Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

IonQ outlined it roadmap for its quantum computing stack as well as various use cases as it aims to create enterprise grade infrastructure that could offload GPU workloads if successful.

In a webinar, IonQ CEO Peter Chapman said the company's strategy revolves around performance, scale and enterprise grade infrastructure. If those pillars are weighted equally, IonQ will generate commercial advantage for its quantum computers.

IonQ is approaching $100 million in annual bookings.

Chapman positioned IonQ as a company that's defining use cases and doubling down on the ones with the most promise. "I think we're homing in on exactly what those superpowers are," said Chapman.

Chemistry and quantum drug discovery have emerged as two primary use cases. The chemistry use cases were barely mentioned during IonQ's pre-IPO roadshow, but has emerged as a go-to enterprise application. "There is some brilliant work on the algorithmic chemistry coming," said Chapman.

Constellation ShortListsâ„¢

• Quantum Computing Platforms
• Quantum Computing Software Platforms
• Quantum Full Stack Players

Generative AI is another area where IonQ can add value, said Chapman, who said IonQ has been focused on machine learning since inception. "One of the new things that we're doing this year is applying quantum to large language models," said Chapman. "We're just at the beginning of that journey, but I hope to have results within a year or so."

If successful, Chapman said IonQ "will be able to offload significant workloads from GPUs and significantly reduce energy requirements for data centers and LLMs."

The focus of IonQ's talk is about developing performance with its roadmap, lowering errors and then scaling. "We hope to find commercially significant applications, but the true promise of quantum will need a lot more qubits and faster gate speeds," said Chapman. "Just as importantly we'll need to network these quantum computers and reduce the costs to make them affordable. Future quantum computers are going to be made up of network individual machines so the cost per qubit comes down as computational power increases."

Chapman said the plan is not to over index on performance, scale or enterprise grade because the pillars have to be in balance.

IonQ SVP of Engineering & Technology Dean Kassmann walked through the IonQ roadmap, developing multi-core quantum infrastructure and systems that go beyond what can be simulated on a classical computer. Kassmann also emphasized modular designs, systems that will be put into data centers with classical infrastructure and software that just works.

The plan for IonQ is to get to a point where it can stack its qubits and technology advances together. "A milestone we have planned for 2025 is physical qubits that are photonically interconnected," said Kassmann. "We have a plan set out where we continually build up numbers of qubits by connecting modules together."

Kassmann added that IonQ is focusing on photonic interconnects between quantum systems to scale as well as smaller vacuum packages and refining components. "The work we're doing needs to be on-ramped into the larger engineering pipeline but represents our thought process to scale 2-, 5-, 10-years from now," he said.

Margaret Arakawa, CMO of IonQ, is a Microsoft alum that is focusing on democratizing quantum computing and scaling with its US manufacturing center in Seattle. To sell quantum--an enterprise category that has typically been more about R&D labs--IonQ plans to lead into use cases and solving big problems.

Some use cases include solving for corrosion in the US Navy, which is an expensive problem for the Department of Defense, Airbus optimization and flight orchestration. "We have an applications and algorithm team working on the most important groundbreaking areas a quantum computer can actually address," she said.

In the end, AI may wind up being the play for quantum computing. Arakawa and Chapman both spoke to it and the general idea is to focus on the part of AI that quantum computing can do better than supercomputers.

More quantum computing:

• Classiq CEO Minerbi on the intersection of quantum computing, HPC and use cases
• Quantinuum, Microsoft claim quantum reliability breakthrough
• IBM launches latest Heron quantum processor, IBM Quantum System Two
• Quantinuum raises $300 million, valued at $5 billion
• Will IonQ make quantum computing enterprise relevant in 2025?
• Why your quantum computing vendors are going to look familiar

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Verizon is betting that its network--5G and fiber--can be the "backbone of the AI economy" with a boom of edge computing generative AI workloads on deck. The problem is Verizon hasn't seen real revenue yet but appears to be leveraging generative AI to become more efficient.

Speaking on Verizon's second quarter earnings call, CEO Hans Vestberg outlined the genAI use cases on the revenue and cost side. Vestberg said:

"We will power the best AI services for our customers. What set us apart with AI is our network's mobile edge computing capabilities and deep fiber footprint. By processing data closer to the source, we enable real-time AI application that requires security, ultra-low latency, and high bandwidth. Our network will be at the forefront of AI and mobile edge compute applications."

For operations, Vestberg said AI is benefiting customer service by routing calls to agents, improving network design and personalizing offers. CFO Tony Skiadas said:

"AI is an enabler of efficiencies. You can think about customer care, you can think about the personalization with myPlan. And we see efficiencies coming from there as well."

In many respects, Verizon resembles many enterprises. Companies are leveraging generative AI to save money and become more efficient. The revenue side of the equation isn't quite baked yet. Enterprises have been expanding generative AI use cases, offering takeaways from projects underway and figuring out how the technology fits in with broader digital transformation.

Progress Through The Five A's of AI | Margin Compression - Tech Vendors Are You Leading The Way Or In The Way? | Enterprises start to harvest AI-driven exponential efficiency efforts

Verizon reported second-quarter revenue of $32.8 billion with net income of $4.7 billion. The results were roughly flat with a year ago. Verizon Business revenue was $7.3 billion, down 2.4% from a year ago.

Verizon sees enterprises building out private 5G networks

Vestberg said Verizon has more line of sight into the enterprise business and genAI than the consumer opportunity, which will depend on adoption of smartphones and features lead to device upgrades. Vestberg said:

"I think where I'm most excited is that we have built the Verizon Intelligent edge network which will be the platform for GenAI. You are going to have to have a lot more compute storage at the edge of the network, and that's how we built the network already 2018 with fiber to all our main hubs and between our main subcenters. On top of that, we have cooling and power at those edges. As we go from the LLMs into commercial products for enterprises our network is set up for that. I'm very excited for that opportunity to go forward together with private networks. There are a lot of things coming into GenAI devices, our efficiencies and a business opportunity for us when it comes to AI."

The problem for Verizon is that the genAI mobile edge payoff isn't here yet. Vestberg said Verizon doesn't have genAI in mobile edge computing to customers but it's clear in conversations with cloud vendors and enterprises that large language models will move to the end points.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

SAP in the second quarter said its cloud revenue was up 25% and CEO Christian Klein said its Business AI efforts are "enabling many deals." The company reiterated its outlook for 2024 and raised its 2025 operating profit guidance due to efficiency efforts.

The company also said its restructuring efforts will impact 9,000 to 10,000 jobs. SAP said in January it expected to cut 8,000 jobs.

For the quarter ending June 30, SAP said its SaaS and PaaS revenue was €4.02 billion, up 28%. Cloud ERP revenue was €3.41 billion, up 33%. The Cloud ERP Suite revenue line includes services that are included in RISE with SAP. SAP S/4HANA Cloud, SAP Business Technology Platform, and applications for HR and payroll, spend management, commerce, customer data, business process transformation, and working capital management also fall under Cloud ERP.

• SAP’s Joule everywhere plan: ‘We are not developing AI just for the sake of AI”
• SAP acquires WalkMe for $1.5 billion
• SAP user group DSAG rips S/4HANA innovation plans, maintenance increases
• Amazon Bedrock integrated into SAP AI Core, SAP to use AWS chips

SAP reported second-quarter revenue of €8.29 billion, up 10% from a year ago, with €918 million in net profit. Earnings per share were €0.76. Non-IFRS earnings per share were €1.10.

In a statement, Klein said "our cloud growth momentum remained strong in Q2, with Business AI enabling many deals." He added that SAP is well positioned to see "accelerating topline growth through 2027."

CFO Dominik Asam added:

"We are staying squarely focused on delivering our outlook for this year. Our current cloud backlog growth during the second half of 2024, and especially in Q4 will be decisive to lay a solid foundation for our cloud revenue ambition for 2025. At the same time, we'll continue to execute against our transformation plan to achieve our 2025 free cash flow ambition despite a mid-triple-digit million cash out for restructuring spilling into next year."

On an earnings conference call, Klein said SAP is landing and expanding as it moves large enterprises to the cloud. "Since Sapphire, we have seen a lot of additional interest from big customers, over 90 partner use cases for co-innovation, including use cases with big systems integrator," said Klein. "Sapphire also helped to significantly boost our pipeline. It's not just a lift and shift to the cloud. It's a holistic offering to increase competitiveness through a deep business transformation to replace the legacy ERP with our modular cloud ERP."

Klein said he was confident that SAP was executing well and seeing a "land and expand" cadence at large enterprises like Exxon." He added that SAP is also investing in SMBs with partners. 

By the numbers for the second quarter:

• Current cloud backlog was up 28% to €14.81 billion.
• Software license revenue fell by 28% to €0.2 billion.
• SAP had repurchased 12,895,525 shares at an average price of €145.20 as of June 30.

SAP also said that its restructuring program is expected to finish in early 2025. SAP said the restructuring will affect 9,000 to 10,000 positions, but the company expects headcount to be similar to 2023.

As for the outlook, SAP projected €17.0 billion to €17.3 billion cloud revenue for 2024, up 24% to 27% from 2023 with €29.0 billion to 29.5 billion in cloud and software revenue for the year.

For 2025, SAP projected non-IFRS operating profit of approximately €10.2 billion, up from previous guidance of €10 billion. The rest of SAP's 2025 outlook remains the same including cloud revenue of more than €21.5 billion and total revenue of more than €37.5 billion.

• SAP, IBM Consulting pair up on process transformation, genAI
• BT150 CXO zeitgeist February edition: Low marks for SAP RISE, process automation, change management, AI risk
• SAP's Supervisory Board to nominate Ala-Pietilä as Plattner successor, Renjen to resign
• SAP's German speaking user group takes aim at cloud contracts, BTP and more
• SAP retools for generative AI, cuts 8,000 jobs, sets 2024, 2025 ambition

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Enterprises are beginning to leverage AI and widen their profit moats just as some companies are seeing customers wobble. The efficiency gains are beginning to highlight how digital transformation and AI strategies are becoming self-funding, keeping expenses below the rate of inflation and optimizing processes.

Not surprisingly, the companies that are using AI leverage happen to be in regulated industries and enterprises that have previously invested in data and digital transformation. Why? These companies tend to have strong data quality, governance and strategies.

The payoff from these AI and data transformation efforts will be critical if and when customers pull back on spending. A growing number of CEOs sound like Shelley Simpson, CEO of J.B. Hunt.

"While admittedly the market has been challenging, we have invested throughout this downturn to set us up for future growth and success across the business. We continue to focus on controlling expenses in the near term without jeopardizing our long-term potential, managing our headcount through attrition, while at the same time continuing to deploy and enhance our technology to increase the productivity of our people," said Simpson.

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

Here are 6 vignettes to ponder from enterprise technology's buy side and how companies are driving toward exponential efficiency. These scenes are part of an ongoing series looking at generative AI use cases, takeaways from projects underway and how the technology fits in with broader digital transformation.

Progress Through The Five A's of AI | Margin Compression - Tech Vendors Are You Leading The Way Or In The Way?

Bank of America

Bank of America expects to spend almost $4 billion on technology initiatives this year focused on AI for its employees and clients. The bank's client insights tool has served up more than 6 million insights to financial advisers to give them proactive reasons to engage.

CEO Brian Moynihan said Bank of America's mobile banking app has more than 47 million active users and digital sales are now 53% of total sales for its consumer business. On the cost side, Bank of America has saved money by streamlining client service requests using AI.

And digital is more than cost. "Digital adoption and engagement continue to improve, and customer satisfaction scores remain near record levels, illustrating customer appreciation of our enhanced capabilities due to our continuous investment," said Moynihan.

The leverage in Bank of America's digital strategy is also in what it calls its "operational excellence platform." Bank of America in its second quarter held its expense growth to 2% from a year ago and below inflation rates.

Bank of America has also kept headcount roughly flat. Moynihan said the company has managed expenses well with the help of AI and digital. "We have huge cleanup stuff going on. We have the new initiatives that free up work," he said.

• Why digital, business transformation projects need new approaches to returns
• Return on Transformation Investments (RTI)
• How 4 CEOs are approaching generative AI use cases in their companies

PepsiCo

In the second quarter, PepsiCo CEO Ramon Laguarta said consumers are being more selective as inflation takes a toll on household budgets. PepsiCo organic revenue growth was 1.9% in the quarter compared to 13% a year ago.

The upshot is that PepsiCo is hitting the limits of price increases. PepsiCo saw its annual revenue surge nearly $7 billion between 2020 and 2023, but noted that "the impacts of persistent inflationary pressures and higher borrowing costs over the last few years have resulted in tighter household financial conditions. Consumers have become more value-conscious with their spending patterns and preferences across brands, packages, and channels."

With consumers becoming tapped out, PepsiCo plans to fund investments going forward with productivity savings. PepsiCo has its process optimization game down.

The company plans to:

• Invest in more automation within warehousing, transportation and logistics.
• Advance its digitization efforts and harmonize IT systems.
• Optimize processes across the value chain.
• Enhance analytics for trade promotions, consumer insights, supply planning and demand forecasting.
• And optimize advertising and marketing spend.

Laguarta said: "We're managing total PepsiCo operating margin and as you've seen, we keep improving the margin. This quarter had almost 100 bps of operating margin improvement, and it's been consistent for the last few years. We feel good about our productivity pipeline, it’s not tactical, it's super strategic and it's multiyear and it's based on automation, it's based on digitalization, simplification of the company, standardization, different service models to the business. So, there is a whole portfolio of productivity ideas that are multiyear in nature and we don't think that we will slow down our productivity in the coming years."

UnitedHealth Group

UnitedHealth reported better-than-expected second quarter results as it grows revenue and optimizes operations. CEO Andrew Witty said: "Our growing AI portfolio made up of hundreds of practical use cases will generate billions of dollars of efficiencies over the next several years. These investments enable us to improve consumer experience, enhance provider find and price care capabilities to meet people's needs and improve clinical back-office execution. We expect technology innovation to become an increasingly core driver of our growth over the next two to five years."

UnitedHealth is still taking an earnings hit due to the Change Healthcare cyberattack, but its focus on efficiencies is minimizing the bottom line hit.

Witty said the AI use cases identified by UnitedHealthcare will drive margins and cost savings through the next two years. Witty added that AI and process improvements go together and that AI will create a "fundamental reimagination of business processes" and "allow an existing process to run more efficiently.”

"We actually take steps out of a process and really start to change things. I'd call out payment integrity as a front-runner in that particular regard," said Witty.

A few examples:

• UnitedHealth onboarded a record number of OptumRx customers but spent 9% less this year than last year due to digitization.
• OptumHealth added nearly more than 1.5 million customers with zero increase in personnel headcount in risk-based businesses.
• UnitedHealth is proactively engaging with three-fourths of its members using technology, up from 62% a year ago.

Witty said UnitedHealth is doubling down on its own cost management efficiency and productivity and that focus "coincides with an extraordinarily and exciting moment around technological innovation, whether that's Generative AI, digitization, all wrapped together in our march toward a greater consumer focus within the organization."

Omnicom Group

Omnicom said it has expanded its genAI efforts for both clients and internal use cases.

The advertising and public relations giant's genAI strategy revolves around becoming more efficient and selling products and services to clients. CEO John Wren said on the company's second quarter earnings call: "We also announced first-mover collaborations with Adobe, Amazon, Getty, Google and Microsoft's OpenAI to gain early access to their large language models. Just over a year later, we're seeing these generative AI platforms' tools and partnerships being activated throughout every area of our business from strategy to creative to production, media and precision marketing."

For instance, Omnicom's TBWA unit launched Collective AI, a suite of tools for employees and clients that automates basic tasks and then provides insights. Collective AI uses TBWA's archives to train large language models. ArtBotAI is a content orchestration platform to create digital assets and personalized experiences.

Omnicom also acquired Flywheel, which focuses on retail media and e-commerce. The idea is to combine Flywheels' commerce product and transaction signals with Omnicom's audience and viewership data, said Wren, who noted that Omnicom has also centralized production to go along with the AI investment.

"From Gen AI to e-commerce to production, we are continuing to enhance our offerings to meet our clients' needs for better inform strategic insights using AI, creatively inspired content that can be personalized at scale and investments in targeted media that can be measured through quantifiable outcomes, all delivered in the most efficient and effective manner," said Wren. "We decided that the only way that we're going to efficiently and effectively grow, especially in this AI environment, which is going to change those legacy production businesses was in fact to centralize it."

Goldman Sachs

Goldman Sachs' CEO David Solomon has talked up the company's AI initiatives before. He said the company has leveraged AI for multiple use cases ranging from coding to equity research and content.

"We are focused on how you can create use cases that increase your productivity," said Solomon. "If you look and you think across the scale of our business, I think you can think of lots of places where the capacity to use these tools to take work that's always been more manual and allow the very smart people to do that work to focus their attention on clients."

Solomon said the AI spending boom is real and can drive productivity and revenue gains. Solomon said: "I am particularly encouraged by the ongoing advancements in artificial intelligence. Recently, our Board of Directors spent a week in Silicon Valley where we spoke with the CEOs of many of the leading institutions at the cutting-edge of technology and AI. We all left with a sense of optimism about the application of AI tools and the accelerating innovation in technology more broadly. The proliferation of AI in the corporate world will bring with it significant demand-related infrastructure and financing needs, which should fuel activity across our broad franchise."

WD-40

While many of the examples revolve around AI, it's worth noting that there are plenty of companies doing the data strategy heavy lifting to take advantage of the technology later. WD-40 is a good example.

WD-40 CFO Sara Hyzer said on the company's third quarter earnings conference call that it is updating its ERP system, launching Salesforce and looking to "drive productivity via enhanced systems."

Hyzer said WD-40 went live with the first phase of its ERP system across much of its business including the US, Latin America and Asia regional distributor businesses. The implementation resulted in some minor disruptions in the third quarter, but most of the critical issues have been resolved.

"We know there is still work to do and have several enhancements that are already being worked on, which is not unexpected at this phase of the project. Most importantly, we have gained numerous learning moments from this implementation, allowing us to make process improvements and become more proactive," said Hyzer.

The other move for WD-40 is to roll out Salesforce in the US to drive sales efficiencies and reduce costs. "We also know that use of data analytics and automated tools, leveraging data is increasing and can be a real enabler for the business," said Hyzer. "The foundational work we are doing now around data governance, centralizing our data architecture and data quality management will allow our people to leverage our data quicker and drive better decision-making."

Insights Archive

• GenAI may be the new UI for enterprise software
• Education tech in turmoil amid genAI: Why consolidation is next
• 14 takeaways from genAI initiatives midway through 2024
• OpenAI and Microsoft: Symbiotic or future frenemies?
• AI infrastructure is the new innovation hotbed with smartphone-like release cadence
• Don't forget the non-technical, human costs to generative AI projects
• GenAI boom eludes enterprise software...for now
• The real reason Windows AI PCs will be interesting
• 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
• Financial services firms see genAI use cases leading to efficiency boom

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Global IT outages on Friday were blamed on a faulty update from CrowdStrike and the impact hit banks, airlines and a host of other companies. But the real hit--beyond CrowdStrike's stock price--was to the platformization play being pitched by cybersecurity vendors.

First, the news. Reddit threads, X posts and various corporate accounts are showing the Blue Screen of Death (BSOD), CrowdStrike support messages and unhappy IT admins. The outage is so bad that CrowdStrike CEO George Kurtz had to play IT admin.

In a post on X, Kurtz said:

"CrowdStrike is actively working with customers impacted by a defect found in a single content update for Windows hosts. Mac and Linux hosts are not impacted. This is not a security incident or cyberattack. The issue has been identified, isolated and a fix has been deployed. We refer customers to the support portal for the latest updates and will continue to provide complete and continuous updates on our website. We further recommend organizations ensure they’re communicating with CrowdStrike representatives through official channels. Our team is fully mobilized to ensure the security and stability of CrowdStrike customers."

By the way, the replies are a gem.

Once the dust settles and IT admin tears dry, the real pain is going to be to the cybersecurity platformization argument. You know the one. Cybersecurity vendors tell CIOs they need to be on one platform to consolidate budget, discounts are handed out and we all go on our secure way with AI-driven solutions.

Palo Alto Networks started this platformization play to battle with CrowdStrike, which is taking budget and a platform.

• CrowdStrike, Palo Alto Networks duel over platforms vs. bundles
• CrowdStrike delivers strong Q1 amid cybersecurity platform debate
• Palo Alto Networks launches platform deals as it aims for cybersecurity share
• Palo Alto Networks Q3 solid, says customers into platform play

The problem with consolidated platforms is that they also serve as single points of failure. The fact that CrowdStrike can push a Friday (!!) update and bring down transportation and financial systems is a bit alarming. Monoculture was seen as a threat to security and now you can put platformization in the mix.

Here's the good news: This CrowdStrike fiasco wasn't a cyberattack. Rest assured; cybercriminals are taking notes.

Constellation Research’s take

Constellation Research analyst Chirag Mehta recapped the fallout from the CrowdStrike outage.

Response from CrowdStrike

CrowdStrike’s response to the recent disruption reads more like a message from an IT administrator than a CEO. George neither explicitly took full responsibility nor apologized for the lapse in care. This lack of accountability is likely to result in angry customers and potential lawsuits, as the disruption has caused significant business continuity challenges.

Platformization and Single Point of Failure

The platformization strategy, where an organization controls the platform and confines others to operate within it, has its risks. It can create a single point of failure (SPOF). Palo Alto’s recent push towards platformization may attract more scrutiny, as customers are wary of being locked into a single platform that could become a SPOF.

EDR/MDR Vendors are Now Spooked

Other EDR and MDR vendors are fortunate that they were not affected this time. They now can evaluate the depth of their integration with operating systems, the methods of air-gapping their updates, and their deployment processes. Overconfidence can be dangerous.

Microsoft Can’t Catch a Break

Although this incident is not technically Microsoft's fault from a Windows or Defender perspective, the company is now entangled in it. Microsoft has been feverishly working to improve its security reputation, but this situation highlights inherent flaws in Windows' architecture and the level of kernel access required by third-party products like CrowdStrike. It serves as a reminder of the large attack surface of Windows, especially older, unpatched versions. It may be time for OS vendors to rethink their core architectures.

Handling Single Points of Failure

Firewall vendors are well aware of the critical importance of their software. A faulty update or poorly managed DDoS attack can shut down entire networks. Cloud providers excel at managing updates and securing environments against DDoS attacks. They often emphasize the security of their distributed cloud infrastructure, which is harder to bring down. Cloud providers, responsible for their own environments, have developed sophisticated practices for testing updates, deploying quickly, isolating incidents, and rolling back changes. I would expect them to talk up their security, especially Google who has growth ambitions in cybersecurity. This will also make it clear why Google is after Wiz who has an agentless approach for cloud security.

Agentless Approach Gets Spotlight

This incident highlights the potential of an agentless approach in various cybersecurity domains, where modifications to the underlying operating system are avoided. This is particularly relevant in OT security within sectors like healthcare, transportation, and aviation, where proprietary devices should not be altered. For instance, the FDA prohibits third-party agents on most healthcare devices to ensure their integrity and functionality.

CrowdStrike Again?

CrowdStrike seems to gain attention for all the wrong reasons. The last time the average person heard about CrowdStrike was during the 2016 presidential campaign when Trump mentioned it in the context of Hillary Clinton’s emails. Despite building a substantial clientele among Fortune 500 companies, CrowdStrike learned today that this prominence can be a double-edged sword.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

Infosys is seeing stronger spending from financial services firms as that industry begins to spend more on scaling generative AI. That demand recovery also aligns with what financial services executives have been saying on earnings calls.

Financial services firms have been among the most aggressive with generative AI implementations because their data strategies are solid due to being regulated. Simply put, financial services firms have a lighter lift when it comes to making the jump to AI-driven projects.

The financial services spending recovery cited by Infosys was also evident in results from Persistent. If this early recovery sticks it'll highlight how generative AI spending is moving beyond infrastructure. 

Infosys reported fiscal first quarter revenue of $4.71 billion with net income of $764 million. Persistent reported first quarter revenue of $328.2 million, up 16% from a year ago.

Speaking on a conference call, Infosys CEO Salil Parekh said the company saw 7.9% sequential revenue growth in financial services. Compared to a year ago, financial services revenue was flat, but Infosys is seeing green shoots in the US. Persistent saw financial services growth of 7.6%.

Parekh said:

"Along with our overall robust performance in Q1 and strong opportunity pipeline, we are seeing early signs of improvement in financial services vertical in the US. While discretionary spends continues to be under pressure, a highly differentiated offering around driving efficiencies at scale and transformation capabilities around generative AI have positioned us well in the market."

Parekh said financial services firms are doing the following:

• Discretionary spending is still under pressure.
• There are a lot of ongoing discussions about generative AI.
• Firms are focusing on efficiency, consolidation and automation.
• Mortgage companies, capital markets and credit card processing are seeing more volume and early signs of recovery.
• Infosys is working on actual genAI projects as they've graduated beyond proofs of concept.

Constellation Research analyst Chirag Mehta said:

"Engineering, Research, and Development (ER&D) services are gaining significant traction, fueled by notable acquisitions in the industry. Infosys' acquisition of a service provider in-tech, focused on German automotive sector, and Cognizant's acquisition of a service provider Belcan, focused on U.S. aerospace and defense service provider, have invigorated the ER&D sector, which is poised to benefit from AI innovations. The manufacturing industry, particularly heavy industries, stands to gain immensely from these AI-driven advancements.

Additionally, Persistent's intent to acquire Starfish Associates, an AI-powered contact center, and its strategic partnership with Google Cloud to develop industry-specific GenAI solutions, highlight a robust commitment to AI adoption. This aggressive move is aimed at capturing a significant share of the growing customer spending on AI solutions."

The general tone among the financial services, banks and insurance companies has been upbeat about genAI. At a recent AWS event in New York, a bevy of customers outlined various use cases.

• Financial services firms see genAI use cases leading to efficiency boom
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JPMorgan Chase at its investor day outlined how AI has moved beyond a central group to being part of every business unit.

"It's not understanding AI. It's understanding how it works," said Jamie Dimon, CEO of JPMorgan Chase. By the end of the year, Dimon estimated that JPMorgan Chase will have about 800 AI use cases across the company as management teams become better at deploying AI. He added:

"We use it for prospect, marketing, offers, travel, notetaking, idea generation, hedging, equity hedging, and the equity trading floors, anticipating when people call in what they're calling it for, answering customer, just on the wholesale side, but answering customer requests. And then we have – and we're going to be building agents that not just answers the question, it takes action sometimes. And this is just going to blow people's mind. It will affect every job, every application, every database and it will make people more efficient."

• JPMorgan Chase: Digital Transformation, AI and Data Strategy Sets Up Generative AI
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Daniel Pinto, Chief Operating Officer and President at JPMorgan Chase, said the company has moved to transform its data so it's usable for AI and analytics. There will also be a central platform to leverage that data across business units. "AI and particularly large language models, will be transformational here," said Pinto.

Goldman Sachs' CEO David Solomon has talked up the company's AI initiatives before. He said the company has leveraged AI for multiple use cases ranging from coding to equity research and content during the company's second quarter earnings call.

"We are focused on how you can create use cases that increase your productivity," said Solomon. "If you look and you think across the scale of our business, I think you can think of lots of places where the capacity to use these tools to take work that's always been more manual and allow the very smart people to do that work to focus their attention on clients."

Solomon said the AI spending boom is real and can drive productivity and revenue gains. Solomon said:

"I am particularly encouraged by the ongoing advancements in artificial intelligence. Recently, our Board of Directors spent a week in Silicon Valley where we spoke with the CEOs of many of the leading institutions at the cutting-edge of technology and AI. We all left with a sense of optimism about the application of AI tools and the accelerating innovation in technology more broadly. The proliferation of AI in the corporate world will bring with it significant demand-related infrastructure and financing needs, which should fuel activity across our broad franchise."

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.&nbsp; <br>Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and… Read more

TSMC’s second quarter earnings were better-than-expected and the chip manufacturer is becoming a barometer for generative AI infrastructure demand. High-performance computing (HPC) is now more than half of TSMC's revenue.

In addition, TSMC’s ability to be bleeding edge has made it the go-to partner for every generative AI infrastructure player including Nvidia and AMD, two companies moving toward an annual GPU cadence. 

• AI infrastructure is the new innovation hotbed with smartphone-like release cadence

TSMC's second quarter revenue was $20.92 billion, up 32.8% from a year ago, with earnings of $1.48 per American Depository Receipt unit. TSMC is projecting third quarter revenue to be between $22.4 billion and $23.2 billion.

Here are the takeaways from TSMC's second quarter earnings call.

Demand for AI processors is still well ahead of supply. TSMC CEO C.C. Wei said the company is working hard to meet customer demand, but supplies of AI chips will remain tight. "We are working very hard to get enough capacity to support customers from now to next year and 2026," said Wei. "The supply continues to be very tight, all the way through probably 2025 and I hope it can be eased in 2026. That's today's situation."

TSMC is disciplined about adding capacity. "Our capital investment decisions are based on four disciplines, that is, technology leadership, flexible and responsive manufacturing, retaining customers' trust, and earning a sustainable and healthy return. To ensure a proper return from our investment, both pricing and cost are important. TSMC's pricing strategy is strategic, not opportunistic to reflect the value that we provide," said Wei.

Wei said TSMC won't repeat the same mistakes made in 2021 and 2022 where demand was driven by pandemic and shortages and not sustainable.

AI demand is more durable than previous boom-bust cycles. "AI demand is more real than two or three years ago," said Wei. "AI will be a very useful tool for human to improve productivity. Everything will need AI."

Wei noted that TSMC is also in line to buy its customers' products because it is leveraging AI to be more productive. Nevertheless, TSMC wants to make sure customers are realistic about future demand for AI chips. "We have a top-down bottom-up approach and discuss with our customers and ask them to be more realistic. I don't want to repeat the same kind of mistake two or three years ago, and that's what we are doing right now," said Wei.

AI will drive PC and smartphone processor demand. Wei noted that customers are all looking to put AI functionality into edge devices, but don't have a handle on demand and replacement cycles yet. He said that AI is likely to drive edge processor demand in about two years.

TSMC will raise prices, but each customer and category are different. Wei noted that doubling capacity isn't cheap--$30 billion to $32 billion in capex for 2024--and TSMC hasn't been able to meaningfully boost the gross margins. TSMC executives repeatedly said the company will "sell the value" so that customer wins also filter down to it.

Wei said: "This is an ongoing and continuous process, and we are continuing to sell our value. And by the way, my customers are doing very well also. You knew that. So, we should do well also."

"When TSMC wants to expand the capacity, we need the land, we need the electricity and we need the talented people," said Wei. "All of my customers are looking for leading-edge capacity for the next few years and we are working with them to support them, both in pricing and in capacity."

The company is ready for an annual GPU product cadence. Wei said typically every processor takes 1.5 years to 2 years to move from design to production. Nvidia gave TSMC the heads up a while ago. "We have been prepared. And not just from June when they announced it, but much earlier," said Wei.