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
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
Palantir's commercial revenue in the US surged 70% as the company delivered in line fourth quarter earnings with revenue that was just ahead of expectations.
The data platform and AI company, which is best known for its government customers, has been working to build out its enterprise business and appears to be succeeding.
Palantir reported fourth-quarter net income of $93 million, or 4 cents a share, on revenue of $608 million, up 20% from a year ago. Adjusted earnings of 8 cents a share were in line with estimates.
In the fourth quarter, Palantir posted commercial revenue of $284 million, up 32% from a year ago. Government revenue was $324 million, up 11% from a year ago. In the US, commercial revenue was $131 million, up 70% from a year ago. Palantir ended the quarter with 221 commercial customers in the US.
For 2023, Palantir reported net income of $210 million, or 9 cents a share, on revenue of $2.23 billion, up 17% from the year before.
As for the outlook, Palantir projected first quarter revenue between $612 million and $616 million. For 2024, Palantir is projecting revenue between $2.65 billion and $2.67 billion with net income each quarter of the year. US commercial revenue is expected to grow at least 40% in 2024.
"The demand for large language models from commercial institutions in the United States continues to be unrelenting. Every part of our organization is focused on the rollout of our Artificial Intelligence Platform (AIP), which has gone from a prototype to a product in months. And our momentum with AIP is now significantly contributing to new revenue and new customers."
Karp said that AIP significantly speeds up data integration and can get enterprise up and running quickly.
"The proliferation of and interest in large language models obscures the simple fact that the sophistication and power of such natural language processing systems mean little without an effective way of allowing those systems to interact with an organization’s underlying and proprietary data, which is often scattered across hundreds if not thousands of disparate repositories. AIP is connective tissue, and the organic and unconstrained demand for its capabilities is unlike anything we have seen in two decades."
Since launching AIP, Karp said Palantir has conducted more than 500 bootcamps and more than 130 commercial pilots.
Editor in Chief of Constellation Insights
Constellation Research
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
Hitachi Vantara and Cisco launched a suite of hybrid cloud services, Hitachi EverFlex with Cisco Powered Hybrid Cloud, that aims to automate deployments and provide predictive analytics.
The two companies have been long-term partners. The combination aims to bring Hitachi Vantara's storage, managed services and hybrid cloud management and integrate them with Cisco's networking and computing stack. Hitachi Vantara and Cisco said customers will see a consistent experience across on-premises and cloud deployments.
Here are the moving parts of the Hitachi Vantara and Cisco combined offering:
Hitachi Infrastructure Orchestration as a Service (HIOaaS) and Cisco Intersight will be integrated to offer an observability layer across hybrid cloud environments along with analytics and automation.
A flexible managed services operating model for provisioning, implementation and transitions.
An elastic consumption model across hybrid cloud and on-premises deployments via Hitachi EverFlex.
Automation of routine tasks.
A full set of security and compliance tools.
Here's a look at the stack and combination of Hitachi Vantara and Cisco and deployment options.
Mark Katz, CTO of Financial Services at Hitachi Vantara, said the explosion of data, most of it unstructured, means that businesses have to be able to manage data, protect personal identifiable information with segmentation and track lineage. "It's not enough to simply store the data and retrieve it," said Katz. "You need a set of data management tools across enormously complex cloud and hybrid cloud environments."
Editor in Chief of Constellation Insights
Constellation Research
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
General Motors has software development problems, and the company is facing a brand risk unless it can get its code, user experience and delivery right.
Yes, GM is an automaker and a profitable one, but its future model depends on software prowess. For the fourth quarter, GM reported net income of $2.1 billion on revenue of $43 billion, roughly flat with a year ago. That profit came amid a strike and a reset for its electric vehicle plans.
However, GM CEO Mary Barra spent a good chunk of the company's software woes. First, GM had to stop selling its Blazer EV due to software glitches. Edmunds review of the 2024 Blazer EV was brutal with 23 fault codes that didn't turn up on the dashboard. GM plans a software update to fix the issues.
In addition, GM's Cruise autonomous vehicle investment is at risk. GM owns 80% of Cruise. In October, Cruise had to pause driverless operations to "examine our processes, systems, and tools and improve how we operate." In October, Cruise vehicles were involved in two accidents. Cruise issued a voluntary software recall and issued an update that should fix issues.
After two high-profile software failures, Barra had to address the software issues in her shareholder letter and earnings conference call. This won't be the first time an automaker has to talk about software issues. Ford recently recalled F-150 Lightning EV trucks over software issues.
Regarding GM's Blaze software issue, Barra said:
"We disappointed these customers, and we know it. We are determined to get the software right and we will. We have made several organizational and process improvements that will help us deliver the best possible customer experience going forward. Among several important organizational realignments, we established a software quality division within the software and services team that has been performing a retrospective on the Blazer EV and has improved the current software development and test processes across the enterprise. Outcomes of this activity are getting applied to all programs going forward and they include improved standardization of the software development and release process, increased focus on test automation at the vehicle level, and additional quality gates and metrics for software at the vehicle level."
On the Cruise incidents, Barra said the 2024 investment plan revolves around being more deliberate and slowing the cash burn rate as it stabilizes its software efforts.
Barra said:
"We've already begun to implement significant changes to build a better Cruise. We are committed to earning back trust with our regulators and the public through our actions. Our plan for 2024 investment in Cruise reflects our more deliberate and cadence go-to-market strategy and we are developing new financial targets and a new roadmap. Spending will be down considerably this year, but we will continue to invest in the people who are advancing the software, specialized hardware, and AI capabilities. This reflects our commitment to our vision, which is to deliver the safety benefits of self-driving technology and a scalable, profitable business."
Simply put, GM seems to understand that it needs to hone its software game if it's going to transition its business model. As a result, GM will push its investor day until later in the year. "This will give our software team the time to focus on software for our upcoming launches, and we will be able to share more tangible proof points on all four pillars of our strategy, ICE, EV, AV, and software," said Barra. "When we do get together, we will show you what we've done, not just tell you what we're going to do. In the meantime, we've already provided a roadmap for EV profitability in 2025, and we'll share updates on Cruise as we finalize the technology and relaunch plans."
It remains to be seen if GM can fix its software issues before 2024 ends. A few thoughts:
Automakers are at risk of losing customer experience to Apple and Google with CarPlay and Android Auto, respectively.
A transition to EVs will mean autos are basically data centers on wheels. Software will be the primary technology driving customer experience.
However, automakers lack the consumer-facing application development experience. There's a reason a company like Tesla can deliver a better software experience than incumbents and even the EV giant can struggle.
User expectations for vehicle systems are higher.
And finally, GM will have to change its culture to improve its application development. It has moved to simplify its offerings, but large companies like GM don't turn on a dime. The pressure is on GM to improve software before the risk to its brand grows.
From our underwriter
Commercial generative AI use cases are promising, but CXOs at the Hitachi Vantara Exchange in New York note there's a lot of work ahead--data management, privacy and training models--to scale. Here's a look at the key takeaways on the use cases that can drive transformation from Hitachi Vantara Exchange in New York.
Editor in Chief of Constellation Insights
Constellation Research
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
Meta Platforms 2023 of efficiency concluded with blowout fourth quarter earnings, a dividend and strong usage across the company's platform. But Meta CEO Mark Zuckerberg's AI ambitions may be the thing to watch in the long run.
Now it's easy to overlook Zuckerberg's ode to AI and open source. Meta’s fourth quarter revenue was $40.1 billion, up 25% from a year ago, and net income was $14.02 billion, up 200% from a year ago. The outlook was strong, and Meta will pay out its first-ever dividend. I could even find something nice to say about Meta's Reality Labs unit in that it had revenue of $1 billion in the fourth quarter (still lost $4.65 billion in the quarter).
Nevertheless, Meta's AI ambitions are clear and on par with Microsoft, Google and Amazon. Meta said 2024 capital expenditures will be $30 billion to $37 billion with a big chunk of that driven by AI-related spending. Here's a look at the AI strategy.
Meta plans to give consumers a copilot. The copilot craze has mostly been an enterprise effort, led by Microsoft, but Zuckerberg's vision was broader. He said:
"We'll be building the most popular and most advanced AI products and services. And if we succeed, everyone who uses our services will have a world-class AI assistant to help get things done, every creator will have an AI that their community can engage with, every business will have an AI that their customers can interact with to buy goods and get support, and every developer will have a state-of-the-art open-source model to build with."
You could call Meta's strategy a copilot for all play.
AI-centric devices won't be today's devices. Naturally, Zuckerberg will talk up smart glasses and Oculus, but the idea is broader. "Everyone will want a new category of computing devices that let you frictionlessly interact with AIs that can see what you see and hear what you hear, like smart glasses. And one thing that became clear to me in the last year is that this next generation of services requires building full general intelligence," he said.
AI models will have to be broad. Zuckerberg pushed back on use case specific AI products because they only do a subset of activities. Life doesn't operate in silos. "We're going to need our models to be able to reason, plan, code, remember and many other cognitive abilities in order to provide the best versions of the services that we envision. We've been working on general intelligence research and FAIR for more than a decade. But now general intelligence will be the theme of our product work as well," he said.
This AI strategy will need hyperscale infrastructure and Meta has it. "By the end of this year, we'll have about 350,000 (Nvidia) H100s, and including other GPUs, that will be around 600,000 H100 equivalents of compute. We're well positioned now because of the lessons that we learned from Reels. We initially underbuilt our GPU clusters for Reels. And when we were going through that, I decided that we should build enough capacity to support both Reels and another Reels-sized AI service that we expected to emerge so we wouldn't be in that situation again," said Zuckerberg.
Infrastructure will be critical since training and operating models are going to be more compute-intensive than today. Zuckerberg added he wasn't sure how much compute will be needed but state-of-the-art large language models have been trained on 10x the compute each year.
Zuckerberg said Meta is looking at novel data center designs as well as its own custom silicon for its workloads.
Long-term AI R&D. "While we're working on today's products and models, we're also working on the research that we need to advance for Llama 5, 6 and 7 in the coming years and beyond to develop full general intelligence," said Zuckerberg. "It's important to have a portfolio of multiyear investments in research projects, but it's also important to have clear launch vehicles like future Llama models that help focus our work."
Open source is a big part of Meta's long-term AI strategy. Meta open sources its Llama models and tools like PyTorch as well as hardware designs. "Open sourcing improves our models. And because there's still significant work to turn our models into products because there will be other open-source models available anyway, we find that there are mostly advantages to being the open-source leader," said Zuckerberg.
He added that strategic benefits of open-source AI approaches include:
Security.
Compute efficiency.
Ongoing feedback and scrutiny.
Standardized approaches to hardware and software.
Developer popularity and the ability to hire talent.
Training data and feedback loops will reinforce models and general intelligence AI. Zuckerberg said:
"When people think about data, they typically think about the corpus that you might use to train a model upfront. And on Facebook and Instagram, there are hundreds of billions of publicly shared images and tens of billions of public videos, which we estimate is greater than the common crawl data set. And people share large numbers of public text posts and comments across our services as well.
But even more important in the upfront training corpus is the ability to establish the right feedback loops with hundreds of millions of people interacting with AI services across our products. And this feedback is a big part of how we've improved our AI systems so quickly with Reels and Ads, especially over the last couple of years when we had to re-architect it around new rules."
Add it up and Meta plans to infuse AI into its platform for new services. Zuckerberg said the company will even put multiple teams on the same project to test versions.
To end the AI strategy talk, Zuckerberg also noted the metaverse investment. Rest assured that the bet is that AI and the metaverse will converge at some point. "I think that people are going to want new categories of devices that seamlessly engage with AIs frequently throughout the AI without having to take out your phone and press a button and point it at what you want to see," said Zuckerberg. "I think that smart glasses are going to be a compelling form factor for this, and it's a good example of how our AI and metaverse visions are connected."
Editor in Chief of Constellation Insights
Constellation Research
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
Apple reported better-than-expected first quarter results with revenue growth of 2%.
The company reported first quarter earnings of $2.18 a share on revenue of $119.6 billion. Wall Street was expecting Apple to report earnings of $2.10 a share on revenue of $117.9 billion.
Apple CEO Tim Cook said the company saw record services revenue in the quarter powered by iPhone sales. Cook added that "our installed base of active devices has now surpassed 2.2 billion, reaching an all-time high across all products and geographic segments."
The company will launch its Apple Vision Pro Feb. 2.
On a conference call with analysts, Cook talked up the Apple Vision Pro launch and said Apple will continue to invest in new technologies. He said:
"We're so focused on pushing technology to its limits as we work to enrich the lives of our users. As we look ahead, we will continue to invest in these and other technologies that will shape the future. That includes artificial intelligence, where we continue to spend a tremendous amount of time and effort and we're excited to share the details of our ongoing work in that space later this year."
Here's the breakdown by product line:
iPhone sales in the first quarter were $69.7 billion, up from $65.77 billion a year ago.
Mac sales were $7.78 billion, roughly flat from a year ago.
iPad sales were $7 billion, well below $9.4 billion a year ago.
Wearable revenue was $11.95 billion, down from $13.5 billion a year ago.
Servies revenue was $23.1 billion, up from $20.77 billion a year ago.
Other than the iPhone, Apple's product lines were on par with expectations or below the mark. Apple did have 13 weeks in the first quarter of fiscal 2024 compared to 14 weeks a year ago.
By geography, Apple's China sales were $20.82 billion, down from $23.9 bilion a year ago. Other geographies showed revenue gains.
Editor in Chief of Constellation Insights
Constellation Research
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
Amazon Web Services' fourth quarter revenue was $24.2 billion, up 13% from a year ago, and below the 30% and 26% growth rates put up by Microsoft Azure and Google Cloud, respectively.
AWS revenue was in line with expectations and fourth quarter operating income of $7.2 billion was well ahead of the $5.2 billion a year ago. AWS's operating income also outpaced the $6.5 billion for Amazon's North America e-commerce business. Amazon's AWS report comes days after both Microsoft and Google reported fourth quarter earnings.
For the fourth quarter, Amazon reported net income of $10.6 billion, or $1 a share, on revenue of $170 billion, up 14% from a year ago. Wall Street was expecting fourth quarter earnings of 80 cents a share on revenue of $166.2 billion.
Amazon reported 2023 net income of $30.4 billion, or $2.90 a share, on revenue of $574.8 billion.
"The regionalization of our U.S. fulfillment network led to our fastest-ever delivery speeds for Prime members while also lowering our cost to serve; AWS’s continued long-term focus on customers and feature delivery, coupled with new genAI capabilities like Bedrock, Q, and Trainium have resonated with customers and are starting to be reflected in our overall results; our Advertising services continue to improve and drive positive results; our newer businesses are progressing nicely."
For the first quarter, Amazon projected revenue of $138 billion and $143.5 billion, or 8% to 13% growth from a year ago. Operating income will be between $8 billion and $12 billion.
Jassy said AWS is also seeing indicators of strong demand ahead. Jassy said AWS is seeing more migration as enterprises start spending on cloud again. He said:
"The lion's share of cost optimization has happened. It's not that there won't be any more that we don't see any more but it just attenuated very significantly. Migrations have started to pick up again.
If you go to the generic GenAI revenue in absolute numbers, it's a pretty big number, but in the scheme of $100 billion annual revenue run rate it's still relatively small. We really believe we're going to drive 10s of billions of dollars of revenue over the next several years (with GenAI). It's encouraging how fast it's growing and our offerings really resonate with customers."
Speaking on a conference call, Jassy made the following points:
North America profit margins have approved because Amazon has retooled its network to bring goods closer to customers. This move has lowered costs to serve. "We reduced our cost to serve on a per unit basis globally. In the US cost to serve was down by more than 45 cents per unit compared to the prior year," said Jassy. "Lowering cost to serve allows us not only to invest in speed improvements, but also afford adding more selection at lower average selling prices or ASP and profitably. We have a saying it's not hard to lower prices. It's hard to be able to afford lower prices."
Advertising revenue was up 26% largely due to sponsored ads across the Amazon network.
AWS added more than $1.1 billion in incremental sequential revenue. "Our customer pipeline remains strong as existing customers are renewing it larger commitments over longer periods and migrations are growing," said Jassy.
AWS' generative AI strategy revolves around options and choices for enterprises. "We've launched Bedrock, which is off to a very strong start with many 1,000s of customers using the service after just a few months," said Jassy. "what customers have learned at this early stage of GenAI is that there's meaningful iteration required. Customers don't want only one model. They want different models for different types of applications and different size models for different applications. Customers want a service that makes this experimenting and iterating simple."
"We're building dozens of Gen AI apps across Amazon's businesses, several of which have launched and others of which are in development," he said. "GenAI is and will continue to be an area of pervasive focus and investment across Amazon primarily because there are few initiatives if any, that give us the chance to reinvent so many of our customer experiences and processes. We believe it'll ultimately drive 10s of billions of dollars of revenue for Amazon over the next several years."
Editor in Chief of Constellation Insights
Constellation Research
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
Commercial generative AI use cases are promising, but CXOs at the Hitachi Vantara Exchange in New York note there's a lot of work ahead--data management, privacy and training models--to scale.
Data management and architecture are the base of generative AI efforts. Mark Katz, CTO of Financial Services at Hitachi Vantara, said the explosion of data, most of it unstructured, means that businesses have to be able to manage data, protect personal identifiable information with segmentation and track lineage. "It's not enough to simply store the data and retrieve it," said Katz. "You need a set of data management tools across enormously complex cloud and hybrid cloud environments."
Debika Bhattacharya, Chief Product Officer, Verizon Business, said enterprises will have to harmonize data to get the most out of generative AI. Bhattacharya said Verizon Business customers are focusing on harmonizing data that's housed in separate towers.
Bharti Patel, SVP, Product Engineering, Hitachi Vantara, said a semantic data plane can be used to bridge these data silos. "The reality is that the data is not going to be static. You have to do it in a metadata way, so the processing is closer to the data," said Patel. "How do you feed LLMs with only the data that makes sense?"
Cyber resilience and privacy are being driven by regulations globally. Part of the data management layer has to be security, so you know exactly what's happening to protect data and recover it at scale, said Katz.
Enterprise use cases for generative AI are just starting. "The thing to keep in mind with generative AI is that it's really early days for commercial use," said Katz. Virtual assistants are a primary use case and consumers are already used to it. Artificial intelligence and machine learning have been used in the enterprise for a while, but generative AI use cases are more experimental.
Katz said credit card companies are an area to watch for generative AI use cases. "More advanced models are coming for new use cases," he said. Indeed, Mastercard launched a generative AI initiative to battle fraud. Jeb Horton, SVP, Global Services, Hitachi Vantara, said enterprises have "varying degrees of embedding AI into what they do."
Bhattacharya said more advanced generative AI use cases are promising. She said personalized healthcare is a fascinating area "as long as the risks are studied and handled the right way."
Santhosh Keshavan, CIO of Voya Financial, said generative AI provides an opportunity to enable investors to make smart decisions from an early age to retirement.
Other use cases that are evolving with generative AI include security, sustainability, customer experience. CXOs noted that use cases for generative AI are almost endless as any process can benefit from a copilot.
Responsible AI frameworks are critical for enterprise adoption. Multiple CXOs at Hitachi Vantara Exchange New York noted that generative AI adoption will depend on trust and responsible use.
Katz said there needs to be traceability into how models were trained and on what datasets. Models should also be explainable.
Smaller models will trump large language models (LLMs) in the enterprise. Katz said enterprises are likely to use models that are use case specific for a host of reasons, including lower compute costs, data safety and more predictive behaviors. In addition, limited training data sets, say a corporate knowledge base, will inherently minimize the risk of errors.
Patel added that one large language model to address multiple use cases isn't efficient. "You'll have fine-tuned smaller models that can delegate tasks when they don't know about certain things," said Patel.
"Train the model on corporate offerings, company financials and recommendations designed for a specific use case," said Katz. CXOs at Hitachi Vantara agreed that commercial use of generative AI will initially be very targeted.
Lan Guan, Chief AI Officer at Accenture, said "your propriety data is your biggest advantage” and success is more about the quality of data.
Traditional AI and machine learning technologies can be turbocharged and advanced with generative AI. "AI is not new, but the recent events have shined the light on AI-based applications that have been developed for years," said Bhattacharya. Verizon has been using machine learning and deep learning for networks for insights on the past and predicting the future. "Now we are tying traditional AI to generative AI to create new content," said Bhattacharya.
Keshavan said generative AI can take lessons from traditional AI and data sets and make companies more productive. Voya is looking to generative AI for efficiency gains as well as improving customer service.
Previous AI, data science and machine learning investments are building blocks for generative AI. Andrew Chin, Head of Investment Solutions and Sciences, AllianceBernstein, convinced his company to build out its data science office 7 years ago and today those investments apply to generative AI.
"The lowest hanging fruit was natural language processing so our analysts can gather data faster," he said. "Now we can apply techniques to read documents and make recommendations and summarize for analysts. Humans still have ownership for the final decision."
Take a crawl, walk, run approach with generative AI. Keshavan said his CIO role is part evangelizing generative AI with the business, aggregating use cases and then going from pilot to production.
Bhattacharya said Verizon Business is taking a cross-functional approach that includes security, product, IT and legal to make sure the right policies are in place. "The foundational building block of AI is data," she said. "We prioritize use cases within Verizon and from a product standpoint we look to embed generative AI for new experiences."
Efficiency and cost savings are the table stakes, but enterprises need to eye broader transformation. Accenture's Guan said, "cost efficiency is the table stakes for generative AI, but how do we transform ourselves?"
CXOs at Hitachi Vantara Exchange said one challenge is getting companies to think more in terms of generative AI transformation over productivity.
Dave Malik, Cisco Fellow and CTO, Customer Experience, said the broader transformation due to generative AI will come as more use cases are adopted. "Once there's trust in the system and adoption people will be willing to take more calculated risk with new use cases," said Malik.
Editor in Chief of Constellation Insights
Constellation Research
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
Match wants to bring dating into the generative AI age and plans to invest to bring AI-driven experiences to its two largest brands, Tinder and Hinge.
Speaking on Match's fourth quarter earnings call, CEO Bernard Kim outlined the company's generative AI efforts. Match delivered fourth quarter revenue of $866 million, up 10% from a year ago, with annual sales of $3.4 billion. Tinder revenue is more than half of Match's sales.
Kim said:
"We believe that AI is existential to the future of Match Group and our business. AI will help us create improved user experiences and will truly make our products better. And that puts us in a different category from other companies that are just looking at optimizing through AI and slight improvements.
This technology is revolutionary for dating, and we're bringing it to life across our entire portfolio. I envision AI to be felt through the entire experience, influencing everything from profile creation to matching and connecting for dates, literally everything."
Here's a look at Match's generative AI plans and how it will drive engagement.
Tinder will adopt a "fast-fail mentality" that will inform moves across the Match properties. "In 2024, Tinder is adopting a fast-fail mentality, a strategy that prioritizes rapid experimentation and testing. This approach is all about agility. If a new idea or feature doesn't yield the anticipated results, the team is prepared to quickly pivot, absorbing valuable insights and move forward. We recognize that not every innovation will be a groundbreaking success," said Kim.
AI will enable Tinder to appeal to a broader audience. "This new generation of singles is digital-first and expect platforms like ours to allow daters to showcase their unique personalities in an engaging setting and be shown highly curated matches," said Kim. "Leveraging AI, Tinder will focus on creating a more inclusive experience beginning with improving the Gen Z and women's experiences, while solving for key user pain points across the dating journey."
Hinge will use AI and aim to "truly understand you and what you're looking for in order to introduce you to the right person sooner." This use case will leverage data from profiles, interactions and "great dates that Hinge has collected over several years," said Kim.
A central innovation team will begin to launch new brands to grow the dating category and bring in new users.
Internal systems will aim to coordinate with the central innovation team to improve the company’s effectiveness. "While AI brings with it cost efficiencies and a potent optimization tool, we view it as far more than just that," said Kim. "AI has played an important strategic role at Match Group for years from trust and safety efforts to our matching algorithms, and I believe it will play an even larger role moving forward."
Kim's bet is that Match's AI investment in Tinder will generate momentum among Gen Z and women with growth in the second half of the year.
"We believe AI can help improve our users' experience and bring resistors into the category, as well as potentially expand our TAM. We have a long list of product features being rolled out at Tinder and Hinge, as well as plans to test new and different products that leverage AI throughout 2024. Our current expectations for incremental 2024 AI-related spend of $20 million to $30 million across Match Group."
Editor in Chief of Constellation Insights
Constellation Research
About Larry Dignan:
Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning.
He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.
Constellation Insights does the following:
Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...
Qualcomm reported strong first quarter results as its Snapdragon platform saw traction across smartphones, automotive, PCs and Internet of things devices.
The company reported first quarter net income of $2.77 billion, or $2.46 a share, on revenue of $9.93 billion, up 5% from a year ago. Wall Street was expecting Qualcomm to report first quarter earnings of $2.37 a share on revenue of $9.52 billion.
As for the outlook, Qualcomm projected second-quarter revenue of $8.9 billion to $97 billion with earnings of $1.73 a share to $1.93 a share. Non-GAAP earnings will be $2.20 a share to $2.40 a share.
For the second quarter, analysts were expecting Qualcomm to report earnings of $2.25 a share on revenue of $9.28 billion.
Qualcomm is betting that on-device generative AI processing and features will drive demand. Qualcomm is embedded in AI-heavy smartphones from Samsung and others and is looking toward more generative AI workloads moving to edge devices.
By device, Qualcomm said handset revenue in the first quarter was $6.69 billion, up 16% from a year ago. Automotive revenue was $598 million, up 31%. IoT sales were $1.14 billion, down 32% from a year ago.
Cristiano Amon, CEO of Qualcomm, said on the earnings conference call that generative AI processing on the edge will move well beyond smartphones into enterprise use cases. Amon said:
"We continue to believe that industrial edge devices with connectivity, high-performance computing and on device AI will become one of our largest addressable opportunities fueled by the secular trends of digital transformation. As such, we're accelerating our investments in solutions, ecosystem and broad channel enablement to position ourselves for growth while we navigate the industry-wide inventory draw down."
Vice President and Principal Analyst
Constellation Research
Title: About Dion Hinchcliffe
Dion Hinchcliffe is an internationally recognized business strategist, bestselling author, enterprise architect, industry analyst, and noted keynote speaker. He is widely regarded as one of the most influential figures in digital strategy, the future of work, and enterprise IT. He works with the leadership teams of large enterprises as well as software vendors to raise the bar for the art-of-the-possible in their digital capabilities.
He is currently Vice President and Principal Analyst at Constellation Research. Dion is also currently an executive fellow at the Tuck School of Business Center for Digital Strategies. He is a globally recognized industry expert on the topics of digital transformation, digital workplace, enterprise collaboration, API…...
The rise of hybrid work has thrown open a pandora's box of possibilities, but also unleashed a tangle of challenges for IT departments struggling to keep remote, in-office, and flexible employees seamlessly connected. In the scenario unfolding today, next-generation 5G wireless Internet access has emerged as a genuine enabler, promising to redefine hybrid work flexibility, efficiency, and security.
The traditional office network, tethered to physical desks and legacy wireless connections, now feels archaic in the face of today's dynamic workforce. Imagine attending a crucial client meeting from a comfortable local co-working space, collaborating on real-time documents from home, or seamlessly transitioning between remote office and central office without missing a beat. 5G's fast bandwidth, ultra-low latency, and vast capacity make such scenarios not just feasible, but highly performant and smooth.
But the benefits of 5G go beyond mere connectivity. In my latest research report on delivering on hybrid work, I explore how next-gen 5G internet gateways -- an example being the widely-used Verizon 5G Business Internet Gateway -- can equip IT departments to tackle the unique challenges of hybrid work.
The crux is success in such hybrid work scenarios is making sure the worker has the capabilities and that it's well supported by the IT department. In my research, supporting the IT department in delivering a high quality hybrid work experience with 5G is a critical succes factor. Imagine a portal that provides real-time visibility into network performance across all hybrid work locations. No more scrambling to diagnose connectivity issues across a scattered patchwork of Wi-Fi hotspots and poorly provisioned regional offices. The such a support portal simplifies network management, security operations, and governance, allowing IT to proactively identify and resolve problems before they disrupt a remote employee's workflow.
But it doesn't stop there. Security concerns abound in the hybrid landscape, with company data potentially accessible from countless public networks. In my exploration of using 5G to unleash hybrid work, I found that solutions like Verizon's VBI Portal can empoower IT to enforce granular security policies across all devices and locations, ensuring every connection adheres to the highest standards, regardless of where the employee is working.
The Data Says: It's a Hybrid Work Future
Industry data speaks volumes. A recent study by Upwork revealed that 64 million Americans performed freelance work in the past year, an all-time high, highlighting the growing number of independent professionals who contribute to hybrid teams. Add to that the vast majority of workers, namely 79% of employees who report they crave more flexible work arrangements in a large Cisco survey. It's clear that hybrid work is not just a trend, it's the future. A new Gallup study found that the top five benefits of hybrid work to both employers and workers is productivity:
And 5G, fully unleashed with enabling management support tools for the IT dpeartment, such as Verizon's VBI Portal, holds the key to unlocking its full potential. Imagine a world where employees can sustainablly work seamlessly from anywhere, unburdened by connectivity troubles, secure in the knowledge that their data is fully protected. It's a world where productivity soars, collaboration transcends boundaries, and workers can focus innovation, which is specifically unleashed by the agility and flexibility of 5G networks.
Robust 5G Infrastructure A Vital Enabler of Hybrid Work
Yes, infrastructure challenges remain. But with continued investments in 5G networks and IT-friendly management tools, hybrid work scenarios once deemed futuristic are now within reach. End-user computing teams and digital employee experience leads are now in a position to embrace the flexibility and efficiency that 5G enables, and empower IT departments with the tools they need to support it all. My finding: The future of work is wireless everywhere, and it's more readily achievable than ever before with today's enabling capabilities.
Benefits of 5G management capabilities for IT departments, like the VBI Portal:
Real-time network visibility and performance insights across all hybrid work locations.
Centralized management and troubleshooting of devices and connections.
Granular security policy enforcement to protect company data.
Simplified deployment and support of hybrid work technologies.
As I conclude in the report, "5G unlocks a future where collaboration and productivity defy physical boundaries." And it's not just about speed – the report sheds light on another vital revelation: 5G gateways can unleash virtual networking and resource sharing in real-time, effectively merging disparate physical spaces into a single, dynamic work environment, but only if the right infrastructure is provided.
This research, soon to be publicly available, is a clarion call for IT departments to step up and become champions of hybrid work. By embracing 5G and its empowering tools, they can shed the shackles of traditional network management and orchestrate a symphony of productivity across continents. It's time to rewrite the rules of work, ditch the limitations of the physical office, and unleash the boundless potential of a truly connected, global workforce. The future is wireless, and the future is here today. I urge IT departments to be at the forefront, guiding the way to this high-potential future of work.
