This list celebrates changemakers creating meaningful impact through leadership, innovation, fresh perspectives, transformative mindsets, and lessons that resonate far beyond the workplace.
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. ...
IBM said it will acquire data streaming company Confluent in a deal valued at $11 billion. The deal will give IBM an open-source data platform with an annual revenue run rate topping $1 billion that can provide governed data to AI agents.
In a statement, IBM said the deal will add to non-GAAP earnings in the first year and boost free cash flow in year two after the deal closes. IBM CEO Arvind Krishna said the companies will "enable enterprises to deploy generative and agentic AI better and faster by providing trusted communication and data flow between environments, applications and APIs."
Confluent gives IBM a platform that will connect and reuse data for applications notably AI agents. In many ways, Confluent will be to IBM what MuleSoft and Informatica is to Salesforce--data connection and integration engines that provide the information that AI agents will need to make decisions. Confluent has said that AI will drive the company's next phase of growth due to the need for real-time data streaming.
Here's a look at the Confluent stack that has multiple deployment options such as Confluent Cloud, a managed data streaming platform, Confluent Platform, a self-managed deployment, WarpStream, a hybrid deployment model, and a private cloud offering.
Confluent CEO Edward Kreps said IBM's scale will accelerate its strategy and boost go-to-market efforts. IBM will use Confluent to advance its hybrid cloud and AI strategy, enhance efforts across the company's portfolio and give it a growth engine. IBM said Confluent will also complement Red Hat and its data and automation portfolio.
Confluent is also based on Kafka and offers managed open source data streaming. That approach fits in with IBM's open source cred, but also appeals to enterprises looking to avoid lock in. Confluent's value prop was outlined by Kreps at a November investor conference:
Managed open source data platform and focusing on what's needed for cloud engineering and running distributed data systems.
Real-time data streaming via a "broad platform where all the parts work together" including connectivity, governance and real-time processing with Confluent's Flink compute offering.
A cloud-native system that works across all environments. "The role of the technology is to kind of act as like a central nervous system that plugs together all the applications and parts of the company," said Kreps.
Here's what IBM is getting with Confluent:
A data platform that can be used to not only wrangle data but offer point-in-time queries on static data that can better automate decisions. Confluent has argued that companies are software and data will enable continuous action.
Permission to play in a hot market. Confluent competes with a range of players including hyperscalers like AWS and its Kinesis.
Connectors and governance that will collapse enterprise systems with an AI layer that turns into the user interface. Kreps said: "We've conceived software applications as being primarily these little islands of UI. And if you think about how these systems are going to work together, that's become less true over the years and AI is probably making it even less true. The access to the data and APIs that drive the functionality is going to be as important as the thing you see on your phone or web browser."
Solid revenue growth and non-GAAP profitability. Confluent went public in June 2021 and through its third quarter report in October topped a $1 billion annual revenue run rate. Cloud revenue in the third quarter was up 24% to $161 million.
Industry data plays that can be scaled with IBM's vertical focus and IBM Consulting.
Constellation Research's take
Michael Ni, a Constellation Research analyst, said:
"This deal gives IBM the nervous system it was missing. Without real-time streaming, you can’t empower real-time agents, AI-driven workflows, or dynamic decisioning. They all depend on with streaming context, signals, and intent-driven triggers. IBM just closed a structural gap and jumped into the autonomous enterprise platform race with Microsoft, AWS, Google, and Databricks. Expect accelerated consolidation across data and AI platforms as IBM continues to repositions itself as one of the major data infrastructure consolidators."
Constellation Research analyst Holger Mueller said:
"IBM is taking a now proven strategy to its third iteration: Buy a key piece of technology with an open source flavor--RedHat, Hashicorp and now Confluent--that enterprises want and need professional services to implement. Confluent's streaming data capabilities are relevant in the current phase of AI adoption in the enterprise as it provides data to all the places where it is needed."
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. ...
Those are a few of the words I've heard when analysts are summing up AWS re:Invent 2025. As usual, there was a firehose of news announcements and talks about strategy today and going forward.
What has emerged is that AWS is becoming a different company. Yes, AWS is firmly committed to developers and dedicated to creating building blocks needed to scale agentic AI. But AWS is clearly more than an infrastructure company now. It's not quite a software company either. When AWS CEO Matt Garman goes through announcements like AWS S3 Vectors in 30 seconds you know the company is a bit more curated.
Here's all the infrastructure stuff AWS announced. In previous years, this slide would take up the whole keynote. In 2025, it's a 10-minute fast break bit.
Like its customers, AWS is on a journey that's being reshaped by AI agents. The AWS picture is never complete. The other thing to realize about AWS is that there's now a 6-month cadence for big rollouts. AWS Summit New York, where the company first took its practical approach to AI for a spin, is now a mini re:Invent. AgentCore, AWS' most important launch of 2025, launched at AWS Summit New York.
Frontier agents are about the future of work than a category.
Garman during his keynote introduced the term with a trio of software development tools. This concept of a frontier agent revolves around having an AI teammate. My hunch is that the term will likely be renamed.
Garman outlined that frontier agents are a new class of agents that are autonomous, scalable and work over time without human intervention. In other words, they're more like teammates.
The frontier agent riff is a concept that's far from fully baked, but you can see AWS focusing on expansion beyond the software development lifecycle. "We think we're only at the beginning of frontier agents," said Garman.
A few observations about where frontier agents may lead:
The concept moves AI agents beyond tools and into collaborators.
AI will ultimately just have to work. The current AI user interface, which will break down software and data silos, isn't human centric. You shouldn't need to learn how to work with an AI agent.
Change management and trust will be critical to move forward with this teammate concept.
Systems of work that have been around for decades will need to be revamped.
However, multiple enterprises and vendors are coalescing around the same vision.
"I believe that over the next few years, agentic teammates will be essential to every team as essential as the people sitting right next to you, they will fundamentally transform how companies build and deliver for their customers," said Colleen Aubrey, SVP of Applied AI Solutions at AWS, during a keynote.
Blue Origin's William Brennan, Vice President of Technology Transformation, highlighted how the space company has deployed more than 2,700 agents into production to assist engineering, manufacturing, software and supply chain teams.
"Everyone at Blue Origin is expected to build and collaborate with AI agents to make their work better and faster," said Brennan, who said the company built its multi-agent orchestration system on AWS. "By equipping our teams with knowledgeable and capable agents, we were able to dramatically accelerate the product life cycle, increase production rate, and, most importantly, reduce the cost of access to space."
It's not surprising that Blue Origin, owned by Jeff Bezos, is an AWS customer, but the use cases were notable.
AI is still far too complicated.
AWS is doing what it does--launch building blocks, combine them into services and solve problems. Yes, AWS made strides in abstracting the creations of AI agents and customizing models, but it's still very early.
There. Isn't. An. AI. Easy. Button.
Garman said AWS is focusing on offering building blocks as well as applications like AgentCore. Large enterprises want building blocks to build agents. Smaller firms will look for a complete package. "AWS has always been giving small customers the capabilities that only the largest companies used to have," said Garman.
Dr. Swami Sivasubramanian, Vice President of Agentic AI, said the aim is to reduce cost and complexity so you don't need an army of PhDs to implement AI. Ironically, many of the speakers this week at re:Invent 2025 had PhDs.
AWS has a software strategy and it's likely to revolve around use cases.
Yes, AWS had its Amazon Bedrock and AgentCore announcements, but the software to watch is Amazon Connect, which has more than $1 billion in annual recurring revenue and is likely to be the starter kit for what Aubrey highlighted about the future of work.
Amazon Connect got some play at re:Invent and largely flies under the radar. Amazon Connect added agentic AI features and the package of applications and building blocks isn't about contact centers as much as it is customer service use cases.
In addition, AWS is tackling other use cases including software development and now model customization. Is AWS a SaaS player. Not really, says Garman: "We don't have a concerted plan around SaaS, and we wouldn't go into it just because we want to go into it. And I think it's more there's an area where we think we have a differentiated idea that we can offer some interesting value to customers. We would always consider it. But it's more around that for us, we love leaning into our partners."
Margin is AWS' opportunity.
Amazon has said for years that fat margins are its opportunity. That approach comes from Amazon's retail DNA where margins in the best of times are single digits. AWS grew up taking margin away from enterprise incumbents. It still is if you just look at AWS Transform. I thought about this margin mantra repeatedly as AWS talked about its Trainium 3 and Trainium 4 launches. Like Google Cloud and its TPUs, AWS can rake in dough by just acquiring some of those workloads that support Nvidia's fat margins. For now, there are AI bottlenecks everywhere, but Trainium 3 is going to see strong demand and likely crib AI inference workloads.
"The response to Trainium 3 has been much stronger than Trainium 2," said Garman.
AI is forcing multi-cloud approaches and hyperscale cloud cooperation.
AWS and Google Cloud announced an interconnect deal and Microsoft Azure will be in the mix too. If it weren't for Oracle's partnership with all three hyperscalers, there's be some surprise. AI is forcing the clouds to collaborate. If you're keeping score at home hell has frozen over a few times already.
AWS Marketplace is a juggernaut.
Given Amazon's commerce roots this takeaway shouldn't be that surprising. However, AWS is removing friction from buying enterprise software at a steady pace. The ability to buy "solutions" is going to be a win for AWS and buyers. When AWS Marketplace is combined with the partner network, it's clear that AWS has its ground game going well.
The $1 billion AWS Marketplace club is also growing. Snowflake said this week that its AWS Marketplace sales have doubled to $2 billion.
Analyst takeaways from re:Invent 2025
R "Ray" Wang:
"AWS has figured out the AI game that they're going to play. It's about builders. It's how builders interface with marketplaces, how builders interface with ISVs, and how builders interface with corporate teams. Everything AWS is doing right now is focused on helping people get there. They were behind on that story, and we're starting to see something different. AWS realizes it has to give everybody the tools they need."
"AWS is moving up the stack and that's the important thing. Amazon is almost an apps company, but we can't say that because it's AI. AWS is going to crank out as many agents as it can. Customers are going to take them and get stuff one. The AI agents AWS uses internally will be the stuff you get to use internally too."
"I think the partners are really excited, and that's the most important piece. They've been selling so much for Amazon. I mean, it's night and day from three years ago."
"This is the first Amazon re:Invent where there wasn't a lot of talk about the future. Something was missing. What about Leo? What about quantum? People think quantum is far away. I think quantum is the one thing that will pull Amazon in a direction it may not expect."
Holger Mueller:
“AWS re:Invent was different in that AWS is moving up the stack and infrastructure as a service was underplayed. “
"The big miss from AWS side, they didn't talk enough about the data side of things. How do you start with lots of framework talk without the data talk."
"I talked to a lot of customers who believed in Athena and were wondering where it was in the keynote. You have to at least show consistency in that you're building stuff."
"Amazon was teeing up something. It was saying we understand the problem here, our abstractions and the outcomes needed."
Mike Ni:
"AI and data clearly go together, and it goes with the brand promise of, you know, best components better together."
“AgentCore delivering on policy and evaluations was important since those pieces are needed to deliver agentic AI.”
"With Nova Forge, you're talking about leveraging your first party data. It's fundamental now to actually go beyond the generic with increased accuracy."
Chirag Mehta:
"Kiro got disproportionate focus in terms of the keynote and attention."
"Partner-ed solution sales exceeded direct sales so we're seeing a new wave of builders where companies are building solutions on top of existing products. Partners are driving adoption."
"Frontier agents are the most murky of terms, but the general idea is that AWS is putting a stake in the ground and saying we're going to build the best DevOps agent anyone can ever have."
Liz Miller:
"This was the first AWS re:Invent, where things like Amazon Connect and applied AI solutions took center stage and a deserved spot in the keynote. You're seeing customers take the building blocks and putting them into action and seeing business results."
"With the Nova suite, AWS has intentionally created very durable, usable and price performant foundation models that can be used to build frontier agents. Nova Sonic is one of the best when it comes to delivering speech to speech."
“I'm going to be watching those customers in 2026. There's a collision between what you're buying between Amazon and what you're buying through AWS. Amazon is a commercially ready package like Amazon Ads and Amazon Connect. AWS is the Lego blocks. When does the Amazon customer look at what they're doing with Amazon and AWS holistically?"
Principal Analyst and Founder
Constellation Research
R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled, Everybody Wants to Rule The World was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg.
Short Bio
R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation Research Inc. He…...
Director of Marketing, Communications & Operations
Constellation Research
Elle is the Director of Marketing at Constellation Research and producer of the weekly enterprise tech show, DisrupTV. She leads marketing and communications efforts across all avenues while also managing an array of programs including the SuperNova Awards, Business Transformation 150, AX100, AI150, S50 and ShortLists. She has previous experience in public relations and has a strong passion for the marketing world.
Contact Elle at [email protected]
...
Mission Grade Intelligence, AI Factories, and the Rise of Introvert Branding: Highlights from DisrupTV Episode 420
This week on DisrupTV, hosts Vala Ashar and R "Ray" Wang sat down with three leaders shaping the future of AI, risk intelligence, and human-centered leadership: Benji Hutchinson, CEO of Babel Street; Mukund Gopalan, Global Chief Data Officer at Ingram Micro and AI150 executive; and Goldie Chan—once dubbed the “Oprah of LinkedIn”—and author of Personal Branding for Introverts.
The episode explored everything from national security–grade AI to enterprise-scale AI factories to the strengths introverts bring to leadership and brand-building. Episode 420 brought together leaders pushing the boundaries of national security, commercial compliance, enterprise AI, and human-centered brand building.
Mission Grade Risk Intelligence: Bringing National Security Rigor to the Enterprise
Benji Hutchinson opened the conversation by unpacking the concept of mission grade risk intelligence—a discipline born in national security that is increasingly essential to commercial operations.
Hutchinson explained that federal agencies and large enterprises now face many of the same threats: cyber intrusions, fraud, identity risk, and global instability. Yet less than 30% of Fortune 2000 organizations truly understand mission grade intelligence or the dual-use technologies that power it. Too many rely on outdated, simplistic tools when modern AI systems can match names across languages, analyze massive datasets, and detect risks in real time.
As AI evolves from statistical models to agentic systems, Hutchinson sees a future where intelligent agents automate routine workflows and deliver fast, high-fidelity intelligence—dramatically increasing organizational resilience.
Ingram Micro’s AI Factory: Industrializing Intelligence at Scale
Next, Mukund Gopalan, Global CDO at Ingram Micro, detailed how the company is building an AI factory—a scalable framework for deploying AI across every part of the enterprise.
Rather than treating AI as a collection of disconnected experiments, the AI factory approach emphasizes:
Data quality and trustworthiness
Human engagement and change management
Transformation of business processes—not just tech adoption
Gopalan described how Ingram Micro is using AI agents to automate back-office tasks, simplify operations, improve customer experiences, and identify sales opportunities earlier and more accurately. Their partnership with Google accelerates this journey, but the real magic, he stressed, comes from keeping humans in the loop: employees must understand the system’s capabilities, limits, and decision-making logic.
Personal Branding for Introverts: Turning Quiet Strengths into Leadership Power
The conversation shifted gears with Goldie Chan, branding strategist and author of Personal Branding for Introverts. Goldie challenged the stereotype that introverts are shy or passive, noting that many are “loud introverts”—individuals who can thrive publicly but need solitude to recharge.
Drawing from her personal journey, including a life-changing cancer diagnosis, Goldie highlighted the importance of living a “recommendable life.” She also shared her signature 5Cs of personal branding:
Clarity
Community
Content
Consistency
Connection
Introverts, she emphasized, have distinct superpowers: deep thinking, analytical skills, empathetic listening, and strong one-on-one communication. With intentionality and thoughtful boundaries, they can build powerful and authentic personal brands.
Key Takeaways from Episode 420
1. Mission-grade intelligence is no longer optional.
National security-level risk analysis is now relevant across industries as threats grow more sophisticated.
2. AI factories are the future of enterprise transformation.
Organizations need systematic, repeatable AI workflows—not isolated pilots—to realize meaningful ROI.
3. Humans remain essential in AI-driven systems.
Change management, training, and transparency are as important as the algorithms.
4. Introverts have strategic advantages in leadership.
Their strengths—listening, deep thinking, and relationship-building—translate directly into trust and influence.
5. Personal brands thrive when rooted in authenticity.
Goldie Chan’s 5Cs offer a roadmap for building a sustainable, human-centered brand.
Final Thoughts
Episode 420 showcased a powerful blend of technology and humanity. From national security intelligence to enterprise AI factories to introvert-centered leadership, this week’s guests highlighted what’s required to navigate the next era of innovation: smarter systems, stronger communities, and more intentional storytelling.
As DisrupTV continues to feature top leaders, authors, and innovators, one theme remains clear—AI may accelerate the future, but it’s people who shape it.
Related Episodes
If you found Episode 420 valuable, here are a few others that align in theme or extend similar conversations:
Vice President and Principal Analyst
Constellation Research
Chirag Mehta is Vice President and Principal Analyst focusing on cybersecurity, next-gen application development, and product-led growth.
With over 25 years of experience, he has built, shipped, marketed, and sold successful enterprise SaaS products and solutions across startups, mid-size, and large companies. As a product leader overseeing engineering, product management, and design, he has consistently driven revenue growth and product innovation. He also held key leadership roles in product marketing, corporate strategy, ecosystem partnerships, and business development, leveraging his expertise to make a significant impact on various aspects of product success.
His holistic research approach on cybersecurity is grounded in the reality that as sophisticated AI-led attacks become…...
Vice President and Principal Analyst
Constellation Research
Holger Mueller is VP and Principal Analyst for Constellation Research for the fundamental enablers of the cloud, IaaS, PaaS and next generation Applications, with forays up the tech stack into BigData and Analytics, HR Tech, and sometimes SaaS. Holger provides strategy and counsel to key clients, including Chief Information Officers, Chief Technology Officers, Chief Product Officers, Chief HR Officers, investment analysts, venture capitalists, sell-side firms, and technology buyers.
Coverage Areas:
Future of Work
Tech Optimization & Innovation
Background:
Before joining Constellation Research, Mueller was VP of Products for NorthgateArinso, a KKR company. There, he led the transformation of products to the cloud and laid the foundation for new Business Process as a…...
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. ...
Vice President and Principal Analyst
Constellation Research
Michael Ni is Vice President and Principal Analyst at Constellation Research, covering the evolving Data-to-Decisions landscape—where CDOs, CIOs, and CPOs must modernize data infrastructure, integrate AI into decision-making, and scale automation to improve business outcomes.
Ni’s research examines how enterprises operationalize AI, automate decision-making, and integrate data management and analytics into core business processes. He focuses on the challenges of scaling AI-driven decision systems, aligning data strategy with business goals, and the growing role of data and decisioning “products” in enterprise ecosystems.
With 25+ years as a product and GTM executive across enterprise software, AI platforms, and analytics-driven technologies, Ni brings a practitioner’s perspective to…...
Principal Analyst and Founder
Constellation Research
R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled, Everybody Wants to Rule The World was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg.
Short Bio
R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation Research Inc. He…...
Vice President & Principal Analyst
Constellation Research
About Liz Miller:
Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform everything from…...
Hannah Mason is a marketing director at Constellation Research. She oversees brand positioning, creative direction, and content development across digital platforms, events, and campaigns. Her work spans branding and design—including graphics, sales collateral, and event presentations—along with website content management, newsletters, and Constellation Insights.
Mason also manages surveys and produces Constellation’s video collateral, including ConstellationTV. Her role ensures that the Constellation brand is communicated with clarity, creativity, and consistency across all channels.
Contact Hannah at [email protected].
...
AWS re:Invent in Las Vegas marked a pivotal shift in the cloud giant's trajectory. Moving beyond its traditional focus on core compute primitives, Amazon Web Services is aggressively "moving up the stack" to dominate applied AI, data strategy, and agentic frameworks.
Hosted by Liz Miller, the Constellation Research analyst team, Holger Mueller, Mike Ni, Larry Dignan, R "Ray" Wang, and Chirag Mehta distilled the various themes to what is most important for an executive audience to know.
Here is the strategic analysis of AWS’s new direction.
The Big Pivot: Moving Up the Stack to Applied AI
For years, AWS was defined by infrastructure. That era is evolving. Holger Mueller noted a distinct change in tone, observing that AWS is "moving up the stack, less infrastructure as a service". The keynotes moved away from compute fundamentals to focus on higher-level solutions.
This shift is driven by a demand for results. Liz Miller emphasized that "AI-powered solutions and applied AI solutions took center stage," moving the conversation from theoretical technology to demonstrable business outcomes. The narrative has shifted from providing raw tools to showcasing results from frameworks like Nova Forge.
The "Untold Hero": Data Context Over Model Quality
While models grab headlines, analysts argued that data remains the true differentiator. Mike Ni identified data as the "untold story," arguing that the bottleneck to AI success is no longer the model itself but the context it provides.
"It’s actually the context," Ni stated. "And this is where you heard the underlying story of data".
To succeed in 2026, organizations must leverage first-party data. Ni highlighted AWS's introduction of AgentCore and Vector Search technology as critical moves to help enterprises enrich models with relevant, proprietary context.
Cloud Economics: Weaponizing Margins
AWS is returning to its retail roots to squeeze competitors. Larry Dignan observed that AWS is aggressively targeting rivals' margins through vertical integration and custom silicon.
"Everybody’s margin is AWS’s gain," Dignan explained. "Whether you look at Trainium, Nova, they’re just going to…collapse all the rivals’ margin and basically run with it".
For executives, this signals a future of more efficient, price-competitive solutions as AWS leverages its scale to win on cost-effectiveness.
The Rise of "Frontier Agents" and the New Builder
The definition of a "builder" is expanding. R "Ray" Wang noted that AWS has clarified its AI strategy: it is about empowering builders to interface with marketplaces, ISVs, and corporate teams.
However, the terminology is shifting. Chirag Mehta pointed out a bold pivot from "applications" to "frontier agents"—first-party AI frameworks designed for enterprise tasks. "We cannot call them applications, but we can call them frontier agents," Mehta noted.
This aligns with a broader ecosystem shift where partner-led solution sales have exceeded direct sales for the first time, signaling a new wave of builders leveraging collaborative ecosystems.
The Misses: Leaving Legacy Behind?
The aggressive focus on AI did leave some gaps. Holger Mueller criticized the lack of attention to data and legacy tools, specifically noting the omission of Athena and virtual desktop updates.
"No mention of Athena in the keynote… Misvalue. At least you have to show consistency with your building stuff," Mueller remarked. This suggests AWS may be prioritizing its AI mission at the expense of visible support for its legacy service portfolio.
Strategic Outlook: What to Watch for in 2026
As AWS pushes into 2026, the panel offered specific predictions on where the cloud giant goes next:
The Agent War: Holger Mueller predicts a "battle of the agentic frameworks," defined by who can build faster, cheaper agentic applications.
Incremental Innovation: Larry Dignan foresees a move toward sustained execution rather than "big bang" announcements, settling into a "steady case" of ongoing innovation.
Partner-Driven AI: Chirag Mehta advocates that partners will be the primary engine driving AI adoption through the marketplace.
Quantum Disruption: R "Ray" Wang predicts that Quantum computing will eventually "pull Amazon in a direction they may not have expected".
Holistic Adoption: Ultimately, success will be measured by customer behavior. Liz Miller will be watching for when customers stop viewing AWS as a "Lego set" and start seeing it as a holistic solution provider.
AWS is undergoing a profound transformation. By betting big on agents, partners, and silicon economics, they are aiming to turn "Lego blocks" into integrated business results.
Vice President and Principal Analyst
Constellation Research
Holger Mueller is VP and Principal Analyst for Constellation Research for the fundamental enablers of the cloud, IaaS, PaaS and next generation Applications, with forays up the tech stack into BigData and Analytics, HR Tech, and sometimes SaaS. Holger provides strategy and counsel to key clients, including Chief Information Officers, Chief Technology Officers, Chief Product Officers, Chief HR Officers, investment analysts, venture capitalists, sell-side firms, and technology buyers.
Coverage Areas:
Future of Work
Tech Optimization & Innovation
Background:
Before joining Constellation Research, Mueller was VP of Products for NorthgateArinso, a KKR company. There, he led the transformation of products to the cloud and laid the foundation for new Business Process as a…...
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. ...
Vice President & Principal Analyst
Constellation Research
About Liz Miller:
Liz Miller is Vice President and Principal Analyst at Constellation, focused on the org-wide team sport known as customer experience. While covering CX as an enterprise strategy, Miller spends time zeroing in on the functional demands of Marketing and Service and the evolving role of the Chief Marketing Officer, the rise of the Chief Experience Officer, the evolution of customer engagement, and the rising requirement for a new security posture that accounts for the threat to brand trust in this age of AI. With over 30 years of marketing experience, Miller offers strategic guidance on the leadership, business transformation, and technology requirements to deliver on today’s CX strategies. She has worked with global marketing organizations to transform everything from…...
Vice President and Principal Analyst
Constellation Research
Michael Ni is Vice President and Principal Analyst at Constellation Research, covering the evolving Data-to-Decisions landscape—where CDOs, CIOs, and CPOs must modernize data infrastructure, integrate AI into decision-making, and scale automation to improve business outcomes.
Ni’s research examines how enterprises operationalize AI, automate decision-making, and integrate data management and analytics into core business processes. He focuses on the challenges of scaling AI-driven decision systems, aligning data strategy with business goals, and the growing role of data and decisioning “products” in enterprise ecosystems.
With 25+ years as a product and GTM executive across enterprise software, AI platforms, and analytics-driven technologies, Ni brings a practitioner’s perspective to…...
Principal Analyst and Founder
Constellation Research
R “Ray” Wang is the CEO of Silicon Valley-based Constellation Research Inc. He co-hosts DisrupTV, a weekly enterprise tech and leadership webcast that averages 50,000 views per episode and blogs at www.raywang.org. His ground-breaking best-selling book on digital transformation, Disrupting Digital Business, was published by Harvard Business Review Press in 2015. Ray's new book about Digital Giants and the future of business, titled, Everybody Wants to Rule The World was released in July 2021. Wang is well-quoted and frequently interviewed by media outlets such as the Wall Street Journal, Fox Business, CNBC, Yahoo Finance, Cheddar, and Bloomberg.
Short Bio
R “Ray” Wang (pronounced WAHNG) is the Founder, Chairman, and Principal Analyst of Silicon Valley-based Constellation Research Inc. He…...
Hannah Mason is a marketing director at Constellation Research. She oversees brand positioning, creative direction, and content development across digital platforms, events, and campaigns. Her work spans branding and design—including graphics, sales collateral, and event presentations—along with website content management, newsletters, and Constellation Insights.
Mason also manages surveys and produces Constellation’s video collateral, including ConstellationTV. Her role ensures that the Constellation brand is communicated with clarity, creativity, and consistency across all channels.
Contact Hannah at [email protected].
...
LIVE from Amazon Web Services (AWS) re:Invent, Constellation analysts give their unique POVs on the conference and report a clear shift: #AWS is moving from infrastructure to applied AI and agents...
Key takeaways from this ConstellationTV episode:
💡 AI = models + data. Nova, Nova Forge, and Nova Sonic are solid, but the real differentiator is how AWS helps customers govern and activate their first-party #data.
💡 From IaaS to “frontier #agents.” AWS is positioning itself as an “almost apps” company with frontier agents built on its own foundation models.
💡 Amazon Connect as a proof point. Now a $1B+ ARR business, Connect shows how applied AI can handle complex service and support at both #enterprise and SMB scale.
💡 Partners and marketplace on top. For the first time, partner-led solutions exceeded direct sales, signaling that an ecosystem of builders and ISVs will drive AI adoption.
AI is still early and “complicated as hell,” but the move to intelligent, outcome-focused solutions is unmistakable.
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. ...
AWS launched new Graviton5 based instances with 192 core per chip and a 5x larger cache as the company continues its custom processor cadence.
Graviton continues to power more than half of the new CPU capacity for AWS for the third year in a row. AWS said that 98% of its top 1,000 EC2 customers have used Graviton.
Although Trainium is getting most of the attention at AWS re:Invent 2025, Graviton is part of the mix as well as Inferentia. AWS cited Adobe, Pinterest, SAP, Snowflake and a bevy of others as Graviton customers.
"The Graviton processor came from a brand new design based on delivering the best price performance for workloads that customers run every day in the cloud," said Dave Brown, VP of Compute and Machine Learning Services at AWS.
In a keynote, Brown and AWS SVP Peter DeSantis noted the following about AWS' custom silicon strategy.
AI is expensive to run.
AWS is investing heavily in lowering the costs of running workloads.
With custom processors, AWS can leverage its Nitro virtualization layer and reduce jitter.
Cloud workloads need to continually optimized for price-performance benefits.
By controlling the entire stack from processor to server, AWS could implement innovations like direct-to-silicon cooling, which reduced fan power consumption by 33%.
Custom processors allow AWS to iterate and optimize performance with greater control over the hardware and innovation cadence.
Another way to put it is that everybody's margin is an opportunity for AWS. Whether you look at Trainium, Nova models or Graviton, AWS is looking to commoditize.
Key items about Graviton:
Graviton5-based EC2 M9g instances have 192 cores in a single package.
Latency is improved by up to 33%.
Graviton5 has a 5x larger L3 cache, 2.6x more than Graviton4.
The processor has up to 15% higher network bandwidth and 20% higher Amazon Elastic Block Store (EBS) bandwidth across instance sizes.
Graviton5 is built on AWS's 3nm technology.
Graviton5 instances leverage sixth-generation Nitro Cards to offload virtualization, storage and networking functions to dedicated hardware.
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. ...
Hewlett-Packard reported solid fourth quarter results, but server sales fell 5%. Server sales were lower in the fourth quarter due to timing of AI server shipments and lower US government spending.
HPE reported fourth quarter earnings of 11 cents a share on revenue of $9.7 billion, up 14% from a year ago. Non-GAAP earnings were 62 cents a share. HPE recently outlined its long-term outlook and strategy on its investor day.
Wall Street was expecting HPE to report non-GAAP fourth quarter earnings of 58 cents a share on revenue of $9.91 billion.
However, HPE's results were mixed by product line. For instance server revenue was down 5% to $4.5 billion. Networking revenue, boosted by the acquisition of Juniper Networks, was $2.8 billion, up 150% from a year ago. Hybrid cloud revenue was $1.2 billion, down 12% from a year ago.
"HPE had a good quarter, but the growth came all from networking. Surprisingly, HPE server revenue was down, and blaming the customer mix change for it is a surprising move," said Constellation Research analyst Holger Mueller. "More interesting is also that half of HPE profit came from networking, but which underlined how important the Juniper acquiaition has been HPE. Now it's all about Antonio Neri and team getting growth back into the server segment."
For the fiscal year, HPE reported a net loss of $59 million, or 4 cents a share, on revenue of $34.3 billion.
CEO Antonio Neri said HPE "finished a transformative year with a strong fourth quarter of profitable growth and disciplined execution."
As for the outlook, HPE projected first quarter revenue of $9 billion to $9.4 billion with non-GAAP per share earnings of 57 cents to 62 cents.
For fiscal 2026, HPE said revenue will grow 17% to 22% with non-GAAP per share earnings between $2.25 to $2.45.
"The underlying demand environment was strong throughout the quarter with orders growing faster than revenues. We saw an acceleration in orders in the last weeks of the quarter, signaling solid demand for our portfolio."
"As we look to 2026, we will draw on our supply chain expertise to secure critical commodity supply and exercise our pricing management discipline. We expect DRAM and NAND costs to continue to increase in 2026, the majority of which we expect to pass to the market while monitoring demand."
"We have discipline in passing through the cost through our pricing which again we already did in November."
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. ...
Salesforce reported better-than-expected third quarter results, said it has reached 9,500 paid deals for Agentforce and upped its outlook for the fiscal year.
The company reported third quarter net income of $2.086 billion, or $2.19 a share, on revenue of $10.26 billion, up 9% from a year ago. Non-GAAP earnings were $3.25 a share.
Wall Street was looking for non-GAAP earnings of $2.86 a share on revenue of $10.27 billion.
The company, which just closed its Informatica purchase, said its current remaining performance obligations in the third quarter were $29.4 billion, up 11% from a year ago.
CEO Marc Benioff said, "Our Agentforce and Data 360 products are the momentum drivers, hitting nearly $1.4 billion in ARR." He added that Salesforce processed 3.2 trillion tokens.
Key figures:
Agentforce accounts in production were up 70% from a year ago.
50% of Agentforce and Data 360 bookings in the third quarter came from existing customers.
Data 360 ingested 32 trillion records in the third quarter.
As for the outlook, Salesforce projected revenue of $11.13 billion to $11.23 billion, up 11% to 12%, with non-GAAP earnings of $3.02 to $3.04 a share.
Salesforce said fiscal 2026 revenue will be $41.45 billion to $41.55 billion with non-GAAP earnings of $11.75 a share to $11.77 a share.
Key themes from the Salesforce call:
Benioff said:
"We're really excited about the harmonization, integration, federation that Informatica plus Data 360 plus MuleSoft is giving us. And that's going to strengthen our overall leadership in data and, of course, AI. And we're ensuring that we have the distribution capacity. That's extremely important for us because we are a direct seller in place to support long-term growth."
"Six of our top 10 deals in the quarter are now driven by companies that just want to transform with Agentforce."
"We use all of the large language models. They're all great. We love all of them. We love all of our children, but they're also all just commodities, and we can have the choice of choosing whatever one we want, whether it's OpenAI or Gemini or Anthropic or there's other open source ones. They're all very good at this point. So we can swap them in and out. The lowest cost one is the best one for us, making us basically the top user of these foundation models."
"I just want to make sure everybody realizes we're not building data centers at Salesforce. We're preserving our gross margins and our cash flow. But we will use the data centers that are being built. And we will take advantage of the lower cost that we're seeing in the market from the incredible build-out of data centers."
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. ...
Snowflake expanded its partnership with Anthropic to cover joint sales efforts and model integration with Snowflake Intelligence, detailed AWS Marketplace growth and teamed up with Accenture on enterprise AI deployments. The company also reported strong third quarter results.
The news lands after Snowflake's acquisition of Select Star. The purchase expands Snowflake Horizon Catalog view into enterprise data. Select Star integrates with multiple database systems and business intelligence tools as well as data pipelines.
Here's a look at the partnerships, which was announced shortly after Snowflake earnings.
Anthropic and Snowflake will collaborate on joint sales efforts and go-to-market motions.
Since the two companies announced their initial partnership, thousands of customers have signed up for Claude models on Snowflake.
Anthropic Claude will be a key model powering Snowflake Intelligence, the company's data intelligence agent.
Sridhar Ramaswamy, CEO of Snowflake, said the partnership with Anthropic was expanded because the two companies are seeing usage surge as a team.
Anthropic CEO Dario Amodei said "this partnership expansion is a direct result of the momentum and demand we’ve already seen from customers who are driving real business value with Anthropic and Snowflake."
Here's a look at Snowflake's deals with AWS and Accenture.
Accenture and Snowflake launched the Accenture Snowflake Business Group to offer AI and data transformation services. The two companies cited Caterpillar as a customer. Accenture and Snowflake will meld Accenture's AI Refinery with Snowflake Intelligence and Snowflake Cortex AI.
Snowflake said it has been leveraging AWS marketplace to drive sales and adoption. The company said AWS Marketplace sales have doubled to $2 billion. Snowflake said it has recognized by AWS across 14 Partner Award categories. The two companies are collaborating on multiple integrations.
Better-than-expected third quarter results
Snowflake reported a third quarter net loss of $291.6 million, or 87 cents a share. Non-GAAP earnings were 35 cents a share on revenue of $1.21 billion, up 29% from a year ago.
Wall Street was looking for non-GAAP earnings of 31 cents a share on revenue of $1.18 billion.
Snowflake said it had 688 customers with trailing 12-month product revenue greater than $1 million. Remaining performance obligations were $7.88 billion, up 37% from a year ago.
As for the outlook, Snowflake projected product revenue of $1.195 billion to $1.2 billion, up 27% from a year ago. Ramaswamy said Snowflake Intelligence, the company's enterprise AI agent, saw "the fastest adoption ramp in Snowflake history."
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. ...
Amazon Connect is the lead for AWS when it comes to taking a bunch of building blocks and "primitives" and compiling them for enterprise use cases. Amazon Connect isn't about being a contact center application as much as it is addressing customer-facing use cases starting with service.
The Amazon Connect playbook is being used for multiple product areas such as Amazon Bedrock, AgentCore and AWS Security Hub to name a few. Amazon Connect has surpassed $1 billion in annual recurring revenue.
During a re:Invent 2025 keynote Wednesday, Colleen Aubrey, SVP, Applied AI Solutions at AWS, said Amazon Connect a precursor to an AI-powered future of work that revolves around more than automation and efficiently. "What I've learned building on Amazon is that transformation and agility are not opposites. They're actually partners," said Aubrey. "The real prize of AI is new products, new services, better customer experiences and new business models, not less effort."
AI agents require a rethinking of work. Aubrey said one of the places where AI has become a teammate is Amazon Connect, which is used internally for customer service, as well as multiple enterprises. "What we see across many customers is that the center of gravity for customer experience is the same. It's starting in the contact center. But let's be clear, the contact center have expanded beyond just the interactions," said Aubrey.
At re:Invent 2025, Amazon Connect rolled out agentic self-service tools that give AI agents the ability to understand, reason and act across voice and messaging channels. AI agents can automate routine and complex tasks and supervisors can spin them up with tracking and identity-based security.
Amazon Connect is also the biggest beneficiary of Nova Sonic, AWS's advanced speech model. Amazon Connect leverages Sonic but also a set of models via Amazon Bedrock and Bedrock AgentCore underneath.
In addition, Amazon Connect is getting tools to analyze conversations for context and sentiment and prepare documentation and handling routine processes. Amazon Connect also has AI-powered product recommendations to turn conversations into potentially revenue-driving engagements.
