| Constellation Research

Google Cloud tops $50 billion annual revenue run rate in Q2

Editor in Chief of Constellation Insights
Constellation Research

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

Google Cloud revenue in the second quarter surged 32% to $13.6 billion as Alphabet parent of Google, delivered better-than-expected results.

Alphabet reported second quarter earnings of $2.31 a share on revenue of $96.4 billion, up 14% from a year ago. The company said it saw strong growth across YouTube, Google Cloud, search and subscriptions.

Wall Street was looking for Alphabet to report non-GAAP earnings of $2.19 a share on revenue of $93.96 billion.

CEO Sundar Pichai said the second quarter was a "standout" that was fueled across its unit.

Referring to Google Cloud specifically, Pichai said the company had "strong growth in revenues, backlog and profitability. Its annual revenue run-rate is now more than $50 billion."

Pichai added that it will spend more on building out its Google cloud infrastructure with capital expenditures of $85 billion in 2025.

As expected, Google Services delivered most of Alphabet's operating income with $33.06 billion on revenue of $82.5 billion. Google Cloud operating income was $2.83 billion.

Pichai said on the earnings conference call:

"Nearly all Gen AI unicorns use Google Cloud, and it's why a growing number including leading AI research labs use TPU specifically."
"Our AI infrastructure investments are crucial to meeting the growth and demand from Google Cloud customers."
"Our 2.5 models have been a catalyst for growth, and 9 million developers have now built with Gemini."
"The number of Google Cloud deals worth more than $250 million doubled year over year."
"We also saw strong growth in the use of multimodal search, particularly the combination of Lens of Circle and Research together with AI overviews. This growth was most pronounced among younger users our new end to end AI search experience. AI mode continues to receive very positive feedback, particularly for longer and more complex questions. It's still rolling out, but already has over 100 million monthly active users in the US and India."

Constellation Research analyst Holger Mueller said:

"Google Cloud is doing well as it looks like enterprises are finally understanding that Google has a 3- to 4-year lead when it comes to putting custom algorithm (Tensorflow) on custom hardware (TPUs). It now has also a 1+ year lead for operating multimodal models. All that results in better and cheaper AI, a powerful formula that seems to be turbocharging Google Cloud."

Data to Decisions Google Chief Information Officer

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OpenAI takes stab at gauging productivity gains, AI economic impact

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

OpenAI plans to measure productivity gains for ChatGPT over the 12 months via the company's economic research team and academic partners.

The research from OpenAI is worth noting. Anthropic has a similar group and recently outlined its use popular use cases and economic impact.

Technology vendors have historically produced research to argue that they boost productivity. Whether it's AI PCs, productivity software or enterprise systems, these research efforts all have some element of marketing involved.

That said, OpenAI has scale--more than 2.5 billion messages per day globally--and insights into use cases. There's also something to be said for collecting data since AI is going to cost jobs over time.

OpenAI's first research volley on economic productivity has a bevy of use cases and stats worth pondering. Here are a few data points:

Learning and upskilling is the most popular use case with 20% of usage.
18% of ChatGPT use cases revolve around writing and communication.
7% of ChatGPT usages is programming, data science and math.
Design & creative ideation is 5%.
24% of US ChatGPT users are between the ages of 18 and 24 with 32% between 25 and 34.
Among OpenAI's enterprise customers 20% are in finance and insurance, followed by 9% in manufacturing and 6% in education services.
OpenAI's o1 model increased lawyers' productivity between 34% to 140% across six workflows.

The upshot to OpenAI's first missive is that time savings across multiple industries is valuable. Most of the value today is eliminating the need to hire another human.

Although the data is worth noting, AI usage will need to be tied to more business metrics and economic impact. The big looming question is this: Will AI's benefits be outweighed by likely job losses and downstream effects?

Data to Decisions Future of Work Innovation & Product-led Growth Tech Optimization Next-Generation Customer Experience Digital Safety, Privacy & Cybersecurity openai ML Machine Learning LLMs Agentic AI Generative AI Robotics AI Analytics Automation Quantum Computing Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain Leadership VR Chief Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

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SAP delivers 24% cloud revenue growth in Q2

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

SAP said its cloud revenue in the second quarter was up 24% with total revenue up 9%.

The company reported second quarter net profit of €2.46 billion, or €1.45 a share, on revenue of €9.03 billion, up 9% from a year ago. A weaker US dollar was a currency headwind in the quarter. Adjusted earnings were €1.50 a share.

Cloud ERP revenue in the second quarter was €4.42 billion, up 20% from a year ago.

As for the outlook, SAP laid out the following:

Cloud revenue at constant currency of €21.6 billion to €21.9 billion, up 26% to 28%.
Cloud and software revenue of €33.1 billion to €33.6 billion, up 11% to 13%.
The company also said its current cloud backlog growth in constant currencies will slightly decelerate in 2025. In the second quarter, current cloud backlog was €18.05 billion, up 22% from a year ago.

CEO Christian Klein touted SAP's efforts with its Joule AI agent and SAP Business Data Cloud. CFO Dominik Asam said:

"Our performance was supported by continued customer demand and disciplined cost control. As we move into the second half, we remain cautiously optimistic, keeping a close eye on geopolitical developments and public sector trends."

Constellation Research analyst Holger Mueller said:

"SAP had a good quarter, and manages to grow - albeit nominally. The expected reductions in cloud backlog means SAP is seeing customers go live on the cloud and expanding capacity. The cloud revenue slowdown maybe part of the seasonality where Q1s are strong and the second and third quarters are affected by vacations in Europe. Interesting to see Spain having an outstanding quarter."

Key takeaways from SAP's earnings call from Klein:

SAP is including Business Data Cloud in deals with Adobe and BAE Systems as wins. Klein added that SAP "is deepening our partnership with Palantir in the context of Business Data Cloud."
"The debate on digital sovereignty and the best way to achieve it has picked up speed in recent weeks. SAP stands out as the only vendor that can offer sovereignty over the entire stack, from the infrastructure to the application. Our platform runs on any hyperscaler and many local providers, but we also operate data centers of our own across the world. Our unique capabilities ensure that customers stay in control of their data at all times. They can be sure, regardless of how their local sovereignty requirements evolve, we will be able to meet them."
"By the end of the year, we expect the total number of available AI agents to reach 40. The agents will work across business functions."
"SAP also uses business AI internally to boost productivity. This is reflected in the solid expansion of our operating profit. We are decoupling expenses from revenue growth thanks to our transformation program."
"Uncertainty in global markets from earlier this year remains. A few individual industries have been impacted by uncertainty, and we are seeing extended approval workflows on the customer side in the US public sector and among manufacturers affected by tariffs. Whatever the market environment may bring, SAP is really well prepared."

Data to Decisions Next-Generation Customer Experience Chief Information Officer

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GM's Q2: A look at the technology, AI takeaways

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

General Motors said it is expanding its software services revenue, adding AI talent and honing its development practices to bring down warranty costs.

The auto giant reported second quarter earnings of $1.89 billion, or $1.91 a share, on revenue of $47.12 billion, down nearly 2% from a year ago.

Here are some of the enterprise technology and AI takeaways from GM CEO Mary Barra and CFO Paul Jacobson.

Customer experiences via OnStar, Super Cruise and software services. Barra said GM has begun pricing vehicles to include a period of basic OnStar services. The move has increased subscriptions giving GM "even more ways to engage directly with our customers through the life of the vehicle," said Barra.

So far, GM has booked $4 billion in deferred revenue from software services. Super Cruise revenue is projected to top more than $200 million in 2025.

GM builds its data factory, eyes genAI

Investing in AI talent. GM's Barra said the addition of Sterling Anderson as chief product officer highlights the company's AI talent investment. Anderson was chief product officer from Aurora, an autonomous trucking company.

"We are also embracing AI across the enterprise, which is why we recruited Google and Cisco veteran, Barak Turovsky to lead our efforts under Apple veteran, Dave Richardson, who leads software and services engineering," said Barra.

The company is looking to AI to improve vehicle performance, customer experience and operations. GM has also partnered with Nvidia to build digital twins, robotics platforms and virtual testing tools.

Using over-the-air updates to bring down warranty claims. Jabobson said GM's higher warranty claims over software issues in electronic vehicles resulted in higher warranty claims. The company is also shifting some supply of components to improve quality.

"Our expanded use of over-the-air updates, lower number of incidents per vehicle and increased robustness in our infotainment system updates are all contributing to this improvement," said Jacobson. "Additionally, we are leveraging our enhanced diagnostics in developing new prognostic tools to identify issues sooner, develop repair procedures faster and minimize unnecessary repairs."

Data to Decisions Future of Work Next-Generation Customer Experience Chief Information Officer

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Udemy launches MCP server, aims to embed learning content into workflows

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Udemy is betting that learning content will be better utilized when integrated into workflows and AI-driven applications.

The company said it will launch a Model Context Protocol (MCP) server that's designed to give enterprises the ability to embed personalized learning into work tools.

According to Udemy, education content can be embedded into AI tools such as OpenAI's ChatGPT, Anthropic's Claude, Perplexity and Cursor.

Udemy's approach is worth noting given that enterprise training and upskilling programs are generally disjointed and segmented from day-to-day work. It wouldn't be surprising if Coursera, which offers business training courses, and Accenture, which acquired Udacity, Ascendient Learning and TalentSprint to build out its LearnVantage platform, launch MCP servers to embed into productivity tools.

Udemy MCP Server will include the following:

On-demand support via micro-courses and curated lessons.
Integration with pre-built MCP connectors for existing AI tools.
Content matching tools to embed learning content into coding environments and CRM systems.
Contextualization by role and business priorities.

The company said Udemy MCP Server will launch in August with Udemy Business customers and partners getting early access.

Data to Decisions Future of Work Chief Information Officer

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OpenAI's CEO of Applications pens intro missive: 5 takeaways

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Fidji Simo, incoming CEO of Applications at OpenAI and Instacart CEO, penned her first missive and laid out an optimistic vision for AI.

Describing herself as a "pragmatic technologist", Simo said OpenAI has to get AI right so that it benefits as many people as possible. "Every major technology shift can expand access to power—the power to make better decisions, shape the world around us, and control our own destiny in new ways. But it can also further concentrate wealth and power in the hands of a few—usually people who already have money, credentials, and connections," said Simo.

She added that OpenAI has to be intentional about how it builds and shares its AI. Here are the takeaways from Simo's introductory memo.

Simo believes in OpenAI's potential. Yes, there's an AI hiring spree going on, but the most interesting item in Simo's hiring is this: Simo is a CEO of a publicly listed company that has a lot of runway ahead and has decided to leave to ride shotgun to an entrenched CEO. There aren't many executives that would make that move. Simo technically is CEO of Applications, but Sam Altman leads the charge.

The vision aligns with OpenAI's verticals. AI can change healthcare outcomes. AI can democratize education. It's not surprising that OpenAI is playing in those same areas.

Simo is likely to be a good buffer between OpenAI, Altman and sometimes tone deaf nerds. Simo's memo noted that she hired a tutor for biology and genetics and has a business coach. Humility and AI tech bros typically aren't mentioned in the same sentence. Before becoming CEO of Instacart, Simo was Vice President and Head of Facebook and also founded the Metrodora Institute, a multidisciplinary medical clinic and research foundation dedicated to the care and cure of neuroimmune axis disorders.

OpenAI is aiming to be a mass market AI coach that can be used for knowledge, health, creative expression, economic freedom, time and support.

A roadmap for applications will emerge to address those broad themes outlined in Simo's memo. As LLM capabilities all converge to be good enough, it'll be critical to create applications and ecosystems for staying power. Simo's job will be to develop OpenAI apps that can compete with frenemy Microsoft, Google and a bevy of others across the consumer and enterprise markets.

Data to Decisions Future of Work Innovation & Product-led Growth Next-Generation Customer Experience Chief Executive Officer

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Verizon bets on AI experiences, Google Cloud to bring down churn

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Verizon has rolled out AI customer experiences and is betting that the move will win accounts in a hotly contested wireless services market. The company announced a partnership with Google Cloud in April to deliver AI experiences with Gemini models and Verizon went live June 24.

Hans Vestberg, CEO of Verizon, said the company was leveraging AI to make customer experiences "simpler, faster and more rewarding." The June rollout includes a personalized expert for complex issues using Google Cloud and Gemini. A new Customer Champion will make sure issues are resolved.

Verizon also launched 24/7 live support and infused the new My Verizon app with an AI-powered Verizon Assistant and Savings Boost.

When Verizon announced better-than-expected second quarter earnings, Vestberg and CFO Anthony Skiadas were asked about returns on those Google Cloud investments.

"The wireless market remains competitive, and we continue to take a strategic and segmented approach, maintaining our financial discipline," said Vestberg. "As expected, postpaid phone churn remained elevated this quarter, reflecting the lingering effects of our pricing actions and ongoing pressure from federal government accounts. We're actively focused on improving retention by strengthening our value propositions, and leveraging our AI-powered customer experience innovations."

In the second quarter, consumer wireless retail postpaid churn was 1.12% and wireless churn overall was 0.90%. A year ago, retail postpaid phone churn was 0.85%. A year ago, Verizon didn't split out its metrics for business and consumer. Verizon reported adjusted earnings of $1.22 a share on revenue of $34.5 billion, up 5.2%, in the second quarter.

Vestberg said Verizon has seen upgrades down in year-over-year comparisons for 8 out of the last 9 quarters. Verizon did see an uptick in the second quarter and it is combining customer wireless plans with fixed wireless access and fiber broadband. Fixed wireless access accounts now have topped the 5 million subscriber mark.

Skiadas said Verizon is focused on keeping customers and courting new ones while preserving profits. "Volume growth is only valuable when aligned with our disciplined financial framework," he said. "We have taken a series of actions to address our elevated churn. On June 24, we launched initiatives designed to improve the customer experience, including leveraging AI for more personalized support. In addition, we continue to enhance our value proposition and build customer loyalty through the best value guarantee. We provide exclusive access to the best events and experiences and our refresh app helps customers maximize the value of their plans."

Vestberg emphasized that Verizon isn't going to sacrifice financials to acquire customers. He added that Verizon will turn up promotions when there are opportunities to acquire high-quality customers and let others go. With churn, Vestberg said he is optimistic about AI-driven experiences and "very encouraged about what the team is doing and how they are working on the loyalty and retention of our customers."

Verizon was also clear that retaining customers was paramount. Vestberg noted the following:

AI tools are critical, but Verizon has also retooled customer care processes. "When it comes to the process, we now will have a customer care employees following any request or a complaint from our customers all the way. So we actually finish it out with the same person starting and ending and also having uptake," said Vestberg.
24/7 customer service is also enabled by AI. "We're giving our customer care employees, an AI tool, so they can treat our customer better and know their problems better because this could be stressful," he said.
Stores matter. Vestberg said 93% of the population in the US has a Verizon store within 30 minutes.

Data to Decisions Future of Work Next-Generation Customer Experience Chief Information Officer

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The rise of good enough LLMs

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Large language models (LLMs) have reached the phase where advances are incremental as they quickly become commodities. Simply put, it's the age of good enough LLMs where the innovation will come from orchestrating them and customizing them for use cases.

This development is great for enterprises, which will be able to buy perfectly serviceable private label, rightsized and optimized models without worrying about falling behind in 10 minutes. Foundation models are reaching the point where for some use cases there won't be much improvement with upgrades. Do you really care if a new LLM is 0.06% better in math or reasoning relative to another you plan to use in the call center on the cheap?

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Use cases for documentation, summarization, extracting information and spinning up content aren't going to see big improvements with model advances. In other words, thousands of enterprise use cases can leverage generic LLMs. The model giants are almost confirming that they’ve hit the wall since they’re competing on personality, snark and faux empathy in LLMs.

The enterprise value is going to be delivered by the orchestration, frameworks and architecture that mix and match LLMs based on specialties.

Here's a look at some developments that point to the age of incremental for LLMs.

Zoho launches Zia LLM, which is essentially a disruptive private label LLM family. Zoho is a company that makes you really question your SaaS bill. And now Zoho is infusing its platform with its Zia LLM, AI agents and orchestration tools. Zoho said by controlling its own LLM layer it can optimize use cases, control costs and pass along savings to customers.

Raju Vegesna, Chief Evangelist at Zoho, said the company isn't initially charging for its LLM or agents until it has a better view of usage and operational costs. "If there a big operational resource needed for intensive tasks we may price it, but for now we don't know what it looks like so we're not charging for anything," he said.

Just like consumers are going to private label brands to better control costs, enterprises are going to do the same. The path of least resistance for Zoho customers will be to leverage Zia LLMs.

Amazon Web Services launches customization tools for its Nova models. Nova is a family of AWS in-house LLMs. I overheard one analyst nearly taunt AWS for having models that don't make headlines. That snark misses the point if Nova offers good enough performance, commoditizes that LLM layer and controls costs.

The Nova news was part of AWS Summit New York that focused on fundamentals, architecture and meeting enterprise customers where they are. As most of us know, the enterprise adoption curve is significantly slower than the vendor hype cycle.

AWS said Nova has 10,000 customers and the cloud provider plans to land more with optimization recipes, model distillation and customization tools to balance price and performance. Nova will also get customization on-demand pricing for inference.

With those two private label moves out of the way there's are developments out of China and Japan worth noting.

Moonshot AI, a Chinese AI startup backed by Alibaba, launched Kimi K2, a mixture of experts model that features 1 trillion total parameters and 32 billion activated parameters in a mixture-of-experts architecture. Moonshot AI is offering a foundation model for researchers and developers and a tuned version optimized for chat and AI agents.

Kimi K2 is outperforming Anthropic and OpenAI models in some benchmarks and beating DeepSeek-V3. The real kicker is that Moonshot is delivering models that cost a fraction of what US proprietary models for training and inference.

Research from Japanese AI lab Sakana AI indicates that enterprises may want to start thinking of large language models (LLMs) as ensemble casts that can combine knowledge and reasoning to complete tasks.

Sakana AI in a research paper outlined a method called Multi-LLM AB-MCTS (Adaptive Branching Monte Carlo Tree Search) that uses a collection of LLMs to cooperate, perform trial-and-error and leverage strengths to solve complex problems.

Add it up but the new age of incremental for LLMs is why I’m wary of the gap between AI euphoria and enterprise value. It’s not a slam dunk that buying the latest Nvidia GPUs, paying $100 million to AI researchers to create super teams and building massive data centers is going to yield the breakthroughs being pitched.

It appears that LLM giants know where the game is headed as they build ecosystems and complementary applications around their foundation models. For instance, Anthropic is best known for its Claude large language model (LLM), but its enterprise software ambitions are clear as the company builds out its go-to-market team. OpenAI is focusing on ChatGPT advances for headlines, but the big picture is more about AI agents.

Data to Decisions Future of Work Chief Information Officer

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Systems integrators look to AI agents as transformation, reinvention engine

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Systems integrators and services companies are launching AI agents, releasing frameworks and trying to help enterprises build multi-agent systems. The big question is whether AI agents turn out to be a boon or a bust for systems integrators in the long run.

In recent days, we've heard from multiple systems integrators with more on tap talk about agentic AI. The extension of integrators into agentic AI makes sense given that they have the expertise to work across systems and processes. Consider:

Kyndryl, a services provider focused more on infrastructure, released the Kyndryl Agentic AI Framework, which orchestrates and dispatches AI agents that respond to shifting conditions. The framework is a way for Kyndryl to move up the stack to higher level offerings because it moves the integrator beyond infrastructure to workflows and processes.

According to Kyndryl, its Agentic AI Framework leverages algorithms, self-learning, optimizations and AI agents to run applications and processes.

Wipro said on its first quarter earnings call that enterprises are shifting discretionary funds to data and AI modernization. "AI is no longer a niche. It's becoming essential to how businesses operate at scale," said Wipro CEO Srinivas Pallia.

He added:

"Our AI capabilities are integrated into both industry and cross-industry solutions. By combining domain expertise with AI, we are able to deliver value through solutions such as hyper-personalized wealth management and predictive industrial insights. We have deployed over 200 AI-powered agents using advanced technologies from leading hyperscalers. These agents enables smarter lending, intelligent claims processing and autonomous network management."

At AWS Summit New York, there were multiple partners talking about the foundation needed for AI and agentic AI adoption. Deloitte's Chris Jangareddy, Managing Director of the company's AI, GenAI and Data Engineering, said the company will have nearly 180 agents on AWS Agent Marketplace.

According to Jangareddy, these agents are aimed at business problems, processes and specific tasks. Deloitte's AI agents are designed to be reusable Lego locks that will ultimately make up multi-agent systems. One offering is AI Advantage for CFOs that serve as a digital twin for CFOs, he said. The agents are built on Deloitte's institutional knowledge base of queries that are now prompts.

"These are not licensed, but are for clients," said Jangareddy, who noted that Deloitte is looking to transform its model from traditional billing to an outcome-based approach.

In a demo, Deloitte outlined Zora AI, which is part of an effort to produce AI agents that are product offerings. Deloitte views AI agents as digital labor that focuses on executing on processes. Zora AI is also integrated with SAP Joule.

AWS’ Brian Bohan, Director, Global Lead, Consulting Partner Center of Excellence, said during a talk that companies automating multiple business processes with agentic AI are seeing 30% to 40% productivity gains. He expects more efficiency to be unlocked.

Why? The cost of models is falling as are training and inference expenses. However, many AI projects aren't scaling due to a lack of architecture, data infrastructure and expertise. "There's just the complexity of integration," said Bohan.

Bohan added that change management, workflow optimization and the pace of innovation are all challenges. Enterprises will get to multi-agent systems across functions like finance, procurement and supply chain.

It's clear that systems integrators see AI agents as a booming business as well as a way to transform their businesses. The flip side of this transformation is that AI agents may ultimately hamper the systems integrator model.

Constellation Research analyst Holger Mueller said:

"As with any new technology, enterprises are looking at system integrators for help adopting them and AI is no difference here. The question is whether AI is so strategic that enterprises need AI skills inhouse, or can they rely on the integrator model. The experience depth is low for anyone as no one has more than two years in genAI experiences. Or more than 10 projects. It is likely going to be strategic for enterprises to have their own AI capacity and competency, especially once we move to inter-enterprise agents and the uptime and capability of frontline and backend agents determine success."

Data to Decisions Future of Work Innovation & Product-led Growth Next-Generation Customer Experience Tech Optimization Digital Safety, Privacy & Cybersecurity ML Machine Learning LLMs Agentic AI Generative AI Robotics AI Analytics Automation Quantum Computing Cloud Digital Transformation Disruptive Technology Enterprise IT Enterprise Acceleration Enterprise Software Next Gen Apps IoT Blockchain Leadership VR Chief Information Officer Chief Executive Officer Chief Technology Officer Chief AI Officer Chief Data Officer Chief Analytics Officer Chief Information Security Officer Chief Product Officer

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Delta starting to scale its AI-driven dynamic pricing system

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Delta Air Lines is pricing about 3% of its domestic fares with an artificial intelligence system and plans to get to 20% by the end of 2025.

Speaking on Delta second quarter earnings conference call, Delta President Glen Hauenstein gave an update on the company's plan to leverage AI-driven dynamic pricing.

In January, Delta outlined its AI plans and pricing initiatives with Fetcherr, an Israeli startup that uses generative AI to create optimized offers.

Hauenstein said:

"We're optimizing revenue through our partnership with Fetcherr, leveraging AI-enhanced pricing solutions. While we are still in the test phase, results are encouraging. You have to train these models and give them multiple opportunities to provide different results. We like what we see and we're continuing to roll it out, but we're going to take our time and make sure that the rollout is successful."

Hauenstein added that the more data and cases Delta feeds to Fetcherr, the more it learns and optimizes offers. If Delta gets to the 20% mark, it should be able to scale dynamic pricing at a faster clip.

On its conference call, Delta emphasized that it continues to roll out its technology including Delta Concierge, a virtual personal assistant built into the Fly Delta app launching later this year.

Delta is also using AI to optimize maintenance and resource availability.

But the biggest wins appear to be revenue optimization via partnerships with Fetcherr. In the second quarter, Delta operating revenue was up about 1% from a year ago to $15.5 billion. Hauenstein said demand stabilized late in the second quarter and business travel was solid. "During the quarter, demand trends stabilized at levels that are flat to last year. Our teams did a great job optimizing revenue performance in this environment by leveraging Delta's structural advantages and engaging customers beyond flight to generate a revenue premium to the rest of the industry," he said. "Diverse, high-margin revenue streams continue to show resilience, growing mid-single digits year-over-year and driving double-digit operating margins. Premium revenue grew 5% over the prior year, outpacing main cabin."

The plan for Delta is to expand profit margins on multiple fronts. The company restored its financial guidance that it cut in the first quarter with earnings of $5.25 a share to $6.25 a share and free cash flow of $3 billion to $4 billion.

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Google Cloud tops $50 billion annual revenue run rate in Q2

Google Cloud tops $50 billion annual revenue run rate in Q2

OpenAI takes stab at gauging productivity gains, AI economic impact

OpenAI takes stab at gauging productivity gains, AI economic impact

SAP delivers 24% cloud revenue growth in Q2

SAP delivers 24% cloud revenue growth in Q2

GM's Q2: A look at the technology, AI takeaways

GM's Q2: A look at the technology, AI takeaways

Udemy launches MCP server, aims to embed learning content into workflows

Udemy launches MCP server, aims to embed learning content into workflows

OpenAI's CEO of Applications pens intro missive: 5 takeaways

OpenAI's CEO of Applications pens intro missive: 5 takeaways

Verizon bets on AI experiences, Google Cloud to bring down churn

Verizon bets on AI experiences, Google Cloud to bring down churn

The rise of good enough LLMs

The rise of good enough LLMs

Systems integrators look to AI agents as transformation, reinvention engine

Systems integrators look to AI agents as transformation, reinvention engine

Delta starting to scale its AI-driven dynamic pricing system

Delta starting to scale its AI-driven dynamic pricing system

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Google Cloud tops $50 billion annual revenue run rate in Q2

OpenAI takes stab at gauging productivity gains, AI economic impact

SAP delivers 24% cloud revenue growth in Q2

GM's Q2: A look at the technology, AI takeaways

Udemy launches MCP server, aims to embed learning content into workflows

OpenAI's CEO of Applications pens intro missive: 5 takeaways

Verizon bets on AI experiences, Google Cloud to bring down churn

The rise of good enough LLMs

Systems integrators look to AI agents as transformation, reinvention engine

Delta starting to scale its AI-driven dynamic pricing system