Meta hopes to accelerate its AI agent plans with Manus acquisition

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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Meta acquired Manus in a deal that aims to give the company a rare win in artificial intelligence after a year of revamping. Manus is critical to fleshing out Meta CEO Mark Zuckerberg's dream of a universal AI assistant to get work done across its products.

Whether Meta allows Manus to run or bogs it down remains to be seen, but there are some fun facts worth noting.

• Manus is on a $125 million annual revenue run rate after eight months.
• The company is growing 20% month-over-month since it releases Manus 1.5.
• Manus' portfolio of agents is focused on getting work done including making presentations, design and a laundry list of other things SMBs need to do. Manus has multiple connectors to various systems.
• The company released its General AI Agent earlier in 2025 and the goal is to enable users to delegate tasks.
• In many respects, Manus was able to move faster than the giants with AI agents that actually deliver results for various use cases.
• Manus plans range from $20 a month to $200 a month with Team plans available.

Yes, Manus flew under the radar relative to OpenAI and Anthropic, but can accelerate Meta's plans. What are Meta's AI plans other than handing out massive pay packages, spending big on capital expenditures and falling behind on LLMs? Here's what Zuckerberg said in October about the company's AI research spending and agentic AI.

"The research is going to enable new technological capabilities to exist. And then those capabilities can get built into all kinds of different products. So the ability to reason more intelligently is, for example, very important across a large number of things. It would be useful for an assistant. It will also be useful in business AI. It will also be useful in the AI agent that we're building to help advertisers figure out what their campaigns are going to be....

There are lots of different capabilities to build. I'm not sure that any one company is going to be the best at all of them. I doubt that's going to be the case. But a lot of what we're trying to do is not like -- not kind of do some things that others have done. We're really trying to build novel capabilities."

In July, Zuckerberg said:

"I believe every business will soon have a business AI, just like they have an e-mail address, social media account and website. Our focus is now deepening the experience and making Meta AI the leading personal AI. As we continue improving our models, we see engagement grow."

• Meta Superintelligence Labs: A look of the challenges ahead

Manus should be able to get Meta closer to its AI agent vision. Meta said in a statement that it will "we will continue to operate and sell the Manus service, as well as integrate it into our products."

The paths forward for Manus could go like this:

• Meta will run Manus independently and it'll become a business AI brand that scales to a multi-billion revenue unit. Meta has built out its Instagram and WhatsApp businesses as part of a portfolio so there's some precedent.
• Manus agents will be built into a series of Meta products and absorbed. The technology remains, but Manus as a standalone business fades.
• Meta both operates Manus as a business and leverages it internally to maximize returns. Manus and Meta iterate on products and services.

Xiao Hong, CEO of Manus, said "joining Meta allows us to build on a stronger, more sustainable foundation without changing how Manus works or how decisions are made."

For now, Meta's Manus acquisition puts it back into the AI conversation as something more than a big spending also-ran.

Constellation Research's take

Holger Mueller, an analyst at Constellation Research, said the Manus deal is more of a hedge against its core advertising business. It's also an agentic AI play, but don't forget the ad angle.

Mueller said:

"In a world where it is not clear how AI is going to change how ads are going to be presented, consumed and paid for, Mark Zuckerberg is doubling down on AI and human supervision. The Manus agents pose interesting automation potential for knowledge workers, and an advertisement funded version of Manus, delivering AI automation first and then the ad at the moment of supervision. Brownie points for Meta if they are context and action aware."

2025 year in review: Quantum computing development accelerates

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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Quantum computing hogged the headlines in 2025 and it was ok to say it was the year of quantum--or maybe qubits--after just a few months. The quantum computing developments were flying, but it's worth noting that we're years away from big commercial adoption.

Nevertheless, CxOs need to get ready. After all, the boardroom is getting tired of AI. The AI trade lost steam. Boardrooms are going to start asking about your quantum computing plans in 3, 2, 1.

Why was 2025 the year of quantum? For starters, there was a new development almost weekly. Pure play quantum stocks were hot. Hyperscale cloud players were deadly serious about quantum, with AWS, Microsoft Azure and Google Cloud all running credible efforts. Quantinuum threaded the needle between AI and quantum computing. IBM scaled aggressively. And real use cases emerged as companies like IonQ cited projects with DARPA, AstraZeneca, and others.

Here's what's happened in 2025.

January

• Nvidia CEO Jensen Huang said quantum computing is 15- to 30-years away from being really useful. Those comments landed at CES 2025 and came up because quantum computing stocks had a torrid run at the end of 2024 as quantum became more practical, focused on hybrid HPC architectures and Google Cloud touted a new quantum chip called Willow.
• Quantum vendors have tried to prove Huang wrong since he made those comments. Days after Huang’s comments the pure plays such as IonQ and D-Wave all cited commercial projects.
• Microsoft launched its Quantum Ready Initiative, which helps enterprises sort out use cases for quantum computing and get ready to deploy.
• IonQ, University of Maryland and State of Maryland announced a $1 billion investment to create the "Capital of Quantum." Under the initiative, IonQ will be an anchor partner as it continues to pursue federal government contracts. IonQ at the University of Maryland's Discovery District, which is near Washington, DC and Annapolis, MD.
• D-Wave said it will expand distribution of its quantum computing offerings via a partnership with Carahsoft, which is a premier distributor of IT to the government. Under the deal, Carahsoft will aggregate D-Wave's offerings as a reseller. The partnership will give D-Wave throughput under Carahsoft's contract vehicles.

February

• Quantinuum launched its Generative Quantum AI framework that aims to combine AI, quantum computing and supercomputers to address problems classical computing can't solve.
• Microsoft launched Majorana 1, a quantum computing chip with a Topological Core architecture. Topological quantum computing uses a concept similar to semiconductors using "anyons," which can arrange qubits into patterns. A topological superconductor is a material that can create a new state of matter. It's harnessed to create a more stable qubit that can be digitally controlled.
• IonQ is doubling down on quantum networking with an acquisition, diversifying globally and has a new CEO along with fourth quarter results and plans to raise more capital. The purchase of ID Quantique gives IonQ more quantum networking patents and diversifies the company's global footprint with expansion in South Korea. In November, IonQ bought Quibitekk. IonQ named Niccolo de Masi CEO, with Peter Chapman becoming Executive Chair. Chapman will focus on strategy and enterprise adoption.
• Amazon Web Services launched Ocelot, a first-generation quantum computing chip that was developed with the California Institute of Technology.
• And for good measure, Constellation Research updated its quantum computing shortlists. Constellation ShortList™ Quantum Computing Platforms | Quantum Computing Software Platforms | Quantum Full Stack Players
• 

March

• D-Wave said its quantum computer outperformed a classical supercomputer in solving magnetic materials simulation problems. The company also reported its fourth quarter results. D-Wave followed up with a quantum blockchain architecture.
• Nvidia CEO Jensen Huang at Nvidia GTC 2025 hosted the company’s first quantum day. A panel that featured most of the quantum computing CEOs amounted to a mea culpa tour following Huang’s comments in January.
• Quantinuum quantum computers have created true verifiable randomness in a project that could be valuable to cybersecurity. In a paper in Nature, Quantinuum along with JPMorganChase, Oak Ridge National Laboratory, Argonne National Laboratory and the University of Texas have generated true randomness critical to cryptography and cybersecurity. Quantinuum said the latest advance was built on research from Shih-Han Hung and Scott Aaronson of the University of Texas at Austin.
• IonQ and Ansys said they also outperformed classical computing when designing medical devices. IonQ also expanded its quantum networking portfolio and raised more than $372 million via an equity offering.
• Classiq said it worked with Sumitomo Corp. and Mizuho-DL Financial Technology to successfully compress quantum circuits in implementing quantum algorithms for Monte Carlo simulations.
• Rigetti Computing and Quanta Computer said they will spend a combined $500 million to accelerate development and commercialization of superconducting quantum computing. The company also reported fourth quarter revenue of $2.27 million and 2024 revenue of $10.79 million. The net loss for 2024 was $200.99 million.

April

• IBM said it will spend $30 billion in R&D in the US as part of a broader $150 billion spend. That R&D in part will be devoted to quantum computing. IBM CEO Arvind Krishna said on the company’s first quarter earnings call: "In Quantum, we are proud to partner with the Basque Government to deploy Europe's first IBM Quantum System 2 in Spain, a milestone in global Quantum leadership." IBM also published a paper on how quantum addresses problems in combinatorial optimization.
• IonQ moved to expand its reach. It established a quantum computing and networking hub in Chattanooga, Tennessee in a $22 million deal. The company also outlined an agreement with Toyota Tsusho and AIST to expand quantum computer reach in Japan. IonQ also signed a memorandum of understanding with Intellian to extend into South Korea. IonQ also said its Forte Enterprise system is available through Amazon Braket.
• D-Wave and Davidson Technologies, a defense technology company, assembled D-Wave's Advantage2 annealing quantum system at Davidson's Huntsville, Alabama headquarters.
• Classiq, a quantum software development company, and Wolfram Research joined CERN’s Open Quantum Institute (OQI). The two companies will target quantum-based technologies to optimize electrical networks.
• Researchers at Tokyo University of Science, Japan unveiled DSAPS, a chip system that overcomes capacity and precision limits with dual scalable annealing processors.
• U.S. Defense Advanced Research Projects Agency’s (DARPA) Quantum Benchmarking Initiative (QBI) selected host of companies to evaluate a variety of technologies for creating quantum bits. The companies include: Alice & Bob, Atlantic Quantum, Atom Computing, Diraq, Hewlett Packard Enterprise, IBM, IonQ, Nord Quantique, Oxford Ionics, Photonic Inc., Quantinuum, Quantum Motion, QuEra Computing, Rigetti Computing, Silicon Quantum Computing Pty. Ltd. and Xanadu.

May

• IonQ went shopping again with the acquisitions of Lightsynq Technologies, a startup focused on photonic interconnects and quantum memory, and Capella Space, which specializes in quantum space networks. See: IonQ’s plan: Quantum networks extending into space
• IBM launched a Flex Plan for access to its quantum computing hardware in a move that aims to expand access for organizations, enterprises and researchers who want access without monthly limits. The IBM Quantum Flex Plan provides access on day one with an entry point of $30,000+ to gain access to Big Blue's entire fleet of quantum systems. Flex plan users will also get the advanced software features, support and early access to new releases.
• 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.
• D-Wave Quantum said its Advantage2 annealing quantum computer is now commercially available and is likely to contribute to revenue growth. Advantage2 is available via D-Wave's Leap quantum cloud service as well as on-premises deployments. Dr. Alan Baratz, CEO of D-Wave, said the system is a milestone in the company's development and able to "solve hard problems outside the reach of one of the world’s largest exascale GPU-based classical supercomputers."
• Cisco is entering the quantum computing networking ring with a lab and prototype processor. The move is notable since Cisco is a networking giant in the enterprise. In addition, quantum networking has been seen as a key piece of infrastructure.

June

• IonQ said it will acquire UK's Oxford Ionics in a deal valued at $1.075 billion in mostly stock and $10 million in cash. The deal is designed to accelerate IonQ's quantum computing roadmap and establish a global hub for research and development.
• Quantum Computing Inc. raised $200 million with an At-the-Market equity offering.
• IBM and Riken, a national research laboratory in Japan, unveiled the first IBM Quantum System Two ever to be deployed outside of US. The quantum computer will be co-located with Riken's supercomputer Fugaku.
• Rigetti completed a $350 million At-the-Market equity offering.
• IBM updated its quantum computing roadmap heading into IBM Quantum Starling, a large-scale fault-tolerant quantum system in 2029. Big Blue said IBM Quantum Starling will be delivered by 2029 and installed at the IBM Quantum Data Center in Poughkeepsie, New York. That system is expected to perform 20,000 times ore operations than today's quantum computers.

July

• D-Wave raised $400 million with an At-the-Market equity offering. The move left D-Wave with about $815 million in cash. D-Wave also outlined a strategic development effort to advance cryogenic packaging.

August

• D-Wave released a collection of developer tools for quantum AI and machine learning.
• Rigetti Computing said its 36-qubit multi-chip quantum computer is generally available and outlined a plan to build a 100-qubit system with 99.5% fidelity by the end of 2025, but quantum advantage is likely 4 years away. Second quarter results fell short of estimates.
• IonQ, which has been on an acquisition spree, reported second quarter results with a net loss of $177.5 million on revenue of $20.7 million. IonQ had $1.6 billion of pro forma cash and equivalents as of July 9. IonQ also filled out its leadership team with David Chung as VP, Corporate Development; Shad Reed as VP, Engineering Public Sector; Petrina Zaraszczak as VP, Business Operations & Integration; and Sterling Zumbrunn as VP, Product Management Networking.
• IBM, AMD eye hybrid quantum computing, supercomputer architectures.
• Microsoft rolls out quantum safe plan, timelines.
• Quantinuum fleshes out quantum software stack with open source Guppy, Selene.

September

• Quantum networking coming into focus with IonQ and Cisco playing roles.
• Microsoft said it will build quantum center in Maryland.
• Rigetti said it landed two orders for quantum computing systems for $5.7 million. Rigetti also announced a $5.8 million AFRL contract with QphoX.
• Quantum Computing closed a private placement of common stock to raise $500 million.
• IonQ announced purchase of Vector Atomic, completed the Oxford Ionics acquisition and inked a US Department of Energy memorandum of understanding to deploy quantum technology in space.
• IonQ launched a federal unit to focus on US government use cases. The company also named Inder M. Singh as Chief Financial Officer and Chief Operating Officer.
• SPACs are back as Horizon Quantum said it would go public via a merger with dMY Squared Technology Group.

October

• Quantum computing companies, often with minimal or no revenue, raise funds at a brisk pace to fortify balance sheets. Raise money when you don't need to is a good motto for CFOs to have. Even after a recent pullback Rigetti shares are up 200% on the year and IonQ is up 50%. D-Wave is up 356%. 
• Swiss Quantum Technology inked a €10 million to deploy D-Wave's Advantage2 system.
• The Basque Government and IBM launched Europe's first IBM Quantum System Two in Donostia-San Sebastián.
• IonQ priced a $2 billion equity offering to fortify its balance sheet following a run-up. IonQ also completed its acquisition of Vector Atomic.
• Arqit Quantum said its second quarter revenue wil be $460,000 to $470,000 with fiscal 2025 revenue of $525,000 to $535,000. The company had $36.9 million in cash.
• Quantum Computing announced a private placement of common stock to raise $750 million.
• Google said its Willow quantum computing chip has achieved quantum advantage. Google's breakthrough hit pure play quantum computing companies.

November

• Quantinuum launches Helios quantum computer, touts fidelity, enterprise customers
• IBM outlined its roadmap and launched its Nighthawk quantum processor. Big Blue also partnered with Cisco on quantum networking.
• IonQ, Rigetti, and D-Wave reported earnings as the pure plays continue to battle the giants.
• IonQ named Scott Millard Chief Business Officer and acquired Skyloom Global.

December

• IonQ and KiSTI finalized plans to bring a 100-qubit quantum system to South Korea.
• D-Wave said it will outline its commercial quantum plans at CES 2026.
• Quantum Computing Inc. named Dr. Yuping Huang CEO and acquired Luminar’s photonics business for $110 million.
• D-Wave launched a US government unit.

What now?

One thing worth noting here is that 2025 became the year of quantum readiness and development rather than deployment. That said, CxOs need to start thinking about quantum. Constellation Research analyst Holger Mueller broke down how you should be thinking about the year of quantum.

• If you need to protect IP against state actors, you should deploy quantum key encryption today.
• If you have smaller planning and simulation issues in your business, get your pilot going.
• If you are on process manufacturing, chemical, pharma etc. - you must have quantum pilots. You likely have them on annealing and laser gate already but need to keep an eye on all super conducting players.
• Everybody else can sit back and get the popcorn, but keep an eye on medium-scale planning and simulation use cases. All enterprises have those. On the tech side, watch stabilization, componentization and then scale loop. IBM is the most advanced and learn from their process.

Nvidia's Groq deal: Acquisition, acquihire or creative licensing deal?

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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Groq announced it has entered a non-exclusive licensing agreement with Nvidia for Groq's inference technology. Groq CEO Jonathan Ross and team will join Nvidia, but Groq will operate independently with GroqCloud.

News of a licensing deal landed as CNBC reported that Nvidia was buying Groq.

CNBC reported that Nvidia is acquiring Groq for $20 billion. CNBC's David Faber cited Groq investor Alex Davis, CEO of Disruptive, has his primary source. Groq, founded in 2016, had a valuation pushing $7 billion.

Groq’s secret sauce is a processor it calls the LPU (language processing unit). ‘The LPU integrates hundreds of MB of SRAM as primary weight storage (not cache), cutting latency and feeding compute units at full speed. This enables efficient tensor parallelism across chips, a practical advantage for fast, scalable inference,” said Groq. Groq's LPU is designed specifically for efficient AI inference.

Following the CNBC report, Groq announced it has entered a non-exclusive licensing agreement with Nvidia for Groq's inference technology. Groq statement in full:

“Today, Groq announced that it has entered into a non-exclusive licensing agreement with Nvidia for Groq’s inference technology. The agreement reflects a shared focus on expanding access to high-performance, low cost inference.

As part of this agreement, Jonathan Ross, Groq’s Founder, Sunny Madra, Groq’s President, and other members of the Groq team will join Nvidia to help advance and scale the licensed technology.

Groq will continue to operate as an independent company with Simon Edwards stepping into the role of Chief Executive Officer.

GroqCloud will continue to operate without interruption."

The Groq-Nvidia deal rhymes with how Meta handled the Scale AI deal. In that deal, Meta invested in Scale and gave it a valuation of $29 billion. Scale's founder Alexandr Wang agreed to work for Meta and now leads its AI efforts.

• Meta Superintelligence Labs: A look of the challenges ahead

In the end, Nvidia will get Groq's AI accelerator chip technology no matter what you call the deal. The Groq purchase would be Nvidia's largest.

• Nvidia launches Nemotron 3 open models to enable multi-agent systems
• Nvidia's Q3 stellar as data center revenue up 66%

2025 in review: AI trends from the buy side and sell side

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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As CxOs zoom out on 2025, it's clear that the year was characterized by AI building blocks and the need for real returns. Agentic AI platforms aren't quite mature, but the industry standards and connections are making deployments more realistic.

If you're an enterprise technology buyer the onus is on the vendors for showing value and more than proof of concepts. The game for both the buy side and the sell side revolves around use cases that show returns and can scale across the enterprise.

For vendors, the appeal of this use-case-by-use-case motion is selling a platform that can create, manage and orchestrate AI agents. For CxOs, the chase is the autonomous enterprise and efficiency and productivity gains that can fund more AI efforts.

In many respects, 2025 was a tale of two halves. The first half was dominated by economic volatility and skepticism about what vendors were pitching.

In the second half, the vendor platforms matured and proofs of concepts began to move to production. There also seems to be consensus that AI, automation and process are comingled.

Get Constellation Insights

For the 2025 analysis, I homed in on all the Constellation Insights articles posted throughout the year and analyzed the broad themes in enterprise technology, the buy side and the sell-side vendors.

Common themes in 2025

Agentic AI grew up, but still isn't what any reasonable executive would call mature. Agentic AI is a heavy lift that includes forward-deployed engineers, an enterprise data strategy that works, services and use case refinement. Simply put, it's easy to build an AI agent. Scaling them with guardrails and building enough trust to let these models run your company is another matter entirely.

AI economics in flux. Salesforce's recent move to offer an agentic enterprise license agreement is notable because it gives enterprises predictability. The consumption approach from SaaS didn't work out for many buyers. Vendors want to monetize the value they're creating, but enterprises are tired of bills continuing to rise. A consensus emerged that there will be multiple models that are combined to optimize for price performance. Hyperscalers are working custom silicon to commoditize compute and models will be rightsized for the task at hand.

Everything is a platform. SaaS providers are branching out beyond their core markets to become broader AI agent platforms. There isn't a vendor that doesn't have a horse in the AI agent platform race.

The real wins will revolve around industry-specific use cases and first-party data. Enterprises are beginning to leverage their unique data to train models and optimize use case by use case and industry by industry. Context is everything. Again, it's easier said than done.

The buy side

AI is an excuse to change operating models. Enterprises are beginning to use the agentic AI push as a way to optimize operations across all processes and use cases. These efforts would take longer under yesterday's transformation projects, but AI is giving smart companies air cover to accelerate plans.

• Costco approaching AI in "very Costco way"
• Rivian's AI strategy: Four takeaways
• CVS Health outlines AI-driven "engagement as a service" plan
• Warby Parker's third act revolves around AI
• JPMorgan Chase's IT, AI bets: Where the returns are

Models are a commodity. Enterprises are no longer wowed by the latest and greatest models. China's DeepSeek and Qwen from Alibaba changed that proprietary model thinking in early 2025. Now enterprises are just as likely to use Nova models from AWS or open source as they are the big three models. That said models are a key ingredient of buying decisions of broader platforms.

• Target cuts deal with OpenAI as it plans customer experience overhaul
• Google Cloud, KPMG outline lessons learned from Gemini Enterprise deployments
• Virgin Voyages: Lessons learned from scaling Google Gemini Enterprise AI agents
• A look at the intersection of AI and customer experience

Multi-cloud, multi-model, multi-everything. Enterprises have always been wary of lock-in (and still do it anyway), but AI is advancing so quickly that CxOs want neutrality and options. Interoperability is a requirement and AWS, Google Cloud and Microsoft Azure are beginning to connect. AI sprawl isn't a concern yet, but will be soon.

Technology strategy and business strategy merge. Spend on infrastructure, applications, models and ecosystems are driven by margins, agility and resilience of all types. Enterprises will look to AI as a way to abstract away technical debt.

• TD SYNNEX CIO Kristie Grinnell on adopting AI, tech debt and change management
• Google Public Sector Summit 2025: Takeaways on data, AI, ROI from 7 technology leaders
• How Wayfair's replatforming sets it up for agentic AI commerce
• Airbnb: A look at its AI strategy
• Citigroup AI agent pilot underway for 5,000 workers
• Goldman Sachs eyes next AI transformation from position of strength
• Delta starting to scale its AI-driven dynamic pricing system

Value over vision. Enterprises are shrinking budget cycles and demanding measurable impact. Enterprises care about efficiency, productivity, customer experiences and revenue gains. Vanity pilots are kaput. Practical AI is in.

• CCE 2025: AI agents: Dreams, reality and what's next
• CCE 2025: What the CxOs are saying about CX, AI, process
• For AI agents to work, focus on business outcomes, ROI not technology
• AI Forum Washington, DC 2025: Everything we learned

It's still all about data. The enterprises that have a coherent data strategy, data quality and modern pipelines and platforms can win in the AI age. Too few enterprises have their data game down.

The sell side

Every vendor wants to be your sole platform. A tenured CxO would chuckle at these AI vendor developments. Why? Vendors have always wanted to consolidate all of your spending with them. Picking a vendor that can be your one go-to agentic AI platform isn't easy.

• Pondering the future of enterprise software

The value sales pitch. Vendors increasingly talked enterprise value, use cases and process optimization. They're certainly talking a good game. By mid-2025, this value-based sales pitch became the norm. Enterprise vendors and even OpenAI and Anthropic are all using the industry and use case playbook with partners or via direct sales.

• BT150 zeitgeist: Consumption-based pricing angst abounds

LLM giants build ecosystems. OpenAI and Anthropic, not to mention Google's Gemini, are building ecosystems and applications that can leverage their models. What's unclear is whether these LLM giants can be the overarching interface that relegates enterprise software to plumbing. Also keep an eye on Databricks and Snowflake, which could leverage their data platforms to be the overarching enterprise layers.

• The enterprise LLM questions you should be asking
• LLM giants need to build apps, ecosystems to go with the models

Orchestration is the big thing. Vendors are pitching themselves as your go-to AI orchestration layer. For a vendor, agent orchestration will drive stickiness and revenue and lock-in. It's also possible that orchestration and data gravity will go together and drive vendor revenue.

Hyperscalers gain clout. Aside from ServiceNow, hyperscalers and integrators are the most natural fit to be that overarching AI platform, abstraction and orchestration layer. The big three cloud players are horizontal, touch every part of the enterprise and have pricing models that naturally go together with AI agents. Add it up and AWS, Microsoft Azure and Google Cloud all gained clout in 2025.

The year in Insights

• Rimini Street’s second act will include heavy dose of agentic AI, UX
• AWS re:Invent 2025: This one was different
• The enterprise LLM questions you should be asking
• Frontline workers get their AI moment
• A look at the intersection of AI and customer experience
• AGI may be far away, but 'jagged AI' will still take jobs
• CCE 2025: AI agents: Dreams, reality and what's next
• OpenAI, Anthropic increasingly diverge as strategies evolve
• Welcome to the context chorus: There’s no AI without context
• Big bank CEOs, CFOs riff on state of AI exuberance
• Neptune Insurance highlights AI exponential, data, build vs. buy trends
• AI Forum Washington, DC 2025: Everything we learned
• Enterprise AI: It's all about the proprietary data
• The big AI, SaaS, transformation themes to watch in 2025’s home stretch
• AI agents, automation, process mining starting to converge
• LLM giants need to build apps, ecosystems to go with the models
• Pondering the future of enterprise software
• Secure browsers will matter more with AI agents
• Watercooler debate: Are we in an AI bubble?
• LLMs on sale: What happens when OpenAI, Anthropic offer Feds value meal pricing?
• Watercooler debate: Is it the data or the infrastructure?
• The road to AI Exponential will be bumpy
• Enterprise technology customers look to AI, efficiency to combat uncertainty
• The rise of good enough LLMs
• The disconnect between tech euphoria, CFOs is jarring
• What we learned from enterprise tech buyers in first half of 2025
• AWS re:Inforce 2025: GenAI, AI agents and common sense security
• A tour of enterprise tech inflection points
• RPA and those older technologies aren’t dead yet
• JPMorgan Chase’s IT, AI bets: Where the returns are
• Agentic AI: Is it really just about UX disruption for now?
• AI infrastructure matures, GPU supply and demand may even out
• Lessons from early AI agent efforts so far
• Every vendor wants to be your AI agent orchestrator: Here's how you pick
• Resilience is the key enterprise theme and it favors the large
• Agentic AI: Everything that’s still missing to scale
• Financial services firms: The only certainty is investing in AI transformation
• AI strategies and projects: The hope, the fear and everything in between
• After volatile first quarter, these 10 questions loom over enterprise technology, CxOs
• Humanoid robots near inflection point courtesy of AI
• The data wars are just starting and agentic AI may be a trigger
• AI? Whatever. It's all about the first party data
• Enterprise AI: Here are the trends to know right now
• The year of quantum computing (already)
• Will CX suffer from an overreliance on AI?
• Hershey finishes SAP S/4HANA implementation: Is it sweet or suite?
• AI agents bring consumption models to SaaS: Goldilocks or headache?
• DeepSeek's real legacy: Shifting the AI conversation to returns, value, edge
• Here’s what technology buyers say about AI, technology, transformation
• GenAI prices to tank: Here’s why
• Delta Air Lines completes cloud migration, eyes data, AI-driven customer experiences
• Physical AI, world foundation models will move to forefront
• 2025 in preview: 10 themes in enterprise technology to watch

ServiceNow makes its cybersecurity move, acquires Armis for $7.75 billion

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 acquired Armis, a cybersecurity exposure management company, for $7.75 billion in cash in a move that will triple the company's addressable market in security.

For ServiceNow, the Armis deal expands its cybersecurity reach and can accelerate growth for its Security, Risk and Operations Technology (OT) portfolio, which delivered more than $1 billion annual contract value in the third quarter. Armis flagship offering is Centrix, a cyber exposure management platform that has real-time visibility, risk assessment and proactive protection. Centrix aims to secure IT, OT, internet of things and medical devices.

Armis has more than $340 million in annual recurring revenue and growth of 50%. Armis, founded in 2015, has about 950 employees that will join ServiceNow.

ServiceNow will be able to integrate Armis Centrix with its AI agents and workflow tools. ServiceNow Autonomous Risk and Security aims to unify cybersecurity and risk operations on one platform. “Autonomous IT only works if platforms can see, decide, and act in one system. Armis gives ServiceNow the ‘see’ layer it needed to make that vision credible," said Constellation Research analyst Chirag Mehta. 

Armis, which competes with Nozomi Networks, Claroty, Dragos, Microsoft, Palo Alto Networks and Fortinet among others, is on multiple Constellation Shortlists:

• Constellation ShortList™ Healthcare Medical Device Security
• Constellation ShortList™ Operational Technology Security
• Constellation ShortList™ Healthcare IT Security

With the Armis deal, ServiceNow also gets a cybersecurity platform that reaches multiple industries including manufacturing, telecom, retail, logistics, automotive, energy and health care. Armis also has a public sector footprint.

In a statement, ServiceNow said the plan is to create a unified security exposure and operations stack. Amit Zavery, president, chief operating officer and chief product officer at ServiceNow, said "together with Armis, we will deliver an industry-defining strategic cybersecurity shield for real-time, end-to-end proactive protection across all technology estates."

Yevgeny Dibrov, co-founder and CEO of Armis, said ServiceNow will help its security platform scale.

ServiceNow said Armis will provide cybersecurity data to ServiceNow AI Control Tower, which manages and governs enterprise AI, and pair up with various components of the ServiceNow AI Platform.

Constellation Research's take

Mehta handicapped the ServiceNow and Armis deal and the implications. 

“ServiceNow’s acquisition of Armis reflects a clear recognition that workflow orchestration alone is no longer sufficient to manage cyber risk in an AI-driven enterprise. As AI adoption expands the attack surface beyond traditional IT into operational technology, medical devices, and unmanaged assets, ServiceNow needed deeper, real-time visibility into what is actually connected and exposed. Armis fills this gap by bringing continuous, agentless asset intelligence and exposure management that extends across IT, OT, and cyber-physical environments. The strategic value lies in pairing Armis’ real-time exposure context with ServiceNow’s ability to prioritize, govern, and act through workflows, moving customers from reactive security operations toward measurable, continuous risk reduction. This deal positions ServiceNow to compete not as another security point product, but as an AI-native control plane where exposure intelligence is directly translated into enterprise action.

ServiceNow had already established itself as a strong orchestration layer for security, risk, and IT operations, supported by CMDB and AI-driven workflows. However, it depended heavily on external tools for asset discovery and exposure data, especially for unmanaged, non-IT, and cyber-physical environments. This created a structural gap: ServiceNow could route and govern work, but it did not natively “see” the full attack surface with sufficient fidelity or timeliness to support autonomous decision-making. Armis brings precisely what ServiceNow lacked: real-time, agentless discovery and classification across IT, OT, IoT, and medical devices, combined with deep exposure analytics. Its strong adoption across Fortune 100 enterprises and public-sector organizations demonstrates that this capability is already trusted at scale.”

More:

• ServiceNow acquires Veza, will integrate into AI Control Tower
• ServiceNow Q3 shines as it raises outlook due to enterprise AI demand
• ServiceNow launches AIx as AI becomes the platform UI
• ServiceNow launches Zurich release, inserts process, task mining into AI agent workflows

HCLSoftware’s Actian acquires Wobby, Jaspersoft as it builds out data 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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HCLSoftware said it will acquire Wobby, a startup focused on providing AI agents for data platforms and combine it with its Actian unit. Separately, HCLSoftware said it's acquiring Jaspersoft from Cloud Software Group in a deal to build out Actian's agentic AI toolset.

Terms of the deals weren't disclosed

Actian, the data and AI division of HCLSoftware, is seeing strong demand for its metadata, data catalog and governance tools. Wobby will bring an agentic AI data analyst to Actian so customers can get insights on complex datasets quickly.

HCLSoftware added that Wobby will accelerate its data engineering roadmap.

Wobby features a natural language interface, a proprietary semantic layer and architecture that interprets context and automates complex workflows. Wobby will complement the knowledge graph in the Actian Data Intelligence Platform.

• Actian adds marketplace, self-serve to Actian Data Intelligence Platform

Actian CEO Marc Potter said in a statement that Wobby will give the company's platform an "LLM-powered natural-language analytics on a unified, governed semantic layer, enabling self-service analytics."

Wobby has multiple integrations including Snowflake, Databricks, Collibra, Cube, Microsoft Data Fabric, Google Big Query and Amazon Redshift. Wobby's flagship AI agent is its Deep Analysis Agent that aims to provide multi-angle analysis on data even with basic prompts using a multi-agent architecture.

The acquisition is expected to close in February.

HCLSoftware's acquisition of Jaspersoft followed the Wobby announcement.

Jaspersoft, a unit of Cloud Software Group, provides analytics and a reporting platform. Jaspersoft will be folded into Actian.

With Jaspersoft, Actian will be able to accelerate its data management experience plans with interactive dashboards, advanced visualizations and reporting. Jaspersoft also brings a developer base of data engineers and architects.

The Jaspersoft purchase is expected to close within six months of signing.

Alphabet buys Intersect for $4.75 billion to boost its data center energy options

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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Alphabet said it will acquire Intersect, a startup focused on energy for data centers, for $4.75 billion and the assumption of debt. Google, a unit of Alphabet, owns a minority stake in Intersect.

Last year, Intersect announced a partnership with Google and TPG Rise Climate to scale renewable power and storage for new data centers.

As cloud providers, notably Google Cloud, AWS, Microsoft Azure and Oracle, scale data centers power becomes the largest hurdle.

In a statement, Alphabet said that Intersect will remain separate from the company and Google. However, Intersect will work with Google's technical infrastructure team to develop projects. Intersect and Google are already collaborating on a co-located data center and power site in Haskell County, Texas.

The focus of the deal is on new assets and don't include Intersect's existing assets in Texas and California. Those Intersect assets will remain independent with the company's existing investors. Sheldon Kimber, CEO of Intersect, will continue to lead the company. Intersect has $15 billion of infrastructure operating or under construction and plans to have 10.8 GW in construction or operating by late 2028. Intersect also has partnerships with Tesla and First Solar as well as Google.

According to Alphabet and Google CEO Sundar Pichai, Intersect will "will help us expand capacity, operate more nimbly in building new power generation." Alphabet and Google said Intersect will augment its energy efforts underway with utilities and energy developers.

"For a long time we thought the AI race was all about the GPUs, but Alphabet's investment in Intersect makes it clear - it's all about energy. Without energy, there's no data center, no GPUs (or TPUs for Google) and no AI," said Holger Mueller, an analyst at Constellation Research.

In a blog post, Kimber said:

"AI today is stuck behind one of the slowest, oldest industries in the country: electric power. The country has racks full of GPUs that can’t be energized because there isn’t enough electricity for them. The grid is a patchwork operating system that’s been running for a century. An engineering miracle in its time but not built for the AI era.

America deserves a better business model for electricity. That model is increasingly ?'bring your own generation.'"

Paychex: How it's playing AI on multiple fronts

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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Paychex is betting that its proprietary data sets in human capital management and adjacent markets will make it a winner in AI via productivity and new products.

The company reported better-than-expected second quarter earnings driven by its acquisition of Paycor, announced a year ago, and AI-driven efficiencies. Paychex reported second quarter earnings of $1.10 a share on revenue of $1.56 billion, up 18% from a year ago. Non-GAAP earnings were $1.26 a share.

• Paychex acquires Paycor in $4.1 billion deal
• Constellation Research Shortlist vendors for payroll for North American SMBs and HCM suites focused on North America.

For fiscal 2026, Paychex is projecting revenue growth of 16.5% to 18.5%. Paychex CEO John Gibson said the company now expects to save $100 million in expenses via the Paycor integration.

Along with the earnings results, Paychex outlined its AI plans and its positioning. The company recently launched agentic AI tools to automate payroll processing, created a knowledge mesh system that organizes unstructured data such as calls and emails into a searchable network and layered generative AI throughout its platform.

Here's a look at the takeaways from Gibson on Paychex earnings call and cover multiple AI disruption points.

AI employment disruption. Paychex business depends on employees and there's a risk that AI will mean less employment and revenue for the company. Gibson said more than 70% of its customers employees work in "blue and gray-collar industries" that are harder to displace. In addition, the Paychex customer base skews SMB where staff where multiple hats. Those roles are harder to replace with AI.

"If AI disrupts large firms disproportionately, talent may shift to smaller businesses, benefiting our clients. Meanwhile, our clients continue to face talent shortages and AI can help improve efficiencies to address those gaps," said Gibson.

Simply put, there’s a valid case that AI disruption at large companies is going to mean that reskilling efforts will need to go well beyond AI and into entrepreneurship.

The Paychex revenue model. Gibson said that Paychex has a revenue model that has a significant fixed base fee component and that historically has insulated it from employment fluctuations. Paychex also HR experts to go along with the technology platform.

Proprietary data. Gibson said: "In terms of our differentiation, AI success hinges on data quality and data scale. With one of the largest proprietary datasets in the industry, we believe we have a powerful competitive advantage to drive superior AI performance."

This first-party data argument is something you're going to hear across multiple enterprises in technology and beyond. The game is going to be leveraging that data to spin off new products and services, becoming more efficient and building a moat around the business model.

"I think AI is going to be very interesting as we try to productize it. We're going to try to improve the customer experience. We're going to try to add more value to our product to differentiate ourselves because there are very few players that have the depth of insights and information from our data that we can provide inside the technology," said Gibson.

Pragmatic AI applications. Paychex plays in a crowded market where it can compete with ADP, Rippling, Intuit, Trinet, Dayforce and a bevy of others depending on the market. The acquisition of Paycor enabled Paychex to cater to more mid-sized businesses.

Gibson said Paychex is focused on "delivering pragmatic AI solutions focused on measurable outcomes such as time saved and friction removed from everyday processes." An AI-driven employment law and compliance platform would be an example. The company is piloting its first agentic AI tools now.

Holger Mueller, an analyst at Constellation Research, said:

"Paychex is playing with its two offerings Paychex at the lower end and Paycor for enterprises. Being able to serve both markets is attractive and investors are seeing a few more quarters of favorable comparisons thanks to the Paycor acquisition. To position itself for the new set of AI startups, Paychex will have to do more though. Fast growing startups in the past would buy large enterprise systems - larger than needed in many cases - to signal to investors they were ready for massive growth. Paychex will need to continue to appeal to those new companies."