Hi-Fi process management needs to be foundation for AI

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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To close the loop between insights and actions enterprises will need to double down on process intelligence and efficiency, or what Constellation Research analyst Holger Mueller calls high-fidelity (hi-fi) process management.

In a report, Mueller said hi-fi process management--a higher quality process-centric approach to driving insights--can be enabled by object-centric process mining (OCPM).

The topic is timely since enterprises and vendors are rushing toward AI agents that will be able to be autonomous, make decisions and carry out tasks. The problem, as I've noted before, is that agentic AI without process intelligence is simply going to scale bad processes. The worst case: Agentic AI is just going to be a lift of shift of inefficiency.

Mueller's report couples two big ideas: Enterprise Acceleration and Infinite Computing. For enterprises to move faster and be more agile, insights will be the enabler of action. The issue is reports, spreadsheets, data warehouses and platforms, big data, visualizations and distribution of insights haven't lived up to expectations.

According to Mueller:

"Unlike generic insight-to-action approaches based on traditional business intelligence (BI), process mining delivers actionability by design—because it starts with a deep, system-level understanding of how processes actually run. By mapping real execution data, process mining not only uncovers inefficiencies but also provides the contextual insights needed to drive precise, high-impact optimizations. This makes it inherently more suited to enabling sustainable, enterprise-scale transformation."

Mueller walks through the advances and OCPM vs. traditional process mining and argues that process needs to be included in data and AI strategies. In fact, process is the glue between the two and the "foundation of the underlying AI."

Mueller added:

"Every 5-10 years the underlying techological capabilties for whole enterprise software categories enable new best practices. In most cases vendors just do a 'lift and shift'. In the case of process mining - the technical capabitlies are powered by Infinite Computing - changing both the operator paradigm from human to software and the ability to model an enterprise with an infinite method - object centric process modelling."

Related research:

• There Is Only ‘One’ (1) IT Strategy in 2025 and Beyond
• Why the C-Suite Must Embrace Enterprise Acceleration
• The Era of Infinite Computing Triggers Next-Generation Applications

Meta Superintelligence Labs: A look of the challenges ahead

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

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

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Meta CEO Mark Zuckerberg has hired away AI experts from OpenAI, Google and Anthropic to create Meta Superintelligence Labs, a supergroup that will allegedly give Meta the ability to develop frontier models that "deliver on the promise of personal superintelligence for everyone."

In a memo published by CNBC and first reported by Bloomberg, Zuckerberg said Meta will put all of its AI groups under Meta Superintelligence Labs (MSL). Meta is committed to Llama 4.1 and Llama 4.2 and will pursue next-gen models with the new group, which will be led by Alexandr Wang, who was the ScaleAI CEO. Nat Friedman will partner with Wang to lead the new group. Friedman, who led GitHub at Microsoft, will lead work on AI products on applied research for MSL.

• The problem with Meta chasing superintelligence
• Meta ups its 2025 spending on AI, data centers
• Meta launches Llama API, Meta AI app
• Meta launches Llama 4 suite, ups ante in LLM wars

Zuckerberg named another 11 AI leads from Google DeepMind, OpenAI and Anthropic. Wall Street is cheering the hiring spree, but super teams don't always deliver. Here's a look at the challenges MSL will face:

Time. Meta is clearly playing catch up or it wouldn't be hiring so heavily and paying out what is likely vast sums to poach AI experts. Zuckerberg said MSL will begin work on next-gen models in the next year. If you assume, work started today it's an open question of whether Meta can realistically close the gap with rivals that aren't exactly standing still.

Management. Many people--including investors--saw Zuckerberg's hiring spree as a positive development. I saw a lot of egos to manage and it may take time Meta doesn't have for MSL to gel as a team.

Llama, open source and developers. Meta didn't do the open source riff that usually appears when the company talks AI. It remains to be seen what the approach is with MSL, but Zuckerberg has spent a lot of money to be on the frontier. He'll want to keep the spoils.

Meta has money, but it's unclear if it's uniquely positioned. Zuckerberg said: "We have a strong business that supports building out significantly more compute than smaller labs. We have deeper experience building and growing products that reach billions of people," said Zuckerberg in his memo. Google, Microsoft, Amazon, OpenAI and much of the field can say the same.

ROI. Zuckerberg has spent billions of dollars on the metaverse and AI served as a nice distraction from the lack of ROI. Facebook and Instagram look tired relative to TikTok. It's possible that Meta's core businesses remain great, but the company faces the same ad disruption as the rest of the field.

What we learned from enterprise tech buyers in first half of 2025

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

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

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Enterprise technology buyers are half way through 2025 and still lack the visibility to make strategic investments with longer time horizons. That said, enterprises are chasing technologies--notably artificial intelligence--to transform, become nimble and optimize so there's a cost cushion due to productivity.

In addition, buyers are also navigating a lot of hype (mostly agentic AI) and trying to comb through technology advances that change almost weekly.

Accenture CEO Julie Sweet recently summed up what enterprise buyers are facing. "We continue to see a significantly elevated level of uncertainty in the global economic and geopolitical environment as compared to calendar year 2024," said Sweet. "In every boardroom and every industry, our clients are not facing a single challenge. They are facing everything at once, economic volatility, geopolitical complexity, major shifts in customer behavior."

Those comments have been echoed on earnings calls repeatedly across industries as companies reported first quarter earnings in April and beyond. AMD CFO Jean Hu said June 3 that "the macro uncertainties are a lot." "We cannot predict what's going to happen," said Hu. "We are trying to really be mindful of the macro environment and make sure we are conservative about the second half."

Coca Cola CFO John Murphy said something similar before noting that a strong balance sheet helps. CarMax, FedEx, Lennar and Truist all noted the uncertainty about the economy due to multiple factors. These comments were all made in the last two weeks.

Simply put, enterprise technology buyers are operating through 2025 in a world where long-term thinking is challenging when every other day there's a dramatic shift. It could be tariffs today, recession tomorrow and war next month. Take your pick or mix and match your set of challenges.

With that backdrop, let's look at the enterprise buyer lessons from the first half of 2025.

Agentic AI. Vendors are agent-washing, but buyers are wary. We heard this repeatedly from CxOs: AI agents are going to be a thing, but right now there's a lot (standards, security, multi-system orchestrate, data and process) preventing me from moving beyond proof of concept.

Now these blockers to agentic AI are being resolved quickly, but skepticism abounds. Agents within applications and silos (CRM, HR, ERP) can work, but the dream for agentic AI is to cut across multiple systems, processes and potentially ditch UI.

Our BT150 CxOs were definitely skeptical.

• BT150 zeitgeist: Agentic AI has to be more than an 'API wearing an agent t-shirt'
• BT150 CxO zeitgeist: AI agents promising, but in transition period
• BT150 zeitgeist: CxOs weigh in on SaaS consumption models for genAI, agentic AI
• BT150 zeitgeist: AI, efficiency, vendor angst and finding the right IT structure
• Boomi's product, technology chief on what's needed for AI agents to work together
• Enterprise AI: Here are the trends to know right now
• Here’s what technology buyers say about AI, technology, transformation

The rise of practical AI. Amid the AI hype, leaders are looking for practical returns and worrying about vendor control and sprawl. Governance of AI is also a key theme. Practical AI means that CxO aren't getting caught up in the bleeding edge technologies when older tools may drive better returns.

• BT150 Spotlight: Karen Higgins-Carter on practical AI approaches
• Infosys, Wipro say clients hitting pause on transformation projects
• AWS re:Inforce 2025: How customers are using AWS security building blocks
• Lessons from early AI agent efforts so far
• 5 projects we’re watching in May 2025
• BT150 zeitgeist: Agentic AI has to be more than an 'API wearing an agent t-shirt'
• AI strategies and projects: The hope, the fear and everything in between

AI driven transformation is about industries. While AI is typically considered to be a broad and horizontal technology, the real transformational use cases are in industries. Perhaps this isn't so surprising when you consider that financial services companies are basically all about technology.

For instance, JPMorgan Chase's organization is almost a master class in driving data and AI use cases. But there are plenty of giants (Bank of America, Goldman Sachs, Citigroup) leveraging AI and digital transformation.

• JPMorgan Chase's Dimon on AI, data, cybersecurity and managing tech shifts
• JPMorgan Chase’s IT, AI bets: Where the returns are
• PayPal eyes agentic commerce platform, but first has to retire tech debt
• Financial services firms: The only certainty is investing in AI transformation
• Bank of America's AI investments boost digital engagement, customer satisfaction
• As tech navigates volatility, here's what the big finance CEOs say about the economy

Retail and consumer good companies are all about the optimization. Across every industry, AI is picking up steam and driving results. A sampling of industry-focused AI use cases.

• A look at Walmart’s platform approach to data, AI, optimization
• Clorox to go live with new SAP ERP system, eyes margin improvement
• AI agents aimed at healthcare, but data interoperability still a big issue
• Delta Air Lines completes cloud migration with focus on AI and data-driven customer experience
• AI 150 Spotlight: LLMental CEO Matt Lewis on using AI to augment mental wellness

Exponential efficiency equates to resilience. The one big theme in the first half of 2025 was efficiency. Drive efficiency and productivity and bank the savings for a rainy day, which is probably coming 15 minutes after you read this. When you're in another-day-another-crisis mode, resilience is everything.

• Resilience is the key enterprise theme and it favors the large
• Research: Exponential Efficiency in the Age of AI

Supply chain optimization. The close cousin to efficiency is supply chain automation and optimization, which is being used by the giants (Walmart, Amazon, P&G to name a few) to move fast at scale.

• P&G outlines Supply Chain 3.0, next digital transformation moves
• Amazon revamps supply chain, last mile delivery, warehouses with AI models
• Hershey finishes SAP S/4HANA implementation: Is it sweet or suite?
• Walmart’s fiscal 2026 bets: Supply chain optimization, AI, automation

The supply chain has had to optimize and retool for the last 5 years due to pandemics, tariffs, and various disruptions. Enterprises are becoming very savvy in AI, robotics, automation and optimization in the supply chain.

Customer and employee experiences are being rewritten due to data and AI. At the Constellation Research Ambient Experience Summit 2025, there were a bevy of takeaways on how AI is changing the game in CX and EX. The Constellation Research AI Forum also featured a bevy of use cases.

• AccentCare's Heather Wilson: How customer and employee experience go together
• Hotwire's Laura MacDonald on AI's role in marketing personalization, analytics
• Constellation Research Ambient Experience Summit 2025: 10 CX takeaways on people, data, AI
• 9 Google Cloud customers on AI implementations, best practices
• Lloyds Banking Group bets on Google Cloud for AI-driven transformation
• Lowe's eyes AI agents as home improvement companion for customers
• Healthcare leaders eye agentic AI as next frontier for clinicians, patients
• Google Cloud, UWM partner as mortgage battle revolves around automation, data, AI
• AX100 Spotlight: RentSpree's Michael Storey on the intersection of CX, AI and success metrics
• Here’s what technology buyers say about AI, technology, transformation
• Starbucks aims for 4 minute barista to customer handoff process to boost CX

Given that much of the agentic AI action is being driven by Salesforce and ServiceNow duking it out for CRM, it's not surprising that CX is a key theme.

Industrial AI investments start to pick up

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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Industrial AI investment is picking up for infrastructure and component vendors indicating that use cases are in the pipeline for manufacturing, automotive and other asset-heavy industries. The quarters ahead will likely see investment move up the technology stack.

Although it's early, the breadcrumbs pointing to industrial AI demand are starting to pile up. Consider:

• Micron Technology, which reported better-than-expected third quarter results and outlook, said it is expanding its memory manufacturing to support aerospace, defense and industrial markets. Micron CEO Sanjay Mehrotra said: "In industrial, we are seeing a resumption in our growth as customers increase their investments for the adoption of AI, including in key areas like factory automation."
• Nvidia CEO Jensen Huang said on the company's most recent earnings call and at the company's Paris GTC event that investment in digital twins, industrial AI and robotics is ramping.
• Hitachi Digital Services highlighted the intersection of IT and operational technology as a key growth area. Manufacturing is looking to AI and automation at factories.
• Amazon and Walmart are increasingly highlighting the use of AI and automation in the supply chain and distribution centers.

These industrial AI use cases are likely to proliferate in the quarters ahead as physical AI models roll out, enterprises need to automate to cut costs amid economic volatility and manufacturing moves away from China to some degree.

FedEx: Data, optimization, scale help navigate supply chain uncertainty

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. ...

Read more

FedEx is planning to leverage data, scale and digital twins to optimize its network and services amid uncertainty about global trade and the economic picture.

Speaking on an earnings conference call FedEx CEO Rajesh Subramaniam said the company is optimizing its supply chain and network as conditions warrant ahead of manufacturing shifts.

During the fourth quarter, Subramaniam noted that the supply chain patterns "are changing as we speak." For instance, FedEx is seeing growth in Southeast Asia as companies look to Vietnam over China. Subramaniam said the company has launched direct flights into Vietnam and routed through Singapore. Latin America demand is strong.

• Supply chain transformation critical as resilience worries stack up
• P&G outlines Supply Chain 3.0, next digital transformation moves
• Amazon revamps supply chain, last mile delivery, warehouses with AI models
• Walmart’s fiscal 2026 bets: Supply chain optimization, AI, automation

FedEx already has a global network and locations in multiple markets. "We get to flex our scale of the network that we build out because we don't have to do much different because we are already there in these markets," said the FedEx CEO. "We had to be careful making sure that our capacity is right in markets, but we can move faster than how manufacturing can move."

This constant change is what Subramaniam calls the "referendum on global supply chains every single day." To manage through that change, Subramaniam said data is critical. "For every country and every commodity, we have the data," said Subramaniam. "Not only do we have the data, but we have engineered it and created a digital twin."

Brie Carere, FedEx Chief Customer Officer, said the Covid pandemic led to supply chain diversification that's paying off now. FedEx's sales team in China notifies their counterparts when a customer is diversifying to another region. That data from the ground influences optimization decisions.

Given the data and scale of FedEx's network, the company has been able to adapt. However, the uncertainty over tariffs and supply chain disruption continues. FedEx provided an outlook for the first quarter, but not the fiscal year.

"It's very difficult to predict what is going to happen over the next 30 to 60 days or even further. And it's a dynamic environment," said Subramaniam. "We just have to live with that. The scale of FedEx comes into play in these kind of situations, both on the physical side and the digital side as the complexity and the friction increases and the trade flow patterns change."

As a buffer to the uncertainty, FedEx's Subramaniam said the company has taken out $2.2 billion in costs due to its DRIVE and Network 2.0 initiatives. Network 2.0 refers to optimization of FedEx's hubs and stations. FedEx expects another $1 billion in transformation savings in fiscal 2026.

FedEx reported fourth quarter net income of $1.65 billion, or $6.88 a share, on revenue of $22.2 billion, flat compared to a year ago. For fiscal 2025, FedEx reported net income of $4.09 billion, or $16.81 a share, on revenue of $87.9 billion.

Clorox to go live with new SAP ERP system, eyes margin improvement

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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Clorox will go live on a new ERP system in July as it wraps up a multi-year transition to SAP S4/HANA Cloud.

Speaking at an investor conference June 4, Clorox CFO Luc Bellet said the ERP upgrade will enable the company to optimize its operations and grow profit margins. The company outlined its plans to upgrade SAP in 2021 and later delayed the transformation during a cyberattack in 2023. Overall, Clorox has said its final tab for the SAP upgrade will be about $560 million to $580 million based on projections given in February by executives.

During Clorox's second quarter earnings call, CEO Linda Rendle defended the SAP project and noted that it will deliver a strong long-term return. Clorox has been operating on a 25-year old ERP system. When analysts questioned why the ERP transition was so expensive, Rendle said it was the first upgrade in more than two decades and in the greenfield project Clorox also invested in a data lake as well as AI.

ERP was also a big topic for analysts on Clorox’s third quarter conference call in May.

Speaking June 4, Rendle said the SAP overhaul is more than just an upgrade and about process and digital transformation. The company is also overhauling its data infrastructure to be more efficient in the future. The project falls under Clorox's broader transformation effort called Ignite.

"Upgrading ERP systems is expensive and risky. Courtesy of Clorox we now know that an average of $20M+ needs to be put aside to pay for the upgrade. It likely did not help for Clorox to wait for 25 years - but it is a key data point for any CIO out there looking into moving to SAP S/4HANA," said Constellation Research analyst Holger Mueller.

• SAP's big plan at Sapphire 2025: Make its Joule AI agent omnipresent
• SAP launches Business Data Cloud, partnership with Databricks: Here's what it means
• SAP Q1 solid amid uncertainty
• SAP launches SAP ERP, private edition, transition option: What you need to know

"We fundamentally have changed and will complete a digital transformation. This is not just an ERP upgrade to the next set of software. This is building a complete data infrastructure across the company, changing the way that we do global finance, changing our ERP, and putting a suite of technologies around that in an effort to create value for our company," said Rendle, who added that Clorox is looking to claw back 900 basis points of gross margins lost due to inflation.

Bellet said the ERP transition has been a "very complex undertaking fraught with risk." However, Clorox has seen many of its peers already go through the ERP transition. "While we're not necessarily proud to be kind of last to the game, that gives us a lot of benefits. And we've been working with very capable consultants and have been working with many of those peers. And we've been embedding learning from their past launches, from their past mistakes in our plans. And we've also been working pretty closely with our retail partners, which had a lot of really good suggestions," said Bellet.

Clorox first piloted the new ERP system in Canada before the US launch. In January, the company moved its global finance reporting to the new SAP system. Clorox also built up inventory at its retails to mitigate risks on out-of-stock conditions. Typically, Clorox has an average of 4 weeks of inventory at retailers and it plans to add another 1.5 weeks.

"Once we're past implementation and stabilization, we're quite excited about having a new ERP because it's going to fundamentally modernize the backbone of our operations. Now just that means a lot more opportunity for productivity in supply chain and working capital and in admin," said Bellet.

The CFO added that Clorox will focus on net revenue management, personalization and other processes that will benefit from a clean data core.

Here's what's next:

• Clorox will go live in July with order fulfillment and order management.
• Manufacturing facilities will move to the new ERP system over the next six months.
• The cadence is transition period for the first half of fiscal 2026 and then optimization.
• Productivity gains will really accrue in fiscal 2027 and fiscal 2028.

HPE launches GreenLake Intelligence, adds AI agents throughout hybrid cloud stack

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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HPE launched new CloudOps Software, layered AI agents throughout its hybrid cloud stack, unveiled GreenLake Intelligence and expanded its AI factory. In addition, Digital Realty said it would standardize its data center footprint on HPE.

At its flagship Discover 2025 conference, HPE showcased its new branding as well as play for AI workloads. The big picture from HPE is that hybrid IT operations, networking, storage and AI operations can be largely turnkey via AI agents.

Antonio Neri, CEO of HPE, said the new vision for hybrid IT "is fueled by agentic intelligence at every layer of infrastructure." HPE, like Dell Technologies, is seeing increased interest in enterprise on-premises deployments of AI infrastructure.

HPE is looking to play at the intersection of hybrid IT, AIOps and agentic AI.

"

• HPE Q2 solid due to AI demand, hybrid cloud
• HPE, Platform9 latest to target VMware customer angst
• DOJ sues to thwart HPE's acquisition of Juniper Networks

During his keynote at Discover 2025 at the Sphere in Las Vegas, Neri made the following points:

• HPE has been reimagined to enable new business models and experiences. 
• "We are HPE and this is more than just a look. We are architects and engineers pioneering the next generation of computing. We are operators and sellers who know your business," said Neri.
• "We are focused on three key essential building blocks: Networking to connect your data more securely and efficiently. Hybrid cloud to give you the flexibility to run workloads where it makes the most sense. And AI to help you unlock the full value of your data to accelerate outcomes," he said. 

Neri said it's time for a new approach with GreenLake and agentic AI:

"You are managing costs, you are chasing alerts. You are patching problems, infrastructure across silos. It takes many people to hold everything together and managing the complexity leaves little time to focus on the true innovation, but that is about to change agentic AI is fundamentally reshaping how we interact and manage it. We are moving beyond AI that simply analyzes and recommends towards a new intelligent agentic AI admin workforce. These AI admins will continuously optimize your infrastructure and resolve issues, helping you save both time and cost."

Here's a look at the key news items from Discover 2025:

• The company launched HPE CloudOps Software that will combine OpsRamp, HPE Morpheus Enterprise Software and HPE Zerto Software. The parts of HPE CloudOps Software can be used individually or as part of a suite.

• GreenLake hybrid cloud platform becomes an AI-powered system with AI agents in multiple roles via GreenLake Intelligence. GreenLake Intelligence uses agents to cut through silos, manual workflows, and optimization hurdles.
• HPE said GreenLake Intelligence was built to bring a unified operating model across its stack. GreenLake Intelligence will deploy AI agents for sustainability operations, orchestration, FinOps, resiliency, security, observability, networking, storage and compute. These agents will work through a reasoning agent that will manage workloads and optimize the HPE stack. The company added that it will support FinOps capabilities with GreenLake Intelligence to optimize workloads and capacity, provide consumption analytics and forecast sustainability impacts.

• With CloudOps offering one control plane, HPE said it will roll out its next-gen HPE Private Cloud AI with Nvidia. HPE said its latest private cloud AI stack will include secure, air-gapped deployment, new HPE ProLiant Gen12 configurations with Nvidia Blackwell support, multi-tenancy and a federated architecture to handle multiple GPU generations. HPE is targeting model builders, service providers and sovereign AI.

• HPE Aruba Networking will be retooled on GreenLake Intelligence and add an agentic AI mesh and networking copilot. HPE Aruba Networking Central will get a copilot that serves as a front-end for root-cause analysis, automated remediation and security issues.
• HPE OpsRamp Software expands its operations copilot with agents for product help and IT management. OpsRamp will get AI-based alerts, incident management and other tools via GreenLake Intelligence.
• HPE Alletra Storage MP X10000 will add AI agent features and support Model Context Protocol (MCP) servers natively. That MCP connection will support GreenLake Intelligence, GreenLake Copilot and natural language interfaces to manage data workflows.
• The company also continues to go after virtualized workloads and said its ecosystem for HPE Morpheus VM essentials has new integrations with HPE Private Cloud, integration with a growing ecosystem and connections to third-party hardware providers. HPE said it added Veeam and Commvault to its backup partnerships. External hardware support branches out to Dell PowerEdge and NetApp gear.

Separately, HPE said Digital Realty, which provides data center capacity, will standardize on HPE Private Cloud Business Edition across more than 300 data centers.

Constellation Research analyst Holger Mueller said HPE's hybrid cloud approach and use of AI agents to manage operations could resonate with enterprises. 

"The AI era comes to all things Ops in IT. And that is a key upgrade to the human operated Ops. When operations run at AI speed inside of the enterprise and outside attacks are powered by AI, then enterprise Ops need to run on AI as well - the sooner the better."

Teradata eyes on-premises AI workloads in regulated industries

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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Teradata launched Teradata AI Factory, which aims to target integrated AI systems for regulated industries.

According to Teradata, its AI factory will include its AI and machine learning tools as well as analytics.

The offering is another indicator that enterprise system providers are looking to court companies looking toward on-premises AI workloads. Teradata AI Factory includes pre-packaged Teradata and various tools for compliance. The system also includes Teradata AI Microservices that can run on Nvidia GPUs and Teradata's Enterprise Vector Store.

For Teradata, the move targeting regulated industries such as healthcare, finance and government is about carving out a niche for AI workloads. Dell, CIsco, HPE and SuperMicro are just a few of the companies looking to scale enterprise AI factories mostly powered by Nvidia, but also AMD.

On-premises AI systems are seen as a way to control infrastructure, secure first party data and manage costs. Teradata AI Factory keeps data on an enterprise's infrastructure. Teradata is looking to return to revenue growth. In the first quarter, Teradata reported net income of $44 million, or 45 cents a share, on revenue of $418 million, down 10% from a year ago.

Key components for Teradata AI Factory, which is available now, include:

• Teradata's IntelliFlex platform along with Enterprise Vector Store is designed for integration of structured and unstructured data.
• AI Workbench, a self-service tool with access to analytics libraries and function, model lifecycle management and LLM deployment options.
• Analytics that connect to customer GPUs via Teradata AI Microservices with Nvidia.
• Native RAG processing in Teradata's ecosystem.
• Data pipeline support for Open Table Formats as well as internal tools such as Teradata's QueryGrid.

Constellation Research's take

Constellation Research analyst Michael Ni said:

"Teradata’s historic strength has been as the platform of choice for regulated, high-performance analytics behind the firewall. AI Factory doesn’t invent a new advantage—it reactivates one, just as the market is circling back to demand sovereign, secure, high-performance AI on-prem.

This all comes at a time when cloud cost volatility and regulatory scrutiny are rising, prompting enterprises to rethink where their most sensitive and strategic AI workloads run.

AI Factory lets Teradata solidify its existing base in regulated industries while positioning to win new customers who assumed on-prem AI meant stitching open-source tools together, or may not have considered Teradata in the past.

With AI Factory, Teradata brings together high-performance analytics, vector stores, and GPU acceleration—all integrated into an on-prem system that removes the complexity many CIOs associate with custom AI deployments.

Teradata isn’t playing catch-up—they’re positioning themselves for a leader for regulated AI. While Snowflake and Databricks started as cloud native and chased cloud market share, Teradata was born on-prem and built the AI command center enterprises need for a unified hybrid experience across platforms, with GPUs, governance, and guardrails included.

Cloud-native rivals aren’t on-prem ready: Snowflake and Databricks have limited to no on-prem AI deployment capabilities today. Their architectures were designed for hyperscaler elasticity, not sovereign infrastructure.

Teradata never left on-prem: It remained the data platform of record for regulated industries like healthcare, financial services, and telco—where cloud migrations remain slow or selective.

AI Factory is turnkey, not toolkit: While competitors may support hybrid integrations, Teradata is offering an integrated hardware-software bundle tailored for private AI—a step ahead in execution for this use case. Teradata is ahead of other on-premise vendors like IBM or HPE or even Intersystems or Vast.

AI Factory gives enterprises a way to scale AI with an out-of-the-box packaged solution—with governance, performance, and control baked in. What stands out is how Teradata integrated model ops, vector search, and LLM pipelines into a turnkey platform providing traceability and compliance from experimentation to production."