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How Dexcom leverages AI to tackle diabetes

How Dexcom leverages AI to tackle diabetes

Dexcom, which makes glucose monitoring equipment and technology, is betting that it can dramatically expand its total addressable market for people with diabetes with a big assist from generative AI.

The company historically has been best known for its monitoring devices for type 1 diabetics, which need insulin injections. With the launch of an AI-powered app and biosensor called Stelo, Dexcom is looking to expand its total addressable market by targeting prediabetics as well as consumers with type 2 diabetes that don't need insulin. Stelo doesn't require a prescription, but is often covered by insurance.

Dexcom's G7 Continuous Glucose Monitoring (CGM) System is for adults with type 1 or type 2 diabetes on insulin or medications. Health insurance usually covers G7 CGM System.

Dexcom's growth is expected to come from Stelo, which has the potential to be new category of consumer wearable device. Stelo comes in a two-pack of biosensors for $99. A one-month subscription plan that includes two Stelo biosensors delivered monthly is $89. A three-month subscription with six Stelo biosensors with refills every 3 months is $252. Stelo biosensors have a 15-day life-span are worn on the back of your upper arm and transmit data to an app available on Apple iOS or Android.

In 2024, 589 million adults aged 20 to 79 were diagnosed with diabetes globally, according to International Diabetes Federation Atlas. In the US, more than 1 in 4 US healthcare dollars are spent on people with diabetes, according to the American Diabetes Association. In 2050, 853 million adults will be diagnosed with diabetes.

Meanwhile, research has shown that continuous glucose monitoring has reduced risks for type 2 diabetes patients not on insulin therapy.

Health insurers also are on board with Dexcom's strategy as Stelo is getting broader coverage.

"As we continue to advocate for broader type 2 coverage, we have already greatly simplified access to Dexcom technology through the launch of our over-the-counter biosensor Stelo," said Dexcom CEO Kevin Sayer speaking on the company's first quarter earnings call in May. "Stelo continues to attract a wide range of new customers across the type 2 diabetes, prediabetes and health and wellness landscapes."

When Dexcom reports its second quarter earnings July 30, Wall Street will be closely watching traction for Stelo. Dexcom has been expanding sales capacity and distribution and went live with an Amazon storefront.

Girish Naganathan, CTO of Dexcom, said the company's AI strategy rolls up to a broader growth plan that features AI for product features as well as efficiency. "We start with a patient and customer first approach, and when we look at transformation plans, AI is a tool," he explained. "Technology is pervasive and we generate data that's used to solve problems and helps us bring innovation faster to patients, improve our product and deliver our solutions."

Dexcom's financial performance has been lumpy as it expands its market. Revenue growth has ranged from 3% to 25% in the last five quarters. Sayer said Dexcom is on its way to returning to growth on a steady basis as it has expanded its sales coverage and now has the largest Pharmacy Benefit Managers (PBMs) covering Stelo.

The company is projecting fiscal 2025 annual revenue of $4.6 billion. For fiscal 2024, Dexcom had to cut its outlook as products for type 1 diabetes fell short of expectations. A year ago, Dexcom shares fell 41% in one day.

Sayer said Dexcom is laying the foundation for reaccelerating revenue growth. The company has had to manage through a lot of disruption. In the first quarter, Dexcom faced supply chain disruptions when a shipment of sensors were damaged in the fourth quarter.

Dexcom CFO Jereme Sylvain said the company charted its direct flights and retooled processes to bring its supply chain back up to speed in the first quarter.

"As we continue to rebuild our inventory levels while addressing increasing demand, we have factored in an additional 100 basis point impact to our global freight costs to support expedited shipping," said Sylvain, speaking on Dexcom's first quarter earnings call in May. "We expect that this impact will lessen as we move throughout the year. We have also built into this gross margin guidance a 50 basis point impact of inflationary pressures from tariffs in the supply chain."

In addition, Dexcom is currently an FDA recall of more than 700,000 devices after as receivers may not provide audible alerts due to a manufacturing problem.

To comply with the recall, Dexcom is replacing Dexcom's G7, G6, One and One+ CGMs.

Data, AI, partnership with Google Cloud

In December 2024, Dexcom launched its generative AI platform for glucose monitoring that would combine its Stelo application with its biosensing technology.

The company also was a headliner at CES 2025 with a session on the future of health AI. Dexcom's generative AI technology is built on Google Cloud Vertex AI and Gemini models.

Naganathan said on a Google Cloud webinar that the company pivoted to focusing on glucose monitoring for diabetes 2 patients and is focused on transforming healthcare delivery.

The bet is that Dexcom can change health, patient habits and outcomes by enabling them to connect the dots between lifestyle choices and glucose outcomes. Dexcom began integrating generative AI into its products and Stelo in 2024.

"We believe that AI will play a transformative role within diabetes management and healthcare by significantly providing a more personalized experience, sharing more actionable insights and eventually empowering people to make decisions to improve their health outcomes," said Naganathan.

For Dexcom, generative AI and data insights could be a differentiator in a competitive market. Dexcom competes with Abbott Labs, Medtronic, LifeScan and others. In regulatory filings, Dexcom noted that it could compete with large publicly traded companies that operate outside of the traditional medical device sector.

Dexcom is using AI tools such as Google Cloud Vertex and Gemini models to synthesize complex data into actionable insights for healthcare providers and patients. The plan for Dexcom is to develop personalized offerings for Stelo for type 2 diabetes patients.

Going forward, Naganathan said AI is becoming more intuitive and combines voice, video, text and images. "You can envision AI in different aspects of the business in development to manufacturing to customer service," he said. "We're also seeing improvements in device performance with AI. Devices can also adapt to user behavior in real time. We see AI evolving from a tool to a true partner in tech, health and lifestyle."

The strategy and stack

Dexcom's AI and machine learning layer is fed by a data flywheel and technology stack that includes the following:

  • Dexcom's stack for continuous glucose monitoring is integrated between hardware and software.
  • Sensors. Dexcom's sensors include biomaterials, membrane systems and low-power electronics designed to track glucose.
  • Receiver and transmitters. Dexcom devices wireless transmit information from the transmitter to receivers to a compatible mobile device.
  • Dexcom Real-Time API. The Dexcom Real-Time API gives authorized third-party software developers the ability to integrate real-time CGM data into health apps and devices for permitted use cases.

Various applications including ones that share a patient's glucose data with wearable devices.

For good measure, Dexcom also has a collaboration agreement and exclusive license for patents and intellectual property with Verily Life Science, which is a unit of Alphabet, owner of Google Cloud.

The data provided by Stelo is what will drive biosensor subscriptions.

Sayer said: "The type 2 patients who are purchasing Stelo are reordering quite regularly and staying on their subscription patterns and are much more likely to sign up for subscriptions. When we have reimbursement and even just those having the experience who are paying cash, we're seeing good retention and good utilization in these populations because the information is incredibly valuable."

In addition, Naganathan said Dexcom is focused on being thoughtful with implementing AI to build trust in the long run. Naganathan said by leveraging AI and data from its devices to power Stelo, Dexcom is hoping to change patient behavior.

"Changing consumer behavior is really challenging," said Naganathan, adding that Dexcom is working to "arm users with more personalized insights based on their health and habits."

With Stelo, Dexcom said in regulatory filings that it will also pursue development partnerships with consumer technology partnerships to bring metabolic health insights to more customers.

Naganathan said Dexcom strategy with AI and its patients has the following tenets.

  • Target type 2 diabetics and Americans with prediabetic conditions.
  • Connect lifestyle choices for sleep, activity and nutrition and connect it to glucose outcomes.
  • Use insights to "nudge not judge" to encourage change.
  • Derive insights from multiple data points including sleep, food and how it connects to glucose.
  • Provide education, resources and tools to enable patients to take care of their health.
  • Provide data to healthcare providers with connections to electronic health record systems. The general idea is that glucose data over time can give primary care physicians a better view of the patient.

Naganathan said that Dexcom's AI journey started with Stelo but is expanding throughout the company's product portfolio.

Dexcom is also deriving internal benefits with AI. Naganathan said Dexcom has used genAI for automating documentation and multiple administrative activities to improve engineering processes. "AI has not only improved efficiency, but also our product development velocity," Naganathan said.

Indeed, Dexcom has been adding features to Stelo including updates for 180-day lookback feature. Sayer said Stelo's customer experience metrics are improving due to the updates. Dexcom also recently received FDA clearance for its 15-day Dexcom G7 system that will roll out later this year.

He added that Dexcom will take a step-by-step approach to adoption of AI. "We're taking a very thoughtful, step-wise approach, starting with retrospective insights and then moving eventually to real time coaching, progressively building confidence and trust as the technology matures. We're also working very closely with the regulatory bodies on this front as we add these insights," said Naganathan.

According to Naganathan, Dexcom is looking at agentic AI, but said it won't happen in one big bang. "I see it happening in sequence as the technology matures and as problems get solved in different parts of the organization," he said.

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Enterprise technology projects we’re watching in July 2025

Enterprise technology projects we’re watching in July 2025

The latest batch of enterprise technology projects we’re watching include a ransomware recovery, SAP clean core implementation, supply chain optimizations, using enterprise AI over genAI and choosing to build instead of buy.

Without further ado, here are the projects we’re watching in July.

Ingram Micro’s ransomware recovery. The company just head of the July 4th long weekend was hit with a ransomware outage. After a few days, Ingram Micro recovered. Now it’s time for those confessions to turn up in regulatory filings and Ingram Micro’s earnings report. How much revenue was derailed in July? How much did Ingram Micro pay? How much did insurance cover? Ingram Micro’s communication strategy was lacking when it was hit by the attack. Now we’ll see what the tab looks like.

Clorox’s SAP ERP upgrade. After a multi-year journey. Clorox has gone live with its upgrade to SAP S4/HANA cloud. The total tab is north of $500 million. Clorox has defended the SAP overhaul and said it encompasses process reinvention, digital transformation and an overhaul of its data infrastructure. The working theory is that now the SAP system is in place Clorox will start seeing margin improvements, AI use cases and efficiency gains.

Clorox now has a clean data core. Here’s what’s next.

  • Clorox will go live in July with order fulfillment and order management.
  • Manufacturing facilities will move to the new ERP system over the next six months.
  • The cadence is transition period for the first half of fiscal 2026 and then optimization.
  • Productivity gains will really accrue in fiscal 2027 and fiscal 2028.

Procter & Gamble’s supply chain 3.0 initiatives. P&G, like most consumer product goods companies has a lot to deal with these days. Consumers are fickle, inflation hurts and tariffs are on, off and then on again. P&G’s coping mechanism largely revolves around what it calls Supply Chain 3.0.

The company is looking at its supply chain as part of the overall value mix that is connected to everything from marketing to in-store inventory. P&G’s KPIs go like this:

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

FedEx’s supply chain efforts. FedEx is wielding its scale and data to essentially retool its network as conditions warrant. FedEx has a digital twin of its logistics network so it can model changes as manufacturing moves from China to Vietnam or when customers reroute to mitigate tariffs. To FedEx every day is a referendum on supply chains. Luckily it has data on every commodity and country.

JPMorgan Chase’s ongoing AI projects. JPMorgan Chase spends about $18 billion a year on IT so rest assured that there’s a good bit of AI. At its recent investment day, JPMorgan Chase talked about the returns on AI. The company is leveraging code assistance and LLMs designed to unlock employee productivity. But what stuck out to me is what executives were saying about the returns on regular enterprise AI . The company noted that it is continually improving its data so it is efficiently consumed by machines and as a result is getting a lot of mileage out of inexpensive AI models that aren’t necessarily genAI.

Netflix’s ad stack returns. When Netflix launched ads on its platform it initially partnered on its ad stack. It quickly decided that it needed to build its own. Netflix has rolled out its ad stack globally and is starting to see the results. "We're fully on our own stack around the world at this point. That rollout was generally smooth across all countries," said Netflix co-CEO Gregory Peters. "We see good performance metrics across all countries and the early results are in line with our expectations. Now we're in this phase of learning and improving quickly based on the fact that being live everywhere means that you get a bunch of feedback about what we can do better."

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Infosys sees good demand for AI agents

Infosys sees good demand for AI agents

Infosys CEO Salil Parekh said the company is "seeing good demand for AI agents" for vertical and horizontal use cases. Infosys is also deploying AI agents within its own business process management unit.

Speaking on Infosys' fiscal first quarter results conference call, Parekh gave some color on AI agent adoption. Services providers, which specialize in horizontal and vertical applications and connecting multiple systems and processes, have been among the more successful vendors deploying AI agents.

Parekh said:

"The main drivers of our growth were our leadership in enterprise AI and our continued success in clients selecting us for consolidation. We are seeing good demand for AI agents. We built 300 agents across business operations and IT areas. Our horizontal and vertical agents are helping our clients drive faster decisions, improve customer experience and improve operational efficiency."

The Infosys CEO didn't name specific customers, but did deliver a bevy of use cases by industry. Here are a few:

  • An oil and gas major is using Infosys AI agents to enhance production quality, orchestrate dynamic pricing in retail stores and automating contract management for trading.
  • A manufacturing company is using Infosys AI agents are being used across the supply chain to resolve issues with malfunctioning equipment.
  • In logistics, a company is using Infosys AI agents in customer care, operations and accounting.
  • A North American retailer is using AI agents to enhance in-store shopping by combining physical AI, automation and computer vision at the edge.

Jayesh Sanghrajka, CFO of Infosys, said the company is seeing customers delay spending over uncertainty, but agentic AI is becoming a priority.

For Infosys, AI agents give the company the ability to potentially consolidate accounts, land customers and make its own operations more efficient.

The company's first quarter was in line with expectations. Infosys reported first quarter earnings of $809 million, or 19 cents a share, on revenue of $4.94 billion, up 4% from a year ago.

Infosys' outlook for fiscal 2026 was cautious given its industries and economic uncertainty. The company projected revenue growth of 1% to 3% in constant currency.

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IBM Q2 strong across AI, software, infrastructure

IBM Q2 strong across AI, software, infrastructure

IBM reported strong second quarter results, a revenue pop for its infrastructure business due to its new mainframe system and a growing backlog for its AI business.

Big Blue reported second quarter earnings of $2.2 billion, or $2.31 a share, on revenue of $17 billion, up 8% from a year ago. Non-GAAP earnings were $2.80 a share.

Wall Street was looking for IBM to report non-GAAP second quarter earnings of $2.65 a share on revenue of $16.59 billion.

During the quarter, IBM outlined a bevy of quantum computing advances and the launch of its latest Power server processor.

IBM unveiled Power11, a major update to its data center CPUs, with a focus on power and easier IT management. Power11 will power a line of high-end, mid-range and entry-level servers from IBM. IBM also said Power11 will be the first to support IBM Spyre Accelerator, which is built for AI inference workloads. Big Blue added that Power11 will be able to detect a ransomware threat in less than one minute with IBM Power Cyber Vault.

In the second quarter, IBM saw a pop in its infrastructure business and strong AI demand. CEO Arvind Krishna said:

"Our generative AI book of business continues to accelerate and now stands at more than $7.5 billion. With our strong first-half performance, we are raising our full-year outlook for free cash flow, which we expect to exceed $13.5 billion."

IBM said second quarter software revenue was up 10% compared to a year ago, consulting revenue was up 3% and infrastructure was up 14%.

Key takeaways:

  • Red Hat revenue was up 16% in the second quarter.
  • Automation revenue was up 16%.
  • IBM Z revenue was up 70%.
  • Hybrid infrastructure revenue was up 21%.

As for the outlook, IBM said it expects constant currency growth to be at least 5%. IBM has benefited from a weaker US dollar.

On a conference call, Krishna said:

  • "Technology continues to serve as a key competitive advantage, allowing businesses to scale, drive efficiencies and fuel growth and we saw this play out in the quarter. While not a major factor overall, geopolitical tensions are prompting a few clients to move cautiously. US federal spending was also somewhat constrained in the first half, but we do not expect it to create long-term headwinds."
  • "HashiCorp is also off to a great start, accelerating performance in our first full quarter since closing, and seeing early wins."
  • "Infrastructure was up 11%, driven by a very strong start to z17. The new IBM Z is an embodiment of the hybrid cloud and AI capabilities we bring to clients."
  • "We are transforming our enterprise operations using technology and embedding AI across more than 70 workflows, leveraging our own IBM software solutions across hybrid cloud, automation, and AI."
  • "We’re seeing strong demand for our AI agents and assistants, RHEL AI, Granite models, as well as an accelerating need for our consulting services to deploy AI."

 

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ServiceNow posts strong Q2 as McDermott reiterates CRM ambition

ServiceNow posts strong Q2 as McDermott reiterates CRM ambition

ServiceNow handily topped expectations in the second quarter and said it is gaining traction in CRM as it expands its footprint.

The company reported second quarter net income of $385 million, or $1.84 a share, on revenue of $3.22 billion, up 22.5% from a year ago. Non-GAAP earnings were $4.09 a share.

Wall Street was looking for non-GAAP second quarter earnings of $3.57 a share on revenue of $3.12 billion.

ServiceNow also saw current remaining performance obligation growth of 24.5% in the second quarter compared to a year ago.

CEO Bill McDermott said the company delivered across all metrics and saw traction in CRM.

In the second quarter, ServiceNow had 89 transactions of more than $1 million in annual contract value and ended the quarter with more than 528 customers with more than $5 million in ACV.

As for the outlook, ServiceNow projected subscription revenue growth between 20% and 20.5% in the third quarter. For 2025, ServiceNow projected revenue growth of 20%.

On a conference call with analysts, McDermott said:

  • "Enterprises in every industry and every region of the world have AI transformation as priority number one, I see budgets are highly resilient and increasingly focused on strategic, mission critical AI."
  • "We run the real risk of a new generation of teams, this time with AI agents scattered around like spare parts. We have no intention, ladies and gentlemen, of allowing that to happen."
  • ServiceNow is focusing on deploying its engineering teams to get customers live quickly.
  • Data Fabric was included in 17 of ServiceNow's top 20 largest deals.
  • "All of our workflows are growing, especially CRM front office workflows. The CRM opportunity for ServiceNow could render traditional CRM obsolete. We secured several notable wins with strong momentum."

Separately, ServiceNow said it launched an extension to its AI agent orchestration platform so enterprises can better manage digital workers. The extension aims to enable AI agents to learn from past experiences, curtail sprawl and optimize processes and provisioning.

In addition, ServiceNow said it would partner with CapZone Impact Investments to develop a national network of digital tools for manufacturing facilities.

 

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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

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."

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OpenAI takes stab at gauging productivity gains, AI economic impact

OpenAI takes stab at gauging productivity gains, AI economic impact

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?

More:

 

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SAP delivers 24% cloud revenue growth in Q2

SAP delivers 24% cloud revenue growth in Q2

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."

 

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

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

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.

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."

 

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

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

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.

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