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

Larry Dignan

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. ...

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Starbucks is leaning in on process improvement for mobile orders, optimization and technology to get wait times down to 4 minutes in most of its cafes, said CEO Brian Niccol.

Niccol, who joined the company from Chipotle and outlined Back to Starbucks plan to reinvigorate the brand and sales, talked process on the company's first quarter earnings call. The efforts at Starbucks are worth watching given that they reside at the intersection of process, customer and employee experience and omnichannel retail.

• Starbucks lands new CEO from Chipotle: Here’s how digital strategy could change
• Starbucks: ‘We can enhance our tech stack to lower costs and reinvest’

Starbucks said the company is investing in labor, marketing, technology and stores to stabilize the business and revamping support teams to execute on its Back to Starbucks plan

Speaking on a conference call, Niccol said:

"The handoff from our barista to the customer is our brand moment of truth, and we've been working hard to get that moment right. Through the quarter, we've continued to test and learn as we position the business to achieve our four-minute throughput goal with a moment of connection."

Niccol added that order sequencing is everything and has created more of a bottleneck than capacity. "Investments in staffing and deployment, processes and algorithm technology demonstrate the greatest opportunity to deliver a four-minute wait time in most of our cafes," he said.

To improve the process, Starbucks is:

• Optimizing labor with precision scheduling and adding coverage hours.
• Simplifying beverage builds with new brewed coffee and tea routines.
• Improve processes in-store and via mobile ordering. Starbucks is reducing its menu selections by 30% in both food and beverages.
• Starbucks also optimized its supply chain to fund further investments.
• Creating a Chief Store Officer role to "be all about driving excellence in our stores."
• Betting that improvements in the partner experience boosts customer experience.

Niccol said:

"Looking forward, 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.

Lastly, we're planning to fully deploy digital menu boards in cafes across our US company-owned stores over the next 18 months to make our offerings more easily understood and to better show customization add-ons."

The working theory is that Starbucks can improve the customer experience, simplify and drive repeat business.

Niccol added that it's still early in the process. Starbucks’ earnings in the first quarter met expectations, but indicate the company has a lot more work to do.

Starbucks first quarter revenue was $9.4 billion, flat compared to a year ago. US same store sales fell 4% in the first quarter, but showed improvement through the quarter. Ticket growth in the US was up 4% and Starbucks curbed discounting.

DeepSeek: What CxOs and enterprises need to know

Larry Dignan

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. ...

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DeepSeek has become an overnight sensation, rattled the US AI sector and may have single-handedly focused CxOs on cost of genAI.

We convened a call of Constellation Research analysts to outline the issues CxOs need to know about when it comes to DeepSeek.

Here are some recent headlines what you need to know about DeepSeek.

• AWS: DeepSeek models available in Amazon Bedrock via custom import, IBM adds DeepSeek to watstonx.ai
• GenAI prices to tank: Here’s why
• Chinese startup DeepSeek drops a bombshell on the AI world
• Ray Wang on the AI war, the freakout, and big tech valuations and disruption.

What is DeepSeek?

DeepSeek is a Chinese AI company that develops open-source large language models. It has launched a series of models that can compete with the likes of OpenAI's ChatGPT, Anthropic's Claude family of models and Meta's Llama. Constellation Research CEO Ray Wang said DeepSeek has "democratized the access to AI." Wang noted that the other benefit is that the model can run in private environments without top-of-the-line hardware. DeepSeek is censored as anyone who has asked the service about Winnie the Pooh or other sensitive topics in China.

What's the big deal about DeepSeek?

The hubbub surrounding DeepSeek in a nutshell is that the company "proved a point that you don't need gazillion dollars to train AI model," said Constellation Research analyst Andy Thurai.

DeepSeek has "proven not only that you can find cheap but also the fact that you can open source the entire thing, which means others can start using it or building it, which is going to challenge all those big guys," said Thurai.

DeepSeek also garnered a lot of attention because Wall Street decided a week after its latest model release that perhaps Nvidia customers didn't need the latest and greatest GPUs.

What did DeepSeek do that was different?

Holger Mueller, analyst at Constellation Research, said:

"Not having the best computing resource always makes for better models and software. China doesn't have availability of so many GPUs and people get creative. The distillation really worked. The second really important thing is that DeepSeek has been training about human intervention."

What's unclear is how much DeepSeek piggybacked off of larger models and IP from around the globe. "It's going to be interesting to see what kind of IP battle is going to unfold," said Thurai.

What should CXOs do?

For now, it's best to monitor DeepSeek, think through use cases and if you experiment make sure it's air gapped and sandboxed. Don't ignore the DeepSeek developments though. Constellation Research analyst Chirag Mehta said:

"If you're a CxO, the best analogy is what open source did to the industry. That's what this model is now doing to its competitors.

If you're a CxO, you have two options: Buy the Ferrari in the high-end platform as a service model or do smaller, specialized, narrow models that are cheaper to run, and almost free. Open source is not quite free. You still have to manage it, and you still have to run it, and you have to maintain it."

Mehta said CxOs need to keep their model options open and stay focused on what problem you're trying to solve with genAI.

Wang said focus on the cost curve. Wang said:

"At this point, we know that it's possible to do reasoning at a lower cost and lighter models are going to be available. We know that people are going to want to do this outside of the cloud and back on premises. The cost curve is coming down on AI, and I think you're going to see more of that. And I think those monetization models are important."

Will DeepSeek mean on-premises AI?

The jury is decidedly mixed on this one. Holger Mueller said AI workloads will reside in the cloud for the most part. "I see still larger models winning and cloud winning. If you might see a dip in revenue. That's totally possible," said Mueller.

Mehta noted that on-prem vs. cloud AI isn't zero sum, but the majority of workloads will go to the cloud with the exception of edge computing use cases.

Should Wall Street be this concerned about DeepSeek?

Thurai said concerns are overblown. If you are building an LLM or using one for inferencing you're still likely to use a Nvidia stack. Where it gets interesting is if DeepSeek used AMD GPUs. "This is a knee jerk reaction and it's going to continue for a while," said Thurai.

Wang said the concerns are more about big spending tech giants and whether the capex will be questioned. He said:

"We have to figure out if it makes sense for a Microsoft to spend $80 billion a year on capex to build out data centers. The short answer is that Microsoft is has to do it. It's really about the payback period that that's going to actually hit them. The second question is whether we need to pay this much for token economics.

"We're living in a world we call exponential efficiency. If you're not 10 times better one tenth the cost, nobody cares. And we're at this point where our existing software vendors have made life so expensive to hold their stock price. So this reset is a good thing in general, because it's going to lower the cost of technology for customers. It's a bad thing for stock investors, because we're going to see valuations at the top plummet if you're not one of the winners."

More:

• Meta plans to end 2025 with 1.3 million GPUs and $60B to $65B spent on AI
• Microsoft to spend $80 billion on capital expenditures
• OpenAI's Stargate Project diversifies its cloud infrastructure
• OpenAI's Altman on AI agents, losing money on $200 per month on ChatGPT Pro subscriptions
• GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs
• Multi-cloud computing isn't 'a bunch of separate clouds'
• AI data center building boom: Four themes to know
• On-premises AI enterprise workloads? Infrastructure, budgets starting to align
• The generative AI buildout, overcapacity and what history tells us

What are the security concerns with DeepSeek?

Mehta said there are concerns about prompt injection and jailbreaking DeepSeek. "AI security is one of the biggest topics for CxOs," said Mehta. "If you don't know how the model has been trained, what data has been used, and how easy or difficult it's going to be to actually break it, do you really want to use that model for your most sensitive data and use cases? Are you really going to do that?"

SAP preps AI agent move, extends on-prem maintenance, sets 2025 outlook

Larry Dignan

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. ...

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SAP CEO Christian Klein said the company will significantly increase its AI investments, launch AI agent innovations Feb. 13 and give customers a three-year reprieve on migrating from on-premises ERP to the cloud.

Klein teased the AI agent orchestration launch as well as licensing changes during SAP's fourth quarter earnings call. He said that customers are spending half of their IT budgets on data and analytics and falling short of leveraging data.

SAP "will harmonize structure and unstructured data" across SAP and non-SAP data with relevant semantics. "We will make AI agents much more powerful," said Klein. "Joule will become the super orchestrator of these agents, carrying out complete tasks autonomously and end to end, taking over significant workload from humans."

On the licensing front, Klein said "we will introduce licensing options that allow customers to upgrade and switch easily to our newest cloud solutions across the whole SAP Business Suite without additional negotiations." In short, SAP will roll out a maintenance offering that will give customers the ability to extend maintenance through 2033 from 2030 if they can't migrate to the cloud completely.

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

Although SAP's fourth quarter earnings and outlook were notable, Klein's comments about AI strategy and licensing were more notable. Klein, who was referring to US AI industry concerns about DeepSeek and cheaper models, noted that SAP can roll with multiple models as needed. The value is in business data, he added.

Klein said SAP is flexible with large language model choices and is betting its AI strategy on contextual data. SAP said half of its cloud deals included AI in the fourth quarter and 2025 cloud revenue will be up 26% to 28%.

"We are flexible when it comes to AI infrastructure and large language modules. We benefit from cost reductions and progress in the LLM space, because we are truly differentiating an element in AI today. However, it is deep process and industry knowhow, combined with access to unique context, rich business data, so value equation is more and more moving up the application layer and to building one semantical data layer, this is exactly what SAP has been focusing on."

• Agentic AI without process optimization, orchestration will flop
• CxOs upbeat on economy, plan to invest heavily on genAI, AI agents
• Agentic AI: Three themes to watch for 2025
• Why your IT strategy will be easier (in theory): There's only one path

On a conference call, Klein touted the "new SAP," which shows strong cloud growth and the ability to leverage Business AI through its suite. "Land and expand is clearly working," said Klein, who said a fifth of customers are using more than one of SAP's solutions. "We are doubling down on AI in 2025."

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”

Klein said SAP brought more than 130 genAI use cases to customers in 2024. Internally, Klein said SAP is using AI internally to be more efficient with 20,000 SAP developers using AI tools, average efficiency gains of 20% on go-to-market activities and contract booking time improvements of 75%. SAP also saw a 20x productivity gain due to AI assisted go-to-cash process automation and has saved €300 million due to AI implementations.

Fourth quarter results and outlook

SAP said fourth quarter revenue was €9.48 billion, up 11% from a year ago, with net profit of €1.62 billion, or €1.37 a share. Adjusted earnings were €1.40 a share.

For 2024, SAP said revenue was €34.18 billion, up 10% from a year ago, with earnings of €3.15 billion, or €2.68 a share. Earnings were down due to restructuring charges. Adjusted earnings were €4.53 a share.

Klein said that SAP finished the year strong and showed the ability to migrate customers to the cloud.

In the fourth quarter, SAP said cloud backlog grew 32% to €18.08 billion. Backlog gained due to Cloud ERP Suite revenue.

However, SAP did note that it expects current cloud backlog growth to "slightly decrease in 2025."

SAP said it projected cloud revenue of €21.6 billion to €21.9 billion. Cloud and software revenue for 2025 will be up 11% and non-IFRS operating profit will be up 26%. The company sees about €8 billion in free cash flow, nearly double from 2024.

For non-financial metrics, SAP plans to improve its Net Promoter Score to 16, up from 12 in 2024.

Don't leave customers behind

Klein said SAP can navigate macro-economic concerns in key industries such as automotive, which is struggling. Klein said SAP customers are navigating many economic and geopolitical concerns and that industries are moving to the cloud, but need time.

The upshot is that Klein said SAP is willing to play the long game with customers and extend maintenance for those that can't get to the cloud to 2033, a three-year reprieve.

SAP's new maintenance program was reported in Handelsblatt and outlined by a consultant.

"We want to be reasonable in our outlook, how we also reflect this facing of these wise deals, because customers need time. I mean, changing business modules is not only a technological move, but also about change management sometimes," said Klein.

Infosys sees 'good traction' with SAP S/4HANA migrations

Klein also acknowledged that some customers aren't going to make its deadline to go move to SAP/HANA.

He said:

"The end of maintenance by 2027 will not be changed. We will stick to that. But you also have to consider, in some parts of the stack, there are third party components included, and they are running out of maintenance as well. We don't want to leave the customers behind. As we moved all of our cloud solutions already on SAP/4HANA Cloud, we do now the same with these on premise customers. We move them to the cloud, we replace the third party components, and with that, there are 100 ERPs supported in a complete, sustainable and supported way. And that is about this offering.

It's actually for a very few large customers who will not making the time. To transform and consolidate ERP and business processes in over 100 countries is sometimes not that easy. It's not about the extension of on-premise maintenance, but it's really reaching out with helping hands with a very few large customers."

Executive changes

SAP also made executive changes.

The company said that Sebastian Steinhaeuser has been appointed to the Executive Board to lead Strategy & Operations, a new board area. Steinhaeuser will be focused on simplifying SAP operations.

SAP also extended the contract of Thomas Saueressig, head of Customer Services & Delivery, for another three years until 2028.

According to SAP, it will also form an Extended Board that will include Philipp Herzig, who takes over as global CTO in addition to Chief AI Officer, as well as two co-chief revenue officers.

Jan Gilg and Emmanuel (Manos) Raptopoulos will co-lead SAP's Customer Success organization as new CROs.

Zoho CEO Sridhar Vembu steps back, becomes Chief Scientist

Larry Dignan

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. ...

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Zoho CEO Sridhar Vembu said he will step down as CEO and become Chief Scientist at the company "responsible for deep R&D initiatives."

Vembu announced the move on X. He also said he will focus on rural development too. Vembu said:

"The future of our company entirely depends on how well we navigate the R&D challenge and I am looking forward to my new assignment with energy and vigor. I am also very happy to get back to hands on technical work."

Zoho co-founder Shailesh Kumar Davey will become CEO. Co-founder Tony Thomas will lead Zoho's US business. Rajesh Ganesan will lead our ManageEngine division and Mani Vembu will lead the Zoho.com division.

Under Vembu, Zoho has cultivated a unique culture that has created disruptive technology in the SaaS market, a model that generates value vs. larger rivals, and builds up offices in smaller communities where it can have a larger impact.

In an interview last year, Vembu outlined the approach.

"It's really about getting closer to the customers at one level, and just talking about business first. But beyond that, it's also putting back into communities that income needed from technology, create good jobs, in smaller communities, which people are not doing enough."

In that interview, Vembu also noted that Zoho has a strong bench. Vembu said Zoho can't run out and hire and have a productive employee in two weeks. "We believe that first we have to nurture the talent and that automatically brings in good people to us over time," he said.

• Zoho CEO Sridhar Vembu: Long-term thought leadership on innovation, technology, people
• A Case Study in Radical Empathy: The Leadership of Zoho CEO Sridhar Vembu
• Zoho CEO Sridhar Vembu: Playing the long game with innovation, technology, people
• Zoho focuses LLM efforts on Nvidia architecture
• Zoholics 2024: Zoho aims to democratize CRM, infuse AI across platform, court developers, create cybersecurity stack
• Zoho Analytics revamp aims to connect, BI, data scientists, business users

GenAI prices to tank: Here’s why

Larry Dignan

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. ...

Read more

Prices for access to generative AI models and features could tank in 2025 amid cheaper foundational models, open source advances and vendors becoming realistic about what customers will actually pay.

Welcome to the only thing in your life that'll be deflationary--generative AI. We're only a month into 2025, but there have been a series of moves indicating that the generative AI gravy train is unlikely because customers will soon be focused on cost per query.

Here are a few reasons why enterprise AI is likely to become less expensive.

Wither add-ons?

Rewind to a year ago and Wall Street was busy modeling revenue growth due to $30 per month per user add-ons for access to generative AI features. Later, those add-on prices became more like $20, but the working theory from vendors was that enterprises will pay for AI that drives productivity.

During this time, the vendors that went for genAI usage and raised prices on their overall SKUs were mocked. Wall Street analysts were almost indignant. When are you monetizing genAI? Zoom, Adobe and Workday all got flack for noting what was kind of obvious--genAI is a feature not the end game.

Fast forward to January 2025 and copilot add-ons are toast. Oracle just launched AI agents for its sales applications without charging extra. Google Workspace dropped Gemini add-on charges, but raised business and enterprise plan prices. Microsoft launched Copilot Chat and now includes copilots in Microsoft 365 in many cases. There are charges for AI agents, but many genAI features will be bundled into enterprise plans.

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Microsoft did something similar with its consumer Microsoft 365 plans and now copilot is everywhere (even if you didn't want it). For what it's worth, I'm more of a Notepad person. Like my appliances, I often like my tools to be on the dumb side. Don't bog me down with features I don't need or want.

Now that Google and Microsoft have ditched the add-on game, rest assured that other software vendors will follow. The argument that genAI is all just part of the software has won out.

Sure, you'll be hit with other AI charges and consumption models, but the add-on game is over.

LLM pricing is going to collapse

The big news this week is that a Chinese AI company called DeepSeek set out to blow up OpenAI's business model. DeepSeek, combined with other open source large language models, is going to be a real threat to model pricing, which revolves around tokens and API calls. ByteDance, owner of TikTok, also released Doubao 1.5 Pro, a model with strong performance.

Yes, there are concerns about censorship on DeepSeek and Doubao 1.5 Pro, but the idea that you can get API access to DeepSeek's R1 model for 14 cents for a million tokens compared to OpenAI's $7.50 is disruptive. OpenAI is clearly positioned as a premium LLM model, but that pricing is disruptive for a company that can't make money on a $200 a month subscription plan.

This DeepSeek news landed on Monday and was overshadowed by an inauguration in the US featuring technology bigwigs, AI infrastructure plans and chatter out of Davos and earnings season.

Nevertheless, it's worth taking DeepSeek for a spin. Many of these models have caught up to what OpenAI can do and are likely good enough for most use cases.

Some reading:

• Simon Willison's blog on DeepSeek
• ZDNet on the pricing implications
• DeepSeek models and pricing
• OpenAI models and pricing

Simply put, LLM margin compression is here. The scary part is the LLM giants didn't have profit margins to begin with. LLMs are going to commodity in a hurry.

AI agents will require price transparency

Although vendors are wrapping in genAI as a bundle, the agentic AI as labor replacement/augmentation rap is just starting.

Enter the consumption model. Enterprises (allegedly) will pay for agentic AI conversations, problems solved and value created by the simple fact companies won't need to add a human.

The problem: The SaaS vendors pushing this agentic AI consumption model aren't used to the level of transparency needed yet.

Cloud providers have consumption dashboards, more transparent pricing and ways to manage costs. SaaS vendors simply don't.

Once consumption becomes part of the mix, SaaS vendors will have no choice but to be more transparent.

Today, SaaS packaging and contracts are complicated and the sales cadence is almost engineered so enterprises make tactical errors along the way. Companies will need to know exact costs by AI use case especially with agentic AI.

We'll have a hybrid seat, subscription and consumption model for the foreseeable future, but ultimately SaaS vendors are going to have to show the math behind the pricing. Value would be nice too.

• CxOs upbeat on economy, plan to invest heavily on genAI, AI agents
• Agentic AI: Three themes to watch for 2025
• Why your IT strategy will be easier (in theory): There's only one path
• 2025 in preview: 10 themes in enterprise technology to watch

What's next?

As early genAI pricing models are disrupted, you'll most SaaS vendors want to become platforms, LLMs bundled with broader software suites and a more holistic sales pitch.

SaaS vendors will want to be more like platforms that enterprises use to leverage AI. ServiceNow is already seen this way, but look for many vendors to follow the same path. What's unclear is whether CxOs who have been cross-sold to oblivion will suddenly think their vendors are platforms.

Meanwhile, LLM visionaries are going to attempt to look more like SaaS companies.

One thing that caught my eye out of Davos was Mistral's take that enterprises will move away from models and to systems. Mistral CEO Arthur Mensch told CNBC that models are merely part of systems that include data and tools that act as agents.

Cohere launched North, an AI platform that combines LLMs, search and agents in one collaboration platform. Anthropic is adding collaboration features as it expands use cases for its Claude models. OpenAI is also expanding but has largely focused on expanding into search to compete with Google.

If you follow the LLM players, it's clear that they think foundational models alone aren't going to pave the way to profitability.

The other thread to watch is how the hyperscalers fare in the agentic AI age. Consumption pricing is already there and AI makes it a lot easier for cloud giants to go vertical as well as horizontal.

In the end, 2025 is going to be a year where enterprise vendors attempt multiple models. And margin compression may be inevitable.

Meta plans to end 2025 with 1.3 million GPUs and $60B to $65B spent on AI

Larry Dignan

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. ...

Read more

Meta CEO Mark Zuckerberg said the company spend $60 billion to $65 billion in capital expenditures largely focused on artificial intelligence.

In a post on Facebook, Zuckerberg outlined the company's 2025 goals. Zuckerberg also highlighted how Meta will build a 2GW+ data center that "is so large it would cover "a significant part of Manhattan."

Zuckerberg's disclosed AI spending spree lands a few weeks after Microsoft said it would spend $80 billion on capital expenditures. Meta's goals for 2025 go like this:

• Meta AI will be the leading AI assistant serving more than 1 billion people.
• Llama 4 will be the leading model.
• The company will build an AI engineer "that will start contributing increasing amounts of code to our R&D efforts."
• Meta will bring online 1GW of compute in 2025 and end the year with 1.3 million GPUs.
• The company will expand its AI teams significantly.

Meta’s disclosure on capital spending comes as technology giants are tripping over themselves to highlight how much is being spent on AI infrastructure. This week, President Trump announced Stargate, an effort to invest $500 billion in AI infrastructure. OpenAI CEO Sam Altman was the lead on Stargate along with Softbank and Oracle, but Elon Musk questioned the funding behind it.

More:

• GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs
• Multi-cloud computing isn't 'a bunch of separate clouds'
• AI data center building boom: Four themes to know
• On-premises AI enterprise workloads? Infrastructure, budgets starting to align
• The generative AI buildout, overcapacity and what history tells us

Verizon launches AI Connect, courts AI inferencing workloads

Larry Dignan

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. ...

Read more

Verizon outlined Verizon AI Connect in a strategy designed to put its network, compute and edge computing infrastructure in the middle of artificial intelligence inferencing workloads.

The company announced AI Connect along with its fourth quarter earnings. Verizon said it has Google Cloud and Meta as key customers for AI Connect.

With Verizon AI Connect, the company is looking to court hyperscale cloud providers and large enterprises with an edge to cloud network. AI Connect will feature Verizon's 5G network, high-speed fiber connectivity, edge locations and power and cooling.

Verizon added that it is looking to expand its AI efforts via partnerships with Nvidia, Vultr, which is a GPU-as-a-service provider, Google Cloud and Meta.

"Our industry sits at the center of the next wave of innovation as AI transforms how consumers and businesses operate," said Verizon CEO Hans Vestberg. "Our network assets and capabilities position us uniquely in this evolving landscape."

• GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs
• Multi-cloud computing isn't 'a bunch of separate clouds'
• AI data center building boom: Four themes to know
• On-premises AI enterprise workloads? Infrastructure, budgets starting to align

Vestberg said:

"If you think about where we are on generative AI today, today, it's large language modules that are trained at large data centers, and that requires enormous capacities. Over time, that will come much closer to the edge of the network, both for applications, but transport cost, and latency in some cases. This is creating an opportunity for us and has already created an opportunity as we had revenue and EBITDA impact in the fourth quarter. We are now looking into how we can use our assets and our capability to serve this market when it comes to the next step of generative AI."

Verizon's AI Connect effort is designed to utilize the company's existing assets including its fiber buildout and long-haul network to handle AI workloads. In addition, Verizon's Converged Intelligent Edge Network will play a role. 

The biggest argument for Verizon's AI Connect is that the AI infrastructure being built will need networking and connectivity to data centers and the edge. 

Kyle Malady, CEO of Verizon Business Group, said:

"As we move through our network transformation work, we will continue to free up more resources that could be made available for AI Connect. In addition, we have between 100 and 200 acres of undeveloped land, some currently zoned for data center build and much of it in prime data center-friendly areas."

In addition, Verizon has $1 billion in backlog just for its existing infrastructure, said Malady.

Verizon also reported fourth quarter and 2024 earnings.

The company reported fourth quarter earnings of $5.1 billion, or $1.18 a share, on revenue of $35.7 billion, up 1.6% from a year ago. Non-GAAP earnings were $1.10 a share.

For the year, Verizon reported earnings of $4.14 a share on revenue of $134.8 billion, up 0.6% from a year ago.

By the numbers:

• Verizon reported fourth quarter wireless revenue of $20 billion, up 3.1% from a year ago.
• The company had 568,000 postpaid net phone additions in the fourth quarter.
• Broadband net additions were 408,000 in the fourth quarter.
• Verizon added a net 373,000 fixed wireless access subscribers for a total of 4.6 million fixed wireless subscribers.

As for the outlook, Verizon is expecting total wireless service revenue growth of 2% to 2.8% and adjusted earnings per share growth of 0 to 3%.