Amazon Bedrock integrated into SAP AI Core, SAP to use AWS chips

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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Amazon Bedrock from AWS will be embedded into SAP's generative AI hub as the two companies expanded a long-running partnership. SAP will also use AWS Graviton3, Trainium and Inferentia chips for SAP HANA Cloud and SAP Business AI workloads.

Ahead of SAP Sapphire, Amazon Web Services said Amazon Bedrock will be integrated into SAP AI Core so joint customers can mix and match large language models (LLMs) with corporate data.

Enterprises frequently run SAP on top of AWS infrastructure. For its part, SAP is trying to make it easier for customers to migrate to S4/HANA and cloud applications via its RISE with SAP program.

The AWS and SAP expanded partnership has multiple pieces, but the integration of Amazon Bedrock into the SAP platform is the most noteworthy. The integration will give SAP customers more options for foundational models and enable them to swap as genAI improves.

Among the key parts of the integration:

• Models within Bedrock can be used for embedded use cases within RISE with SAP as well as SAP Business Technology Platform.
• Bedrock tools will be available in SAP's generative AI hub across the application portfolio.
• Use cases will cover finance, product lifecycle management and other areas. 

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In addition, the companies said SAP will use AWS Graviton3 chips for its SAP HANA Cloud. SAP said Graviton3 on AWS EC2 instances have improved cost, performance and carbon footprint. AWS and SAP will also collaborate on the next generation of Graviton4 for SAP workloads.

"SAP plans to use AWS Graviton to support SAP solutions and applications such as SAP BTP, SAP Datasphere, SAP Analytics Cloud, and the SAP Cloud ALM solution," the companies said.

SAP added that it will use AWS Trainium and Inferentia chips for AI and machine learning workloads in future SAP Business AI offerings. SAP engineers have already built out proof of concept projects to train and tune LLMs.

And finally, Amazon Project Kuiper will join other business units running on SAP for supply chain and other applications.

More on genAI:

• Copilot, genAI agent implementations are about to get complicated
• Generative AI spending will move beyond the IT budget
• Enterprises Must Now Cultivate a Capable and Diverse AI Model Garden
• Secrets to a Successful AI Strategy
• Return on Transformation Investments (RTI)
• Financial services firms see genAI use cases leading to efficiency boom
• Foundation model debate: Choices, small vs. large, commoditization

Box's Q1 offers insights to its long-term content, AI vision

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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Box is seeing customers upgrade to its enterprise content management suite to get access to Box AI and there's a big opportunity in mining unstructured data, workflows and vertical use cases. But the payoff to Box will take time.

To say Box CEO Aaron Levie is enthusiastic about what generative AI can do for unstructured data and content management is an understatement. The company launched Box AI recently, acquired Crooze and has an architecture that allows it to add new models--including OpenAI's GPT-4o. It doesn't hurt to have partnerships with the likes of Nvidia and ServiceNow either.

During Box's first quarter earnings call, Levie said the company is seeing an increasing number of customers upgrade to its Enterprise Plus plan for Box AI. Demand has been across multiple industries. For instance, a commercial real estate company is using Box AI to find trends across leases, analyze client dynamics and generate marketing content.

Levie said:

"All of the insights necessary to create better business decisions and smoother business processes are living inside of an enterprise's content. It's the key data points inside of contracts that help businesses close new deals. The assets that create a major new ad campaign, the manufacturing and R&D files that enables the next breakthrough product to ship on time and the financial documents that help close the books smoothly. Yet for as important as all of this unstructured data is, and it makes up 90% of our corporate information, we've never been able to fully extract all of the value from it."

Box's bets revolve around AI transformation bets on workflow and collaboration. Box AI for Hubs, which is rolling out to Enterprise Plus customers, users can ask questions across multiple documents and give enterprises retrieval augmented generation use cases from the content repository.

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Levie is also bullish on content metadata.

"With Box AI, customers will soon be able to extract metadata from a large number of document and content types within their enterprise. Once you have metadata on content, you can automate almost any workflow in the enterprise, from invoice processing and contract management to digital asset management and clinical trial management. This is why we acquired Crooze back in December, and we are working aggressively to natively integrate Crooze's no code application building and metadata features into Box to support powering content centric workflows on Box."

Box, which has integrations with all of the primary players in the enterprise stack, is looking to be an abstraction layer connecting AI models to content. "We are at a major moment as an industry. With AI, the role of unstructured data in enterprises has exploded," said Levie. "We will look back on this as a defining period for how work was shaped for decades to come."

What’s the problem?

Box's vision is on target, but its growth isn't showing it. In the first quarter, Box had revenue of $265 million, up 5% from a year ago. The company has about 1,800 customers paying more than $100,000 annually. The attach rate for suites on those large deals was 85%. Box Suites is 56% of Box's revenue. Earnings per share were 39 cents a share, 3 cents a share better than estimates.

The company also raised its fiscal 2025 outlook with adjusted earnings of $1.54 a share and $1.58 a share on revenue of $1.075 billion and $1.08 billion, up 4%.

Constellation Research analyst Holger Mueller said:

"Box is doing all things on the R&D side from a growth perspective – and should grow well in the teens if not twenties. The question remains if it is customer loss or commoditization of basic capabilities that does not allow the whole industry to show growth that is in line with the growth of business relevant electronic information that is growing 30-40% every year. The reality is that the Future of Work for knowledge workers is filled with a lot of “blood sweat and tears” from manual labor around documents."

To drive growth Box will have to expand its market. Levie noted that customer spending on Box still largely comes from the IT budget. AI spending is moving beyond IT and into other business units, but that movement is still early. Levie said:

"If we maybe fast forward a year or two from now, I could see that the budget increases when you look at line of business that will be able to drive more efficiency because of AI, that we're only in the earliest days of what that looks like. But certainly, as AI really drives workflow automation and more business process transformation, I think you'll see even increased budget that opens up for AI use cases around content."

With Hubs just launching in beta, it's unclear how demand and interest will shape up into revenue growth.

Box's master plan for AI and its "scaffolding, abstraction layer and platform services" vision makes sense since every model needs content access. How long this vision takes to play out remains to be seen.

Cybersecurity platformization: What you 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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Platformization is the buzzword du jour in cybersecurity circles. The general idea is that enterprises are consolidating vendors and will ultimately bet on one platform to solve for cybersecurity.

Palo Alto Networks earlier this year set off the debate with a plan to bet that it could be the leading cybersecurity platform. Although the company said it has seen strong interest from customers, it's far too early to say the debate is settled. After all, CrowdStrike and a bevy of others also have platform plans.

But we've seen this movie before. Platformization isn't exactly new. It's a strategy that has been deployed in enterprise software for decades and mainframes before that. The benefit is customers get one throat to choke. The downside is you bet on a platform and lose your negotiation leverage.

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With that backdrop, I caught up with Constellation Research analyst Chirag Mehta, who noted the potential risks of platformization in a Wall Street Journal article.

Here are some of the takeaways.

Two perspectives of platformization (vendor and customer). "Platformization is not something new. The word sounds new, but it's been in existence for many years," said Mehta. "A vendor tries to create a single platform where it can control the experience that end users get since data is shared across applications without requiring explicit integrations. The platform shares the common fabric. You can think about the operating system as a platform."

And the customer gets more simplicity. "From a customer perspective it's a best of breed versus best of suites approach. Best of breed is specific niche vendors who provide functionality that you really care about. And you have many of those, and some of them talk to each other. Some of them don't talk to each other. Best of suite you trust one vendor to do many, many different things and you expect that the vendors roadmap will align with your business needs."

When platformization bites back. Mehta said the issue with platformization occurs when you bet on a vendor that doesn't meet your needs. For instance, the enterprise resource planning space had multiple vendors, but the industry has consolidated. There aren't ERP startups to drive innovation. "It's very difficult to compete against a best of suite vendor," said Mehta. "It becomes difficult for a CXO to make a business case to buy something outside of the best of suite. You might see benefits in the short term because you are consolidating multiple applications on one platform, but in the long run it always costs more and limits the choices you have."

Mehta added:

"You want to be really careful if you are going down the road of platform migration because of how much influence you're going to have on that platform, what your roadmap is, and how open that platform is, and whether it works with some of the other solutions that you have today, or you might consider in the future."

Is the cybersecurity industry maturing enough to bet on one platform? The short answer from Mehta is no. He said:

"Cybersecurity is far from mature when it comes to the business processes, categories, specific functionalities or use cases. It's still a very specialized domain and fragmented landscape. If you look at the innovation that is happening there are many startups doing amazing things. At the same time, there are few large vendors but there are very few of them. There are many midsized vendors. So, the domain is not mature. And the processes are not mature at all."

Open platforms matter. Mehta said CXOs should evaluate platforms based on how open they are. "I'm not against platform isolation, but openness is key," said Mehta. "Many operating systems have been open. You can go build applications. If the platform is not very easy to plug into--technology, ecosystem and commercial advantage--you can be in a difficult situation. If you are going to have multiple systems, spend the time and energy to make sure the platform is actually open."

The importance of data in cybersecurity. Mehta said the importance of data in cybersecurity from telemetry is critical. Any bet on a platform has to be able to integrate data from multiple systems. "More data and more information from different systems actually improves your security posture," said Mehta. "If and when you decide to go down the platformization route make sure you understand how it fits into your overall landscape."

The real reason Windows AI PCs will be interesting

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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Microsoft and its merry band of PC makers launched AI PCs at scale. The launch of Copilot+ PCs, ahead of Microsoft Build 2024, was notable for a host of reasons once you get past how executives were a bit obsessed with outperforming Apple's MacBook.

Consider:

• The first Copilot+ PCs will launch with Qualcomm's Snapdragon X Elite and Snapdragon X Plus processors. The rollout of AI PCs is big for Qualcomm and the Arm PC ecosystem.
• Microsoft did say that it will have AI PCs powered by AMD and Intel paired with Nvidia and AMD GPUs. AMD CFO Jean Hu said at an investor conference that the chipmaker will outline its AI PC processors in "coming weeks." "It's a very exciting product and very competitive to power the AI applications in the PC market. We do believe AI PC is a very significant inflection point. It will potentially help refresh the PC market," said Hu.
• Businesses can easily add AI PCs to the mix with the same controls they do today. Copilot+ PCs are billed as a productivity and collaboration booster.
• Copilot+ PCs have neural processor units (NPUs) capable of more than 40 trillion operations per second. In other words, a lot of inferencing work can be done on the edge.
• During his Build 2024 keynote, Microsoft CEO Satya Nadella said there are 40 models included into Copilot+ PCs including its new Phi-3 models, OpenAI's GPT-4o and other small language models as well as large ones. "We have 40 plus models available out of the box including Phi-3 Silica, our newest member of our small language family model designed to run locally on Copilot+ PCs to bring that lightning-fast local inference to the device. The copilot library also makes it easy for you to incorporate RAG (retrieval-augmented generation) inside of your applications on the on-device data,” said Nadella.
• Features like Recall, which makes your PC a recorder of all of the information, relationships and associations. Recall can help you remember items to create individual experiences. Cocreator and Live Captions are additional AI-driven features.

Add it up and CIOs are going to start testing these Copilot+ PCs and pondering their refresh cycles. Perhaps there's a future of work or productivity play to be had. The reality is that CIOs probably have more business transformation projects with higher priority rankings.

This post first appeared in the Constellation Insight newsletter, which features bespoke content weekly and is brought to you by Hitachi Vantara.

But what's surprising is how the big picture was glossed over with the Copilot+ PC launch. If these AI PCs scale, you're going to have a lot of computing power at the edge that can be used for inferencing and potentially even training.

Think peer-to-peer networked model inference. Smartphones are increasingly building in the capacity for AI models. Now you add in PCs. Generative AI can be decentralized from the AI factory vision that's popular today. Generative AI requires costly computing infrastructure. Why wouldn't you offload some of that work to the nodes on the edge?

For businesses, this emerging distributed AI computing system could mean using the PC to run models for personal identifiable information (think mortgage applications) and build personalized apps on the fly. You could automate any process that touches a customer using that person's compute power.

Are we there yet? Not really since these AI PCs just launched and it's doubtful any of these features are going to cause a buying frenzy. But PCs are already past their normal shelf life so the refresh cycle will drive some demand.

And the economic incentives are there to figure out a more peer-to-peer computing approach. At some point, enterprises are going to grow weary of paying up for AI compute. Finding a way to leverage AI PCs in the field could be a salve. There's a reason Dell Technologies considered AI PCs as part of its AI factory vision.

More on genAI:

• Copilot, genAI agent implementations are about to get complicated
• Generative AI spending will move beyond the IT budget
• Enterprises Must Now Cultivate a Capable and Diverse AI Model Garden
• Secrets to a Successful AI Strategy
• Return on Transformation Investments (RTI)
• Financial services firms see genAI use cases leading to efficiency boom
• Foundation model debate: Choices, small vs. large, commoditization

Intuit sees 'green shoots' from its generative AI strategy

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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Intuit CEO Sasan Goodarzi said generative AI is increasing the company's total addressable market as TurboTax users flocked to its data, AI and virtual expert platform. Now the company has learned from its genAI efforts, Intuit will double down on what's working. 

"TurboTax live revenue is expected to be $1.4 billion representing approximately 30% of total consumer revenue growing at a significant scale. This gives us confidence that we can digitize a very manual, disaggregated and high price assisted category," said Goodarzi on Intuit's third quarter earnings call.

Under Goodarzi, Intuit has built out its data platform on AWS and then scaled into generative AI. He said genAI financial assistance played a big role in the TurboTax experience. Goodarzi added that 24 million customers used intuitive AI to explain refunds, answer questions and check for accuracy.

Customer story: Intuit’s Bet on Data, AI, AWS Pays Off Ahead of Generative AI Transformation

"GenAI is working at scale for both our customers and our AI powered experts. I'm excited about what we're working on for next season to accelerate innovation and deliver even more customer benefit," he said.

Now that Intuit has one tax season of generative AI enhancements in the books, it can revamp experiences and add new models as needed via Amazon Bedrock and other services. The current generative AI models are much more advanced than a year ago. 

Goodarzi said Intuit is looking to AI to reinvent customer experiences and drive revenue growth. He reiterated the big bets for genAI on TurboTax and QuickBooks.

"To increase our investments in the outline focus areas given the green shoots we're observing, we are taking a hard look at what we can stop doing and where we can reallocate investments to accelerate top line growth while remaining committed to delivering operating margin expansion in fiscal year 2025 and beyond," said Goodarzi.

Goodarzi's remarks were on Intuit's third quarter earnings call. The company reported third-quarter revenue of $6.7 billion, up 12% from a year ago, with earnings per share of $8.42 a share. Non-GAAP earnings were $9.88 a share.

As for the outlook for the fiscal year, Intuit expects TurboTax Live revenue to grow 17% to $1.4 billion and average revenue per return to increase 10%.

Overall, Intuit said its fiscal 2024 revenue will be between $16.16 billion to $16.2 billion, up 13%. Non-GAAP earnings will be $16.79 a share to $16.84 a share. Small business and self-employed group revenue will be up 18% and consumer revenue up 7% to 8%.

More on genAI:

• Copilot, genAI agent implementations are about to get complicated
• Generative AI spending will move beyond the IT budget
• Enterprises Must Now Cultivate a Capable and Diverse AI Model Garden
• Secrets to a Successful AI Strategy
• Return on Transformation Investments (RTI)
• Financial services firms see genAI use cases leading to efficiency boom
• Foundation model debate: Choices, small vs. large, commoditization

Workday reports strong Q1, says 25 generative AI use cases on roadmap

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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Workday reported a strong first quarter as the company leveraged AI within its platform and continued to become more efficient.

The company reported first quarter net income of 40 cents a share, non-GAAP earnings of $1.74 a share and revenue of $1.99 billion, up 18.1% from a year ago. Wall Street was expecting Workday to report earnings of $1.58 a share on revenue of $1.97 billion.

Workday said its 12-month subscription revenue backlog was $6.6 billion, up 17.9% from a year ago. Total subscription revenue backlog was $20.68 billion, up 24.2% from a year ago.

Carl Eschenbach, Workday's CEO, said customers are looking to manage through the "shifting talent landscape, and pressure to realize operational efficiencies."

According to Workday, the company has more than 50 AI use cases in production and 25 generative AI use cases on the roadmap. Workday also expanded a partnership with AWS and formed a partnership with Google Cloud.

Workday CFO Zane Rowe said the "we were pleased with our progress across key growth initiatives in Q1, which help build a foundation for long-term growth." He added: "Our updated subscription revenue guidance reflects the elevated sales scrutiny and lower customer headcount growth we experienced during the quarter."

As for the outlook, Workday projected fiscal 2025 subscription revenue of $7.7 billion to $7.725 billion, up 17%, with non-GAAP operating margins of 25%. For the second quarter, Workday projected subscription revenue of $1.895 billion, up 17%, with non-GAAP operating margins of 24.5%.

Insights:

• Workday to buy HiredScore amid mixed Q4
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• Generative AI spending will move beyond the IT budget
• Workday lays out growth plans through fiscal 2027: Here are the takeaways

On a conference call with analysts, Eschenbach said the first quarter is typically Workday's slowest. He said Workday outperformed in healthcare, public sector and financials. 

"When purchase decisions are being made, our win rates remain strong but within the quarter, we experience increased deal scrutiny as compared to prior quarters. And we are seeing customers committing to lower headcount levels on renewals compared to what we had expected," he said. "We expect these dynamics to persist in the near term, which is reflected in our revised FY 25 subscription revenue guidance. While we can't control the macro, we are focusing on what's in our control. And that is innovation, scaling our go to market engine and partner ecosystem and delivering customer value."

Workday executives also said they are often selling full platform plays and that sales cycle is longer. 

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Eschenbach said more than 90% of the company's nearly 2,000 financial customers also have HCM. 

On AI, Eschenbach said:

"We've built AI into the core of our platform, which means AI features and functionality are embedded natively in all of our applications. And with more than 65 million users generating more than 800 billion transactions per year on our platform, the volume of clean, trusted data that workday and our ecosystem can leverage for AI is truly unmatched. We continue to make significant investments to further enhance our leadership in this area in deliver trusted and responsible AI innovations that drive meaningful business results. We now have more than 50 ai use cases live in production in 25 generative AI use cases on our roadmap."

These use cases are primarily content generation, job descriptions and knowledge base articles as well as insights for things like payroll and talent optimization.

Eschenbach said Workday is building out its partner ecosystem and go-to-market efforts. Workday is also building out its ecosystem via Extend, a marketplace for Workday platform applications. Workday's AI marketplace will go live next month with AI tools from the company and third parties. 

Constellation Research's take

Constellation Research analyst Holger Mueller said:

"Workday had a good first quarter, just missing the $2 billion overall revenue milestone by $10 million. And with that it grew itself back to a profit compared to last year's quarter. But margins are tight, with net income of just over $100 million. The good news is that Workday keeps innovating, with generative AI use cases coming soon, as well as the addition of Australia with native payroll. Now all eyes are on Q2. Can Workday keep growing, break the $2B in revenue and control costs?"