IBM outlines quantum computing roadmap through 2029, fault-tolerant systems

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

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.

For IBM, Quantum Starling will be the headliner of a fleet of quantum computing systems. IBM CEO Arvind Krishna said the company is leaning into its R&D to scale out quantum computing for multiple use cases including drug development, materials discovery, chemistry, and optimization. IBM also recently outlined flexible pricing models for quantum computing to expand usage and upgraded its Quantum Data Center to its latest Heron quantum processor.

The news lands as quantum computing players outline plans to scale organically or via acquisition. IonQ just announced its plans through 2030 and quantum computing vendors have been laying out plans throughout 2025.

IBM said Starling will be able to run 100 million quantum operations using 200 logical qubits. A logical qubit is a unit of an error-corrected quantum computer tasked with storing one qubit’s worth of quantum information. Quantum computers need to be error corrected to run large workloads without fault.

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

Starling will also be a foundation system for IBM Quantum Blue Jay, which will be able to run 1 billion quantum operations over 2,000 logical qubits.

To get to fault tolerant scale, IBM is building an architecture that is fault tolerant, able to prepare and measure logical qubits, apply universal instructions and decode measurements from logical qubits in real time. This architecture, which was outlined in two research papers, also has to be modular and energy efficient.

Here's how IBM is going to get to Starling and beyond:

• 2025: IBM Quantum Loon will launch to test architecture components for quantum low-density parity check (qLDPC) codes, which reduce the number of physical qubits needed for error correction and cuts overhead by about 90%.
• 2026: IBM Quantum Kookaburra will feature a modular processor to store and process encoded information and combine quantum memory and logic operations.
• 2027: IBM Quantum Cockatoo, will feature two Kookaburra modules that will link quantum chips together like nodes in a larger system.

Holger Mueller, an analyst at Constellation Research, said:

"Sometime in the last 6 months quantum vendors realized that they will not be able to produce enough qubits for real world use cases and are focusing on error correction. What is unique with IBM is that it's modular approach has led to the realization that there are challenges to overcome when putting multiple quantum computers together, hence a roadmap change and a focus on qLDPC based couplers, with 'Loon', coming this year. Next year will then be the showcase and proof point that all of this works with IBM Quantum Kookaburra. Kudos go to IBM for laying out its roadmap further, all the way to its Starling system, allowing CxOs to align their quantum uptake plans."

More IBM Quantum:

• IBM launches Qiskit services for quantum computing
• When Quantum SDKs Go to the Gym, Qiskit Wins
• IBM Boosts the Software Side of Quantum

IonQ acquires Oxford Ionics for $1.07 billion, gets quantum-on-a-chip technology

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

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.

The purchase is IonQ's largest to date. Niccolo de Masi, IonQ CEO, said in a statement that the Oxford Ionics purchase will " set a new standard within quantum computing and deliver superior value for our customers through market-leading enterprise applications."

According to IonQ, the Oxford Ionics will bring complementary technology to the company. IonQ focuses on trapped ion systems and Oxford Ionics holds world records in fidelity, which measures the accuracy of quantum applications. The game plan for the combined company is to provide an integrated quantum computing stack that features IonQ quantum computing, applications and networking with Oxford Ionics ion-trap technology, which is manufactured on standard semiconductors.

Oxford Ionics ability to bring ion-trap-on-a-chip to IonQ and enable the combined company to "accelerate IonQ’s commercial quantum computer miniaturization and global delivery." Oxford Ionics founders, Dr. Chris Ballance and Dr. Tom Harty, are expected to remain with IonQ after the acquisition is completed.

In an SEC filing, IonQ said it will issue up to about 35 million new shares to pay for the deal. The company said:

"The number of shares of Common Stock to be issued will not be less than 21,143,538 or more than 35,241,561. The final number of shares of Common Stock to be issued as Transaction Consideration will be calculated using the volume-weighted average price for shares of Common Stock for the 20 trading days immediately preceding, but not including, the third business day prior to the date of the Closing, but will not be more than $50.37 per share or less than $30.22 per share."

Ballance said Oxford Ionics' quantum chip can be manufactured in standard semiconductor fabs. "We look forward to integrating this innovative technology to help accelerate IonQ’s quantum computing roadmap for customers in Europe and worldwide," said Ballance.

IonQ has been on an acquisition spree of late with an emphasis on quantum networking. The acquisition of Oxford Ionic is designed to bring scale to compute and use cases in materials science, drug discovery, logistics, financial modeling and defense.

Here's a look at IonQ's acquisitions.

• Lightsynq Technologies, a startup focused on photonic interconnects and quantum memory. Capella Space, which specializes in quantum space networks. See: IonQ’s plan: Quantum networks extending into space
• ID Quantique, focused on quantum safe networking and quantum detection systems. See: IonQ doubles down on quantum networking, names new CEO as it eyes scale
• Quibitekk, a quantum networking company. IonQ’s bet on commercial quantum computing working, acquires Quibitekk

IonQ has also been expanding its global footprint and Oxford Ionics will be a beachhead in the UK.

Oxford Ionics outlined its roadmap last month with a plan that features enterprise grade quantum computing by 2027. IonQ's roadmap features a similar timeline and will bring an established customer base and sales team to better commercialize Oxford Ionics.

In a statement, IonQ said the combined company plans to build systems with 256 physical qubits with 99.99% accuracy by 2026 and scale to 10,000 physical qubits with logical accuracy of 99.99999% by 2027. Ultimately, IonQ wants to hit 2 million physical qubits in quantum computing by 2030.

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

IonQ and Oxford Ionics held a technology overview call featuring Ballance and Dr. Mihir Bhaskar, CEO of Lightsynq, which was acquired. De Masi touted a recent use case with Astra Zenica, IonQ, Nvidia and AWS and added that Oxford Ionics will accelerate commercial usage.

"IonQ, Lightsynq and Oxford Ionics will create the winning quantum computer in each year and every era of quantum computing," said de Masi.

Dean Kassmann, SVP of engineering and technology at IonQ, said the company's latest acquisitions will "represent a significant acceleration of our planned development work to realize our vision to build the world's best quantum computers to solve the world's most impactful and complex problems."

Kassmann also outlined IonQ's roadmap with Oxford Ionics in the fold.

Ballance said Oxford Ionics approach to leveraging existing technologies to go along with quantum computing will be scalable. Ballance said:

"We have a clear path to apply this to systems with 10s of 1000s of qubits in a single chip, and we've been to be working on our 256 qubit quantum processor units. Our technology allows us to scale devices to millions of qubits by building bigger and bigger chips. But what's more, these chips can be networked by photonic interconnects to allow for distributed compute."

Constellation Research analyst Holger Mueller said:

"The road to commercial quantum uses cases goes this way: (a) more qubits, (b) better error correction or (c) a combo of both. For a decade the industry was squarely rooted in more qubits. More recently it's about error correction, which means that vendors think they have sufficient qubits. IonQ is the perfect example of saying it's a combo of both to enable more sophisticated quantum use cases."

Apple's WWDC 2025: Apple Intelligence leaves a void as execs go redesign happy

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

Apple executives acknowledged at the company's Worldwide Developer Conference (WWDC) that Apple needs more time to make Apple Intelligence work well. In the meantime, Apple executives outlined Liquid Glass, a redesign that'll flow through Apple devices.

The company also announced new naming conventions for iOS, watchOS, tvOS, macOS, visionOS and iPadOS.

If anything, Apple's developer keynote highlighted how Apple Intelligence, outlined in 2024 with great fanfare, has fallen short of expectations. Craig Federighi, SVP of Software Engineering at Apple, noted how Apple Intelligence did ship features including email and notification summarization, notes, smart replies and ways to clean up video and photos.

Federighi said:

"We delivered this while taking an extraordinary step forward for privacy and AI with private cloud compute, which extends the privacy of your iPhone into the cloud so no one else can access your data, not even Apple. We also introduced enhancements that make Siri more natural and more helpful, and as we've shared, we're continuing our work to deliver the features that make Siri even more personal. This work needed more time to reach our high quality bar, and we look forward to sharing more about it in the coming year."

He said that Apple Intelligence will get more languages, but the approach is incremental for now. "We're making the generative models that power Apple intelligence more capable and more efficient, and we're continuing to tap into Apple intelligence in more places across our ecosystem. Throughout today's presentation, you'll see new Apple intelligence features that elevate your experiences across iPhone, Apple, watch Apple vision pro Mac and iPad. Plus, this year, we're doing something new, and we think it's going to be pretty big. We're opening up access for any app to tap directly into the on device," said Federighi.

As for LLMs, Apple Intelligence will have a new foundation model framework that gives developers direct access with privacy and offline access built in.

"We think this will ignite a whole new wave of intelligent experiences in the apps you use every day. For example, if you're getting ready for an exam, an app like Kahoot can create a personalized quiz from your notes to make studying more engaging," said Federighi. "And because it uses on device models this happens without cloud API costs. We couldn't be more excited about how developers can build on Apple intelligence to bring you new experiences that are smart, available when you're offline, and that protect your privacy."

With that Apple Intelligence tease--that may not be reality until 2026--Apple moved on to other key items including a redesign for iOS that already has Windows Vista trending due to the resemblance. 

A few thoughts:

• Apple Intelligence appears to be banking on local LLMs but given the rate of innovation that could be a mistake. Developers will need to figure out how much they can differentiate with Apple’s on-device model.
• Key details about the Apple Intelligence's approach for developers is lacking.
• Apple is clearly betting on privacy as a pitch for AI, but it's unclear whether focusing on its edge devices will keep pace with OpenAI, Google, Anthropic and Microsoft to name a few.
• Apple does appear to be integrating OpenAI's ChatGPT across its applications. For instance, Apple said ChatGPT image generation is now available in Image Playground.
• It's quite possible that Apple will have to buy its way out of this AI pickle, but historically the company hasn't made big acquisitions. The valuations are stretched for foundational model players.
• The risk here is that Apple devices are merely a vessel for other companies' AI no matter how pretty the operating systems become.

Other news items:

• Apple's WWDC keynote was devoted to the redesign and the changes across devices looked strong. However, much of what Apple is proposing is in the latest Android today. See: Apple release on redesign.
• Developers are getting new APIs for location, enhancements to notifications in Apple Watch, App Intents, and other goodies.
• Visual Intelligence will pull up context across iPhone apps to give you more information, rating and other data.

Qualcomm acquires Alphawave for $2.4 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. ...

Read more

Qualcomm said it will acquire Alphawave IP Group, a UK company, for $2.4 billion in a move that will give it assets to speed up its data center expansion.

The purchase will give Qualcomm IP in high-speed connectivity and compute for its Qualcomm Oryon CPU and Hexagon NPU processors. In May, Qualcomm outlined its data center CPU efforts and said it will connect with Nvidia's NVLink Fusion initiative.

Qualcomm said it can bring low-power inferencing to data centers as well as custom processors for AI workloads.

Cristiano Amon, CEO of Qualcomm, said Alphawave will bring complementary technology for its CPUs and NPUs. "The combined teams share the goal of building advanced technology solutions and enabling next-level connected computing performance across a wide array of high growth areas, including data center infrastructure," said Amon.

The deal is expected to close in the first quarter of 2026.

RPA and those older technologies aren’t dead yet

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

Robotics process automation (RPA) isn't dead and arguably should get more attention in your enterprise automation portfolio. Simply put, RPA still has a role in an overarching AI strategy and in many cases can be good enough. Keep that in mind for old school AI, machine learning, process automation and even hybrid cloud.

We’ll stick to RPA for now, but the general theme remains: Automation and returns are what matters. And you don’t have to rely solely on heavy compute, reasoning large language models to get there.

Rest assured that most vendors aren't going to preach the benefits of RPA, but orchestration is about more than AI agents. Process, automation and workflow matter. Use the tool for the right job. If a rule-based approach like RPA works use it to deliver returns. Ditto for workflow engines, traditional AI and any other non-agentic technology. For things you already know about there’s no reason to force an LLM to reason repeatedly.

This theme has been bubbling up in recent months amid the agentic AI marketing barrage. CxOs in Constellation Research's BT150 have been noting that RPA is part of the generative AI mix and some acknowledged that the technology may be good enough in many use cases. In fact, older technologies—traditional AI and machine learning—are good enough to deliver significant value.

• Agentic AI: Everything that’s still missing to scale

Marianne Lake, CEO of JPMorgan Chase's Consumer & Community Banking unit, set the scene during the bank’s annual investor day: "Despite the step change in productivity we expect from new AI capabilities over the next five years, we have been delivering significant value with more traditional models. Not every opportunity requires Gen AI to deliver it."

Vendors that play to value instead of the buzzwords seem to be faring well.

During his PegaWorld keynote, Pegasystems CEO Alan Trefler said orchestrating automation, workflows and AI is about finding the right tool for the task at hand. Yes, Pegasystems has RPA, but didn't mention it during PegaWorld or on recent earnings calls. The company has been riding its GenAI Blueprints for revenue growth and launched the Pega Agentic Process Fabric as well as a blueprint that’ll help you ditch legacy infrastructure.

Overall, Pegasystems broad platform includes decisioning, workflow automation and low code development.

Trefler said agentic AI is being talked about extensively due to "magical marketing." He said that there will be thousands of AI agents running around in enterprises and leading to sprawl and no orchestration.

"The right AI for the right purpose is absolutely critical and candidly forgotten by the pundits that just want to dump things in and hope everything goes right. Large language models aren't everything. Languages models are great for some stuff, but for other things you want to use other forms of AI," said Trefler.

Trefler, like Philipp Herzig is Chief AI Officer and Chief Technology Officer at SAP, argue that prompt engineering is dead. Why? Semantic approaches leave too much uncertainty for processes that need to be followed repeatedly. And you don’t need agentic AI to do everything because it’ll make your costs balloon just on energy consumption.

"If you go down the philosophy of using the GPU to do the creation of the workflow and a workflow engine to execute the workflow, the workflow engine takes a 200th of the electricity because it's not reasoning. It's all this reasoning. You don't have to reason on things you already know about," said Trefler.

The upshot is that old-school AI, machine learning and rule-based RPA can be used in a comprehensive automation strategy. In other words, AI agents and genAI simply think (reason) too much.

Francis Castro, head of digital and technology customer operations at Unilever, said at PegaWorld: "I'm a technologist 25 years in the company, driving technology. Sometimes you fall in love choosing the right tool and the right technology. Sometimes we fall in love with the technology, or we fall in love with the problem, but we forget about what we want to achieve."

The takeaway from Pegasystems is that workflows, automation, agentic AI, process and RPA all go together. It's one continuum. ServiceNow sings from the same hymn book, but sure does talk a lot about AI agents today. In the end, RPA is good enough to automate specific, repetitive and rule-based tasks.

"While the market has been talking about Agentic AI and overloading buyers with a laundry list of AI agents, bots and orchestrators, Pega has been focused on the underlying processes and workflows that have long been their bread and butter," said Liz Miller, analyst at Constellation Research.

Systems integrators are busy building AI agents and have shown they're better at it than vendors. But the big picture for these integrators is automation of processes for customers and internally for business process management.

Verint is another vendor playing the value game. The company's first quarter results were better than expected as customers used its AI bots to automate specific processes without the need to change infrastructure or platforms.

Verint CEO Dan Bodner said: "First, more and more brands are fatigued by the AI noise and are looking for vendors that can deliver proven, tangible and strong AI business outcomes now. And second, brands are looking for vendors with hybrid cloud that can deploy AI solutions with no disruption and with a show me first approach."

The CX automation company's secret sauce is delivering value over talk about orchestration, LLMs and agentic AI protocols. "More brands are fatigued by the AI noise and are looking for vendors that can deliver proven, tangible and strong AI business outcomes now. And second, brands are looking for vendors with hybrid cloud that can deploy AI solutions with no disruption and with a show me first approach," said Bodner.

Here's a look at a Verint slide on returns for use cases:

In fact, Bodner mentioned LLMs just twice at the very end of Verint's earnings call. Verint is agnostic about the LLMs it uses for its bots, which were mentioned 24 times. The game for Verint is to automate "micro workflow" in various processes to deliver returns. Verint bots use Verint's Da Vinci AI and are designed to automate tasks and workflows. Verint bots are focused on specific tasks instead of being general purpose.

“Verint’s bet that simple is better paid off,” said Miller. “While everyone was ramping up the hype machine around AI Verint dug into the idea that all of these innovations were great, but outcomes were better. So their simplified preset bot approach where you start with the intended outcome and then connect the automation dots with automation, skills and workflows works.”

Like Pegasystems, Verint doesn’t talk about RPA anymore. In 2019, Verint talked a lot about RPA and has plenty of docs about the technology lying around.

For UiPath CEO Daniel Dines, the company's RPA heritage is an advantage and he hasn’t banned the acronym yet. "Our extensive installed base of robots and AI capabilities already operating autonomously across more than 10,000 customers gives us unparalleled insight into real enterprise processes and workflows where agents are a natural extension," said Dines on UiPath's fiscal first quarter earnings call. "We uniquely bridge deterministic automation or RPA and probabilistic automation or agentic, allowing customers to extend automation into more complex adaptive workflows."

• UiPath launches next-gen platform: 'Agents think. Robots do. People lead.'

UiPath has been building out its automation platform and launched UiPath Maestro, which aims to leverage AI agents, RPA and humans to orchestrate processes. UiPath’s first quarter results were better-than-expected due to traction for its agentic automation platform.

"There is a tremendous benefit of combining AI agents with robots. And when you go and decide on an AI genetic automation platform, it's a natural way to think maybe we should bring the robots into the same platform," said Dines. "Again, the benefits from the security and governance perspective and having agents and robots and managing humans also in the same platform are tremendous."

Naturally, Dines is going to say RPA has a role in automation given UiPath has a significant legacy business tied to the technology. However, I don't think he's off. AI agents aren't needed for everything when a robot will do fine. And none of these agents are going to work without process intelligence.

CxOs need to deliver value and chasing agentic AI when there are other tools that provide returns faster isn't a great blueprint. Is RPA going to see a renaissance? Probably not. But RPA is definitely worth keeping in the automation toolbox. A lot of those older, less buzzworthy technologies should stick around too.

Celonis, SAP reach data access cease fire amid litigation

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

SAP has agreed to not interfere with Celonis' data extractor for customer data until the litigation between the two companies has been resolved. In turn, Celonis has withdrawn its motion for a preliminary injunction.

As previously reported, the Celonis lawsuit against SAP is worth watching given agentic AI largely depends on enterprise technology vendors providing data access to other applications--and AI agents.  

SAP said: "SAP rejects Celonis’s claims and continues to seek dismissal of the case. In the meantime, SAP has agreed to maintain the status quo with Celonis and avoid confusion for the benefit of SAP’s customers. SAP will continue to evaluate its IP rights and take action as appropriate."

In March, Celonis sued SAP in federal district court in San Francisco alleging that SAP used anticompetitive practices to thwart Celonis' process mining applications. SAP owns Signavio, a process mining tool that's often combined with the ERP giant's platform.

Celonis alleged that SAP is using its ERP dominance to block Celonis in the process mining market.

Under the agreement, SAP will enable Celonis customers to access their own SAP data without additional fees or licenses.

Related:

• The data wars are just starting and agentic AI may be a trigger
• Lessons from early AI agent efforts so far
• Every vendor wants to be your AI agent orchestrator: Here's how you pick
• Agentic AI: Everything that’s still missing to scale
• AI? Whatever. It's all about the first party data

P&G outlines Supply Chain 3.0, next digital transformation moves

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

Procter & Gamble's two-year restructuring includes a heavy dose of digital transformation, artificial intelligence and supply chain automation and optimization.

The headlines from Procter & Gamble's appearance at the Deutsche Bank Global Consumer Conference revolved around the company's move to cut 7,000 jobs. However, P&G Chief Financial Officer Andre Schulten and Chief Operating Officer Shailesh Jejurikar outlined the bigger picture.

P&G is navigating an uncertain economy, shifting tastes, inflation and tariffs. P&G's approach is to use productivity to fund growth initiatives over the years. Its next phase is focused on developing its systems and digital capabilities to support automation, data strategy, insights and analytics, said Schulten.

"We believe we now have the opportunity to step forward to enable the tremendous growth opportunities we have with an even more focused and efficient portfolio, supply network, and organization," said Schulten. "In fiscal 2026, we will begin a 2-year noncore restructuring program. This program includes 3 interdependent elements: portfolio choices, supply chain restructuring and organizational design changes."

P&G plans to shed brands in various categories and categories will be outlined more in July when the company reports its fiscal year end results.

Here's a look at the high level transformation moves from P&G:

• The company will right size its supply chain, optimize by locating production to drive efficiencies, speed up innovation and cut costs.
• P&G will make roles broader and shrink teams as the company leverages automation and digitization.
• P&G will cut up to 7,000 non-manufacturing roles, or 15% of its non-manufacturing workforce. Those job cuts are incremental to what P&G has outlined for its Supply Chain 3.0 savings.

"This restructuring program is an important step toward ensuring our ability to deliver our long-term algorithm over the coming 2 to 3 years. It does not, however, remove the near-term challenges that we currently face," said Schulten. "All the more reason to double down now on the integrated growth strategy that has enabled strong results over the past 6-plus years, executing our strategy and accelerating this opportunity, especially under pressure is our path forward."

According to Schulten, future success for P&G requires innovation for product, packaging, brand communication and marketing and retail execution. Schulten said all of those variables have to work together to deliver value. No one thing can carry the team. He explained:

"Superior performing products and superior packages provide noticeably better benefits to consumers. They become aware of and learn about these products through superior brand communication. This comes to life in stores and online with superior retail execution and deliver superior consumer value at a price that is considered worth it across each price tier in which we choose to compete."

Here's a look at the P&G plan:

Fund investment with productivity gains. Schulten said P&G can mitigate cost and currency headwinds by becoming more efficient across cost of goods sold to marketing to in-store and online execution.

Data and insights across the value chain. Jejurikar said the company was looking for "better consumer insights on what's required for the specific job to be done; integrated technical capabilities applied across formulated chemistry, assembled products and devices to deliver the superior solution; integrated communication across package, shelf, online and other channels; and at a value that balances price and performance for the consumer and the retailer."

Use AI to make the marketing and advertising spend more efficient. Jejurikar said the company is using programmatic and algorithm-based media buying to find consumers most likely to be receptive to messaging. "Our proprietary Consumer 360 data platform enables brand to use target audience algorithms to serve ads at the right frequency each week, all year round, more effective reach and more cost efficient," he said. P&G's media reach in the US has grown to 80% from 64% over five years. Reach in Europe is now 75%.

He added:

"We are driving advertising effectiveness, starting with superior consumer insights and leveraging AI as a tool to deliver superior content creation. We're improving efficiency using AI tools for ad testing improving quality, cost and speed. Ads can now be tested and optimized in just a few days versus weeks at 1/10 of the cost versus prior methods."

In-store optimization via data and computer vision. Jejurikar said P&G was combining point-of-sale data with millions of retail shelf images to optimize shelf design. P&G has proprietary tools that enable the company to analyze assortment online and offline.

Supply Chain 3.0. Jejurikar said P&G is looking to extend that supply chain data from suppliers to customers to retail shelves. "We are investing in advanced supply planning technologies to better anticipate consumer demand and adjust production and inventory levels, accordingly, helping minimize stock-outs overproduction and waste," said Jejurikar.

The supply chain transformation will have a heavy dose of automation in manufacturing sites. P&G is capturing images and visual data on manufacturing lines to improve quality.

According to Jejurikar, P&G's warehousing center of excellence will be the hub for the company's 50 distribution centers. This hub will coordinate warehouse activity from the moment a truck enters the gate until it leaves. This coordination is improving productivity 50% on indirect administrative work at each site.

Jejurikar also outlined the KPIs for Supply Chain 3.0:

• 98% on-shelf and online availability.
• Up to $1.5 billion before tax in gross productivity savings each year.
• 90% of free cash flow productivity.

Those targets are in addition to savings of $1.5 billion in cost of goods sold and $500 million in marketing previously outlined.

Broadcom delivers strong Q2 on AI networking demand

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

Broadcom reported strong second quarter results amid "robust demand for AI networking."

The company, which is thriving as hyperscale cloud providers buy processors for AI workloads, delivered second quarter earnings of $4.96 billion, or $1.03 a share, on revenue of $15 billion, up 20% from a year ago. Non-GAAP earnings were $1.58 a share, two cents ahead of Wall Street estimates.

Broadcom CEO Hock Tan said AI revenue in the second quarter was up 46% from a year ago to $4.4 billion. "We expect growth in AI semiconductor revenue to accelerate to $5.1 billion in Q3, delivering ten consecutive quarters of growth, as our hyperscale partners continue to invest," said Tan.

CFO Kirsten Spears the company free cash flow was a record $6.4 billion, up 44% from a year ago.

Semiconductor revenue in the second quarter was $8.41 billion, up 17% from a year ago. Software infrastructure revenue, led by VMware, was $6.6 billion, up 25% from a year ago.

As for the outlook, Broadcom projected third quarter revenue of $15.8 billion with adjusted EBITDA of at least 66% of projected revenue.

Constellation Research analyst Holger Mueller said:

"Broadcom Is firing on all cylinders breaking the $15 bilion milestone in revenue by a hair. The demand for AI keeps growing Broadcom's semiconductor and infrastructure software businesses. It's good to see an extra $400 million invested into R&D, even if it cost Broadcom some revenue. CEO Hock Tan and team know Broadcom needs to invest into product to keep the growth going."

On the conference call with analysts, Tan said the following:

• "Custom AI accelerators grew double digits year-on-year, while AI networking grew over 170% year-on-year. AI networking, which is based on Ethernet was robust and represented 40% of our AI revenue. As a standard-based open protocol, Ethernet enables one single fabric for both scale out and scale up and remains the preferred choice by our hyperscale customers. Our networking portfolio of Tomahawk switches, Jericho routers and NICs is what's driving our success within AI clusters in hyperscalers."
• "We continue to make excellent progress on the multiyear journey of enabling our 3 customers and 4 prospects to deploy custom AI accelerators. As we had articulated over 6 months ago, we eventually expect at least 3 customers to each deploy 1 million AI accelerated clusters in 2027, largely for training their frontier models. And we forecast and continue to do so a significant percentage of these deployments to be custom XPUs. These partners are still unwavering in their plan to invest despite the certain economic environment."
• "There's no differentiation between training and inference in using merchant accelerators versus custom accelerators. I think the whole premise behind going towards custom accelerators continues, which is it's not a matter of cost alone. It is that as custom accelerators get used and get developed on a road map with any particular hyperscaler, there's a learning curve, a learning curve on how they could optimize the way the algorithms on their large language models gets written and tied to silicon."
• "Why inference is very hot lately--we're only selling to a few customers hyperscalers with platforms and LLMs--. is these hyperscalers and those with LLMs need to justify all the spending they're doing. Doing training makes your frontier models smarter. There's no question. Make your frontier models by creating very clever algorithms that consumes a lot of compute for training smarter. You want to monetize inference. And that's what's driving it. Monetize. To justify a return on investment on training you create a lot of AI use cases, and consumption through inference. And that's what we are now starting to see among our small group of customers."
• Customers are increasingly turning to VCF (VMware Cloud Foundation) to create a modernized private cloud on-prem, which will enable them to repatriate workloads from public clouds while being able to run modern container-based applications and AI applications. Of our 10,000 largest customers, over 87% have now adopted VCF."