What Are the Top 5 Hyperscalers?

Alphabet, Amazon, Apple, Meta Platforms and Microsoft are the five largest, most comprehensive hyperscalers in the world by a wide margin. This group of Tier 1 hyperscalers are collectively referred to as MAMAA.

 

TBR research shows only the Tier 1 hyperscalers can transcend most, if not all, of the major lifestyle categories to provide a seamless end-to-end ecosystem experience, touching all aspects of people’s lives, primarily due to their scale and access to resources.
 

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The World’s Largest Hyperscalers Are Positioned to Win an Outsized Share of the New Opportunities Created in the Digital Era

Tier 1 hyperscalers have momentum as they pursue their end-to-end digital ecosystem goals. Key reasons why hyperscalers will succeed in their digital ecosystem endeavors include:

• Scale
• Network effect
• Proficiency at building and scaling platforms
• Adept at translating data into outcomes
• Near limitless financial resources
• Access to the best talent
• Have the best legal teams
• Control essential intellectual property and patents (e.g., devices, chipsets, AI/machine learning algorithms, Lidar)
• Tax advantaged — pay relatively little in taxes

Tier 1 Hyperscalers Intend to Own and Control Critical Aspects of the Value Chain in the Digital Era

The End Goal: Full-scope Digital Ecosystems

TBR believes the top 5 hyperscalers will own and control foundational and critical aspects of the digital economy and capture an outsized portion of the value created during the digital era.

• Societies will become dependent on their clouds.
• The majority of internet traffic will run over their networks.
• Transportation will be directed by their self-driving technologies.
• A significant portion of financial transactions will be processed via their payment platforms.
• And much, much more

 

If current trends play out, and assuming interference from regulators remains manageable, TBR believes MAMAA will ultimately become fully integrated, end-to-end digital ecosystem owners, providing essential solutions for businesses and consumers worldwide.

 

At a high level, hyperscalers are all pursuing the same strategy, which is to maximize the value of data. All of the Tier 1 hyperscalers are entering similar markets, introducing similar products and services, investing in similar technology areas, and pursuing similar business models. The underlying goal is to provide an immersive, seamless, end-to-end digital experience to end users (consumers and businesses), which will maximize hyperscalers’ value capture in the digital era. Value in its most basic form resides in the data that hyperscalers have access to, but leveraging that data to produce outcomes is how the hyperscalers make their money.

As Hyperscalers Redefine Digital Ecosystems, Industry Consolidation and Adaptation Become Essential for Long-Term Relevancy

As hyperscalers build out their ecosystems, some incumbent entities will become marginalized and fail, and the remaining incumbent players across industries will have to consolidate, adapt and/or partner with hyperscalers in some way or risk fading from relevancy. The markets for IT, advertising, retail, media, entertainment, financial services and other industries are already facing this disruption. TBR believes transportation, healthcare, education, telecom and other industries will also experience hyperscaler disruption during this decade.

 

The lifeblood of the digital era is data, and the heart is the systems, platforms, marketplaces and other digital infrastructure that make use of that data. Hyperscalers have thus far created the most compelling digital infrastructure that is capable of amassing, synthesizing, automating and utilizing vast amounts of data, which is the key underlying reason why they have been so successful in creating economic value over the past two decades.

Leidos’ Domestic DOD, Intel and National Security Operations Are Seeing Modest to Moderate Growth

Leidos’ reorganization is delivering positive results, particularly down the company’s income statement, where profitability reached record levels in 1H24. Midsingle-digit top-line growth is being buoyed by strong bookings activity with the Department of Defense (DOD) and civilian agencies.

 

Leidos’ top-line expansion is also being driven by the continued surge in program volumes in Leidos Health, which itself is sustaining year-to-year sales growth and operating margins near 20%. Outside of federal IT, Leidos’ Australia subsidiary is parlaying the company’s innovations in military-grade cybersecurity and software into new growth avenues in the fast-expanding Australian defense sector.
 

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3Q24 Vertical Analysis

National Security & Digital (NSD)

NSD is booking new work with the DOD to modernize existing software platforms and implement new software that will accommodate future advanced weapons systems and digital technologies like AI-enhanced battlespace solutions. Leidos’ DevSecOps capabilities heavily underpin NSD’s efforts to enable the DOD to achieve its “Army of 2030” concept. NSD is also actively touting the potential benefits of GenAI for national security and DOD missions by addressing the upfront ethical and security risks of GenAI for defense and national security agencies.

Defense Systems (DS)

Sequential margin improvement for DS owes to efforts to optimize contract delivery. DS houses Dynetics, where activity is accelerating to develop satellite, force protection and hypersonics solutions for the DOD. Margins in DS will improve further in 2H24 as programs in these three areas transition from the R&D phases to production and delivery to clients.

Health & Civil (H&C)

Underpinning H&C’s robust performance of five straight quarters of double-digit growth as of 3Q24 are higher program volumes in H&C’s managed health services (medical examinations, diagnostic tests and automated reporting – delivered principally through Leidos’ QTC Health Services subsidiary) and disability exam programs with the VBA (Veterans Benefits Administration).

 

H&C was also awarded a five-year $326 million contract in 3Q24 with the National Institutes of Health (NIH) for Agile software development to modernize NIH’s grant management system, further extending H&C’s relationship with the NIH. (H&C provides scientific and operational support to the NIH’s 27 institutes and centers.)

Commercial & International (C&I)

Top-line growth for C&I, which includes Leidos’ commercial energy, international and Security Enterprise Solutions (SES) operations, is holding at low-single-digit rates. Segment expansion owes to higher program volumes in Australia, accelerating activity in Leidos’ energy unit and the continued rebound of Leidos’ now-restructured SES group.

 

For more data and analysis on Leidos’ 3Q24 performance, as well as TBR’s entire federal IT research stream, start your TBR Insight Center™ free trial today.

 

Shift to Maintenance Services Bolsters Telecom Infrastructure Services Margins Amid 5G Deployment Declines and U.S. Market Contraction

Despite India growing within the telecom infrastructure service revenue mix and the U.S. declining, TBR-benchmarked vendors’ average telecom infrastructure services operating margin increased 20 basis points year-to-year to 14.2% in 2023. TBR attributes the increase in large part to a shift in the telecom infrastructure services revenue mix from deployment services, which typically carry the lowest margins, to maintenance services, which tend to carry the highest margins among telecom infrastructure services segments.

 

The shift in business mix comes as communication service providers (CSPs) wind down their 5G coverage rollouts in the key countries of China, the U.S. and India and focus on densification. In late 2023 and 1H24, declining deployment activity in India is also helping to improve profitability as margins in the country can be relatively low. The 5G gear that vendors have built out in these and other countries in the past few years is leading to follow-on support revenue, which will enable maintenance services to be a relatively strong-performing segment among TBR-benchmarked vendors despite global decommissioning of legacy infrastructure.

Telecom Infrastructure Services Operating Margin Insights

Leading Vendors Remain Those with Large Bases of Hardware or Software Support Subscriptions and Those that Rely Heavily on India-based Labor

Operating margin leaders derive a smaller percentage of telecom infrastructure services revenue from deployment services, which are often provided at or below break-even margins and/or delivered by third parties. Leaders provide a high degree of support, including repeatable and remote services as well as consulting & systems integration services.

 

Automation, analytics, AI and machine learning will prove critical to helping vendors improve margins. Examples include portions of Nokia’s AVA (Analytics, Virtualization and Automation) portfolio and Ericsson’s Operations Engine. However, with a significant portion of revenue coming from deployment services, RAN-centric vendors will be unable to expand overall telecom infrastructure services margins significantly.

 

India-based IT firms such as Tata Consultancy Services and Infosys obtain high telecom infrastructure services margins due to favorable labor rate differentials between India and developed markets as well as the high degree of application development and maintenance services they provide to CSPs in developed markets. With over 40% of its workforce based in India, Accenture also benefits from this market dynamic.

 

Other IT services firms, such as Atos, have a smaller offshore workforce (about 32% based in India) and obtain lower margins as a result.

 

To access TBR’s historical and current telecom infrastructure gross margin data, start your free Insight Center™ trial today.

Generative AI (GenAI) clients are looking for offerings that complement existing technologies and use cases built around customer zero and that deliver fast ROI. In this blog, we highlight some of the GenAI use cases currently seen in the professional and IT services, cloud, IT infrastructure, and telecom industries. To learn more about TBR’s AI and GenAI analysis and data, start your TBR Insight Center™ free trial today!

 

Perhaps no two questions have bedeviled the business side of the GenAI space more than which use cases are resonating with clients and where TBR and others expect to see near-term adoption and growth.

 

According to TBR’s research, use cases that provide a quick ROI with minimal enterprisewide disruption and no significant increase in risk profile get funded now; use cases with demands on data, dependencies on external data and/or long horizons to ROI remain the subjects of innovation sessions, proofs of concepts and road maps.

As Multimodal AI Extends GenAI’s Promise, Buyers Still Seek Immediately Effective Use Cases

Different from traditional large language models (LLMs), multimodal AI can process and interpret several types of data inputs, including text, images and sounds, at the same time. This versatility makes multimodal models critical for expanding the viable use cases for GenAI, specifically to support the creation of marketing content.

 

According to TBR’s latest research, multimodal AI is currently a top five use case for GenAI. Cloud service providers and foundation model vendors alike have made efforts to internally develop multimodal models or form collaborations to harness GenAI’s data interpretation capabilities. TBR believes cloud service providers and foundation model vendors will drive innovation of multimodal models to improve data interpretation and insights across all business segments.
 

GenAI Use Cases Across Industries

Professional and IT Services GenAI Use Cases

• In February 2024 Cisco launched Motific, a SaaS solution that enables adoption and application of GenAI in support of clients’ needs around data, security, AI and overall cost reduction. Through Motific, Cisco speeds up GenAI deployment while using automated controls to reduce the risks associated with the technologies. Leaning on its security prowess, Cisco applies its risk management tools, sensitive data capabilities and monitoring services to protect clients’ environments.
• Hewlett Packard Enterprise (HPE) introduced HPE GreenLake for LLMs, a cloud service that provisions AI-optimized high-performance computing resources designed for dedicated single-workload utilization, setting itself apart from public cloud resources that share infrastructure and run multiple workloads.
• Through its partnership with ServiceNow, EY looks to apply GenAI to risk management and governance. In June 2024 EY adopted ServiceNow’s Assist GenAI capabilities to facilitate its internal operations as well as drive innovation in AI risk and regulatory compliance needs.
• Some ongoing Leidos AI initiatives include helping the Department of Defense make training and other materials more easily accessible and improving the efficiency of new software testing using digital twinning solutions. GenAI also increasingly features in Leidos’ digital transformation work, as the company utilizes the technology to expedite the mapping of legacy IT infrastructures, which in turn accelerates downstream systems modernization. Leidos has also developed AI-based natural language solutions enabling military operators to interact more easily with autonomous drones deployed in contested environments.
• Infosys launched the Responsible AI suite, which includes accelerators across three main areas: Scan (identifying AI risk), Shield (building technical guardrails) and Steer (providing AI governance consulting). These capabilities will help Infosys strengthen ecosystem trust via the Responsible AI Coalition as well as foundation models and emerging startups. These models and startups are increasingly important among clients, many of which are reaching a point of fatigue and confusion amid a slew of GenAI-related announcements.

Cloud GenAI Use Cases

• Staying true to its history of releasing nascent services to the market and building them up into more feature-rich offerings over time, Amazon Web Services (AWS) recently launched new capabilities for Bedrock. For example, Custom Model Import allows customers to automatically pull entire Bedrock models they have already customized, likely with SageMaker, into the Bedrock interface. This allows customers to access their own custom model through the Bedrock API interface like they would with any other model from third parties, such as Anthropic and Cohere. The feature, in addition to other built-in tools native to Bedrock, reaffirms AWS’ commitment to making the service the best place to not only access out-of-the-box models but also customize them and develop applications that will ultimately spin the IaaS meter on AWS infrastructure.​
• Google Cloud is putting Gemini to work, embedding the LLM into core Google Cloud Platform (GCP) products, from BigQuery for analytics use cases like data preparation and query recommendation to Looker for conversational analytics and automated BI. With these features and capabilities, Gemini is now at the heart of Google Cloud’s portfolio and replaces the existing Duet AI tool, which Google Cloud touted as its “always-on AI collaborator” in both GCP and Workspace just a few months ago. Google Cloud’s rapid transition from Duet AI to Gemini speaks to how quickly the GenAI space is evolving, as new vendors enter the market with out-of-the-box LLMs and incumbents expand context windows to make models more powerful and capable of handling more complex tasks.

IT Infrastructure GenAI Use Cases

• Dell Technologies and Supermicro have seen rapid growth with their 8-GPU servers certified on NVIDIA’s HGX platform and continue to add new liquid cooling options, networking choices and accelerator variants. In recognizing the opportunity in this market segment, Lenovo recently announced its first competing server.
• HPE’s AI server strategy primarily revolves around its Cray supercomputers and delivering solutions through its flagship HPE GreenLake platform, although the company has also rolled out a smaller validated server stack with NVIDIA.
• IBM is incorporating AI into its mainframe business through its Telum processor and close integrations with the watsonx platform.

Telecom GenAI Use Cases

The telecom industry is contemplating hundreds of use cases for GenAI, including those that are an evolution of traditional AI, such as chatbots.

Customer care:

• Chatbots (intelligent versus static) to handle higher-level customer issues
• Bill explainer
• Dynamic, contextualized prompts for care agents
• Foreign language support
• Truck route optimization

Administrative functions:

• Meeting transcription — notes/summarization
• Legal document creation
• Corporate document querying

IT:

• Code development
• Advanced threat detection and autonomous rectification

Sales:

• First pass at creating proposals
• Dynamic, contextualized prompts for salespeople
• Offer customization and personalization

Marketing:

• First pass at creating marketing materials

Network:

• Code development
• Performance monitoring
• Advanced alarm management

 

Digital Transformation Market Status

As Digital Transformation Programs Mature, So Do Buyers’ Expectations, Testing Vendors’ Engagement and Partner Strategies

As the most mature digital transformation component, customer experience (CX) has compelled buyers to embark on omnichannel projects to unify insights and processes across the customer life cycle for years now. Vendors have plenty of use cases to rely on, but slower discretionary spend is pressure-testing vendors’ value propositions rooted in trusted algorithms.

 

The digital marketing services space, as tracked by TBR, will expand at a CAGR of 6.5% from 2023 to 2028, reaching $145 billion, which is lower than our forecast from six months ago of $152 billion. The marketing industry is on the cusp of transformation with the advent of generative AI (GenAI) chatbots, particularly in relation to content development and brand safety. Vendors have an opportunity to optimize personalization at scale, but only if they also address talent management and data protection, compelling them to carefully balance messaging across ecosystem stakeholders.
 

Watch Below: TBR Principal Analysts Discuss How the GenAI Disruption Is Similar to Prior Disruptions, as well as How It Is Different, and Which Technology Vendors Are Best Positioned to Win and Why

GenAI Remains the Single Most Disruptive Technology, Testing Vendors’ Ability to Deliver Transparent Campaigns Through Ecosystem Lenses

Since we began estimating the digital marketing services market seven years ago, we have projected annually that Strategy and Creative & Branding services would grow the fastest. Creative & Branding served as the DNA of digital marketing, and brands have constantly sought guidance on how to adapt to operating in digital environments.

 

GenAI will change that, as the technology has the potential to bring the cost of content development to $0. This will pressure Creative & Branding revenue growth but also test vendors’ analytics models as the spending shifts toward Advertising & Analytics services, provided vendors ensure that transparency, governance and clear data strategies are in place.

Examples of Vendors’ Recent Digital Transformation Activities

• Ogilvy launched Influencer Shield, a risk management solution that helps target opportunities around brand safety.
• Bain strengthened its footprint in APAC with the acquisition of the consulting and managed services division of Max Kelsen, an Australia-based AI and machine learning solution provider.
• Accenture Song has been chosen as the global creative and content agency of record for the talent company Randstad. Accenture Song will also support the transformation of Randstad’s marketing department through the use of GenAI.
• AKQA launched a new campaign for IBM, showcasing the transformative power of IBM Hybrid Cloud using visuals and a cinematic storytelling approach.
• McKinsey & Co. launched its Salesforce-enabled Growth Tech capability. The service will pair McKinsey’s AI modules from QuantumBlack and help the firm pursue business transformation opportunities with clients seeking to optimize the Salesforce stack.
• Capgemini and Salesforce partner to provide GenAI for CX Foundry to deliver personalized and data-driven customer experiences by automating customized content creation.
• IBM Consulting launched a practice that helps clients create AI foundation models and large language models utilizing open-source approaches and proprietary data to train purpose-specific AI models through IBM’s InstructLab solution. IBM is also expanding the IBM Consulting Advantage portfolio by adding new assistants, assets and methods that will support specific consulting roles, and client engagements around application modernization and management as well as data and business process transformation.

 
TBR’s Digital Transformation: Digital Marketing Services Benchmark provides key service line, regional and operational data and analysis across 19 leading digital marketing services vendors. Vendor coverage includes Accenture, Capgemini, Deloitte, HCLTech, IBM Consulting, McKinsey & Co., Tata Consultancy Services, and more. Service lines covered are Strategy, Creative & Branding, Web, Mobile & Commerce, and Advertising and Analytics. To access all available Digital Transformation: Digital Marketing Services Benchmark data and analysis, start your free Insight Center™ trial today.