resides is going to be critical to AI agents.

Given the importance of data integration it's not shocking that ServiceNow launched its Workflow Data Network, which is powered by RaptorDB Pro. These connections include Snowflake, Databricks, Boomi, SAP, the hyperscale cloud providers, Jira and Workday.

Process and use case knowhow

What has been most shocking about the AI agent hype is how little play process gets. If the process isn't continually optimized, AI agents are likely to simply take the screwed up processes enterprises have today and scale them.

Microsoft, ServiceNow, SAP and UiPath talk process and use cases more than the rest of the field. IBM talked about 150 pre-built agents in watsonx Orchestrate across domains ranging from HR, sales, procurement and IT and a catalog of agents for partners.

• Agentic AI without process optimization, orchestration will flop

ServiceNow is looking to a suite of AI agents as an overlay of systems in HR, procurement and finance.

Bottom line: Your AI agent layer should have some serious process intelligence behind it.

Integration skills

Today, AI agents don't exactly work well out of the box. There are a few prepackaged AI agents within SaaS silos, but integration across systems and data silos matters.

This enterprise-specific integration is one reason why it's quite possible that this agentic AI layer is built by companies with the help of consultants such as Accenture, IBM, Infosys, Cognizant and a bevy of others.

• The Future of Agentic AI: Get Ready to Build Your Own Agents With Ease
• Cross-Platform Agentic AI: Infosys Topaz
• Constellation ShortList™ Cross-Platform Agentic AI

Start with the business problem you're trying to solve, think through the integration and then platform options.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Can data, AI and agility enable merchants to navigate economic volatility and scattershot tariff policies? Shopify is betting on it.

Speaking on Shopify's first quarter earnings call, President Harley Finkelstein outlined a bevy of data and AI tools to help merchants--including a bevy of small businesses--to navigate tariffs.

For Finkelstein, economic uncertainty only highlights Shopify's data platform and AI-driven agility. "We're monitoring for potential slowdowns but our data through April shows little of that. It's still early to assess the full impact of the current environment," said Finkelstein. "We're here to help merchants of all sizes absorb change rapidly and at scale."

Finkelstein also said the goal is to make merchants more resilient. Resilience has been a common theme among enterprises.

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And to build resilience, a flywheel of commerce data goes a long way. Finkelstein said that Shopify's 875 million unique buyers on the platform give the company visibility into what consumers and merchants are doing and how both sides react to economic uncertainty. "Because of our visibility, we're learning a ton," he said.

Here's what Shopify is doing to boost merchant resilience.

Product development

Shopify shipped features focused on cross-border trade and making it easier to buy local, calculate duties and ship. These features went into production days after the US announced its tariff plan, which morphed almost daily. Shopify said that when new duties are announced most merchants can be compliant within hours. Finkelstein said the goal is to allow merchants to manage markets independently.

On the Shop app, Shopify added a feature to allow buyers to filter products by country and buy local. Since the feature has rolled out "hundreds of thousands of unique sessions" have been generated said Finkelstein.

The company also launched duty inclusive pricing so merchants can set international prices including duties for transparent processing at the start of a transaction.

Shopify also launched tariffguide.ai. This tool provides duties based on a product description and country of origin so merchants can source goods based on tariff rates.

AI first

The commerce platform company took a lot of heat for its AI-first memo, but Finkelstein said Shopify is transforming its processes with AI. Finkelstein highlighted the following efforts.

Shopify built a dozen of model context protocol (MCP) servers that make the company's work accessible to AI. "Anyone within Shopify can ask questions, find resources and leverage those tools for greater efficiency. This reflects the use of AI goes well beyond internal improvement. It supercharges our team's capabilities and drive operational efficiencies, keeping us agile," said Finkelstein.

On the merchant side of AI, Shopify overhauled its AI engine for deeper reasoning, enhancing processing of large data sets and supporting multiple languages. The AI engine powers Shopify Sidekick, the AI support copilot, for merchants as well as employees. "Our monthly average users of Sidekick continue to climb more than doubling since the start of 2025," said Finkelstein. "Now this is still really early days, but the progress we are making is already yielding some really strong results from merchants, both large and small."

Shopify also closed the acquisition of Vantage Discovery, which has technology that accelerates the development of AI multi-vector search across search, APIs, shop and storefront search.

Shopify reported a first quarter net loss of $682 million on revenue of $2.36 billion, up 27% from a year ago. Adjusted net income was $226 million.

As for the outlook, Shopify projected second quarter revenue growth in the mid-twenties percentage range. The company didn't provide an outlook for 2025.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

IBM said quantum computing will hit quantum advantage in 2026 starting with chemistry use cases followed by optimization and mathematical computation.

Speaking at an IBM Think keynote, Jay Gambetta, IBM Fellow and Vice President of IBM Quantum, said the industry has moved to solving problems in a hybrid way with quantum systems and classical supercomputers. The next step would be leveraging quantum computing to solve problems classical computing can't. "We believe quantum advantage will actually happen by 2026," said Gambetta. "And it's not just us. It's a community of researchers. Every month, every week new papers are put out with different examples."

• IBM launches Flex Plan for quantum computing, aims to expand use cases
• 2025 is the year of quantum computing (already)
• CxOs need to focus on quantum computing readiness, not the noise
• Constellation ShortList™ Quantum Computing Platforms | Quantum Computing Software Platforms | Quantum Full Stack Players

Gambetta added:

"We're going to see quantum advantage in chemistry first, followed closely by optimization. And third, there is a lot of exciting work in mathematical problems where the teams are exploring AI quantum machine learning problems that could even have an impact in AI in the future."

IBM CEO Arvind Krishna noted in his Think keynote that bigger things were on tap for quantum computing and scale will occur "in the 4-, maybe 5 year time frame."

Krishna said:

"Quantum is no longer science fiction. It's now in the realm of engineering. And when you're in the realm of engineering, the question becomes, how do you get that next step? And then these systems are going to be at a scale that is going to be truly remarkable and truly surprising."

He said IBM can bring the same engineering rigor to quantum computing that it brings to the mainframe.

"What do I mean by engineering rigor? We should stand up a quantum computer, and it runs for a full year without breaking down, without needing a room full of experts to kind of retune it after every application, and it can stay and maintain itself. People can access it with just an API. That's what I mean by the engineering rigor of making it a computer, not just a science experiment," said Krishna.

Gambetta said that "we have a roadmap to create a fault tolerant quantum computer by 2029." He said IBM will have more to say about the roadmap in the weeks ahead.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

IonQ just keeps buying quantum networking companies. The company is determined to become a leader in quantum networking as it acquired two more companies--Lightsynq and Capella Space--to flesh out its quantum internet roadmap.

The move highlights how the money in quantum computing may revolve around the network over time. After all, there are multiple types of quantum computing systems and at some point we're going to hit the VHS vs. Betamax moment. There are superconducting quantum systems (IBM, Google and Rigetti) as well as trapped ion (IonQ and Quantinuum), neutral atom (QuEra), quantum annealing (D-Wave) and topological (Microsoft).

A quantum network moves and transmits qubits and will be necessary to connect quantum computers. Quantum internet projects have been started by the US, European Union and China that are emphasizing quantum-secure links between sites.

With its first quarter earnings report, IonQ said it was acquiring Lightsynq Technologies, a startup founded by experts in quantum memory with more than 20 patents. IonQ said Lightsynq's technology will help it build repeaters to network quantum systems over longer distances.

IonQ also said it will acquire Capella Space, which has government contracts for top-secret projects, to launch a space quantum key distribution (QKD) network. IonQ is looking to have a quantum network that extends into space.

Those two purchases follow IonQ's acquisitions of Qubitekk and ID Quantique, two companies focused on quantum networking. IonQ also recently inked a memorandum of understanding with Intellian Technologies, a provider of satellite communications antennas and ground gateway technologies. In our 2025 play-by-play of quantum computing developments, IonQ has been clearly busy.

• IonQ doubles down on quantum networking, names new CEO as it eyes scale
• IonQ’s bet on commercial quantum computing working, acquires Quibitekk
• IonQ's quantum computing bets: Quantum for LLM training, chemistry and enterprise use cases

Terms of all these deals haven't been disclosed, but IonQ is strategically using its balance sheet with $687 million in cash and equivalents to pick up parts and patents to build an integrated quantum system. IonQ reported a first quarter net loss of $32.2 million on revenue of $7.6 million. Most pure play quantum computing companies talk in terms of backlog instead of actual recognized revenue.

On IonQ's first quarter earnings call, Executive Chairman Peter Chapman said the company is focused on its "path to tens of thousands and ultimately millions of qubits is to photonically interconnect qubits across the network to run applications across multiple QPUs acting as one large single quantum computer."

IonQ CEO Niccolo de Masi said:

"Whether on the ground or in space, IonQ solutions are poised to be there and lead. We believe our now near-boundless photonic interconnect scalability provides IonQ customers with the winning quantum computing and internet ecosystem, not just this decade, but we expect for the entire 21st century."

• CxOs need to focus on quantum computing readiness, not the noise
• Constellation ShortList™ Quantum Computing Platforms | Quantum Computing Software Platforms | Quantum Full Stack Players

The networking play

IonQ recently put Jordan Shapiro in charge of networking as President and GM of Quantum Networking. Shapiro joined IonQ in 2020 and was previously a venture capitalist at New Enterprise Associates. Shapiro has spearheaded IonQ's networking shopping spree and will be in charge of developing the roadmap.

Like IonQ's approach with its quantum systems, the company is focused on business value today ahead of quantum supremacy that may take years--some would say decades. The pre-quantum supremacy world revolves around government contracts with the likes of DARPA, hybrid systems with classical high-performance computing, use cases in chemistry, life sciences, finance and engineering, and experimental projects.

While IonQ has a strong balance sheet it is competing with giants including all the hyperscale cloud giants, IBM, which has networked its quantum systems together into an offering, and a bevy of others.

The giants:

• Cisco launches quantum lab, unveils quantum networking chip
• IBM launches Flex Plan for quantum computing, aims to expand use cases
• Microsoft unveils Majorana 1, aims to scale quantum computing
• Google outlines performance of Willow quantum chip, highlights roadmap
• AWS launches Ocelot quantum chip, claims error correction breakthrough

IonQ's de Masi said networking is a way to compete with giants. He said Nvidia's rise provides a blueprint.

"Lightsynq's technology is expected to accelerate IonQ's existing photonic interconnect activities and enable our commercial systems to scale to tens of thousands and eventually millions of qubits. The Lightsynq architecture is uniquely powerful and will underwrite our quantum computing leadership for decades to come.

The parallels are strong, so I would not be surprised if in the fullness of time, Lightsynq becomes as accretive for IonQ, as Mellanox has been for NVIDIA. Equally exciting and importantly, Lightsynq's technology will also power the future quantum internet by allowing repeaters to ultimately be spaced over 100 kilometers apart."

That distance de Masi referenced also highlights how early it is in quantum system development. Nevertheless, IonQ sees itself as a quantum vendor creating an entire ecosystem.

"Quantum networking will naturally be the foundation of the quantum internet, which will be a watershed achievement in creating a worldwide ultra secure communications grid," said Shapiro.

It's early

Chapman explained the quantum networking today doesn't go more than about 20 miles. Lightsynq is part of a plan to build a repeated network that could go more than 100 miles and build from there. Space is also a factor.

"Ultimately, what you need to do and you're seeing this now in China and also the EU, is to build quantum networks in space from satellite to satellite and ultimately from satellite to ground station. And protecting that with the QKD network as well," said Chapman.

He added that IonQ's purchase of ID Quantique gives it access to real world environments since it works with South Korea's SK Telecom. Capella adds the space environment.

However, Chapman said there's a big difference between the real-world and lab. "It's one thing to get it working in a lab, it's another thing to get it working in a busy city with trucks driving over your fiber and all the rest of that," said Chapman. "So all these things are about building out the capability and making sure they work in the real world."

Today, IonQ has four quantum networks running globally for government and commercial customers, said Shapiro.

What about quantum computing?

IonQ's first quarter earnings call was notable because executives didn't talk much about the actual deployments of its quantum computing systems and roadmap. Chapman and de Masi said IonQ can focus on both networking and compute because they're converging.

" Last year, we announced that we were doing quantum networking, but it required two quantum computers to be built. We announced it as a networking project, but we actually built two quantum computers to network the two quantum computers together," said Chapman. "You're pushing the compute side so that you can do the networking."

de Masi said:

"The business's focus on quantum computing remains. We're determined to be the ultimate ecosystem there. We've expanded our ecosystem to do quantum networking, obviously organically and inorganically. The quantum internet requires pretty much all the pieces that we've assembled. You need the nodes to be computers, you need repeaters to have any kind of distance between the nodes, you need QKD to be able to actually send information securely. And you need to be able to do that as an integrated communications network on the ground and in the heavens.

We see growing opportunities in computing and growing opportunities in networking, both short-term, medium-term and long-term."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Microsoft said it will support Google Cloud's Agent2Agent (A2A) standard in Azure AI Foundry and Copilot Studio.

Microsoft’s support for A2A likely means the enterprise software ecosystem will follow.

At Google Cloud Next, Google Cloud launched A2A, a communications standard that also has some big backers. A2A complement's Anthropic's Model Context Protocol (MCP). Both standards have gained wide support quickly since vendors need their various agents to work across platforms. Anthropic created MCP as an open standard for connecting AI assistants to systems where data lives. OpenAI and a bevy of others are backing MCP.

The promise of AI agents is that they can reason, navigate work and act autonomously. As Microsoft noted in its blog, "interoperability is no longer optional” because enterprises "want their agents to orchestrate tasks that span vendors, clouds, and data silos."

• Agentic AI: Everything that’s still missing to scale
• ServiceNow, UKG integrate AI agents across platforms

Microsoft said A2A support will be in Azure AI Foundry so enterprises can build multi-agent workflows across vendors, partners and infrastructure. Copilot Studio agents will extend beyond Microsoft's platforms.

The software giant said it will contribute to A2A as well as MCP. Microsoft also joined the A2A working group in GitHub.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

SAS launched a bevy of updates or its Viya platform including synthetic data, tools for building and deploying AI agents, and managed cloud services. The company also launched new AI models and digital twins for manufacturing.

The news, announced at SAS Innovate, aim to position SAS more in the AI technology stack.

Here's a look at what was announced:

• SAS Viya said its SAS Data Maker, a synthetic data generator, will be generally available in the third quarter. SAS Data Maker was announced in private preview last year.
• SAS Viya Intelligent Decisioning, which will incorporate the ability to build and deploy AI agents. SAS' approach revolved around balancing LLMs with humans to determine the right levels of autonomy and governance based on tasks.
• SAS Viya Essentials, a managed cloud services offering aimed at smaller enterprises, includes a hosted version of select SAS Viya products.
• SAS Viya Copilot, a conversational assistant that's embedded throughout SAS Viya, is available in private preview with availability in the third quarter. The SAS Viya Copilot was built on Microsoft Azure AI Services.
• SAS Viya Workbench, a cloud-based coding environment, will get support for R coding to complement Python through Visual Studio Code or Jupyter Notebook. Viya Workbench will now be available on AWS Marketplace as well as Microsoft Azure Marketplace.
• The company launched new models for AI-driven entity resolution and documentations, medication adherence risk in healthcare, supply chain optimization in manufacturing and payment integrity for food assistance and tax compliance for sales tax in the public sector.
• SAS Digital Twins for manufacturing. SAS has developed enhance digital twins for manufacturers in a partnership with Epic Games.  Georgia-Pacific was cited as a customer.