• Amazon will invest another $10 billion in Ohio data centers, Ohio Gov. Mike DeWine said.
• The company will consider locations outside its power-strained hub in Columbus.
• In exchange for tax credits, Amazon committed to more than 1,000 new jobs in its Ohio data centers.

Amazon has committed to spending $10 billion on the expansion of its Ohio data center operations, in addition to the billions of dollars it has already said it plans to spend in the state, Ohio Gov. Mike DeWine said Monday.

The tech giant's new Ohio facilities, which should be completed by the end of 2030, will help power the push into AI by its cloud computing unit, Amazon Web Services.

Just last year, AWS said it would invest $7.8 billion to expand its data center hub in Columbus and the surrounding suburbs. The company started building data centers in the region in 2015 and has at least six different campuses that are either operational or under construction.

Ohio has committed to spending more than $23 billion on data centers in the state between the money it has already spent and its committed investments, a spokesperson for Ohio's Department of Development said.

The investment in Ohio is part of Amazon's aggressive spending plan on data center construction to support AI demand. Amazon CEO Andy Jassy said on the company's third-quarter earnings call in October that it plans to spend $75 billion on capital expenditures in 2024, most of which will go to cloud computing and data centers, and it expects to spend even more next year.

Local politicians have dubbed the Central Ohio "the Silicon Heartland." Gov. DeWine touted the AWS announcement this week as "strengthening the state's role as a major technology hub."

Most of Amazon's data centers are located in Northern Virginia, the largest data center market in the world. That area has become saturated with new facilities waiting to be connected to the electric grid. In the last 18 months, Amazon and its competitors have announced plans to build data centers in states nationwide. Just this year, Amazon announced plans to spend $11 billion on data centers in Indiana and $10 billion in Mississippi.

Job creation in Ohio

Ohio, which offers a generous slate of state and local tax incentives, including an up to 100% sales and use tax exemption for data center equipment, has seen a sharp uptick in development.

For this latest investment, the Ohio Tax Credit Authority approved additional job creation tax credits in AWS's existing economic development agreement with the state. In exchange for annual job creation tax credits, AWS has promised 1,058 "full-time equivalent" jobs with a minimum average annual payroll of $101.37 million, a spokesperson for Ohio's Department of Development told Business Insider.

Ohio law defines "full-time equivalent employees" as the result of a calculation, or "dividing the total number of hours for which employees were compensated for employment in the project by two thousand eighty." The employees must be directly employed by Amazon for the company to receive its tax credits, although there is no requirement for the kinds of jobs Amazon must offer.

When BI contacted AWS and asked what types of jobs would be available in its new Ohio data centers, an AWS spokesperson reiterated the information listed in Gov. DeWine's press release, which referred to the jobs as "new" and "well-paying."

Electricity demand rises

AWS's financial commitment to the state will hinge on whether local utilities can provide the amount of electricity the company eventually says it will need.

AEP Ohio, the Columbus utility that serves Amazon, said earlier this year that it received 30 gigawatts of service requests from data centers alone — an amount that would put the region's demand for electricity close to New York City's.

Much of that demand comes from the wealthy suburban enclave of New Albany, Ohio, where Meta, Microsoft, Google, and QTS are all constructing major data center projects. The site of Intel's future semiconductor chip plant is in neighboring Johnstown, Ohio. The New Albany Company, the real estate company founded by billionaire retail mogul Les Wexner, orchestrated many of the area's major land sales to tech companies, including Intel.

For its newest data centers, AWS will look to sites beyond the Columbus region, though no locations have been finalized, according to a statement from Gov. DeWine's office. If AWS locates a data center outside the Columbus region, it would likely be outside AEP's service territory.

AEP has asked Ohio's public utilities regulator to approve a tariff and a special rate class for data centers that would require the power-hungry facilities to pay for the majority of electricity they anticipate needing — even if they ultimately do not consume all of it.

The data center industry, including Amazon, is working to quash AEP's proposal. In a November testimony filed with the Public Utilities Commission of Ohio, Michael Fradette, who leads Amazon's energy strategy, called the proposal a "discriminatory structure" that "unfairly targets data center customers by targeting customers in specific industries."

The matter has sowed division among corporate interests in Ohio. Those who oppose the tariffs include the Ohio Manufacturers' Association Energy Group, a lobbying offshoot of the state's major manufacturing industry trade group, and the Ohio Energy Leadership Council, which is represented by David Proaño, a lawyer in BakerHostetler's Columbus office who also represents Amazon's data center business before the Public Utilities Commission of Ohio.

Meanwhile, Ohio Energy Group, which counts Cargill, Ford, GE, and Intel as members, has testified in favor of AEP's proposed data center tariffs. Walmart, a large customer of AEP in Ohio, has also come out supporting the tariff.

AEP is planning new transmission infrastructure projects to service data centers in the Columbus area, as well as the Intel chip plant. The future of the chip plant, which is supposed to bring 3,000 advanced manufacturing jobs to central Ohio, is uncertain as the company debates spinning off its struggling foundry business.

Rising energy demand from Columbus area data centers has triggered the need for new transmission infrastructure. Under AEP's existing rate structures, the costs of new transmission lines to data centers could be spread to other ratepayers.

Many of AEP's residential, commercial, and industrial customers saw transmission costs rise by $10 monthly in April, the fourth rate increase approved for the utility in three years. Next year, average bill totals will increase another $1.50 a month to support grid reliability, the utility said.

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• Bank of America downgraded AMD on Monday, citing higher competitive risk in the AI market.
• AWS customers' low demand for AMD AI chips and Nvidia dominance impact AMD's growth potential.
• AMD could still succeed due to Nvidia supply issues and its server chip market position.

Bank of America downgraded AMD after a Business Insider report raised concerns about demand for the tech company's AI chips.

Analysts at BofA cut AMD shares to a "neutral," citing "higher competitive risk" in the AI market, according to an analyst note published on Monday.

BofA analysts also lowered their AMD GPU sales forecast for next year to $8 billion, from $8.9 billion, implying a roughly 4% market share.

AMD's stock dropped roughly 5.6% on Monday, after falling about 2% on Friday. Its shares are down about 5% so far this year.

The declines follow BI's report on Friday that said Amazon Web Services was "not yet" seeing strong enough customer demand to deploy AMD's AI chips through its cloud platform.

Bank of America cited this AWS customer-demand issue, alongside Nvidia's dominance and the growing preference for custom chips from Marvell and Broadcom, as factors limiting AMD's growth potential.

"Recently largest cloud customer Amazon strongly indicated its preference for alternative custom (Trainium/ MRVL) and NVDA products, but a lack of strong demand for AMD," the Bank of America note said, referring to AWS's in-house AI chip Trainium and its close partnerships with Marvell and Nvidia.

AWS's spokesperson said in an email to BI, "AWS and AMD work together closely, as we continue to make AWS the best place to run AMD silicon. Based on the success of AMD CPUs on AWS, we are actively looking at offering AMD's AI chips."

An AMD spokesperson didn't respond to a request for comment on Monday.

AMD recently increased its GPU sales forecast, just a year after launching its line of AI chips. But its GPU market share is still far behind Nvidia's.

Bank of America said AMD could still succeed in the AI chip market, in part due to Nvidia's supply constraints and premium pricing, making it a strong alternative, especially for internal cloud workloads. It also said AMD is well positioned in the server chip market, as rival Intel continues to struggle.

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• AWS launched new AI chips that compete with Nvidia's GPUs.
• AWS says its goal is to provide more customer choice, not to dethrone Nvidia in the AI chip market.
• Gadi Hutt, a senior director at AWS, also talked about partnerships with Intel, Anthropic, and AMD.

Amazon Web Services launched an upgraded line of AI chips this week, putting the company squarely in competition with Nvidia.

Except AWS doesn't see it that way.

AWS's new AI chips aren't meant to go after Nvidia's lunch, said Gadi Hutt, a senior director of customer and product engineering at the company's chip-designing subsidiary, Annapurna Labs. The goal is to give customers a lower-cost option, as the market is big enough for multiple vendors, Hutt told Business Insider in an interview at AWS's re:Invent conference.

"It's not about unseating Nvidia," Hutt said, adding, "It's really about giving customers choices."

AWS has spent tens of billions of dollars on generative AI. This week the company unveiled its most advanced AI chip, called Trainium 2, which can cost roughly 40% less than Nvidia's GPUs, and a new supercomputer cluster using the chips, called Project Rainier. Earlier versions of AWS's AI chips had mixed results.

Hutt insists this isn't a competition but a joint effort to grow the overall size of the market. The customer profiles and AI workloads they target are also different. He added that Nvidia's GPUs would remain dominant for the foreseeable future.

In the interview, Hutt discussed AWS's partnership with Anthropic, which is set to be Project Rainer's first customer. The two companies have worked closely over the past year, and Amazon recently invested an additional $4 billion in the AI startup.

He also shared his thoughts on AWS's partnership with Intel, whose CEO, Pat Gelsinger, just retired. He said AWS would continue to work with the struggling chip giant because customer demand for Intel's server chips remained high.

Last year AWS said it was considering selling AMD's new AI chips. But Hutt said those chips still weren't available on AWS because customers hadn't shown strong demand.

This Q&A has been edited for clarity and length.

There have been a lot of headlines saying Amazon is out to get Nvidia with its new AI chips. Can you talk about that?

I usually look at these headlines, and I giggle a bit because, really, it's not about unseating Nvidia. Nvidia is a very important partner for us. It's really about giving customers choices.

We have a lot of work ahead of us to ensure that we continuously give more customers the ability to use these chips. And Nvidia is not going anywhere. They have a good solution and a solid road map. We just announced the P6 instances [AWS servers with Nvidia's latest Blackwell GPUs], so there's a continuous investment in the Nvidia product line as well. It's really to give customers options. Nothing more.

Nvidia is a great supplier of AWS, and our customers love Nvidia. I would not discount Nvidia in any way, shape, or form.

So you want to see Nvidia's use case increase on AWS?

If customers believe that's the way they need to go, then they'll do it. Of course, if it's good for customers, it's good for us.

The market is very big, so there's room for multiple vendors here. We're not forcing anybody to use those chips, but we're working very hard to ensure that our major tenets, which are high performance and lower cost, will materialize to benefit our customers.

Does it mean AWS is OK being in second place?

It's not a competition. There's no machine-learning award ceremony every year.

In the case of a customer like Anthropic, there's very clear scientific evidence that larger compute infrastructure allows you to build larger models with more data. And if you do that, you get higher accuracy and more performance.

Our ability to scale capacity to hundreds of thousands of Trainium 2 chips gives them the opportunity to innovate on something they couldn't have done before. They get a 5x boost in productivity.

Is being No. 1 important?

The market is big enough. No. 2 is a very good position to be in.

I'm not saying I'm No. 2 or No. 1, by the way. But it's really not something I'm even thinking about. We're so early in our journey here in machine learning in general, the industry in general, and also on the chips specifically, we're just heads down serving customers like Anthropic, Apple, and all the others.

We're not even doing competitive analysis with Nvidia. I'm not running benchmarks against Nvidia. I don't need to.

For example, there's MLPerf, an industry performance benchmark. Companies that participate in MLPerf have performance engineers working just to improve MLPerf numbers.

That's completely a distraction for us. We're not participating in that because we don't want to waste time on a benchmark that isn't customer-focused.

On the surface, it seems like helping companies grow on AWS isn't always beneficial for AWS's own products because you're competing with them.

We are the same company that is the best place Netflix is running on, and we also have Prime Video. It's part of our culture.

I will say that there are a lot of customers that are still on GPUs. A lot of customers love GPUs, and they have no intention to move to Trainium anytime soon. And that's fine, because, again, we're giving them the options and they decide what they want to do.

Do you see these AI tools becoming more commoditized in the future?

I really hope so.

When we started this in 2016, the problem was that there was no operating system for machine learning. So we really had to invent all the tools that go around these chips to make them work for our customers as seamlessly as possible.

If machine learning becomes commoditized on the software and hardware sides, it's a good thing for everybody. It means that it's easier to use those solutions. But running machine learning meaningfully is still an art.

What are some of the different types of workloads customers might want to run on GPUs versus Trainium?

GPUs are more of a general-purpose processor of machine learning. All the researchers and data scientists in the world know how to use Nvidia pretty well. If you invent something new, if you do that on GPU, then things will work.

If you invent something new on specialized chips, you'll have to either ensure compiler technology understands what you just built or create your own compute kernel for that workload. We're focused mainly on use cases where our customers tell us, "Hey, this is what we need." Usually the customers we get are the ones that are seeing increased costs as an issue and are trying to look for alternatives.

So the most advanced workloads are usually reserved for Nvidia chips?

Usually. If data-science folks need to continuously run experiments, they'll probably do that on a GPU cluster. When they know what they want to do, that's where they have more options. That's where Trainium really shines, because it gives high performance at a lower cost.

AWS CEO Matt Garman previously said the vast majority of workloads will continue to be on Nvidia.

It makes sense. We give value to customers who have a large spend and are trying to see how they can control the costs a bit better. When Matt says the majority of the workloads, it means medical imaging, speech recognition, weather forecasting, and all sorts of workloads that we're not really focused on right now because we have large customers who ask us to do bigger things. So that statement is 100% correct.

In a nutshell, we want to continue to be the best place for GPUs and, of course, Trainium when customers need it.

What has Anthropic done to help AWS in the AI space?

They have very strong opinions of what they need, and they come back to us and say, "Hey, can we add feature A to your future chip?" It's a dialogue. Some ideas they came up with weren't feasible to even implement in a piece of silicon. We actually implemented some ideas, and for others we came back with a better solution.

Because they're such experts in building foundation models, this really helps us home in on building chips that are really good at what they do.

We just announced Project Rainier together. This is someone who wants to use a lot of those chips as fast as possible. It's not an idea — we're actually building it.

Can you talk about Intel? AWS's Graviton chips are replacing a lot of Intel chips at AWS data centers.

I'll correct you here. Graviton is not replacing x86. It's not like we're yanking out x86 and putting Graviton in place. But again, following customer demand, more than 50% of our recent landings on CPUs were Graviton.

It means that the customer demand for Graviton is growing. But we're still selling a lot of x86 cores too for our customers, and we think we're the best place to do that. We're not competing with these companies, but we're treating them as good suppliers, and we have a lot of business to do together.

How important is Intel going forward?

They will for sure continue to be a great partner for AWS. There are a lot of use cases that run really well on Intel cores. We're still deploying them. There's no intention to stop. It's really following customer demand.

Is AWS still considering selling AMD's AI chips?

AMD is a great partner for AWS. We sell a lot of AMD CPUs to customers as instances.

The machine-learning product line is always under consideration. If customers strongly indicate that they need it, then there's no reason not to deploy it.

And you're not seeing that yet for AMD's AI chips?

Not yet.

How supportive are Amazon CEO Andy Jassy and Garman of the AI chip business?

They're very supportive. We meet them on a regular basis. There's a lot of focus across leadership in the company to make sure that the customers who need ML solutions get them.

There's also a lot of collaboration within the company with science and service teams that are building solutions on those chips. Other teams within Amazon, like Rufus, the AI assistant available to all Amazon customers, run entirely on Inferentia and Trainium chips.

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• Amazon is emphasizing customer choice over market dominance with its AI strategy.
• Amazon unveiled a new series of AI models called Nova this week.
• Amazon's Bedrock tool supports diverse models from multiple providers, unlike OpenAI.

Amazon believes AI models are not in a winner-take-all market.

The company drilled down on this message during this week's re:Invent, the annual extravaganza for its Amazon Web Services cloud unit. Even after unveiling a new series of homegrown AI models called Nova, which, by some measures, are as powerful as other market leaders, Amazon stressed the goal is to provide more choice to customers.

AI models have become the new battleground for tech supremacy since OpenAI released its popular ChatGPT service in late 2022. Companies have rushed to up the ante, trying to outperform each other in model performance.

Amazon has largely been absent from this race. Instead, it has tried to stay neutral, arguing that the generative AI market is so big and varied that customers will want more model choices that fit their different needs. Amazon still believes this is the right approach.

"There are some that would want you to believe there's just this one magic model that could do everything — we never believed in it," Vasi Philomin, AWS's VP of generative AI, told Business Insider. "There'll be many, many winners and there are really wonderful companies out there building some amazing models."

Different positioning

As part of this, Amazon has used Bedrock, an AI development tool that gives access to many models, as its main horse in the AI race. This approach differed from OpenAI, and Meta, which mostly focused on building powerful models or chatbots. Google has a leading AI model in Gemini, but also provides access to other models through its Vertex cloud service, and Microsoft has a similar offering.

This week, Amazon further leaned into its strategy, announcing an array of new updates for Bedrock, including a marketplace for more than 100 specialized models and a distillation feature that fine-tunes smaller, more cost-effective models. It also unveiled new reasoning and "multi-agent" collaboration features that help build better models.

Swami Sivasubramanian, AWS's VP of AI and data, told BI that AWS "pioneered" the model-choice approach and intends to continue to promote it as a "core construct" of the business.

"GenAI is a lot bigger than a single chatbot or a single model to reach its full potential," Sivasubramanian said.

More companies appear to be taking the multi-model approach. According to a recent report by Menlo Ventures, companies typically use 3 or more foundation models in their AI services, "routing to different models depending on the use case or results."

As a result, Anthropic, which Menlo Ventures has backed, doubled its share in the AI model market to 24% this year, while OpenAI's share dropped from 50% to 34% year-over-year, according to the report.

'Choice matters'

Amazon may have no choice but to stick to this narrative. When OpenAI captivated the world with ChatGPT a couple of years ago, Amazon was caught flat-footed, leading to an internal scramble to find answers, BI previously reported. Its first in-house model, called Titan, drew little attention.

Having its own advanced, powerful AI models could help Amazon. It might attract the largest AI developers and promote AWS as the leader in the AI space. It would potentially also encourage those developers to continue building within AWS's broader cloud ecosystem.

Amazon isn't giving up on building its own advanced models. Last year, it created a new artificial general intelligence team under the mandate to build the "most ambitious" large language models. On Tuesday, Amazon unveiled the early results of that effort with its Nova series, which includes a multimodal model capable of handling text, image, and video queries.

Still, Amazon's CEO Andy Jassy downplayed any notion of Nova going after competitors. He said he's been surprised by the diversity of models developers use and that Nova is just one of the many options they will have.

"There is never going to be one tool to rule the world," Jassy said during a keynote presentation this week.

It's hard to know how successful this approach is as Amazon doesn't break out its AI revenue. But Jassy was even more bullish on the AI opportunity during October's call with analysts. He said AWS was now on pace to generate "multi-billion dollars" in AI-related revenue this year, growing at "triple-digit percentages year over year." Amazon's AI business is "growing three times faster at its stage of evolution than AWS did itself," he added.

Rahul Parthak, VP of data and AI, go-to-market, at AWS told BI that Nova's launch was partly driven by customer demand. Customers have been asking for Amazon's own model because some prefer to deal with one vendor that can handle every aspect of the development process, he said.

Amazon still wants other models to thrive because its goal isn't about beating competitors but offering customers "the best options," Parthak added. He said more companies, like Microsoft and Google, are following suit, offering more model choices via their own cloud services.

"We've been pretty thoughtful and clear about what we think customers need, and I think that's playing out," Parthak said.

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• AWS announced plans for an AI supercomputer, UltraCluster, with Trainium 2 chips at re:Invent.
• AWS may be able to reduce reliance on Nvidia by developing its own AI infrastructure.
• Apple said it's using Trainium 2 chips for Apple Intelligence.

Matt Garman, the CEO of Amazon Web Services, made several significant new AWS announcements at the re:Invent conference on Tuesday.

His two-and-a-half hour keynote delved into AWS's current software and hardware offerings and updates, with words from clients including Apple and JPMorgan. Graphics processing units (GPUs), supercomputers, and a surprise Apple cameo stuck out among the slew of information.

AWS, the cloud computing arm of Amazon, has been developing its own semiconductors to train AI. On Tuesday, Garman said it's creating UltraServers — containing 64 of its Trainium 2 chips — so companies can scale up their GenAI workloads.

Moreover, it's also building an AI supercomputer, an UltraCluster made up of UltraServers, in partnership with AI startup Anthropic. Named Project Rainier, it will be "the world's largest AI compute cluster reported to date available for Anthropic to build and deploy its future models on" when completed, according to an Amazon blog post. Amazon has invested $8 billion in Anthropic.

Such strides could push AWS further into competition with other tech firms in the ongoing AI arms race, including AI chip giant Nvidia.

Here are four takeaways from Garman's full keynote on Tuesday.

AWS' Trainium chips could compete with Nvidia.

Nvidia currently dominates the AI chip market with its sought-after and pricey GPUs, but Garman backed AWS's homegrown silicon during his keynote on Tuesday. His company's goal is to reduce the cost of AI, he said.

"Today, there's really only one choice on the GPU side, and it's just Nvidia. We think that customers would appreciate having multiple choices," Garman told the Wall Street Journal.

AI is growing rapidly, and the demand for chips that make the technology possible is poised to grow alongside it. Major tech companies, like Google and Microsoft, are venturing into chip creation as well to find an alternative to Nvidia.

However, Garman told The Journal the doesn't expect Trainium to dethrone Nvidia "for a long time."

"But, hopefully, Trainium can carve out a good niche where I actually think it's going to be a great option for many workloads — not all workloads," he said.

AWS also introduced Trainium3, its next-gen chip.

AWS' new supercomputer could go toe to toe with Elon Musk's xAI.

According to The Journal, the chip cluster known as Project Rainier is expected to be available in 2025. Once it is ready, Anthropic plans to use it to train AI models.

With "hundreds of thousands" of Trainium chips, it would challenge Elon Musk's xAI's Colossus — a supercomputer with 100,000 of Nvidia's Hopper chips.

Apple is considering Trainium 2 for Apple Intelligence training.

Garman said that Apple is one of its customers using AWS chips, like Amazon Graviton and Inferentia, for services including Siri.

Benoit Dupin, senior director of AI and machine learning at Apple, then took to the stage at the Las Vegas conference. He said the company worked with AWS for "virtually all phases" of its AI and machine learning life cycle.

"One of the unique elements of Apple business is the scale at which we operate and the speed with which we innovate," Dupin said.

He added, "AWS has been able to keep the pace, and we've been customers for more than a decade."

Now, Dupin said Apple is in the early stages of testing Trainium 2 chips to potentially help train Apple Intelligence.

The company introduced a new generation of foundational models, Amazon Nova.

Amazon announced some new kids on the GenAI block.

AWS customers will be able to use Amazon Nova-powered GenAI applications "to understand videos, charts, and documents, or generate videos and other multimedia content," Amazon said. There are a range of models available at different costs, it said.

"Amazon Nova Micro, Amazon Nova Lite, and Amazon Nova Pro are at least 75% less expensive than the best-performing models in their respective intelligence classes in Amazon Bedrock," Amazon said.

• AWS recently laid out growth plans for 2025 in internal documents.
• One of the initiatives is focused on working more with consulting firms.
• Accenture was among several consulting firms mentioned by AWS.

Amazon Web Services wants to work more with consulting firms, including Accenture, part of a broader plan to spur growth in 2025, according to an internal planning document obtained by Business Insider.

AWS is looking to expand work with external partners that can sell its cloud services to hundreds of their existing customers. AWS sees an untapped market worth $250 billion and thousands of contracts up for renewal, the document explained.

Beyond Accenture, AWS mentioned Tata Consultancy, DXC Technology, and Atos as partners in the planning document.

AWS will prioritize these partners' existing customers and proactively reach out to them before contract-renewal time, and help the partners become "cloud-first," the document explained.

AWS pioneered cloud computing and still leads this huge and growing market. Over the years, the company has done a lot of work with customers through in-house cloud advisers. So the plan to expand its relationships with outside consulting firms is notable.

Ruba Borno is the VP leading the initiative, which will "review and prioritize partner's incumbent customers based on workloads and relationship," the document also stated.

Borno is a Cisco veteran who joined AWS a few years go to run its global channels and alliances operation, which works with more than 100,000 partners, including consulting firms and systems integrators and software vendors.

These plans are part of new AWS growth initiatives that include a focus on healthcare, business applications, generative AI, and the Middle East region, BI reported last week.

These are part of the AWS sales team's priorities for next year and Amazon refers to them internally as "AGIs," short for "AWS growth initiatives," one of the internal documents shows.

A spokesman for Tata Consultancy declined to comment. Spokespeople at Accenture did not respond to a request for comment.

• AWS faces competition from OpenAI, Microsoft, and Google in AI, risking its cloud dominance.
• It offers new financial incentives for AI sales. That comes with higher pressure and new demands.
• AWS CEO Matt Garman wants his teams to move even faster.

This summer, Amazon Web Services rolled out a new internal campaign.

The initiative, called "Find One, Launch One, Ramp One," introduced goals, prizes, and other incentives for Amazon's huge cloud-support teams across North America.

The ultimate aim was to sell more of the company's new AI offerings. Sales architects, customer-success managers, and people in other roles were recruited into the broad push.

"This is a great time to partner with our sales teams for this #OneTeam effort," AWS said in an internal memo obtained by Business Insider.

These AWS staffers were asked to find at least one sales opportunity each month for Q, Amazon's artificial-intelligence assistant, and Bedrock, the company's AI platform.

Then, the initiative asked employees to launch one Bedrock or Q customer workload.

The final requirement, the "Ramp One" part, pushed teams to generate real revenue from these workloads.

AWS created a leaderboard for everyone to see the top performers. With December 1 as the deadline, the company dangled prizes, including an evening of pizza and wine at an executive's home (with guitar playing as a possibility).

A race for AI supremacy

This initiative is just one example of AWS trying to squeeze more out of its massive sales and support teams to be more competitive in AI. There's more pressure and urgency to sell AI products, along with new incentives, according to several internal documents and more than a dozen current and former AWS employees.

Messaging from AWS CEO Matt Garman, previously the cloud unit's top sales executive, is to move even faster, these people said. They asked not to be identified because they're not authorized to speak with the press. Their identities are known to BI.

Much is at stake for Amazon. OpenAI, Microsoft, and Google, alongside a slew of smaller startups, are all vying for AI supremacy. Though Amazon is a cloud pioneer and has worked on AI for years, it is now at risk of ceding a chance to become the main platform where developers build AI products and tools.

More pressure

The revamped sales push is part of the company's response to these challenges. As the leading cloud provider, AWS has thousands of valuable customer relationships that it can leverage to get its new AI offerings out into the world.

Many AWS sales teams have new performance targets tied to AI products.

One team has to hit a specific number of customer engagements that focus on AWS's generative-AI products, for instance.

There are also new sales targets for revenue driven by gen-AI products, along with AI-customer win rates and a goal based on the number of gen-AI demos run, according to one of the internal Amazon documents.

Another AWS team tracks the number of AI-related certifications achieved by employees and how many other contributions staff have made to AI projects, one of the people said.

Hitting these goals is important for Amazon employees because that can result in higher performance ratings, a key factor in getting a raise or promotion.

More employees encouraged to sell AI

Even people in roles that traditionally don't involve actively selling products are feeling pressure to find opportunities for AI sales, according to Amazon employees who spoke with BI and internal documents.

AWS software consultants, who mostly work on implementing cloud services, are now encouraged to find sales opportunities, which blurs the line between consultants and traditional salespeople.

The Find One, Launch One, Ramp One initiative includes AWS sales architects. These staffers traditionally work with salespeople to craft the right cloud service for each customer. Now they're incentivized to get more involved in actual selling and are measured by the results of these efforts.

"Customers are interested in learning how to use GenAI capabilities to innovate, scale, and transform their businesses, and we are responding to this need by ensuring our teams are equipped to speak with customers about how to succeed with our entire set of GenAI solutions," an AWS spokesperson told BI.

"There is nothing new or abnormal about setting sales goals," the spokesperson added in a statement. They also said that AWS sales architects were not "sellers" and that their job was to "help customers design solutions to meet their business goals."

There are "no blurred lines," the spokesperson said, and roles and expectations are clear.

Selling versus reducing customer costs

One particular concern among some AWS salespeople revolves around the company's history of saving cloud customers money.

Some staffers told BI that they now feel the company is force-feeding customers AI products to buy, even if they don't need them. The people said this represented a shift in AWS's sales culture, which over the years has mostly looked for opportunities to reduce customers' IT costs.

In some cases, salespeople have also been asked to boost the attendance of external AWS events. Several recent AWS-hosted AI events saw low attendance records, and salespeople were told to find ways to increase the number of registrations by reaching out to customers, some of the people said.

AWS's spokesperson said customer attendance had "exceeded our expectations for a lot of our AI events" and that the number of participants at the re:Invent annual conference "more than doubled."

The spokesperson also said the notion that Amazon had moved away from its goal of saving customers money was false. The company always starts with "the outcomes our customers are trying to achieve and works backwards from there."

A hammer and a nail

Garman, Amazon's cloud boss, hinted at some of these issues during an internal fireside chat in June, according to a recording obtained by BI. He said there were sales opportunities for AWS in "every single conversation" with a customer but that AWS must ensure those customers get real value out of their spending.

"Too often we go talk to customers to tell them what we've built, which is not the same thing as talking to customers," Garman said. "Just because you have a hammer doesn't mean the problem the customer has is the nail."

AWS's spokesperson said the company is "customer-obsessed" and always tries to consider decisions "from our customers' perspectives, like their ROI." The spokesperson added that some of AWS's competitors don't take that approach and that it's a "notable contrast," pointing to this BI story about a Microsoft customer complaining about AI features.

More pressure but also more rewards

Amazon is also doling out bonuses and other chances for higher pay for AI-sales success.

AWS recently announced that salespeople would receive a $1,000 performance bonus for the first 25 Amazon Q licenses they sell and retain for three consecutive months with a given customer, according to an internal memo seen by BI. The maximum payout is $20,000 per customer.

For Bedrock, Amazon pays salespeople a bonus of $5,000 for small customers and $10,000 for bigger customers when they "achieve 3 consecutive months of specified Bedrock incremental usage in 2024," the memo said.

Some AWS teams are discussing higher pay for AI specialists. Sales architects, for example, in AI-related roles across fields including security and networking could get a higher salary than generalists, one of the people said.

AWS's spokesperson told BI that every major tech company provides similar sales incentives. Amazon continually evaluates compensation against the market, the spokesperson added.

Fear of losing to Microsoft

Inside AWS, there's a general concern that Amazon was caught off guard by the sudden emergence of generative AI and is playing catch-up to its rivals, most notably Microsoft, the people who spoke with BI said.

Some Amazon employees are worried that Q is losing some customers to Microsoft's Copilot because of a lack of certain AI features, BI previously reported.

Microsoft has an advantage because of its wide variety of popular business applications, including its 365 productivity suite. That may make it easier for Microsoft to show customers how AI can improve their productivity, some of the Amazon employees told BI. AWS, meanwhile, has struggled to build a strong application business, despite years of trying.

AWS's spokesperson challenged that idea by noting that AWS has several successful software applications for companies, including Amazon Connect, Bedrock, and SageMaker. The spokesperson also said Amazon Q launched in April and was already seeing robust growth.

It's "no secret that generative AI is an extremely competitive space," the spokesperson added, saying: "However, AWS is the leader in cloud and customer adoption of our AI innovation is fueling much of our continued growth. AWS has more generative AI services than any other cloud provider, which is why our AI services alone have a multibillion-dollar run rate."

More speed

A major AWS reorganization earlier this year hasn't helped the AI-sales effort, some of the people who spoke with BI said.

The big change switched AWS to more of an industry focus rather than a regional one. That caused confusion inside the company, and some large customers lost their point of contact, the people said. AWS is still figuring out how to run as a more cohesive group, which has resulted in a slower sales cycle, they added.

AWS's spokesperson said it's inaccurate to say its sales process has slowed, adding that year-over-year revenue growth accelerated again in the most recent quarter and that the business was on pace to surpass $100 billion in sales this year.

In his June fireside chat, Garman stressed the importance of speed and told employees to "go faster."

"Speed really matters," Garman said. "And it doesn't necessarily mean work more hours. It means: How do we make decisions faster?"

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• Internal AWS documents obtained by BI lay out the cloud giant's growth priorities next year.
• The company is focusing on at least 7 areas with codenames such as "ACDC" and "T2K."
• AWS faces competition from Microsoft and Google, though it leads the cloud market.

Amazon Web Services recently laid out new growth initiatives that include a focus on healthcare, business applications, generative AI, and the Middle East region, according to internal documents obtained by Business Insider.

These are part of the AWS sales team's priorities for next year and Amazon refers to them internally as "AGIs," short for "AWS growth initiatives," one of the internal documents shows.

Greg Pearson, AWS's VP of global sales, recently told employees that these AGIs are designed to drive "needle-moving, incremental revenue" and bring an "array of customers, faster than ever," a separate internal email seen by BI showed.

For AWS, the success of these initiatives is consequential. Competition from Microsoft and Google keeps growing and the rise of generative AI has put more pressure on AWS, particularly its sales team, BI previously reported. The company may share more details on these initiatives next week, when it hosts its annual re:Invent conference.

AWS revenue continued to reaccelerate in the most recent quarter, jumping 19% to $27.5 billion. That was slower than Microsoft's and Google's cloud business, on a percentage basis.

Amazon regularly adds more cloud revenue than its rivals, in absolute dollar terms. And the company still accounts for 30% of the global cloud infrastructure market, ahead of Microsoft's 20% and Google's 12% share, according to Synergy Research Group.

"We obsess over our customers and are proud of the many tailored programs we have in place to help them take advantage of the reliability, scale, and innovative services that AWS has to offer," AWS spokesperson Patrick Neighorn wrote in an email to BI.

Here are 7 of the "AGIs" for 2025 that AWS described in the internal document:

Accelerate to the Cloud from Data Centers (ACDC)

Amazon wants to fast-track customers to AWS's cloud-computing services. Ideal customers are companies that run their own data centers, have strong senior-level relationships with AWS, or have experience with AWS or other cloud-computing services, the document explained.

It added that AWS is "uniquely positioned" to win because it has longer experience in the cloud than competitors and can offer potential customers the right structure and incentives.

AWS Top 2000 (T2K)

AWS is targeting the world's largest companies with multiple billions of dollars in revenue, starting with those on the Forbes Global 2000 list, the document stated. It breaks down customers by contract size and growth stage.

These companies have very large, highly complex technical architectures requiring significant investment and time. AWS wants to customize solutions based on each company and industry, and speed up deals by using external consultants and partners, it added.

Business Applications Acceleration

AWS is focused on "winning the largest Business Application providers" in the enterprise resource planning (ERP) and customer relationship management (CRM) markets.

Many companies still use their own data centers to run business applications from providers such as Salesforce, Adobe, and ServiceNow.

Amazon wants to drive growth by getting more of these applications running on AWS's cloud, the document said.

Long-Range Plan: Middle East

The document lists the Middle East market as one of the top business opportunities. In March, for example, AWS announced plans to invest more than $5 billion in Saudi Arabia.

AWS also launched in Bahrain, the UAE, and Israel in 2019, 2022, and 2023, respectively.

IDC estimates the Gulf Cooperation Council (GCC), which includes Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the UAE, to have a cloud infrastructure market opportunity of $2.8 billion in 2024 and $15.5 billion by 2030.

Generative AI Innovation Center

Last year, AWS launched a $100 million program called Generative AI Innovation Center, which connects customers with AWS's AI scientists and experts to help launch generative AI solutions.

AWS plans to lean on this program to help customers build proofs of concept with generative AI and deploy new products, the document said. AWS's spokesperson told BI that more than 50% of the proof-of-concept solutions developed through this program are now in production.

AWS thinks generative AI is still in its "infancy," where customers are caught between "embracing innovation while also needing to play it safe," the document added. But the potential keeps growing, and its customers understand they need to "act fast," it explained.

IT & Application Outsourcing

AWS plans to expand its work external partners, including Accenture and Tata Consultancy, that can sell AWS services to hundreds of their existing customers, the document explained. AWS sees an untapped market worth $250 billion and thousands of contracts up for renewal, it added.

AWS will prioritize these partners' existing customers and proactively reach out to them before contract-renewal time, and help the partners become "cloud-first," the document said.

Epic Growth Initiative

AWS wants to onboard more customers to Epic System's electronic medical record software, hosted on AWS's cloud infrastructure, the document said. AWS and Epic have been close partners for years.

AWS wants to target hundreds of medical providers that use Epic's own data center services, and work with industry partners to "accelerate proactive moves to Epic on AWS," it added.

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• Swami Sivasubramanian is the VP of AI and Data at Amazon Web Services.
• He shares how while AI may cause short-term job displacement, it offers long-term productivity gains.
• He suggests that workers use AI to take over mundane tasks so they can do more valuable work.

The era of generative AI has arrived, bringing both promise and caution. Many people are wondering if AI can coexist peacefully and productively alongside a broad human workforce with diverse talents, skills, and abilities.

I believe that AI isn't coming to take away jobs — it's coming to take away tasks. 80% of employees' time is consumed by low-value, repetitive, time-intensive, uninteresting tasks, while only 20% gets devoted to the more interesting activities that generate higher value for the organization.

What if we could flip that ratio? What if we could free humans to solve, build, and create? That's what I believe AI can do. In the process, this new AI paradigm can unlock the value of an accelerated and more fulfilling career. I strongly believe that what we invent today can lead to a profound impact on the world — changing industries and people's lives.

Marie Kondo-ing with AI

Thoughtfully deployed, generative AI can remove drudgery and help people find more meaning in their work. It can free you to work on the parts of your job that are more interesting and more valuable — the reasons you got into your profession in the first place.

I think the Marie Kondo principle applies: If the task doesn't spark joy, let AI take it from you. Our goal must be to kindle (or rekindle) our joy, to bring out curiosity and creativity, and to reimagine what's possible, now that we're no longer burdened with an assortment of mundane tasks. In a sense, AI can give each of us a job promotion, not be a job replacement.

There will be short-term displacement but it will self-correct

Of course, the widescale adoption of Gen AI will have impacts and implications, and it would be foolhardy to ignore them. Increased productivity and greater cost efficiencies will inevitably lead to short-term workforce displacement — for example, contact centers with faster resolution times need fewer workers.

However, I believe that AI will also play a self-correcting role in such a macroeconomic picture. Efforts must be made to close wage disparities and potential economic or opportunity gaps. Community colleges should offer guided and hands-on training to ensure AI is accessible to the broadest areas of our workforce. Similarly, technology companies must offer low-cost or free training and certification programs to promote AI's widespread adoption and use.

I believe AI can cut the time for this upskilling process in half and foresee a world where nearly anyone can be an app builder and creator or where a junior technician can do senior-level repairs.

Decisions should still be made by humans

Whether it's conversational search, agent assistants, image creation, or other forms of intelligent automation, AI becomes a supportive foundation that translates into time — time to evaluate, investigate, strategize — and solves problems.

AI will give us access to a nearly limitless set of highly accurate, data-driven predictions. Nonetheless, decisions shouldn't be automated. They should remain the sole province of humans, who have a better understanding of tradeoffs, nuances, and strategies.

Here are some examples of how humans can work alongside AI:

• Customer Care: Gen AI can provide agents with personalized, real-time responses and prompts based on customer questions and interactions. Agents then exercise their judgment to use them.
• Manufacturing Design: Engineers can use AI to create digital twins to simulate interactions and their effects with far greater speed and far less expense before they decide on a design.
• Consumer Behavior: Gen AI can predict the preferences and responses of groups or individual buyers. This will allow marketers to focus on how to optimize campaigns and offers.
• Drug Discovery: With Gen AI, scientists can slash the time required for drug discovery, accelerate therapy development, and find vaccines that are cheaper and more accessible.
• Media: By automating the difficult art and production aspects of games and entertainment, Gen AI frees designers to create and ideate more. It can even create personalized gaming experiences.
• Financial Services: Gen AI can strengthen fraud detection and compliance while increasing the efficiency of loan officers making lending decisions.

By being able to focus on decisions and outcomes, we unlock new creativity that we can channel to solving bigger and harder problems. With this new era of generative AI discovery, there has never been a better time to transform businesses and work as we know it.

Dr. Swami Sivasubramanian is the Vice President of AI & Data at AWS. His team's mission is to help organizations leverage the power of AI and data to solve their most urgent business needs.

If you're an AI expert and would like to share your opinions on the impact of AI on the future of work, email Jane Zhang at [email protected].

• Amazon on Friday announced another $4 billion investment in the AI startup Anthropic.
• The deal includes an agreement for Anthropic to use Amazon's AI chips more.
• The cloud giant is trying to challenge Nvidia and get developers to switch away from those GPUs.

Amazon's Trainium chips are about to get a lot busier — at least that's what Amazon hopes will happen after it pumps another $4 billion into the AI startup Anthropic.

The companies announced a huge new deal on Friday that brings Amazon's total investment in Anthropic to $8 billion. The goal of all this money is mainly to get Amazon's AI chips to be used more often to train and run large language models.

Anthropic said that in return for this cash injection, it would use AWS as its "primary cloud and training partner." It said it would also help Amazon design future Trainium chips and contribute to building out an Amazon AI-model-development platform called AWS Neuron.

This is an all-out assault on Nvidia, which dominates the AI chip market with its GPUs, servers, and CUDA platform. Nvidia's stock dropped by more than 3% on Friday after the Amazon-Anthropic news broke.

The challenge will be getting Anthropic to actually use Trainium chips in big ways. Switching away from Nvidia GPUs is complicated, time-consuming, and risky for AI-model developers, and Amazon has struggled with this.

Earlier this week, Anthropic CEO Dario Amodei didn't sound like he was all in on Amazon's Trainium chips, despite another $4 billion coming his way.

"We use Nvidia, but we also use custom chips from both Google and Amazon," he said at the Cerebral Valley tech conference in San Francisco. "Different chips have different trade-offs. I think we're getting value from all of them."

In 2023, Amazon made its first investment in Anthropic, agreeing to put in $4 billion. That deal came with similar strings attached. At the time, Anthropic said that it would use Amazon's Trainium and Inferentia chips to build, train, and deploy future AI models and that the companies would collaborate on the development of chip technology.

It's unclear whether Anthropic followed through. The Information reported recently that Anthropic preferred to use Nvidia GPUs rather than Amazon AI chips. The publication said the talks about this latest investment focused on getting Anthropic more committed to using Amazon's offerings.

There are signs that Anthropic could be more committed now, after getting another $4 billion from Amazon.

In Friday's announcement, Anthropic said it was working with Amazon on its Neuron software, which offers the crucial connective tissue between the chip and the AI models. This competes with Nvidia's CUDA software stack, which is the real enabler of Nvidia's GPUs and makes these components very hard to swap out for other chips. Nvidia has a decadelong head start on CUDA, and competitors have found that difficult to overcome.

Anthropic's "deep technical collaboration" suggests a new level of commitment to using and improving Amazon's Trainium chips.

Though several companies make chips that compete with or even beat Nvidia's in certain elements of computing performance, no other chip has touched the company in terms of market or mind share.

Amazon's AI chip journey

Amazon is on a short list of cloud providers attempting to stock their data centers with their own AI chips and avoid spending heavily on Nvidia GPUs, which have profit margins that often exceed 70%.

Amazon debuted its Trainium and Inferentia chips — named after the training and inference tasks they're built for — in 2020.

The aim was to become less dependent on Nvidia and find a way to make cloud computing in the AI age cheaper.

"As customers approach higher scale in their implementations, they realize quickly that AI can get costly," Amazon CEO Andy Jassy said on the company's October earnings call. "It's why we've invested in our own custom silicon in Trainium for training and Inferentia for inference."

But like its many competitors, Amazon has found that breaking the industry's preference for Nvidia is difficult. Some say that's because of CUDA, which offers an abundant software stack with libraries, tools, and troubleshooting help galore. Others say it's simple habit or convention.

In May, the Bernstein analyst Stacy Rasgon told Business Insider he wasn't aware of any companies using Amazon AI chips at scale.

With Friday's announcement, that might change.

Jassy said in October that the next-generation Trainium 2 chip was ramping up. "We're seeing significant interest in these chips, and we've gone back to our manufacturing partners multiple times to produce much more than we'd originally planned," Jassy said.

Still, Anthropic's Amodei sounded this week like he was hedging his bets.

"We believe that our mission is best served by being an independent company," he said. "If you look at our position in the market and what we've been able to do, the independent partnerships we have Google, with Amazon, with others, I think this is very viable."