ServiceNow Yokohama release ups AI agent game

Larry Dignan

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. ...

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ServiceNow launched its Yokohama release of its Now Platform including AI agent orchestration, analytics and a workflow data fabric that integrates apps, data warehouses and lakes, and a workspace and studio to design and integrate agents.

The release highlights ServiceNow's broader strategy, which is to leverage its ability to tap into workflows and data across multiple enterprise systems and connect those dots to enable AI agents. ServiceNow, which scaled due to its role as a neutral workflow orchestrator, is betting it can also enable multi-agent flows across the Now Platform and third party apps and platforms.

ServiceNow’s Yokohama release is a fast follow up to its $2.85 billion acquisition of Moveworks.

"We are focused on a future where AI agents work autonomously with and for people to unlock outcomes and transform business," said Amit Zavery, ServiceNow's President, Chief Product Officer and Chief Operating Officer. "Right now, many AI agents are stuck in the same isolated systems that have created siloed ways of working for decades."

Simply put, ServiceNow is aiming to be the connective layer for agentic AI and adding context via the Now Platform's access to data, records and workflows. Yokohama will bake in AI agents throughout the ServiceNow platform to address use cases across IT, CRM, HR, security, finance and application development.

"We are building multi-agent systems to control workflows and independently solve tasks with proper governance," said Zavery. "Work doesn't really happen in silos, and neither does our AI, our orchestration capabilities connect every function through AI powered workflows."

ServiceNow's Yokohama release is also the first release under the company's hybrid pricing model that includes AI agents in Pro Plus and Enterprise Plus licensing models. As a result, enterprises will be able to use AI agents without additional charges, but there is a limit with consumption charges after that.

The release, which has ServiceNow's Workflow Data Fabric at its core, also has an updated Common Service Data Model (CDSM), a standardized framework for managing IT and business services.

CEO Bill McDermott has called ServiceNow's pricing model a win-win and a Goldilocks scenario in terms of enabling customers to adopt AI agents at their own pace without commitment up front. ServiceNow has more than a 1,000 customers using its AI agents.

Internally, ServiceNow said it has been using its AI agents to improve case deflection rates by 80% in the last 6 months in go-to-market operations, providing answers to seller questions 99% faster than request tickets and driving 20% productivity increases across HR and IT support.

Key parts of the Yokohama release include.

• AI Agent Orchestrator and AI Agent Studio are generally available for customers.
• AI Agent Orchestrator monitors agents, oversees them and develops plans for them to work together. ServiceNow's AI agents have the ability to connect to other systems. There are more than 50 integrations set for the AI agents in Yokoyama.
• AI Agent Studio enables customers to build agents with guardrails, workflows and actions and tools and data available.
• Service observability, which unifies multiple monitoring and observabilities tools in one dashboard.

• Preconfigured AI agents for security incident lifecycle, change management and proactive network test and repair. The autonomous change management AI agents generate custom implementation, test and backout plans based on impact, historical data and similar changes.
• Voice input for hands free interaction to summarize incidents and generate knowledge articles.
• AI agent analytics to gauge efficiency, productivity and alignment with enterprise KPIs.

• ServiceNow Studio, an AI-powered workspace where developers can use no-code, low-code and pro-code tools to build and deploy workflows and AI agents. ServiceNow Studio is integrated with AI Studio.
• The ability to create robotic process automation (RPA) bots with natural language to speed up development.

Early adoption

ServiceNow's Dorit Zilbershot, Group VP of AI Experiences and Innovation, said early adopters of AI agents are developing use cases with a "wide range of complexity."

Support is an obvious use case for AI agents, but one ServiceNow customer is using agents to navigate policies and how to address requests. That work is now automated, but it took hours for humans to address, said Zilbershot.

Sunil Tulyani, Service Management Platform Leader at Eaton, a power management company. Tulyani said Eaton started with ServiceNow for IT service management and then expanded into HR.

Eaton, which has been a ServiceNow customer, for more than two years has adopted Now Assist and the vendor's generative AI tools. "We gained the value from Now Assist already in this last year of just getting it," said Tulyani, who noted that Now Assist has removed manual tasks and helped Eaton engage with customers in forums and portals.

Eaton's AI agent goals include:

• Boosting productivity and becoming more efficient.
• Resolving tickets at a higher level with better customer service, resolution and speed.
• AI agents won't replace people, but for Eaton it's doing more with the same number of people.
• "We plan to expand and we can double our capacity over the next four years, but with our same headcount to support and drive the business," said Tulyani.

Eaton has started an AI council to leverage AI across the company. Tulyani noted that Eaton will use multiple models and plans to focus on use cases with ServiceNow being the core data structure, chassis and technical debt buster. "Our AI council is going to be evaluating which AIs are ready for us to integrate," he said.

Moving parts Tulyani said Eaton must navigate as it looks at AI agents include:

• "We see AI adopted well on the user side, but it was a little slower on productivity," said Tulyani. "We're focusing more on the productivity side with AI agents, but have issues and concerns."
• Those concerns include better data quality and Eaton has a project to clean up data and prep it for AI use cases.
• Eaton is looking for more automation to move data into the story and create structured data. The process is too manual today.
• AI will be used earlier in the data cleansing process to leverage AI later.

Tulyani didn't comment on Eaton's plans for managing consumption pricing as AI agents are adopted down the line. He did note that ServiceNow "was a little expensive," but worthwhile since it was delivering value and shedding tech debt.

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Rocket buys Redfin, pays $437.5 million per petabyte of data

Larry Dignan

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. ...

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Rocket Companies is buying Redfin in a move that can reinvent the real estate purchase funnel by bulking up the first party data used to train AI models.

Under terms of the all-stock deal, Rocket will acquire Redfin for $12.50 a share, or $1.75 billion. The plan is that Rocket will benefit from Redfin's nearly 50 million monthly visitors. Those leads at the top of the funnel can feed Rocket's mortgage business as well as other consumer services.

On the surface, Rocket and Redfin can combine forces and lower costs of real estate purchases. But you may want to look at the Rocket-Redfin deal through a data and AI lens.

We've previously chronicled Rocket's master plan and AI efforts. The company is built on first-party data and ongoing purchase signals that feed its AI models.

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To look at Rocket's acquisition of Redfin in a different way consider that the company is paying $437.5 million per petabyte of consumer data. In a statement, Rocket CEO Varun Krishna said the purchase of Redfin is about creating a unified search and financing process in real estate. "Together, we will improve the experience by connecting traditionally disparate steps of the search and financing process with leading technology that removes friction, reduces costs and increases value to American homebuyers," he said

.

"The companies with the most data will win, and no industry is safe from the disruption or the opportunity that AI creates," said Krishna. "As commoditization and disintermediation accelerate, access to scaled proprietary data is what separates industry leaders from the rest."

Redfin is also well positioned with its brokerage services since real estate compensation has been revamped. Glenn Kelman, CEO of Redfin, will continue to run that business and noted that "we want a customer to be able to check her phone and find out what she can afford, see which homes are right, schedule a tour and get a prequalified loan in minutes."

The ultimate goal for both companies is to create an AI-driven real estate buying experience. To deliver that experience, it takes data.

A few key figures:

• The combined companies will have more than 14 petabytes of data with information about homebuyers, sellers, agents and a repository of more than 100 million properties.
• This data repository will generate revenue across search, real estate brokerage, mortgage origination, title and servicing.
• Rocket expects the combined company to save more than $200 million in annual expenses by 2027. Rationalizing operations will represent $140 million of that total with another $60 million coming from revenue synergies.
• Redfin facilitated 61,000 home transactions in 2024.

Krishna said the goal of Rocket and Redfin are to disrupt real estate. Speaking on a conference call, he said:

"For far too long, the home ownership process has been outdated and disconnected. Home search, brokerage, mortgage title closing, servicing all exist in separate ecosystems, forcing consumers to piece together a complex and frustrating journey. This disjointed system creates confusion, adds friction and drives up transaction fees totaling roughly 10% of a home's cost, and yet this inefficient, costly experience is still the accepted norm."

Krishna said the aim is to leverage the data from the combined companies to create a virtuous cycle that will boost efficiency and enable Rocket to pass along savings to consumers. "Rocket and Redfin sit at the crossroads of technology and human connection. We empower our team members with AI driven tools to help them provide the best client service in the industry. AI eliminates paperwork and administrative work, allowing agents and loan officers to focus more time on advising clients," said Krishna.

For instance, Rocket's AI has enabled loan officers to serve 54% more clients per team member than the previous years. Rocket also doubled its automation rates for appraisal and asset verification in 2024, and saved more than 1 million hours equating to $40 million in savings with AI.

In fiscal 2024, Rocket reported net income of $636 million on revenue of $5.1 billion, up 34% from the previous year amid an uncertain real estate market.

Krishna said that the combined company will ramp its investment in data and AI. "We want to invest deeply in data, in AI, and we see this deal as really accelerating both," he said.

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Asana: AI-driven work orchestration promising, but CEO search, multiple transitions ahead

Larry Dignan

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. ...

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Asana projected decelerating growth and is starting a search to replace CEO Dustin Moscovitz, but sees strength for its AI work coordination platform, AI Studio, amid economic uncertainty.

The company is about to make its AI Studio generally available with the aim of coordinating human and digital labor and automating workflow. Moscovitz cited use cases such as using AI to model workflows of SAP process testing, cybersecurity coordination as well as multiple workflows across industries.

"Unlike standalone AI Chatbots or simple task automation, we provide a structured, intuitive framework that both humans and AI can navigate and evolve together. This enables us to deliver AI capabilities exactly where teams work, with the essential context and security controls that enterprises demand. And our power extends beyond our proverbial walls," said Moscovitz. "Our strategy is to be the essential coordination layer for humans and AI across all teams and tools."

Asana plans to build more autonomous capabilities in AI Studio to make work management more adaptive. Asana has integrated Amazon Q Business into its platform for more insights on work.

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"Our competitive advantage doesn't depend on owning massive amounts of data," said Moscovitz. "We excel at orchestrating work across multiple AI agents and human teams, managing complex access controls and governance frameworks, and connecting cross-system workflows with enterprise-grade reliability."

The issue is that Asana's fourth quarter was largely in line. The company reported a net loss of 27 cents a share on revenue of $188.3 million, up 10% from a year ago. On a non-GAAP basis, Asana broke even. For fiscal 2025, Asana delivered revenue of $723.9 million, up 11% from a year ago.

As for the outlook, Asana said revenue growth will decelerate. Asana is projecting non-GAAP earnings of 2 cents a share on revenue of $184.5 million to $186.5 million, or growth of 7% to 8%. For fiscal 2026, Asana projected non-GAAP earnings of 19 cents a share to 20 cents a share on revenue of $782 million to $790 million, up 8% to 9%.

The deep dive on Asana is warranted for a few reasons. First, Asana has expanded into non-tech verticals and revenue from those customers were up 15% in the fourth quarter compared to a year ago. Asana's fastest growing verticals were manufacturing, energy, retail and media. That expansion also gives Asana a better view of the economy.

In addition, Asana's AI Studio is consumption-based, agentic AI-led and focused on "human AI coordination." Asana's goal is to have the "definitive platform for human AI coordination." said Moscovitz, who noted AI Studio is seeing strong demand. However, there are growing pains.

My hunch is what Asana is talking about is going to be repeated by other SaaS vendors in the quarter ahead. Customers are growing cautious, agentic AI will be consumption based and enterprises will wrestle with visibility and vendors are going to see lumpiness ahead.

• AI agents bring consumption models to SaaS: Goldilocks or headache?
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The CEO search. Moskovitz's retirement means that there's a search underway that's just getting started. The search will be internal and external and Asana will be patient about finding the right person. Moscovitz said he's at the helm for the duration. "I really think of the fiscal year ‘26 plan as my plan. And my personal goal is to be able to build the fiscal year ‘27 plan together with the next person," said Moscovitz.

Takeaway: It's unclear whether Moscovitz's retirement will affect buying behavior from enterprises. It’s difficult to replace a long-tenured CEO.

The consumption model. A quarter ago, Moskovitz was very bullish on AI Studio and its uptake. He still is, but AI Studio could be "a solid base hit for the company or it could be a grand slam." He said it has been hard to narrow the range of expectations because Asana doesn't have enough data to forecast the uptake by customers.

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Moskovitz said:

"When we've been forecasting internally, we repeatedly come to two specific variables that the model is incredibly sensitive to, but they're actually tiny percents with very large error margins.

So they create big swings in the outcome. The first is how many of our customers are going to adopt AI Studio at all? And generally, how many of our users are potential workflow builders? We've started by approaching our power users, the people who we think make great early adopters. That's going really well. I think we can forecast that now. But there's a much larger potential population of non-power users. And the difference between converting 1% or 3% or 5% of that population is just a massive swing in the model. And it's really going to depend on things like how effective our marketing is and how easy we make it to customize out-of-box workflows."

Asana is moving away from seat-based pricing and offering a credit-based consumption model focused on AI Studio Basic, which all customers have, and a Pro tier that includes credit. Most enterprise software vendors are moving to this seat-consumption hybrid model.

Takeaway: Asana is going to launch self-service for AI Studio and it will be able to tweak the experience and better model adoption. This refrain from Asana is likely to be a common theme from other SaaS vendors moving to consumption models.

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Consumption models can be lumpy and customers and vendors will need to be able to model usage. Moscovitz noted that all consumption models are going to be tricky to model. The current approach is vendors and customers are trying to model and average level of consumption. Moscovitz said:

"There's going to be a stratification with a small portion of customers consuming the vast majority of credits, like an 80-20 rule or probably a power law distribution. And I've seen plenty enough to be fully confident we're going to have some of those, as we refer to them, whales. Individual customers paying six figures, maybe even seven figures for consumption by the end of the year. But I haven't seen enough to know whether there's going to be five of those or 50 or even 5,000. So again, massive swing on the model."

He added that Asana's channel network is another swing factor for AI Studio.

Takeaway: What's unclear for Asana, and other SaaS vendors, will be whether consumption whales spread the love to multiple vendors or prefer one or two.

The pricing environment is at an inflection point and enterprises are wary. Asana's Moscovitz talked repeatedly about product, pricing and packaging. Asana is looking for "a menu of options to align price to value." This menu "is specific to both regional and macro dynamics," he said.

"What I've observed in the macro cycle is just more cautious buying behavior and customers becoming more budget conscious. And that means the growth opportunity involved in getting those details right has dramatically increased. The previously inelastic patterns are now more elastic. Customers want a lot more agency in choosing how their budget is leveraged."

Takeaway: Enterprise customers may be able to customize contracts a bit more.

Tech customers vs. non-tech customers and a potential recession. Asana said it has made a lot of traffic with verticals such as manufacturing, but those customers are the ones that are most cautious about adopting something like Asana AI Studio. Non-tech customers will expand Asana's market reach but that cohort is also more cautious.

However, Asana noted that tech customers are also showing signs of caution.

Anne Raimondi, Chief Operating Officer and Head of Business, said:

"Tech is definitely continuing to adjust spend and decision timelines continue to be elongated. We have not seen customer sentiment degrade thus far, but we also appreciate there's just a lot of uncertainty right now and things can and will likely change quickly. We're paying close attention to that in all of our customer conversations. I do think our focus over the last year on diversification and investments in additional verticals like retail, manufacturing, financial services have helped us with kind of steady and consistent growth, especially outside the U.S. But again, we know things could change rapidly."

Takeaway: Note the talk about customers becoming more cautious. Enterprises can't plan with any confidence due to tariff whipsaws, uncertain economic moves and flagging consumer confidence.

Constellation Research's take

Liz Miller, analyst at Constellation Research, said:

"Work management has been a hot space for early interest and experiments with AI in the hope that agentic intervention and process automation could transform work itself. However, as we see from Asana and other players in the space, once the lowest hanging fruit of efficiency and operational effectiveness that can be achieved by, for example, automating the repeatable or mundane, or expanding beyond to address precision automation and decision velocity has been a slower road marked by caution from buyers. 

The space is also being challenged by platform players looking to integrate work management and project management into their overarching workflow and work management. For example, Asana is not just facing competition from the likes of Smartsheet that has capabilities across work and project management, but also includes the Brandfolder product for asset and brand asset management. There is also pressure from enterprise platforms like Adobe that arguably knows the work of specific use cases like Marketing just as well if not better than Asana. Work management is at risk of becoming a commodity and not a strategic differentiator…and that is exactly where Asana should be looking to advance the conversation."

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Oracle Q3 a miss, but backlog portends big revenue growth ahead

Larry Dignan

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. ...

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Oracle continued to put up strong cloud and infrastructure as a service revenue growth, but its third quarter results fell short of expectations. However, Oracle said its cloud backlog is pointing to revenue growth of about 15% in the new fiscal year that starts in June.

The company reported third quarter earnings of $1.02 a share on revenue of $14.1 billion, up 6% from a year ago. Non-GAAP earnings for the quarter were $1.47 a share. Oracle has been wrestling with currency exchange rates vs. the US dollar like other global firms.

Wall Street was expecting Oracle to report earnings of $1.49 a share on revenue of $14.39 billion.

Nevertheless, Oracle's cloud growth has been impressive. By the numbers:

• Oracle cloud revenue in the third quarter was $6.2 billion, up 23% from a year ago.
• IaaS revenue was $2.7 billion, up 49% from a year ago.
• SaaS revenue was $3.6 billion, up 9% from a year ago.

8229391. Catz, Oracle CEO, said the company signed sales contracts worth more than $48 billion in the third quarter. "We have now signed cloud agreements with several world leading technology companies including: OpenAI, xAI, Meta, NVIDIA and AMD. We expect that our huge $130 billion sales backlog will help drive a 15% increase in Oracle's overall revenue in our next fiscal year beginning this June," she said.

CTO Larry Ellison said the company is "on schedule to double our data center capacity this calendar year." He added that Oracle's database revenue from Microsoft, Google and Amazon is up 92% in the last three months. GPU consumption for AI training was up 244% over the last year.

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In addition, Oracle said it is signing its first Stargate contract. Stargate is an effort by the US government, OpenAI, Oracle, Softbank and others to invest $500 million in domestic AI infrastructure.

Ellison added that Oracle is seeing "enormous" demand for AI inferencing on customer private data. Oracle is launching Oracle AI Data Platform that connects "OpenAI ChatGPT, xAI Grok and Meta Llama directly to Version 23ai of the Oracle Database with advanced vector capabilities," said Ellison.

Speaking on a conference call, Catz said "the growth of our power capacity under contract is even higher than the growth in the number of data centers, and we expect that our available power capacity will double this calendar year and triple by the end of next fiscal year."

That capacity will double this fiscal year and triple by the end of next fiscal year. "What we are seeing in the market is that we are the destination of choice for both AI training and inferencing. This is due to the fact that our gen two cloud is faster and therefore cheaper than our competitors, and also due to our ultra high speed networking engineering that we started decades ago and that is now highly relevant for AI," she said. 

Other key items from Catz:

• Component delays have slowed expansion this year, but should ease in the first fiscal quarter. 
• Cloud infrastructure revenue growth should top 50%. 
• Oracle revenue growth will be 15% in fiscal 2026 and accelerate to 20% in fiscal 2027. 
• Fourth quarter will continue to see currency headwinds. In constant currency, Oracle will see revenue growth of 9% to 11% in constant currency and 8% to 10% in US dollars. 
• Total cloud revenue will grow 25% to 27% in the fourth quarter in US dollars. 
• Fourth quarter non-GAAP earnings will be between $1.61 a share to $1.65 a share. 
• Stargate is not included in Oracle's remaining performance obligations. 

Holger Mueller, analyst at Constellation Research, said Oracle is clearly doubling down on cloud even though the third quarter was mixed. 

"Oracle had a tough quarter, slipping into the single zone 'pedestrian' growth, and barely beating inflation. It is clear that Oracle needed the Cloud @ business to maintain its level of revenue. What stands out is that Oracle doubles down on cloud with record capex close to $15 billion. Safra Catz usually invested 50% of cash flow into datacenters. Now it's 75%.  2025 will show if Oracle's doubling of OCI capacity can be monetized. AI workloads seem to be a key growth engine. But customers can also be fickle." 

 

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ServiceNow acquires Moveworks for $2.85 billion as it eyes CRM for agentic AI expansion

Larry Dignan

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. ...

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ServiceNow said it will acquire Moveworks in a deal valued at $2.85 billion in cash and stock. The purchase will give ServiceNow a front-end AI assistant and enterprise search tools to combine with its Now Platform.

According to ServiceNow, Moveworks will round out its strategy to be an agentic AI orchestration platform. ServiceNow is looking to do for AI agents what it did for workflows. In addition, ServiceNow said Moveworks will enable it to extend into CRM.

Moveworks and ServiceNow already have multiple joint customers. Moveworks is in FedRAMP Marketplace--a first for agentic AI platforms--and counts HP, Databricks, Unilever, Marriott and Toyota as customers. Here's a look at Moveworks' architecture.

Amit Zavery, president, chief operating officer and chief product officer at ServiceNow, said the combination of the Now Platform and Moveworks will "take another giant leap forward in agentic AI‑powered business transformation." Bhavin Shah, CEO of Moveworks, said the acquisition will accelerate its enterprise search and AI agent reach.

Key items about the ServiceNow acquisition of Moveworks include:

• Moveworks agentic AI platform has nearly 5 million employee users in 18 months.
• 90% of Moveworks customers have deployed it to all employees.
• The companies have about 250 mutual customers.

The plan going forward is to unify ServiceNow and Moveworks to provide a unified search and self-service experience for all employees across every workflow. AI agents will be focused on tasks across IT, CRM, finance and HR.

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Use cases for Moveworks revolve around automation for sales, CRM, finance and HR. Moveworks AI assistant is often deployed to bring customer data forward to service agents. Employee tasks for HR are another common use case. With the purchase, ServiceNow could be seen as more of a competitor to Salesforce, which has its own AI agent ambitions with Agentforce.

In fact, ServiceNow isn't shying away from CRM. The company said:

"The company plans to further integrate solutions such as CRM and customer service tailored to customer personas to deliver a cohesive sell, fulfill, and service experience on a single platform. By integrating Moveworks’ capabilities even further, ServiceNow will accelerate its AI‑powered solutions to improve customer interactions."

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Constellation Research's take

Constellation Research analyst Andy Thurai said:

"ServiceNow has already become the de facto enterprise standard in many services and support workflow management. This will help them convert to agentic AI-based workflows faster.

While ServiceNow's agentic AI and automation strengths in their platform have been around for a while, it needed a solution to build front-end AI assistants quickly and easily, and this deal helps. Combining the Moveworks assistant and AI-based enterprise search technology can accelerate employee productivity and customer service by deploying agents in within workflows. 

ServiceNow, along with the previous acquisition of Cuein in Jan now has an “AI-native” conversation data analysis platform, to enhance its data processing capabilities. ServiceNow is on the right track and moving fast in the agentic AI space."

Holger Mueller, an analyst at Constellation Research, added: "ServiceNow is building out its AI portfolio with Moveworks--evidently it wanted and needed functional capabilities. The question now is how fast it will the be of use for the border ServiceNow customer and prospect base."

On Bluesky, Chirag Mehta, an analyst at Constellation Research said:

"Salesforce is leading the market with agentic AI. It required them to undertake a massive engineering effort to rearchitect and retool everything in their portfolio. ServiceNow doesn't have the luxury of time. The agentic world is moving fast! A good validation of agentic AI and a good exit."

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Boomi launches AI Studio, makes its move on AI agent orchestration

Larry Dignan

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. ...

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Boomi launched Boomi AI Studio as it moves to be a hub to create AI agents, manage and orchestrate them.

The company is looking to address the reality that agentic AI has been largely confined to individual platforms. However, enterprises are rapidly scaling them. Boomi's bet with AI Studio is that enterprises will look for neutral vendors to create, govern and orchestrate AI agents.

Boomi AI Studio, which is in early access preview, can manage AI agents built by Boomi or third parties. Ed Macosky, Chief Product and Technology Officer at Boomi, said Boomi has deployed more than 25,000 AI agents for customers. Speaking at Constellation Research's AI Forum, Macosky said:

"We're all in on agents being the future. But the orchestration layer needs to bring them together into something intelligent. Do you have visibility? Nobody has that answer today. The number one concern in terms of agents and AI and business is security, compliance, governance and risk."

Macosky and Boomi CEO Steve Lucas will outline more details about Boomi AI Studio during a webinar. The company has been building its AI agent strategy.

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Boomi AI Studio has an integrated stack for AI agent design, governance and orchestration and includes that following:

• Agent Designer, which enables users to create and deploy AI agents with no-code templates. Boomi also has tools to ensure AI agents are grounded on enterprise data with security guardrails.
• Agent Control Tower has monitoring, visibility and control over Boomi AI agents and third-party agents via Amazon Bedrock with more partnerships planned. The Agent Control Tower also includes security and compliance features.
• Agent Garden gives enterprises the ability to design, test and deploy AI agents. Customers can interact with AI agents with natural language, collaborate and carry out tasks.
• Agent Marketplace will sit in Boomi Marketplace and be a hub for enterprise to discover and acquire pre-built AI agents that can be customized.

Boomi said it is accepting applications for early access to Boomi AI Studio. In the early adopter phase, a limited number of enterprises will access and offer feedback. General availability is expected in the second quarter.

More on AI agents:

• AI agents bring consumption models to SaaS: Goldilocks or headache?
• Agentic AI: Three themes to watch for 2025
• Agentic AI without process optimization, orchestration will flop

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Enterprise AI: Here are the trends to know right now

Larry Dignan

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. ...

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Enterprise AI is evolving at such a breakneck pace that it’s tough to keep up. AI, notably agentic AI, generative AI and the mutations to come, is rewriting business and society in real-time. Constellation Research's AI Forum in Silicon Valley surfaced a bevy of themes about enterprise AI.

Here's a look at what matters right now.

What DeepSeek taught us?

Dheeraj Pandey, CEO and Co-Founder at DevRev, said DeepSeek's surprise reset expectations in the AI and technology market. "DeepSeek busts the myth that America innovates, Europe regulators and China imitates," said Pandey. "You can take a big thing, make it small, and it's disruptive."

Karen Silverman, CEO of Cantellus Group, said DeepSeek illustrates how assumptions can change overnight. "For many years we've been staring at that exponential curve stick straight up. That's what DeepSeek feels like. Overnight there can be a complete shift in assumptions," she said.

DeepSeek moments will also have repeatedly. "I think this is going to happen again and again," said Silverman. "We need to saddle up."

• DeepSeek: What CxOs and enterprises need to know
• DeepSeek's real legacy: Shifting the AI conversation to returns, value, edge

Future of models

Models will need to replicate more than language. "The idea that models are going to replicate human interaction is absurd. We need to start thinking more completely and contextually. When you think about how humans interact, language is just 10% of how we communicate," said Silverman.

Models will become more of a hierarchy of services, as well as adaptation and innovative memory systems. "I think the next move is going to be low data," said Silverman. The idea of massive training and expense is going to be diminished.

More from AI Forum 2025:

• China vs. US AI war: Fact, fiction or missing the point?
• Boomi's product, technology chief on what's needed for AI agents to work together

Security and AI applications

AI will need to be developed for security. Yaron Singer, VP of AI and Security at Cisco, said bad actors can extract training data from a model, put instructions in a document that the models can learn, and do a lot of bad things at scale. "We are spinning off a team to build state of the art AI for security applications," said Singer, who was CEO at Robust Intelligence that tested vulnerabilities inside of AI applications and added protection.

Attack surfaces with AI will become much larger. Singer said:

"What I think is interesting about AI security specifically, is that not only that the attack surface becomes much larger, but the nature of AI makes it such that the solutions are very different. You can very easily manipulate the classification piece and then trigger operations, right that cause unwanted behavior. It's so non-deterministic that traditional security solutions that we have just don't apply."

Cisco is creating reference architectures to secure RAG and integrated security systems for the AI stack. As technology evolves and innovations like reasoning models emerge so will the threats.

Singer said he was bullish on open models over proprietary, but acknowledged that there may be more security risks.

He added that the biggest security worry is that generative AI models will develop their own protocols that become risks. Singer said that the risks will become even more magnified as AI codes.

Herding AI agents

Agents will have to work together on tasks and automate across business processes, but orchestration layers need to be built. "We're all in on agents being the future," said Ed Macosky, Chief Product & Technology Officer at Boomi. "But the orchestration layer needs to bring them together into something intelligent."

• AI agents bring consumption models to SaaS: Goldilocks or headache?
• Agentic AI: Three themes to watch for 2025
• Agentic AI without process optimization, orchestration will flop
• 13 artificial intelligence takeaways from Constellation Research’s AI Forum New York 

Will AI agents replace humans?

Walter Sun, Global Head of AI at SAP, said agents in the enterprise will serve to do repetitive tasks and be a junior assistant for each persona. "You still need a human being to address exception handling," said Sun.

Seema Swamy, Head of Insights and Data at Walmart, said: "I actually see a very good role for AI in optimization, because there are so many things that humans cannot do it as effectively." In tasks that are less about optimization and efficiency, Swamy is concerned about biases and transparency. AI is data and efficiency, and humans are creativity and innovation.

Jana Eggers, CEO of Nara Logics, agreed especially in marketing where enterprises can have more standardization in branding. Humans will take on more creative roles with AI focused on optimization. "Stop focusing on making AI superhuman, and start focusing on making it super. Stop trying to make AI replicate us," said Eggers.

Wannia Hu, VP of Product Management at UKG, said AI agents are about freeing up humans not replacing them, but the burden is on the employer to alleviate fears. "It is unfair to place all of the mindset change on employees. Call on employers to think about reskilling, upskilling, and making that part of the day to day. It's absolutely critical," said Hu.

David Levine, Founder of PlanDataAI, said AI agents won't replace humans, but the fear is palpable. Levine describes AI as evolutionary and the human element is critical to implement genAI. "I'm going to say AI is evolutionary not revolutionary. If you tell people that they're more open to it," said Levine.

Hu said the biggest risk is entry level jobs where college grads are expected to come in at a higher level with little training ahead of time.

AI investments

Barney Pell, Venture Partner at Radical Ventures, said "I'm seeing AI coming to every niche, and now I'm seeing companies being evaluated on how good their AI is."

"AI is big business and the whole stack," said Pell. "There's this constant motion of companies and teams coming out of the bigger companies to start companies. The innovation will all come at the application level."

Efficiency as AI starts to run companies

David Giambruno, CEO of Nucleaus, is a master at cutting costs (as noted on CCE 2024). He said:

"The world is going to change super-fast, like super-fast. Once you automate your infrastructure, your infrastructure is not your code. Your code now runs everything that is from a bottoms up view. We are starting to train the AI to run companies. We're going to go through a Darwin event. You see the magnitude of change and the ability for the systems to run themselves, it is absolutely fascinating."

Sunil Karkera, Founder of Soul of the Machine, said voice interfaces will be the UI of the future. That reality will also mean less overhead while expanding margins. Karkera's company is built on AI agents.

Giambruno said that there will be casualties due to efficiency. He was decidedly less optimistic than others due to following the money. He said:

"I'll be blunt, right? 50% of the people don't make it. What I do is as much as a technology exercise is a financial exercise. It's not the technology that's hard. It's the financial engineering."

What's next for agents, adaptive inference?

Denise Holt, CEO of AIX Global Media, said AI will ultimately learn and adapt through adaptive inference. In a nutshell, adaptive inference means that pretraining won't be necessary because AI will learn more like a biological system. Holt highlighted active inference at CCE 2024.

She said:

"This means that IoT and AR, VR, all these emerging technologies now become interoperable, so IoT becomes sensory information for these agents to understand this live data. It's unstructured. They can now seek to make sense of it. They have a grounded understanding of the actual real physical world as it's changing over time. So they don't rely on pre trained data sets. They can learn in real time from real data, and they can learn and share this information with each other in the exact same way. So then you have this knowledge layer that begins to grow and evolve as a collective intelligence."

Barbat Hodjat, CTO of AI at Cognizant, said the intersection of language models and the transformer training model and active inference will be critical to scaling. The problem is far from solved. "There are some really interesting interdisciplinary approaches," he said.

• Physical AI, world foundation models will move to forefront

Advanced AI compute and data centers go specialized

AI's power problem is being worked on, but the focus is more on choosing the right workloads for power. Sunny Madra, COO, President GTM, Operations and Supply Chain at Groq, said: “When it comes to energy consumption, we're not heading towards more efficiency or less energy. In fact, we're increasing the amount of energy. We look at that in terms of the racks that people are deploying and what they're going towards.”

Niv Zilberman, COO Aquatron DC Partners, said the industry is moving from general purpose processors. “We’re moving from general purpose compute and I'm just going to throw more compute at any problem into being workload driven. I think it is really optimizing not just the power and efficiency, but being able to deliver the accuracy in the right scale.”

AI as process automation tool

A panel of CFOs and finance execs outlined how they are using AI and in some cases process automation has driven cash flow improvements. The key takeaways:

• “Finance is a conversative function, but AI can be used to automate transactional-based functions. AR (accounts receivable) and AP (accounts payable) are the best AI use cases,” said Cathleen Nilson, CFO Xsolla. “AR and AP are a no brainer for any company of any size.” She added that AR and AP efficiency also improve cash glow for enterprises.
• Isabelle Wang, CFO Legion, is using AI to analyze the customer base and due diligence for internal project approval.
• Arnulfo Sanchez, Chief Accounting Officer at Datastax, said AI will eliminate monthly and quarterly close cycles. “Closes will be every day,” said Sanchez.

The panel wouldn’t use AI for tasks that require compassion, deal structure and deciding on big contracts and acquisitions.

The macro picture for AI

Navin Chaddha, Managing Partner of Mayfield, outlined the firm’s investment theses. He explained how AI is a once in a generation opportunity. Key points:

• “Our belief is AI is essentially going to team up with humans. I agree it will be humans in the loop to make them super humans.”
• “We think we are entering an era of collaborative intelligence, where AI will work with humans to change the way we work, live and play as humanity. Yes, in the short run, there'll be pain. Anytime a new technology comes up, there is pain, and the focus till now has been on, hey, let's cut costs. Let's improve efficiency. But what we are seeing with the new startups that are coming up, they’re actually being very smart. They are going after jobs that are not filled, jobs that humans don't want to do, or jobs that humans can't do.”
• “There are 30 million neglected small businesses. They can't hire knowledge workers. Now, suddenly, AI is an AI teammate. The technology is called agents, but the form it appears itself in, we call it a teammate, and that now expands the market, and it creates endless possibilities. Half the US economy is either 1099, or works in small businesses and now they can afford knowledge workers, which happen to be in the form of AI, and you pay for them when you use it.”
• The AI stack will be consumed by humans but also humans. “Every line of business function is going to have an AI teammate. Our thesis is AI teammates is a massive opportunity,” said Chaddha. “Today, the value is increasing to the hardware line, but it's going to very quickly move up to the app and the user layer.”

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Cybersecurity vendors race to secure AI agents, win platform

Larry Dignan

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. ...

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The cybersecurity majors are betting that the enterprise move to autonomous AI agents will speed up platform consolidation. The biggest takeaway may be that securing agentic AI may be a headache initially.

However, the destination is clear. Agentic AI will ultimately be secured by cybersecurity agents.

The big cybersecurity vendors--CrowdStrike, Palo Alto Networks and Zscaler--have been pitching platform consolidation for a year. And judging by recent earnings reports, enterprises are consolidating cybersecurity platforms. AI agents could be the accelerator to cybersecurity consolidation.

What remains to be seen is whether cybersecurity vendors are simply cribbing the playbook from SaaS vendors. Enterprise software vendors--Salesforce, SAP, ServiceNow and Microsoft to name just a few--are outlining agentic AI possibilities and not surprisingly these agents happen to work best if you're consolidated on their platforms. After all, the standards of communication, negotiation and the handoff between AI agents on different platforms aren't set.

Cybersecurity vendors also want you on their platforms to consolidate the data footprint. The reality is a bit messier. Yaron Singer, VP of AI and Security at Cisco, said at Constellation Research’s AI Forum in Silicon Valley that AI applications are expanding the attack surface. Singer said:

"What I think is interesting about AI security specifically, is that not only that the attack surface becomes much larger, but the nature of AI makes it such that the solutions are very different. You can very easily manipulate the classification piece and then trigger operations, right that cause unwanted behavior. It's so non-deterministic that traditional security solutions that we have just don't apply."

CrowdStrike CEO George Kurtz said agentic AI will require a new strategy. "More access to more third-party and in-house agentic applications and services requires rethinking identity and data protection," said Kurtz. "Who is accessing data and where is it traveling matters more now than ever before? Securing AI starts a broader enterprise data discussion. I'm seeing CISOs, CIOs, and CEOs going to the drawing board to reinvent their technology stack with AI-powered platforms of record. For security, it's even more pressing."

Kurtz indicated that securing agentic AI is going to require more cybersecurity agents. CrowdStrike features Charlotte AI, which works across its Falcon platform. The general idea is that Charlotte is a security analyst that can leverage CrowdStrike's first party data.

Palo Alto Networks CEO Nikesh Arora hit similar points when it came to securing agentic AI. Arora started cybersecurity's platformization push last year.

Arora said on Palo Alto Networks second quarter earnings call that companies need to harmonize data across the network and various enterprise systems. "Unless we can harmonize the data across the network, it will be challenging for customers to adopt AI-enabled security capabilities in the future," said Arora. "We have to believe that in the future, all solutions will need to integrate, harmonize data and use that to train AI agents to solve security."

The Palo Alto Networks CEO said that enterprises will move away from disparate cybersecurity tools in part because they'll need to consolidate data silos.

"These 1,150 customers who are platformized have data that is harmonized. We can run and build agents on top of that," said Arora.

In the future, you'll see AI security agents chasing down threats to AI agents focused on making decisions and automating workflows. Arora argued that one platform means you can harmonize data and security policies.

"I found a new raison d'etre for platformization. Our earlier sort of narrative was that you need a platform so you get a single pane of glass," said Arora. "As we go down this journey, we've been talking about deploying agents. Why do we need human beings trying to do these complex tasks and trying to understand how security you deploy it? Why can't we have agentic personas to be your network configurator or your phishing remediator. Why can't we design security agents? That's when you realize you can't design an agent unless you have the data."

Zscaler CEO Jay Chaudhry hit similar themes during the company's earnings call: "The growing adoption of AI is driving demand across multiple dimensions, including data protection and our AI-powered security products."

Zscaler is seeing strong demand for its data protection modules as generative AI is adopted. Enterprises are looking to prevent data loss to public AI apps.

Chaudhry added that cheaper foundational models will enable more attacks as well as productivity. "The release of DeepSeek R1 highlights advancements in model training, which can make Gen AI capabilities more widely available. Someone called it Jevons Paradox, which I agree with," he said. "In fact, I think this is the internet moment of AI, which will drive rapid adoption of AI in every aspect of our lives and will create a greater need for better security."

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Broadcom reports strong Q1, ups outlook on XPU gains

Larry Dignan

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. ...

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Broadcom and its custom AI processors are seeing strong demand as the company handily topped expectations for the fiscal first quarter.

The company, known for its AI XPUs, reported first quarter earnings of $5.4 billion, or $1.14 a share, on revenue of $14.92 billion, up 25% from a year ago. Non-GAAP earnings were $1.60 a share.

Wall Street was expecting non-GAAP earnings of $1.50 a share on revenue of $14.61 billion in the first quarter.

In the first quarter, Broadcom reported first quarter semiconductor revenue of $8.21 billion, up 11% from a year ago. Software revenue was $6.7 billion, up 47% due to VMware.

For the second quarter, Broadcom said revenue will be about $14.9 billion, well above the $14.59 billion.

CEO Hock Tan said:

"We expect continued strength in AI semiconductor revenue of $4.4 billion in Q2, as hyperscale partners continue to invest in AI XPUs and connectivity solutions for AI data centers."

 

Tech Optimization Data to Decisions Big Data Chief Information Officer Chief Technology Officer Chief Information Security Officer Chief Data Officer

HPE Q1 mixed, cuts outlook as it ‘could have executed better’

Larry Dignan

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. ...

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Hewlett Packard Enterprise saw server revenue surge in a mixed first quarter, but the company cut its outlook for the second quarter and fiscal year.

HPE reported first quarter earnings of 44 cents a share on revenue of $7.9 billion, up 16% from a year ago. Non-GAAP earnings were 49 cents a share, which was within HPE's previous guidance but a penny short of estimates.

Server revenue for HPE was $4.3 billion, up 29% from a year ago. Intelligent edge revenue was $1.1 billion, down 5%. Hybrid cloud revenue was $1.4 billion, up 10% from a year ago.

CEO Antonio Neri said the company's new products were "met with customer enthusiasm," but noted "we could have executed better in some areas."

HPE CFO Marie Myers said the company is cutting costs.

As for the outlook, HPE projected second quarter revenue between $7.2 billion and $7.6 billion with non-GAAP earnings of 28 cents a share to 34 cents a share. Wall Street was expecting second quarter non-GAAP earnings 50 cents a share on revenue of $7.93 billion.

For fiscal 2025, HPE projected revenue growth of 7% to 11% with non-GAAP earnings of $1.70 a share to $1.90 a share relative to Wall Street estimates of $2.13 a share.

By the numbers:

• HPE said it had $1.6 billion in new AI systems orders and AI systems backlog was up 29% sequentially to $3.1 billion.
• Operating profit margin in the service business was 8.1% due to "aggressive competitive discounting, executing challenges in inventory costs and transition."
• HPE GreenLake cloud ended the quarter with 41,000 customers.

HPE said it still is planning to close the Juniper Networks purchase and noted that its lawsuit vs. the US Department of Justice is scheduled for July 9.

• DOJ sues to thwart HPE's acquisition of Juniper Networks

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