Larry Dignan

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.&nbsp; <br>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… Read more

Uber addressed long-running concerns about its autonomous vehicle strategy with a plan that revolves around partnering and leveraging its data platform to manage workloads and rides.

However, Uber noted that autonomous vehicles (AVs) needed a lot of things to go right to scale adequately. The biggest hurdle is costs. AV rides need to drop below what it costs a human to shuttle you place to place.

Speaking on the company's fourth quarter earnings conference call, Uber CEO Dara Khosrowshahi said AV costs including hardware such as vehicle and sensor kit, operating costs with compute, storage and maintenance and fleet management cost more than $2 million a mile. Those costs don't include demand gen, marketing, payments and cost to serve. Humans rides are about $2 a mile.

Khosrowshahi said 2024 was a turning point for AV technology as Waymo, WeRide, Pony and Baidu made self-serving rides to the public. Other players are likely to follow. The big question for Uber was whether it would get disrupted. Khosrowshahi outlined many threads worth considering:

"Even as we see AV technology advancing, we expect AV commercialization will take significantly longer. Several pieces of the go-to-market puzzle still need to come together, including: a consistently super-human safety record; enabling regulations; a cost-effective, scaled hardware platform; excellent on-the-ground operations; and a high-utilization network that can manage variable demand with flexible supply.

Every one of these five pieces must work in concert, or the puzzle falls apart. For example, even the lowest-cost AV fleet will struggle to generate revenue if its vehicles are not highly utilized. And even a well-utilized but fixed fleet will struggle to meet consumer demand at peak times."

Uber obviously sees its role in at the application and data layer of that AV stack. The plan is simple and on brand: Leverage its data platform and AI to manage rides, supply and demand and continually optimize.

• How Uber's tech stack, datasets drive AI, experience, growth
• Uber aims to press its 'data advantage' for AI, model training

Khosrowshahi made the following points about the moving AV parts.

• Safety will have to surpass what humans can do for mass adoption. He said Waymo is a safety leader with its transparency, but multiple tech platforms and approaches will create more risks.
• Regulations are fragmented across states and a national framework in the US for AV testing and deployment would be welcome. International markets such as Abu Dhabi may move faster.
• The software stack from auto OEMs has been slow. Without OEMs, it will be hard to scale AVs. AV companies have retrofitted traditional vehicles with sensors that mean costs of more than $200,000 per vehicle. Costs need to come down. It is likely that all new vehicles will be sold with L4-capable software and that will increase supply.
• Fleet management and operations. Uber said an average AV can run as much as 100,000 a year. That scale means charging and service costs will increase. Uber sees a role in managing cleaning, parking and operational issues such as fare disputes, stranded vehicle rescue and insurance claim resolutions.
• Utilization. If all of the pieces of the AV puzzle fall into place, AV operators will need to manage supply and demand. Ride demand patterns fluctuate and AV vendors will struggle meeting weekly peaks and downtime.

"Given the scale of the Uber platform, and human drivers’ ability to dynamically fulfill demand spikes—and take a break during demand troughs—partnering with Uber allows AV players to move much faster than they could on their own. This fact gives us confidence that the Uber network, with a hybrid of AV and human drivers, will deliver the highest asset utilization and revenue generation opportunity for our partners," said Khosrowshahi. "We are spending an enormous, yet appropriate, amount of organizational energy to execute on our AV strategy. We will have much more to share through the year, starting with our public launch with Waymo in Austin next month and Atlanta this summer."

In other words, Uber's plan is to plug into those AV networks just like it does for human drivers and then adding support, technology and payments to the stack.

While Uber's AV chat was the most notable, the company's fourth quarter results were solid. The company reported fourth quarter earnings of $6.9 billion, including a tax valuation release and unrealized gains from investments, on revenue of $12 billion, up 20% from a year ago.

Gross bookings in the fourth quarter were up 18% to $44.2 billion. Uber delivered 3.1 billion trips in the fourth quarter, or 33 million trips per day.

For the first quarter, Uber projected gross bookings growth of 17% to 21%.

Larry Dignan

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.&nbsp; <br>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… Read more

SAP made it official and granted SAP customers an option to extend the move to SAP Cloud from on-premise ERP by three years. But there are a few wrinkles you need to know.

The company, which outlined the extension on its fourth quarter earnings call, said the formal SAP ERP, private edition, transition option rollout will come in the second quarter.

For SAP, the offering is designed to help large complex enterprises that weren't going to meet a 2030 deadline. Key points about SAP ERP, private edition, transition option include:

• The offering is a new cloud subscription that revolves around SAP ECC and a set of services focused on moving to SAP Cloud ERP.
• SAP ERP, private edition, transition option will support enterprises with patches for security, legal and software issues.The subscription will be available in 2028 and be active to use from 2031 to 2033.
• SAP ERP, private edition, transition option is an additional subscription. Customers that can complete the move to SAP Cloud by the end of 2030 won't need it.
• While SAP ERP, private edition, transition option is centered on SAP ECC it won't include all of the features in SAP Business Suite 7, which will be available until the end of 2030.
• SAP HANA is the only supported database for SAP ERP, private edition, transition option. Older versions of Java and third-party technology aren't supported.
• SAP said SAP ERP, private edition, transition option is not an extension of maintenance. There aren't changes for customers running on-premises SAP ERP systems after 2030.

Got all of that? Now you know why SAP is disclosing SAP ERP, private edition, transition option early. There are a lot of moving parts and SAP said more details will roll out closer to the 2028 availability.

Related research:

• There Is Only ‘One’ (1) IT Strategy in 2025 and Beyond
• SAP Loves ABAP (Again)

Constellation Research analyst Holger Mueller said the extension doesn't mean SAP customers can coast. Mueller said:

"SAP did not manage to keep the hard deadline of 2027, and is now extending the offering to its customer by three years – but with a catch – all customers join the RISE program. With this move, SAP now can show higher adoption numbers for the years to come.

For customers it is good as they gain more time. But they cannot sit and let the year go by – as they have in the past – but must move to HANA, clean up the tech stack, and make sure they are licensed.

Even with three more years available – it is time for SAP customer CxOs to get going with its migration towards S/4HANA – probably best for the public cloud edition. The big variable for 2025 is going to be success and adoption of SAP Business AI. If SAP creates enough value, customers will be self-motivated to move to S/4HANA as soon and as fast as they can. So, 2025 is a critical year for the SAP customers, SAP and the SAP ecosystem. All eyes on the value and uptake of the AI offerings (that are gated to the public cloud)."

Indeed, SAP is preparing to launch a big agentic AI push as part of its SAP Business AI strategy. By launching new innovation, SAP is hoping to woo customers still holding out. SAP said it is positioning Joule as the new UI for its software.

• Amazon Bedrock integrated into SAP AI Core, SAP to use AWS chips
• SAP gives ABAP code a genAI boost, adds data lake capabilities to Datasphere
• SAP’s Joule everywhere plan: ‘We are not developing AI just for the sake of AI”

SAP's German speaking user group, DSAG, commented on SAP ERP, private edition, transition option when reports surfaced last month. DSAG said it generally welcomed the program and the extension, said SAP was obviously trying to convert customers to RISE and still forcing a switch to the cloud.

DSAG: SAP's innovation focus on cloud, discriminates against on-premise users

A translation from a German statement in English indicated DSAG wanted more flexibility in the program, but was constructive on the move.

DSAG is likely to have more comment when it reviews the additional details.

Larry Dignan

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.&nbsp; <br>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… Read more

AMD reported better-than-expected fourth quarter results as its data center revenue was $3.9 billion, up 69% from a year ago doing to its GPU and server chip demand.

The chipmaker reported  fourth quarter earnings of $482 million, or 29 cents a share, on revenue of $7.66 billion, up 24% from a year ago. Non-GAAP earnings for the quarter were $1.09 a share.

Wall Street was expecting AMD to report fourth quarter non-GAAP earnings of $1.09 a share on revenue of $7.53 billion.

For the year, AMD reported earnings of $1.64 billion, or $1 a share, on revenue of $25.78 billion.

As for the outlook, AMD projected first quarter revenue of $7.1 billion, give or take $300 million. At the midpoint, AMD is projecting revenue growth of about 30% from a year ago.

AMD CEO Lisa Su said 2024 was transformative and the data center business is strong. "Data Center segment annual revenue nearly doubled as EPYC processor adoption accelerated and we delivered more than $5 billion of AMD Instinct accelerator revenue. Looking into 2025, we see clear opportunities for continued growth," said Su.

"AMD is growing in its transition phase, where datacenter is the star," said Constellation Research analyst Holger Mueller. "Overall the numbers work for Lisa Su and team, but investors expect AI turbocharged growth coming from the data center segment. AMD needs to pull off a few EPYC (pun intended) moves in 2025 before investors will be really happy."

By the numbers:

• AMD reported fourth quarter data center revenue of $3.9 billion due to "the strong ramp of AMD Instinct GPU shipments and growth in AMD EPYC CPU sales." For 2024, AMD reported data center revenue of $12.6 billion, up 94%. The data center unit drove AMD's operating income gains for the fourth quarter and year.
• Client revenue was $2.3 billion, up 58% due to strong demand for Ryzen processors. For 2024, AMD's PC chip business revenue was $7.1 billion, up 52% from a year ago.
• Gaming revenue was $563 million, down 59% from a year ago. Annual revenue for gaming was $2.6 billion.
• Embedded revenue was down 13% from a year ago in the fourth quarter at $923 million. For 2024, embedded revenue was $3.6 billion, down 33% from a year ago.

Larry Dignan

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.&nbsp; <br>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… Read more

Google Cloud revenue in the fourth quarter were $12 billion, up 30% from a year ago, amid mixed results from parent Alphabet, which said it will spend $75 billion in capital expenditures in 2025. The company also said its Google Cloud business was capacity constrained.

The company reported net income of $26.54 billion, or $2.15 a share, on revenue of $96.47 billion, up 12%. Wall Street was expecting Alphabet to report fourth quarter earnings of $2.13 a share on revenue of $96.67 billion.

For 2025, Alphabet reported earnings of $100.1 billion, or $8.04 a share, on revenue of $350.02 billion, up 14%.

• Google Cloud launches Agentspace to create, deploy agents
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• Google Workspace drops Gemini add-on charge, raises business, enterprise plan prices

Sundar Pichai, CEO of Alphabet, said:

"We are building, testing, and launching products and models faster than ever, and making significant progress in compute and driving efficiencies. In Search, advances like AI Overviews and Circle to Search are increasing user engagement. Our AI-powered Google Cloud portfolio is seeing stronger customer demand."

By the numbers:

• Google Cloud revenue in the fourth quarter was $11.95 billion, up 30% from $9.19 billion a year ago. Microsoft Azure put up quarterly revenue growth of 31%. Operating income for Google Cloud was $2.09 billion, up from $864 million in the fourth quarter a year ago.
• Google search revenue in the fourth quarter were $54.03 billion.
• Google advertising revenue was $72.46 billion.
• Google services operating income was $32.84 billion and that unit includes the Gemini team.
• Alphabet ended the quarter with 183,323 employees.

Anat Ashkenazi, Alphabet CFO, said: 

"We do see and have been seeing very strong demand for AI products in the fourth quarter in 2024. We exited the year with more demand than we had available capacity. So we are in a tight supply demand situation, working very hard to bring more capacity online. As I mentioned, we've increased investment in CapEx in 2024, continue to increase in 2025, and will bring more capacity throughout the year."

Pichai said the following on the company's earnings call:

• "Cloud customers consume more than eight times the compute capacity for training and inferencing compared to 18 months ago."
• "We are working on even better thinking models and look forward to sharing those with the developer community soon. We're also excited by the progress of our video and image generation models."
• 4.4 million developers are using Gemini models, double from six months ago.
• AI overviews are now available in more than 100 countries. Circle to Search is now available on over 200 million Android devices in cloud and YouTube.
• "Those who have tried Circle to Search before now use it to start more than 10% of their searches."
• The number of first-time commitments to Google Cloud doubled in 2024 and the company is closing more strategic deals over $1 billion and doubled the number of $250 million deals.
• Vertex AI saw a 5x increase in customers in the fourth quarter compared to a year ago.
• Waymo is averaging more than 150,000 trips each week.

Anat Ashkenazi, Alphabet CFO, said: 

"We do see and have been seeing very strong demand for AI products in the fourth quarter in 2024. We exited the year with more demand than we had available capacity. So we are in a tight supply demand situation, working very hard to bring more capacity online. As I mentioned, we've increased investment in CapEx in 2024, continue to increase in 2025, and will bring more capacity throughout the year."

Constellation Research's take

Constellation Research analyst Holger Mueller said:

"Alphabet narrowly missed revenue targets. The surprise though is that the contribution of the advertisement business did better than the its cloud business, not the expectation investors had for 2024 results. The good news is that the Alphabet core business is proving itself in the AI era – even before Google has started to infuse advertisement into its Gemini offering.

The argument can be made that the hopes of its advertisement / search business competitors (Microsoft) are not materializing, which is good for Alphabet. Sundar Pichai and team know this and are doubling down on investment – with $75 billion committed to capital expenditures in 2025, a record commitment. And despite all the investment and raising EPS earnings by almost 40%, the question for Q1 will be: How can Thomas Kurian and team get the Google Cloud growth back to expectations? Google Cloud capacity limitations were cited as core reason for the slowdown. The first half will be critical to see how well Google Cloud can help carry Alphabet into high teens / maybe even low twenties revenue growth."

Larry Dignan

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.&nbsp; <br>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… Read more

Dynatrace updated its platform as it aimed to expand AIOps into preventive operations, add to its security roster and enhance developer workflows.

The launches were outlined at Dynatrace's Perform conference in Las Vegas. Steve Tack, Chief Product Officer, said observability is set up to expand to multiple teams as AI and cloud native workloads converge along with logs and security.

"While cloud modernization is continuous and we're capturing that, it's really everything else that surrounds that, whether it's the different roles that are engaged, spanning across development teams, SREs, platform engineering and more to the types of projects and the end to end, observability and security they're looking to achieve, whether it be for new AI native workloads or more," said Tack. "Given the dynamism of the cloud, the scale, the hyper scale, or workloads, it's really changing the way teams are leveraging observability and the way they're driving it forward."

Here's a look at the announcements from Perform:

Dynatrace expanded its AIOps reach into preventive operations with enhancements to its Davis AI engine. Davis AI will be expanded into operations with the goal to prevent outages and drive returns.

Bernd Greifeneder, Dynatrace CTO and Founder, said Dynatrace with its stack has been able to combine observability, security and business level applications.

Greifeneder said Dynatrace's platform will leverage AI to combine automated root cause analysis, an automation engine and abilities to remediate automatically.

According to Dynatrace, Davis AI will get the ability to provide root cause analysis and automate remediation workflows. Davis AI will also get natural language explanations with context.

Constellation Research analyst Andy Thurai said:

"Natural language processing (NLP) interface has been a gamechanger for AIOps, enabling any incident responder to converse with observability data and try to get to the root cause of the incident, versus waiting for an experienced observability practitioner who fully understands the system to step in. When a large language model (LLM) is trained with ITOps-specific data and enhanced with enterprise-specific observability telemetry, the GenAI immediately understands the telemetry data that is fed into it and leaps into action without needing to wake up someone with the tribal knowledge for help."

• Constellation ShortListâ„¢ Observability
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• Constellation ShortListâ„¢ AIOps

Dynatrace launched Continuous Security with Cloud Security Posture Management (CSPM) for enterprises managing multi-cloud and hybrid cloud environments.

The company said Dynatrace CPSM extends existing Kubernetes Security Posture Management (KSPM) capabilities so enterprises can manage security via one dashboard. Dynatrace also enhanced its security investigator with multiple angles of analysis as well as attack vectors.

In the big picture, Dynatrace is aiming to use CPSM to provide continuous compliance and auditing. Greifeneder said Dynatrace will be able to automate about 80% of the compliance tasks.

Dynatrace launched tools to give cloud application development teams more insights.

The company added new dashboards with advanced log, metrics and trace analytics via Davis AI. The new tools will make it easy to optimize apps, monitor health and analyze interactions.

Dynatrace also launched Live Debugger, which extracts debugging information without performance impact. The company also added self-service tools for enterprise developers.

Dynatrace's outlook

The company recently reported its fiscal third quarter results with earnings of $1.19 a share on revenue of $436 million, up 19% from a year ago. Non-GAAP earnings were 37 cents a share.

Dynatrace also upped its outlook for the fourth quarter and projected revenue of $432 million to $437 million, up 13% to 15% with non-GAAP earnings of 29 cents a share to 31 cents a share.

CEO Rick McConnell said on an earnings conference call that the company is expanding the use cases for observability.

"Our conviction in the observability market continues to strengthen," said McConnell, who added that cloud adoption and AI are making observability a must have. The problem is that there are dozens of observability tools and enterprises face sprawl.

"We believe that an AI-powered observability platform with sophisticated analytic and automation capabilities is vital in providing the visibility needed for software to work perfectly," said McConnell.

Larry Dignan

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.&nbsp; <br>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… Read more

Quantinuum launched its Generative Quantum AI framework that aims to combine AI, quantum computing and supercomputers to address problems classical computing can't solve.

The launch of "Gen QAI" is designed to move quantum computing use cases toward business needs today. Many of these approaches involve hybrid strategies that blend quantum computing and supercomputing.

In January, these quantum computing use cases (and the pure play stocks) came under scrutiny after Nvidia CEO Jensen Huang said corporate value was 15 to 30 years away.

• Taking stock of quantum computing’s kerfuffle and what's next
• CxOs need to focus on quantum computing readiness, not the noise
• Practical quantum computing advances ramp up going into 2025
• Quantum computing all in on hybrid HPC with classical computing

According to Quantinuum, Gen QAI will leverage unique data generated by quantum computing to enable commercial applications ranging from medicine discovery, financial markets and supply chain optimization.

Specifically, Quantinuum's H2 quantum computer will generate data that can be used to train AI systems to enhance models. In other words, quantum computing could become the real AI factory.

In mid-2025, Quantinuum is on schedule to launch its Helios system, a more advanced quantum computer that can expand use cases.

• Quantum Computing Platforms
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• Quantum Full Stack Players

Dr. Raj Hazra, President and CEO of Quantinuum, said:

"We are at one of those moments where the hypothetical is becoming real and the breakthroughs made possible by the precision of this quantum-generated data will create transformative commercial value across countless sectors."

Merck KGaA was cited as a customer using Quantinuum's framework to generate synthetic data.

From here, Quantinuum said it will work with industry partners to expand use cases beyond GPUs. The company said it is working with HPE to utilize quantum computing in the automotive sector.

More:

• Quantinuum, Microsoft claim quantum reliability breakthrough
• Microsoft claims hybrid quantum breakthrough with Quantinuum, partners with Atom Computing
• Quantinuum raises $300 million, valued at $5 billion

Larry Dignan

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.&nbsp; <br>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… Read more

Palantir CTO Shyam Sankar said DeepSeek's latest models highlight how models are commoditizing and "the price of inference is dropping like a rock."

Speaking on Palantir's blowout fourth quarter earnings call, Sankar also said that DeepSeek also shouldn't be underestimated. Sankar said:

"One of the things I want to make sure we all do realize is that the engineering in R1 is exquisite. The optimizations that they've done are really impressive. And I don't think you can get away with the facile explanation that the Chinese just copy and we're the only innovators, we have to wake up with the respect for our adversary and realize that we are competing."

• DeepSeek: What CxOs and enterprises need to know
• GenAI prices to tank: Here’s why
• AWS, Microsoft Azure, IBM watsonx.ai add DeepSeek models via custom import
• Chinese startup DeepSeek drops a bombshell on the AI world

All of that said, Sankar went on to say that DeepSeek likely stole a good bit of that innovation.

"They absolutely did steal a lot of that through distillation of the models and perhaps they stole even more.

And then you can look at the GPU sales growth in Singapore. It's a tiny island nation. I'm pretty sure there's some sanction invasion going on there, and we have to realize that the AI race is winner-take-all and it's going to be a whole of nation effort that extends well beyond the DoD in order for us as a nation to win."

Another theme from the DeepSeek rise is that models are commoditizing and that'll have benefits for enterprises. However, enterprises should note that DeepSeek usage on the web goes to China for processing. If you download the model open source and work on it via a hyperscaler, the data stays put. We saw DeepSeek put through its paces side-by-side with other models and it appeared to need a good bit of tuning. 

Sankar said:

"I think one of the obvious lessons of DeepSeekR1 is something that we've been saying for the last two years, which is that the models are commoditizing. Yes, they're getting better across both closed and open, but they're also getting more similar and the price of inference is dropping like a rock. But I think the real lesson, the more profound one is that we are at war with China. We are in an AI arms race."

Larry Dignan

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.&nbsp; <br>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… Read more

Palantir delivered better-than-expected fourth quarter earnings, closed 32 deals worth more than $10 million, and gained enterprise momentum.

The company reported fourth quarter net income of $79 million, or 3 cents a share, on revenue of $828 million, up 36% from a year ago. Palantir's adjusted earnings in the fourth quarter were 14 cents a share. Wall Street was looking for 11 cents share on $799 million in revenue.

Palantir also delivered a rule of 40 score of 81%. Rule of 40 refers to a SaaS metric that dictates that a company's combined revenue growth rate and profit margin should equal or top 40%.

Alex Karp, CEO of Palantir, said the company said large language models are commoditizing and the value is more about data and ontology. "Our early insights surrounding the commoditization of large language models have evolved from theory to fact,” said Karp.

• DeepSeek: What CxOs and enterprises need to know
• GenAI prices to tank: Here’s why

The growth for Palantir continues to come from the US and commercial sector even though its core government revenue is also strong.

In a shareholder letter, Karp said:

"This is not an incremental advance or marginal acceleration of our business. This is a new phase. We have the products and reach of an established incumbent and the speed, growth, and agility of an insurgent startup. It is that most lethal of combinations that we have been seeking to build, and the future is now coming into sharp focus. The strength of our commercial business in the United States, in particular, continues to astound even our most ardent believers."

• Lowe's betting on AI to drive customer experience, optimize multiple processes
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By the numbers:

• US revenue in the fourth quarter was $558 million, up 52% from a year ago. US commercial revenue growth was 64% and government revenue growth was 45%.
• Palantir said it closed 129 deals of at least $1 million, 58 deals of at least $5 million, and 32 deals of at least $10 million.
• The company ended the fourth quarter with cash and equivalents of $5.2 billion.

For 2024, Palantir reported net income of $462 million, or 19 cents a share, on revenue of $2.865 billion, up 29%. The company has continued deliver strong results and land enterprises.

• Palantir Q3 strong amid strong AI demand; Karp says 'we intend to take the entire market'
• Lowe's bets on AI, technology to navigate slowing demand
• Disruption is coming for enterprise software
• Palantir to deploy platforms on Microsoft Azure
• Palantir will move workloads to Oracle Cloud as both court governments and enterprises
• Palantir Q2 shines as US enterprise growth accelerates, eyes manufacturing, ERP with Warp Speed

As for the outlook, Palantir projected revenue between $858 million and $862 million with adjusted income of operations between $354 million to $358 million. For 2025, Palantir is projecting revenue between $3.74 billion and $3.76 billion with US commercial revenue of $1.08 billion, up at least 54%. Palantir projects GAAP net income in each quarter.

Karp in his shareholder letter continues to take a victory lap.

"We have been preparing for this moment diligently for more than twenty years. A certain indifference to the doubts and opinions of others, to the shiny and fashionable thing, was absolutely required. But our patience, and what some would fairly describe as our disregard for the received wisdom, has been rewarded."

Constellation Research analyst Holger Mueller said:

"Palantir had a good quarter, and it manages to show impressive growth rates. The 'dirty secret' is though - it is growing slower than the cloud provider growth rates. Enterprises are buying compute and storage for a 'do it yourself' approach at a higher rate than Palantir can convince them to use their platform and tools. The verdict is still out for the fiscal year if this is the toolset, professional services or both."

The power of ontology

Speaking on the earnings conference call, Karp said Palantir's approach to data ontology is its secret sauce. Ontology is what allows you to manage the LLMs to be more exact at scale.

"To get the AI to actually work in an enterprise, you have to re-segment, re-concatenate the large language models in a way where the use-case is thin enough that they can actually provide exact enough information and the concatenation of that is exact enough to provide real results in an enterprise context," said Karp. "In order to be able to teach a large language model to get more exact precise information, you would have to have a secure and clean access to the underlying data of the enterprise. No other company in the world has that kind of access like Palantir."

Ryan Taylor, Chief Revenue and Legal Officer, said the proliferation of AI models means the "raw AI labor supply is exploding." Taylor added that "while everyone else is focused on the model supply side, we're transforming AI into a measurable stream of high-value finished goods and services."

Taylor added that Palantir ability to weave LLMs into their enterprise and unlock AI leverage is helping enterprises execute faster. "Most organizations are currently stuck on the wrong side of the widening chasm, working on their two, five, and 10-year plans, which become obsolete days later failing to ever take action," said Taylor.

CTO Shyam Sankar said Palantir is in a strong position to take advantage of LLM commoditization and noted "the cost per token for inference continues to drop." The emergence of DeepSeek-R1 drove the commoditization theme home.

Sankar said:

"We viewed LLMs as a new runtime for the AI labor to capture the productive value of this AI labor, you need an intermediate representation of your enterprise that AI can actually interact with.

We are convinced the normative value for AI is enterprise autonomy, the self-driving company. Users go from performing the workflow to supervising an army of agents, teaching them how to handle edge cases and reducing 12-time, this is where we are maniacally focused with our customers."

Larry Dignan

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.&nbsp; <br>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… Read more

OpenAI's launch of Deep Research, an AI agent designed to create in-depth report, is the latest launch in a bid to make the $200 a month ChatGPT Pro subscription worth it.

The launch of Deep Research, a tool that can create in-depth research complete with citations, can create a report in anywhere from 3 minutes to 30 minutes.

Deep Research, assuming it can create reports that are analyst quality, could be handy for various industries in finance, academics, science and policy. It can also be handy for purchases of high-ticket items--something OpenAI notes in its blog post.

When you couple Deep Research with OpenAI Operator, which also launched on ChatGPT Pro, the $200 per month subscription starts to look more palatable based on time, or what you'd pay for an ala carte report.

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OpenAI CEO Sam Altman noted that ChatGPT Pro isn't profitable yet, but the offering is young and frankly the company hasn't made the ROI case. Operator was a nice demo, but it's unclear whether it's worth the time savings.

However, Deep Research may make more sense to justify the subscription--even though I expect Google to do something similar soon.

Bottom line: You may not need lower level analysts anymore across multiple industries.

Assuming Deep Research can produce quality reports, the industries disrupted will be extensive. IT, Wall Street, legal, healthcare and other areas that deploy junior analysts won't need them. Can OpenAI Deep Research replace Bloomberg? How about that Gartner subscription? How about paralegals? Sell-side analysts on Wall Street? Management consultants? That promising college grad? Me?

OpenAI said:

"Deep Research was trained using end-to-end reinforcement learning on hard browsing and reasoning tasks across a range of domains. Through that training, it learned to plan and execute a multi-step trajectory to find the data it needs, backtracking and reacting to real-time information where necessary. The model is also able to browse over user uploaded files, plot and iterate on graphs using the python tool, embed both generated graphs and images from websites in its responses, and cite specific sentences or passages from its sources. As a result of this training, it reaches new highs on a number of public evaluations focused on real-world problems."

ChatGPT Pro users get access to Deep Research with a limit of 100 queries per month due to the reality that the model is "very compute intensive."

There is a rather large caveat worth noting.

"Deep research unlocks significant new capabilities, but it’s still early and has limitations. It can sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations. It may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately. At launch, there may be minor formatting errors in reports and citations, and tasks may take longer to kick off. We expect all these issues to quickly improve with more usage and time."

However, OpenAI is getting closer with ChatGPT Pro depending on quality. If you spend on research reports, the $2,400 a year subscription to ChatGPT Pro can be justified quickly.

Larry Dignan

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.&nbsp; <br>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… Read more

Earnings season for the December quarter and the January conference calls that follow are great for setting the scene for enterprise technology buying cycles for the year ahead.

Many of the major enterprises with multi-billion dollar technology budgets have reported earnings and with those calls come a pretty good read on the state of IT buying. Here’s a look at some choice quotes from the buy side of enterprise technology and how they’re thinking about AI, technology and transformation. These comments were taken from dozens of earnings calls in January.

The comments from CxOs highlight an optimistic view of AI and technology transformation as well as the benefits of automation. However, CxOs are focused on efficiency as well as financial prudence. 

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RTX (formerly Raytheon) CEO Chris Calio:

“We're innovating how we do our work as we continue to implement AI applications across RTX. Last year, we saw benefits in areas including product testing, first article inspections and RFP responses. For example, using Generative AI, Collins' avionics business has seen software testing cycle times improve by 3x, while maintaining our same quality standards. We have a plan this year to deploy another 40 use cases. Through our continued initiatives to leverage machine learning and generative technologies, we expect to improve operational speed, cycle times and capital utilization, while decreasing our dependency on external labor.”

T-Mobile President, Technology Ulf Ewaldsson:

"The whole network team has industrialized a process over the last years that gives the opportunity for us to dedicate towers, build up, upgrades, everything we do to exactly where customers need it. We're using AI to analyze thousands and millions of data points across the network on a daily basis to understand sentiments and movements in our customer base and correlate that with business outcomes, which is giving us the ability to allocate capital. I think what is really good with the network team now is that we are able to platformize the network using AI capabilities for an autonomous network model."

Starbucks CEO Brian Niccol:

"We're beginning to pilot a new in-store prioritization algorithm and are exploring other technology investments to improve order sequencing and our efficiency behind the counter. We're also progressing efforts that build on the strength and popularity of the Starbucks app. This includes development of a capacity-based time slot model that allows customers to schedule mobile orders and a midyear update that will simplify customization options, improve upfront pricing, and provide real-time price changes as customers customize beverages.”

Also: Starbucks aims for 4 minute barista to customer handoff process to boost CX

AT&T CEO John Stankey:

“In December, we established a new $3 billion plus run rate cost savings target that runs through the end of 2027. In 2025, we'll make progress on this goal by further integrating AI throughout our operations. We also expect to realize cost savings as we evolve our technology stacks and work to exit our legacy copper network operations across most of our wireline footprint by the end of 2029.

If you kind of look at our cost of service dynamics, a lot of that has been driven by AI tool application. And it's not that we're necessarily exclusively replacing individuals with the technology, but we're making them a lot more effective and efficient in how they handle customer needs and then complementing that with customer supported AI.

We’re also seeing demonstrative improvements in our code effectiveness. We're spending less right now to develop new code internally and getting more through the application generative AI.”

Capital One CEO Richard Fairbank:

“We’re investing more in technology and at the same time, getting all the benefits on the efficiency side, both in terms of growth and in terms of costs. Hopefully our investors share our excitement that this 700 basis point improvement that has happened since we began our tech transformation in 2013 has certainly been good. There are multiple things behind that, but the biggest driver is the technology transformation. Even as we invest a lot, there are also ways to create savings through reduced vendor costs, legacy technology and the benefits of the cloud to rebuild the company and how it operates.”

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Travelers CEO Alan Schnitzer:

“In 2024, our strategic tech investment approached nearly half of our overall tech spend of more than $1.5 billion. At the same time, our efforts to improve operating leverage also enable us to lower our expense ratio by more than 3 points, or about 10%. Broadly speaking, we're digitizing the value chain. That’s digitizing the customer journey. It's modernizing the foundation. It's advanced analytics. It's automation. It's faster speed to market, getting the right price on the risk, those sorts of things. At the enterprise level, we're also investing in talent and AI and third-party data, product development.”

Jane Fraser, CEO Citigroup:

“We accelerated our use of AI arming 30,000 developers with tools to write code and launched two AI platforms to make our 143,000 colleagues more efficient. The investments we're making to modernize our infrastructure, streamline processes and automate controls are changing how we run the bank.

We consolidated our balance sheet reporting to one unified ledger. We implemented a cloud-based solution for risk analytics to better value trading assets. We have closed out three longstanding consent orders.

We're all very focused on improving our operating expense base. Consolidating technology, the simplification work, automation, getting different utilities put in place rather than fragmented around the firm using AI tools.”

Mark Mason, CFO Citigroup:

“We spent $11.8 billion on technology, focused on digital innovation, new product development, client experience and other areas such as cybersecurity. We continue to reduce stranded costs, drive efficiencies across the businesses, and as benefits from investments in transformation and technology allow us to eliminate manual processes.”

United CEO Scott Kirby:

“We do have the leading digital team in the business. You can see in the app; you see in all kinds of places. And we have been, I think, done a Yeoman's effort, but really using genAI in all types of ways to be impactful for the airline and operations. One of the things that I'm most proud of is how much better we communicate with customers when there are delays to choice and explaining it in terms of they understand.

Another one of the interesting applications of genAI is that we have these old labor contracts that go back decades. And they've got all these provisions that have built up over decades. And you have people that have 25, 30 years of experience trying to interpret what the labor contracts mean in unusual situations. There’s literally a team of people that try to interpret and get those right, and they don’t always know. Amazingly, genAI can read the contract and give you a really good answer of what the output is.”

Also: Delta Air Lines completes cloud migration with focus on AI and data-driven customer experience

Rick Wurster, CEO Charles Schwab:

“In 2024, we invested in new technologies and capabilities that help our employees do their jobs more efficiently. We increased usage of Schwab Knowledge Assistant by 90% in 2024, which is our AI technology supporting the efficiency of our service professionals.

Through these efforts and others, we're able to drive down our cost per client account, which has decreased more than 25% in the last decade. On an inflation-adjusted basis, cost per account has decreased nearly 50%. This focus helps us keep costs low for our clients while also enabling us to invest in our highest priority growth opportunities.

In 2025, these critical efforts will continue. We'll invest in continued process transformation and systems modernization. We'll continue to invest in AI and other technology to help employees across the firm do their jobs more efficiently and free up expense capacity to fund our growth.”

Brian Moynihan, CEO Bank of America:

“Our digitalization and engagement expanded across all our businesses. We saw more than 14 billion logins to our digital platforms in 2024. Our Erica capability surpassed 2.5 billion interactions from its inception. And our CashPro app surpassed $1 trillion in payments made through the app in 2024. It's also worth noting that digital sales in our consumer product areas crossed 60% in the fourth quarter again.”

Morgan Stanley CFO Sharon Yeshaya:

"Self-funding investments remains a priority. In the short run, additional modernization efforts focused on decommissioning legacy technologies. This alongside business enabled innovation and process optimization with AI should support the firm's future efficiency path.

We've been investing in all of our processes and our systems in order to engage and make sure that we have a robust infrastructure in order to meet all of our growth objectives. And that has to do with everything across technology side, better understanding of our data, better, servicing our clients and the underlying infrastructure.”

UnitedHealth CTO Sandeep Dadlani:

“Our AI, digital, automation and modernization agenda has focused largely on removing administrative menial tasks in the system and improving consumer experiences. Some examples have been around our call center efforts. We received 10% less calls for the same consumer base compared to last year. And we haven't even scaled this fully. By the end of 2025, we will be scaling this fully, and that's one of hundreds of use cases that we are scaling.

As we focus in 2025, we are excited about more compelling consumer experiences, helping providers and clinicians with documentations and summaries, and digitizing all the paperwork in the entire healthcare experience--benefits documents, facilities, provider contracts and frictionless claims processing.”

Goldman CEO David Solomon:

“We are leveraging AI solutions to scale and transform our engineering capabilities, simplify and modernize our technology stack, drive productivity. These efficiencies will allow us to further invest for growth and improve client experience. This firm is zealously focused on its expense base and creating efficiencies that give us the capacity to invest in our franchise and grow our client franchise. We're going to continue to use technology to make the firm more productive. We're going to continue to scale and create automation of platforms.”

JPMorgan Chase CFO Jeremy Barnum:

“We're putting a lot of effort into improving the sort of ability of our software engineers to be productive as they do development and there's been a lot of focus on the development environment to enable them to be more productive. We also have a lot of focus on the efficiency of our hardware utilization.

We have probably reached peak modernization spend. Inside the tech teams, there's a little bit of capacity that gets freed up to focus on features and new product development.”

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