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. ...
Cisco rolled out a series of portfolio additions designed to simplify networking and security as well as lay the groundwork for AI and ML workloads.
At Cisco Live in Las Vegas, the company outlined its Cisco Networking Cloud vision, which will unify the company's portfolio with a single platform to manage networking. The general idea is to proactively manage networks, automate and assure performance across Internet of things, Wi-Fi, 5G, AI and security deployments.
Cisco Networking Cloud will feature a nimbler Cisco Catalyst switch stack as well as tools to monitor data center power and energy consumption. Cisco Catalyst products will also have a flexible subscription model as well as simplified licensing.
Cisco also added AI data center blueprints to improve performance.
The first step to Cisco Networking Cloud is enhancements to the company's portfolio including single sign-on, API key exchange/repository, cross platform navigation and a common user interface.
According to Cisco, its ThousandEyes software will expand visibility across any network, deliver insights and provide workflows tied into Cisco Networking Cloud.
Among other items from Cisco Live:
Cisco Secure Access, a security edge system that offers access across locations, devices and applications. Other security enhancements include Secure Firewall 4200.
Cloud native application security tools being added to Panoptica to secure the multicloud application lifecycle from code to development to production.
Cisco Full-Stack Observability (FSO) is now generally available. FSO also has integration between AppDynamics and ThousandEyes for monitoring.
Webex by Cisco will add generative AI summaries of meetings. Cisco also launched Room Bar Pro, which can be deployed into workspaces.
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…...
Catch the latest #CX Convo between Liz Miller and Alan Masarek, CEO of Avaya. They cover what's next for the organization, how Avaya has re-centered its brand financially and culturally, and how this #transformation will empower and shape its #customerexperience and #employeeexperience moving forward...
Alan Masarek unpacks these four key objectives of Avaya...
?? Objective #1: Make Avaya a Destination Place to Work (DPTW) - a company that attracts the most talented in its industry. Culture wins all.
?? Objective #2: #Innovate on behalf of our customers, telling them about our product in a transparent and reliable way to regain trust. We believe in "innovation without disruption" where customers can choose where they want to be in the journey to public #cloud.
?? Objective #3: Be a #customer delight company. Everything is about #CX. "We're selling the promise that a business will generate a better customer experience for their downstream customer through our product... we have to be a fabulous customer service company or think how cognitively dissonant we would be."
?? Objective #4: #Accountability to one another, our customers, and our results...if you do the first three well, number four takes care of itself.
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. ...
Three experts on work, employee experiences and balancing life held court on DisrupTV Episode 324 and the takeaways are keepers.
Here's an abbreviated list of the lessons on the latest episode as companies and employees struggle with the new hybrid normal.
Tiffani Bova, Global Growth Evangelist at Salesforce
A strong employee experience leads to good customer experiences. "The happy employee leads to happier customers and growth," said Bova. "The trick here is that growth starts with employee experience. The great resignation and quiet quitting are a reflection of the lack of investments we've been making for employees that last few decades."
"It's not fair to think that customers are going to love your company before employees."
Enterprises have overemphasized customer experiences relative to employee experiences. Companies that have solely focused on customer experiences have created imbalances where "the employee gets that second rung of attention," said Bova. "It's about making sure we give more attention in a more intentional and thoughtful way," she explained. “If you do something for the customer what is the intended or unintended consequence on the employee?"
Technology improves employee experiences. "The biggest disconnect between what executives think is happening and what employees think is happening is in IT," said Bova. She added that technology impacting employee experiences goes beyond HR software. "I think a lot of it has to do with executives that are not actually using the technology they're deploying," said Bova. "Outdated tech, outdated processes and a lack of integration is slowing down employees."
Priya Krishnan, Chief Digital and Transformation Officer for Bright Horizons
Life balance is an equation. "We are in the service of others and it's shocking for me when there isn't an employee first mindset," said Krishna. She said companies need to think about helping employees solve the work-life equation. Krishna resists the work-life balance approach.
"I talk about a work life equation because there are days, I have to prep for a board meeting and it means switching off from home," she said. "I'm also not feeling guilty about switching off from work. It's less about balance and finding that equation that works for you. It's easier said than done."
Hybrid work. "During the pandemic we all went from living at work and then went to working from home," said Krishna, who argues that hybrid work will become the new norm. "Employers need to pay attention to hybrid as it's the way of the world so far."
There's no handbook for the most important parts of your life. "Nobody gives us a handbook for the three most important events in our life: When you enter the workforce, when you get married and when you have children," she said.
These life events should matter to employers. Krishna said employers need to tune their benefits to families. If your mind is in a crisis at home, you're not going to be functioning well at work. "How do we restructure our benefits to what employees are looking for?" asked Krishna.
She added that benefits should be nimble enough to cover a sandwich generation of employees taking care of parents as well as kids. In addition, the definition of families is changing. "Most organizations have five generations in their workforce so it's not one size fits all," she said. "there are people who have different needs."
Morra Aarons-Mele, Author of The Anxious Achiever
Achievement, anxiety and fear. Aarons-Mele said anxiety and achievement often go together. She started by breaking down the anxiety and fear differences. Fear and stress are external. Anxiety is internal and usually triggered by past events.
The link between anxiety and achievement. Aarons-Mele said "there are many of us out there who always push and never stop because our anxiety is constantly motivating us and telling us if you don't do this you're going to fail."
When is anxiety bad? Aarons-Mele said her line is when anxiety is dragging you down instead of motivating you. "Is my anxiety serving me or harming me. That's the deciding question," said Aarons-Mele.
Companies, culture and anxiety. Aarons-Mele said companies need to ensure that they don't reward people for always being anxious. If companies foster anxiety-ridden performance, employees will burn out.
Know your triggers and minimize them. Aarons-Mele said anxious achievers need to identify the triggers, say parents' unreasonably high standards, and minimize them. "I actually think therapy is the best leadership tool you can invest in," said Aarons-Mele, who noted that triggers are specific to individuals.
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. ...
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. ...
Apple launched its $3,499 Vision Pro extended reality headset with its VisionOS software, its first new software platform since watchOS launched with the Apple Watch in 2015. The core pitch: Vision Pro can be a hybrid work and collaboration tool. Vision Pro is available early next year.
"This is a day that has been years in the making. Augmented reality is a profound technology," said Apple CEO Tim Cook. "It's the first Apple product you look through, not at."
Vision Pro will include immersive media consumption, MacOS integration, and outward-facing cameras so users can see people around them. Apple's Vision Pro will also have its own App Store to enable gaming, watching sports and media and fitness and meditation.
A toggle similar to the Digital Crown will enable users to switch between AR and VR modes. Enterprise use cases may revolve around FaceTime, which will have a VR version, and productivity features for Apple's Keynote, Pages and Numbers software.
As for the hardware, Apple Vision Pro has Apple's M2 chip, but further specifications weren't disclosed during the WWDC keynote or on Apple's product page. Vision Pro has a sleek design, but there are a bevy of compromises including an external battery pack, which provides about 2 hours of power similar to HTC's Vive Pro. When plugged in, Vision Pro can run all day. Among the takeaways from Apple's WWDC keynote:
Cook said Vision Pro will usher in the era of spatial computing.
One of the first use cases shown for Vision Pro was for work. Apple showed office, remote and collaboration use cases.
Microsoft productivity apps will be ready for Vision Pro as will Zoom and Cisco WebEx.
Unity apps will also work with Apple Vision Pro.
Developers can use Reality Composer Pro, which works with existing Apple frameworks in iOS and MacOS.
Of course, there were consumer use cases as Disney outlined a few sports, movie and entertainment scenarios. Think Disney World and Marvel via Vision Pro. Disney+ will be available at launch.
When you open Vision Pro you see your apps in your physical space to create presence.
There are no hand controllers because Vision Pro has eye tracking and hand tracking.
Iris scanner can be used for security via Optic ID. Vision Pro will also mask where you look from apps. Camera data is processed at a system level.
Apple said it focused on a glass device with wearability via a modular design for a precise fit and included flexible straps.
Vision Pro can connect to Apple Watch, iPhone and iPad.
In addition to an M2 chip, Apple included R1, a processor to eliminate lag and process real-time data from sensors and 12 cameras. M2 offers performance. R1 ensures experience quality.
Siri is the voice interface.
Like Apple's other product lines, you can expect new Vision Pro units at lower price points as well as one that's business-friendly.
“This is the next generation of computing and how developers respond to the launch will determine how robust the ecosystem will be for Apple,” said R “Ray” Wang, CEO of Constellation Research.
What's unknown is whether Apple's ecosystem leverage can make AR, VR and the metaverse more of an enterprise staple. The metaverse was a big theme in 2022 but has taken an enterprise back seat to generative AI, optimization efforts and automation.
Apple's vertically integrated approach with hardware and software has gained enterprise traction with its Mac, iPhone and iPad lineup and the software that powers it. Augmented and virtual reality, which is often pitched for mainstream consumers, has more enterprise use cases including training, collaboration and remote maintenance.
Cook usually gives Apple’s enterprise traction a mention on earnings conference calls even though the company doesn’t break out sales to consumers vs. businesses. On Apple’s most recent earnings call, Cook noted: “We see business customers continuing to invest in the Apple platform to drive higher employee productivity and satisfaction.”
Cook added:
“We have our estimates for how much is enterprise versus consumer. And the enterprise business is growing. We have been focusing a lot on BYOD programs and there's more and more companies that are leaning into those and given employees the ability to select which is plays to our benefit, I believe, because I think a lot of people want to use a Mac at work or an iPad at work.
And so, but we're certainly primarily a consumer company in terms of our revenues, obviously.”
When Meta launched its Quest 3 headset last week, it noted that Quest Pro is optimized for work use cases. With Quest 3's increased performance, Quest 2 and Quest Pro will also see better performance via an upcoming software update.
Meta now has three headsets at different price points and use cases. Quest 3 starts at $499.99, and Quest 2 starts at $299.99. Quest Pro starts at $999.99.
In comparison, Apple's Vision Pro headset is going to be too pricey for wide enterprise adoption. However, Apple can leverage its ecosystem of apps and developers to jump-start enterprise use cases. It's unlikely that Apple will talk up business for the Vision Pro, but the odds are good that it'll garner enterprise attention over time.
After all, Apple's iPhone pulled the iPad and Mac into the enterprise.
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. ...
Goldman Sachs CIO Marco Argenti said his firm is betting on generative AI and technology that won't replace human workers but make them superhuman and prioritize the customer.
Speaking during the keynote at the Domino Data Lab Rev 4 conference, Argenti outlined a bevy of thoughts on digital transformation and staying ahead of the AI curve. Among the key takeaways from the Rev 4 keynote:
Being a fully digital company. Goldman Sachs has roughly 45,000 employees and 12,000 are in technology. "We are a fully digital company. We've determined technology is the lifeblood of the organization. It was always tech that started in the back office, but it has worked its way up, so you notice it," said Argenti (check). "Technology has been disruptive in every sector and you have to put software at the center of what you do."
The beauty of being an outsider. Argenti, who was Vice President of Technology at Amazon's AWS before joining Goldman Sachs in 2019, figured he needed some sort of financial background. After an interview with Goldman Sachs CEO David Solomon, it became clear that being an outsider was a plus. "If you want to disrupt you need an external viewpoint of some kind," he said.
AI's importance. Goldman Sachs has plenty of AI and machine learning technology and generative AI will be another wrinkle over time. "There's a realization from the very top of Goldman Sachs that you cannot be a leader in your industry without technology. It's even more so with AI. The leaders in any industry will be leaders in AI," said Argenti.
The mental model for AI management and prioritizing. Argenti said the scaling of AI can rattle humans. "It's hard to say you're an expert in anything with AI," said Argenti. "It comes down to how you think about the future."
He said his mental model revolves around using AI to augment humans by prioritizing what makes Goldman Sachs special. To Argenti technology comes down to saving money and making money. "There's a bias toward saving money you have to fight. You can over index for productivity, but being fit doesn't make you a champion," said Argenti.
Argenti's approach is to use AI to "assure the synergy between human and machine and be something superhuman." His focus areas for AI revolve around impact and quantity.
Developer productivity is a big area since productivity improvement can boost returns on high impact, high-cost workers. Bankers are another area where AI can help by making meetings more valuable for clients and the firm.
Education and training are also areas where AI can be a force multiplier. "There is a lot of knowledge in people's heads and generative AI can provide summarization and learning content," explained Argenti. "What can we do to shorten the apprenticeship?"
He also said that ultimately every major persona within Goldman Sachs will have an AI copilot.
Generative AI. "When you talk about generative AI, the first question to ask is 'what is it good at?'" he said. Indeed, Argenti said more traditional AI and machine learning are better at certain tasks. Generative AI can take large amounts of unstructured data and summarize it and it's good at connecting dots. This ability could mean generative AI can connect dots to ultimately drive investment returns.
AI architecture. Argenti said Goldman Sachs is internally trying to get consensus over the AI strategy, but it's likely there will be humans, large language learning models and a "swarm of small models to create a constellation of specialists." "Humans will focus on relationships, intuition, wisdom and instruction," he said.
Whether this effort is successful will depend on the following:
Quality of data.
Access to clients.
A set of people to provide a flywheel of feedback that creates something unique to Goldman Sachs.
Data strategy. Argenti said Goldman Sachs has been investing in its data platform to have one single version of the truth, transparency to lineage and easy discovery. "The data is the foundation of any AI effort," he said.
The future of engineers. Engineers will move from focusing on how something gets done to what and why, he said. "You'll have to understand the customer and customer benefit," said Argenti. "We're all becoming prompt engineers. With generative AI it will be more about writing instructions than code. It will be all about the mental model."
Argenti likened the change in the computer science profession to when compilers were abstracted. "Engineers will have to conceptualize and understand why they are doing something," he said.
Changing a culture with data. Argenti said he wants his team to move from a vertical approach to one that's more horizontal and distributed. To change culture, you need trust, he said. Data transparency will be key. "Data creates transparency. Transparency creates trust. Trust shifts culture," said Argenti.
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. ...
Data center infrastructure companies say there will be a spike in demand for AI-optimized hardware, but it'll take time to develop as many customers are working on their generative AI plans and determining what workloads will be on-premises, edge, or cloud.
Earnings conference calls from NetApp, Pure Storage, HPE and Dell Technologies provided insights into AI workloads and how they are shaping data centers. Here are some key themes across those companies.
Enterprises are tightening budgets, but spending on hardware enables transformation and drives productivity. NetApp CEO George Kurian said:
"Even as customers are tightening their budgets in response to the macro, they are not stopping investments in applications and technologies that drive business productivity and growth. Digital transformation projects involving business analytics, AI, data security, and application modernization, both on premises and in the cloud remain top priorities for IT organizations."
HPE CEO Antonio Neri added:
"In our HPC & AI’s business, we saw a significant sequential increase in orders this quarter, with a noteworthy uptick across customer segments from Fortune 500 companies including a large cloud provider to digital native start-ups looking for optimized AI supercomputing solutions."
Data centers will move to flash storage since there will be no such thing as cold data when training AI models. Charlie Giancarlo, CEO of Pure Storage, said:
"The days of hard disks are coming to an end. We predict that there will be no new hard disks sold in 5 years...We expect our leading role in AI to continue to expand, but we are equally excited that the requirements for Big Data will drive even more use of high-performance flash for traditional bulk data."
Giancarlo added that Pure Storage's FlashBlade//E enables it to compete for secondary tier storage as well as low-tier storage, which has been dominated by hard drives.
Hardware is likely to be upgraded for generative AI, but customers are just figuring out their strategies. Yes, Nvidia is busy selling chips to hyperscalers, but enterprises are evaluating plans. Giancarlo said:
"Every company is looking at large language models, ChatGPT, et cetera, trying to determine exactly what it means for them. We've seen some interest in that area, but it still remains a minority. The majority being traditional, much -- if I can use that word, with AI traditional AI projects. But we're most excited by is both the opportunity for a high-performance FlashBlade systems."
Kurian said:
"Today's environments are not the advanced LLM model, the majority of the business we see today are really around re-platforming from Hadoop to more modern environments as well as the use of advanced neural networks.
We see the impending onslaught of ChatGPT and tools like that, where customers will take the OpenAI or open-source generative AI model, but then build it on top of their own data sets, which require the storage that we have."
Those comments were echoed by Dell Technologies co-Chief Operating Officer Jeff Clarke. He said:
"What customers are trying to do is to figure out how to use their data with their business context to get better business outcomes and greater insight to their customers and to their business.
And while there's a lot of discussion around these large, generalized AI models, we think the more specific opportunity is around domain-specific and process-specific generative AI, where customers can use their own data. The datasets tend to be smaller. Those datasets then can be trained more quickly, and they can use their business context to help them inform and run their businesses better."
AI workloads and systems are greenfields for new architectures. Giancarlo said:
“AI systems are typically greenfield. So, we're not generally replacing. What we are competing with are solely all-flash systems. Hard systems just can't provide the kind of performance necessary for a sophisticated AI environment.
Of course, you still have hard disk systems in there for some analytics environments, where the performance is not generally as required. But for anything that's machine learning or real-time AI-oriented, it's only all-flash systems."
AI will mean more inference on the edge. HPE has seen strong growth for its intelligent edge unit, which was bulked up the acquisition of Aruba in 2015. Neri said:
"I consider AI a massive inflection point, no different than Web 1.0 or mobile in different decades. But obviously, the potential to disrupt every industry, to advance many of the challenges we all face every day through data insights, it's just astonishing. And HPE has a unique opportunity in that market because ultimately, you need a what I call a hybrid AI strategy.
You need strong inference at the edge. And that really comped by being able to connect and process data, whatever is created with very efficient and low carbon footprint, meaning sustainable solutions with lower power consumption. And then on the other side, you need a training environment where you take some part of the data, where you can train for different needs, different models for different type of used cases."
Dell Technologies co-Chief Operating Officer Chuck Whitten said on the company's first quarter earnings conference call:
"Customers, enterprises, are broadly pursuing and experimenting with AI efforts right now. They're doing it on premises and at the edge. Demand for our XE9680, that's our 16G and first-to-market purpose-built AI server with eight NVIDIA H100 or A100 GPUs has been very good, but we're also seeing demand across our portfolio. It's not simply the specialized eight-way GPU servers that can run AI, not everything needs billions of parameters."
Whitten added that "excitement for AI applications is ahead of GPU supply" and AI-optimized servers are a small part of the overall mix. In other words, the interest in AI-optimized infrastructure is there, but it will take time to flow to the bottom line.
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. ...
Generative AI is the topic du jour on earnings conference calls and technology press releases, but enterprise customers are wary of data security, compliance and hype. There's a generative AI rocket ship ahead, but the timing of lift off is debatable.
Speaking at Domino Data Lab's Rev 4 conference in New York City, Jan Zirnstein, Director of Data Science at Honeywell Connected Enterprise, said the company has been looking at generative AI use cases but questions remain.
"Generative AI has tipped the public perception of what AI is, but tipped it a little too far," said Zirnstein. "There's nothing in the actual training model and architecture that's tied to truth and factual correctness. We're looking at use cases tied to where factualness isn't imperative like saving time on the creative side. There are also use cases on the summarization side."
Zirnstein said generative AI can speed up software development, but there's also a chance that the technology can simply scale poor code.
Neil Constable, head of quantitative research and investments at Fidelity, said at Rev 4 that there are multiple data safety issues to consider with generative AI. "If you use ChatGPT and think what you put in won't show up in some future version you're sadly mistaken," said Constable. Nevertheless, Constable said enterprises should explore generative AI, but "a lot of work should go into looking at what you should and shouldn't do."
He said it's worth bringing in smaller models and learning how to find tune them. "There's a lot of proprietary data I'd like to throw into it," said Constable. "When trained properly there's the ability to use generative AI across the organization but only internally. The data security issue is no joke."
Those security concerns are why vendors like Salesforce are pushing a trust layer. "Large customers must maintain data compliance as a critical part of their governance, while using generative AI and LLMs. This is not true in the consumer environment, but it is true for our customers, our enterprise customers who demand the highest levels of this capability," said Salesforce CEO Marc Benioff on the company's earnings conference call.
He added:
"Where customers who for years have used relational databases as the secure mechanism of their trusted data, they already have that high level of security to the row and cell level. We all understand that. And that is why we have built our GPT trust layer into Einstein GPT. The GPT trust layer gives connected LLM secure real time access to data without the need to move all of your data into the LLM itself."
Beyond Nvidia, however, no tech vendor has meaningfully raised guidance based on generative AI demand. Yes, hyperscale cloud providers are ramping up generative AI infrastructure, but the other layers in the tech stack aren't benefiting just yet.
C3 AI CEO Tom Siebel said there are inbound calls about AI. He said:
"I do not believe that it's an overstatement to say that there is no technology leader, no business leader and no government leader, who is not thinking about AI daily. AI chipmakers like NVIDIA are accelerating production to try to keep up with the very real demand that's out there. And all of this is being accelerated by the advent of generative AI.
The interest in AI and in applying AI to business and government processes has never been greater. Business inquiries are increasing, the opportunity pipeline is growing, demand is increasing."
But Siebel also noted that enterprise customers' interest won't translate into revenue right away. "In terms of applying AI to enterprise we're in first half of the first inning. This is an embryotic market," he said. "We're going to see where this goes in the next few years."
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. ...
Dell Technologies saw its revenue fall 20% in the first quarter, but lower operating expenses enabled it to handily beat expectations.
The company reported first quarter earnings of 79 cents a share on revenue of $20.9 billion, down 20% from a year ago. Non-GAAP earnings in the first quarter were $1.31 a share.
Wall Street was expecting Dell Technologies to report first quarter non-GAAP earnings of 85 cents a share on revenue of $20.27 billion.
The company said it maintained pricing discipline, cut operating expenses and benefited from a normalized supply chain.
In prepared remarks, Chuck Whitten, co-Chief Operating Officer at Dell Technologies, said:
"We continued to see demand softness across our major lines of business, all regions, all customer sizes, and most verticals. In what was a challenging demand backdrop, we executed extremely well and stayed focused on what we could control. Looking ahead, we expect the cautious IT spending environment to continue in Q2."
Whitten said he expects demand to be muted for infrastructure and PCs with some pockets of stabilization.
Even with better-than-expected results, Dell Technologies' core units saw revenue declines. By the numbers:
The Infrastructure Solutions Group had revenue of $7.6 billion, down 18%. Storage revenue was $3.8 billion, and servers and networking sales were $3.8 billion. Operating income for the unit was $740 million.
Client Solutions Group had revenue of $12 billion, down 23%. Commercial revenue was $9.9 billion of that sum. Operating income was $892 million. Commercial revenue was down 18% and consumer revenue fell 41%.
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 first quarter earnings and CEO Marc Benioff said the company will infuse "trusted, secure generative AI across our entire product portfolio."
Not surprisingly, Salesforce was talking about generative AI. After all, what vendor isn't talking about generative AI? Benioff, however, noted Salesforce has a portfolio of generative AI brands including Einstein GPT, Slack GPT and Tableau GPT. The company also said its Salesforce GPT Trust Layer is designed to deploy generative AI in a way that secures enterprise data.
As previously reported, enterprises are currently working on how to leverage generative AI and tune using corporate data sets securely.
Speaking on an earnings conference call, Benioff said every CEO realizes that it must invest in generative AI. "Every CEO wants more productivity, automation and intelligence by using AI," he said.
Customers also need to understand where their data is going while keeping compliance, said Benioff. Enterprise customers will have to worry about compliance, security and regulation more than consumer industries will, he added. "This AI revolution is just getting started," said Benioff, who said AI will lead to a new super cycle. He said he was in a customer meeting and all anyone wanted to talk about was generative AI.
Salesforce is planning an AI event in New York in June.
Salesforce reported first quarter earnings of 20 cents a share on revenue of $8.25 billion, up 11% from a year ago. Non-GAAP earnings were $1.69 a share. Wall Street analysts were expecting Salesforce to report first quarter earnings of $1.61 a share on revenue of $8.17 billion.
Benioff also added that Salesforce has become more efficient by improving its non-GAAP margin by 1,000 basis points from a year ago. Salesforce reiterated its revenue outlook for fiscal 2024 and updated its earnings outlook.
"We are transforming every corner of our company," said Benioff, who said Salesforce is improving profitability as well as efficiency. "While the economy isn't in our control our margins are."
For the second quarter, Salesforce is projecting revenue of $8.51 billion to $8.53 billion, up about 10% from a year ago. Non-GAAP earnings for the quarter will be $1.89 a share to $1.90 a share.
For fiscal 2024, Salesforce is projecting sales of $34.5 billion to $34.7 billion with non-GAAP earnings of $7.41 a share to $7.43 a share.
By cloud, Salesforce's Sales Cloud had first quarter revenue of $1.81 billion, up from $1.63 billion a year ago.
Service Cloud had revenue of $1.96 billion, up from $1.76 billion a year ago.
Platform and Other had revenue of $1.57 billion, up from $1.42 billion a year ago.
Marketing and Commerce had revenue of $1.17 billion, up from $1.09 billion a year ago.
And Data Cloud had revenue of $1.13 billion, up from $955 million a year ago.
