Telecom Infrastructure Services: Navigating the Post-peak 5G Era and Future Growth Opportunities

The telecom infrastructure market (TIS) market is shaping up to bring good news outstripped by bad as the pace of decline slows toward the end of 2024, led by U.S. federal government spend. Join TBR Senior Analyst Michael Soper Thursday, June 20, at 1 p.m. EDT/10 a.m. PDT for a TBR Insights Live session detailing findings in our latest Telecom Infrastructure Services Global Market Forecast.
 
TBR research shows spend in the TIS will retreat in 2024 after a substantial decline in 2023 due to 5G deployments in China and the U.S. entering the post-peak stage. However, growth in 2025 and 2026 is expected as government stimulus aimed at bringing broadband internet speeds to underserved and unserved areas drives higher spend.
 
During this live event, Michael will discuss include digital transformation initiatives and the implementation of complex technologies such as multivendor open vRAN driving professional services growth and intensifying hyperscaler investment in the access layer. Additionally, he will identify headwinds that will limit market growth and create a negative revenue curve in 2027, including legacy decommissioning, telcos’ more conservative cash management posture and increasing consolidation.

 


 

In This FREE TBR Insights Live Session on the Telecom Infrastructure Services Market You’ll Learn:

  • Where will the limited opportunities for growth be found
  • Key growth drivers and detractors expected in the TIS market through 2028
  • How government spend and geopolitics will influence the TIS market
  • Which vendors are positioned to capitalize on trends in the TIS market

 

TBR Insights Live sessions are held typically on Thursdays at 1 p.m. ET and include a 15-minute Q&A session following the main presentation. Previous sessions can be viewed anytime on TBR’s Webinar Portal.
 
For additional information or to arrange a briefing with our analysts, please contact TBR at [email protected].

Fusion Data Intelligence Propels Oracle to Full-stack Cloud Provider

TBR Perspective

TBR joined industry analysts at Oracle’s (NYSE: ORCL) former headquarters in Redwood City, Calif., for the one-day Oracle Analytics & AI Summit, which centered on trends, advancements and use cases in the world of analytics and generative AI (GenAI). While we did not shatter any course records on the Oracle Red Bull Racing simulator, we did grasp how Oracle is addressing one of the top trends we see in the market: Cloud computing has become table stakes in digital transformation, and customers are shifting their focus to the data and how it can be translated into actionable insights.

 

In five years, Oracle has consolidated Oracle Analytics Cloud (OAC) and launched prebuilt cloud-native analytics solutions for each of its four Fusion apps suites. Oracle is now embarking on a new frontier with Fusion Data Intelligence (FDI), the intelligent analytics layer that will fuse Oracle’s roles as both a SaaS and IaaS provider in the race for GenAI workloads.
 

New Intelligent Data Layer Elevates Oracle’s Role as Full-stack Cloud Provider

At TBR, we often talk about how Oracle uniquely serves the entire cloud stack at scale with infrastructure, platform services and applications. With its strengths solidified in database and back-office apps, the rapid emergence of Oracle Cloud Infrastructure (OCI) is rounding out Oracle’s full-stack narrative, driving a greater level of stickiness with customers looking to consolidate point solutions and potentially reduce costs.

 

But we are seeing an inflection point in the market. Cloud computing has become a standard component to digital transformation in some capacity, and buyers are shifting their focus to the data; specifically, how they can access and integrate cross-departmental data to capitalize on GenAI and streamline their business.

 

With finance, sales and HR data already sitting in Fusion applications — which are native to OCI — and an OCI lakehouse architecture built on trusted database services (e.g., Exadata, MySQL Heatwave), Oracle has a unique ability to build out an intelligent data analytics layer that cements Oracle’s role as both an IaaS and SaaS provider. We are seeing this firsthand with FDI.

 

Announced at Oracle Cloud World 2023, FDI marks a shift in the Oracle Analytics strategy to focus less on addressing one-and-done tasks but more on making analytics part of an ongoing, integrated process with additional AI models. For instance, FDI still draws on the platform foundation of OAC and the four Fusion Analytics modules (ERP, Supply Chain Management [SCM], Human Capital Management [HCM] and Customer Experience [CX]) but also incorporates new prebuilt models for predictive and prescriptive insights within those Fusion applications. For example, in Fusion HCM, these models might support analytics use cases for continuous listening, diversity analysis and employee skill matching.

Because of Fusion Applications, Oracle Analytics Can Close the Loop on Business Processes

With the Fusion applications suite, Oracle Analytics has always had a unique ability to engage with HR, finance and supply chain leaders directly within their workflow to solve a unique problem. We expect FDI will fast-track adoption of analytics among Fusion customers by allowing them to run Fusion data pipelines uninterrupted with each software update and then perform tasks like snapshots and KPIs on that data as part of a single SKU.

 

This is particularly true of customers that want to focus less on DevOps and more on analytics but also want to close the loop on an entire business process. One compelling example was a theoretical healthcare organization using FDI to not only understand why vaccination rates are down but also connect to Fusion HCM to see if there are enough staff on hand to launch a new program, and schedule accordingly. FDI already exists today for Oracle Health and is one of the key value propositions behind the Cerner acquisition.

AI Enhances OAC’s Value for Both Customers and Partners

Oracle has a rich history of embedding AI into its products, and the company’s approach to GenAI is no different. With support for the OCI GenAI service in OAC, the core component of FDI, Oracle is enabling self-service analytics with features like natural language queries that help analysts contextualize and interpret data.

 

One of the more interesting features we experienced through an OAC demo was the use of AI-based avatars. Oracle is working with Synthesia, a third-party firm, to pull data from OAC and have different avatars tell stories around that data for specific clients. In addition to watching live demos, we also heard directly from customers in industries like healthcare, transportation and technology on how they are using OAC. As is true for many Oracle solutions, the primary adoption driver for OAC was standardization and the ability to consolidate disparate tools like Power BI (business intelligence) and Tableau on a single platform that can be scaled to different personas throughout the organization.

 

We also heard from both Tier 1 and Tier 2 professional services partners that are driving SI business by migrating customers from the legacy Oracle BI stack to OAC and, increasingly, selling FDI as part of broader app transformation engagements. If the global system integrators (GSIs) want to drive high-margin consulting services around GenAI, we believe they need to account for an intermediary layer that bridges the gap between cloud infrastructure and the back, middle and front office. FDI serves this purpose. Since for most customers analytics will almost always be the end state, GSIs have an opportunity to work backward from FDI into key workloads, including data lakes and ERP systems as part of a client’s cloud transformation, supplemented by their own IP.

OCI GenAI Service Hits the Market

At the start of this year, the OCI GenAI service became generally available, officially marking Oracle’s entry into a budding market. With general availability, Oracle extended support for large language models (LLMs) beyond Cohere, including Meta’s (Nasdaq: META) Llama, as part of the notion that customers should be able to use different models that can be tweaked with their own data, according to use case.

 

Meanwhile, capabilities like OCI AI Agents — which enable RAG (retrieval augmented generation) — and AI Quick Actions within OCI Data Science, also support specific use cases by helping customers contextualize data and access third-party LLMs. On their own, these capabilities do not necessarily differentiate Oracle from what other hyperscale clouds are delivering — although Oracle was smart to cozy up to NVIDIA (Nasdaq: NVDA) for GPUs early on — but the ability to power the same analytics and apps stack with the OCI GenAI service is unique. As we have long said, differentiation in GenAI will not come from the models themselves but rather from the data that feeds into them and ultimately connects customers to solutions and use cases.

 

As such, successful vendors will take a measured approach and will need to partner with GSI peers to address data literacy challenges and apply model governance. FDI’s ability to collect data from Fusion applications and deliver a unified data model that can establish a governance framework and help train nontechnical personas speaks to the elevated role of Oracle Analytics in not only capturing GenAI workloads but also executing on the full-stack narrative throughout the broader Oracle organization.

MongoDB Is Positioning as the Standard Platform for Next-generation Apps

At our first MongoDB, Inc. event, MongoDB.local, TBR was able to learn firsthand about MongoDB’s evolution from an operational database to a developer platform for modern apps. The keynote, breakout sessions, executive Q&A and customer stories reinforced the value of MongoDB’s widely accepted document architecture, which is already powering many enterprise applications today and will propel MongoDB in its efforts to build new developer capabilities and cutting-edge applications. Partners, including all three major hyperscalers and SIs, had a significant presence at the event, speaking to MongoDB’s ability to tap into a growing ecosystem of hyperscalers and global system integrators (GSIs) eager to harness a technology-agnostic data layer for generative AI (GenAI) leadership.

TBR Perspective

In his opening keynote, MongoDB (Nasdaq: MDB) CEO Dev Ittycheria put GenAI in perspective, offering a realistic point of view that while GenAI may help draft emails, it is premature to be used in truly transformative ways. In other words, there is no comparison between the rise of GenAI and the internet boom and subsequent evolution of brands like Amazon (Nasdaq: AMZN), Netflix (Nasdaq: NFLX), Google (Nasdaq: GOOG) and Uber (NYSE: UBER), which launched new business models, elevated consumer experiences and completely transformed markets.

 

We see his point, as our own Cloud Infrastructure & Platforms Customer Research continues to reveal that back-office tasks like customer support and administration are the most common GenAI use cases. We also share his optimism that GenAI will help streamline developer productivity and thus pave the way for a new set of applications that are actually disruptive, not only in how they enhance productivity and cut costs but also in how they transform business operations.

 

MongoDB humbly recognizes that becoming the standard platform to enable this next wave of apps may be a longer-term play, as we are still only scratching the surface of GenAI’s potential. The first players to recognize the benefit will be those that enable, provide and host large language models (LLMs), namely NVIDIA (Nasdaq: NVDA) and the hyperscalers. But the next set of companies to benefit will be platforms like MongoDB, and by honing the document database architecture, relationships with the hyperscalers and an R&D engine catered to the developer experience, MongoDB is positioning to become the standard developer platform for GenAI.

 

MongoDB has solidified itself as the most popular NoSQL database but quickly realized that to handle the demands of complex applications, developers need broader functionality than what a core operational database offers. Adding features like Atlas Search and Time Series collections to its document database has allowed MongoDB to deliver a more complete, integrated platform and grow mindshare with the 175,000 developers who try MongoDB for the first time each month.

 

Naturally, MongoDB has recently focused on adding features for GenAI as part of its longer-term play to power next-gen apps, as evidenced by MongoDB’s launch of Atlas Vector Search last year. Other cloud database vendors also offer vector search, which retrieves information from unstructured data. Enhanced features like Vector Search are also key to the allure of Atlas, the fully managed, scalable, multicloud offering of MongoDB’s platform that is an alternative to Enterprise Advanced (EA) and Community Server, the free version of MongoDB.

 

Since Atlas launched in mid-2016, MongoDB has been actively leveraging GSI partners, its own professional services division and a series of code conversion tools as part of the “technology + process + people” methodology. This approach helps customers transition from on-premises MongoDB products, as well as external relational databases like Oracle and Microsoft SQL Server, to Atlas.

 

These initiatives, coupled with go-to-market support from the hyperscalers eager to have a feature-rich platform on their infrastructure, are making MongoDB largely synonymous with Atlas. With over 46,000 customers, Atlas now accounts for 66% of MongoDB’s total revenue and is available in 117 cloud regions across Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP).
 

MongoDB Rallies Ecosystem Around its Evolving Developer Platform to Power Next-gen Apps

A prerequisite for any successful platform company, MongoDB partners with all the major hyperscalers, tapping into their vast infrastructure scale, customer bases and native toolsets, to attract new workloads. Looking to make Atlas the foundational data layer for GenAI in the cloud, MongoDB has made its Vector Search capability available with all the hyperscalers’ GenAI hosting services, including Amazon Bedrock, Google Vertex AI and Azure OpenAI Service.

 

Vector search is by no means a unique capability in the age of GenAI. Hyperscalers are also using vector search in their own databases, but the vast amount of operational data already sitting within MongoDB will be a key consideration for customers that would otherwise consider a stand-alone vector database.

 

Meanwhile, integrating with the hyperscalers’ code assistants and copilots to abstract complexity and make it easier for developers to build on MongoDB will be a key component of the partner strategy. From a go-to-market perspective, cloud marketplaces will remain key to MongoDB’s success, as they give customers a way to consume Atlas as part of their existing cloud commitments.

 

MongoDB has added hundreds of customers by incentivizing direct sales teams to land more self-service customers on the hyperscalers’ marketplaces, an approach that will serve as a productivity lever by freeing up strategic resources for top enterprise accounts with a focus on onboarding net-new workloads.

Key Takeaways From Each of MongoDB’s Hyperscaler Relationships:

  • AWS: Over the years, we have seen AWS become more welcoming of ISV solutions that overlap with its own native services, provided those solutions land on AWS infrastructure. This shift has benefited partners. For example, MongoDB is delivering integrations with AWS, including Atlas Vector Search with Amazon Bedrock, which allows for the customization of models in Bedrock using data stored as vector embeddings in MongoDB. Developer empowerment has always been a trademark for AWS and with Bedrock, AWS’ goal is to democratize GenAI, making it accessible to not only the largest corporations but also startups, which closely aligns with MongoDB’s value proposition. Meanwhile, after experiencing triple-digit growth in the active number of customers, the expansiveness of the AWS Marketplace is unmatched and continues to be an investment focus for the cloud giant, more recently in the form of new APIs, IaC (Infrastructure as Code) assets and lower prices.
  • Microsoft: Microsoft (Nasdaq: MSFT) has taken a large stake in the legacy database market, and with roughly 20% of new Mongo EA business coming from applications migrated from legacy relational databases, MongoDB has arguably a more contentious relationship with Azure compared to that with the other hyperscalers. However, as highlighted during a one-on-one chat between Ittycheria and Microsoft VP of Global ISV Solutions Alvaro Celis, over the past two years Microsoft has become more effective at embracing the platform mindset to make Azure the de facto platform for enterprise data estates. Like AWS, Microsoft had a shift in mindset to overcome when it comes to partners; for Microsoft, it was recognizing that if it wanted to truly be a prominent cloud platform company, it had to offer customers maximum choice. We are now seeing this approach facilitate ISV activity and pave the way for MongoDB to align with Azure more closely in areas like engineering to improve the Atlas on Azure experience and deliver more integrations with Azure data services, including Microsoft Fabric. MongoDB’s primary focus is becoming a standard for the enterprise at the operational data layer, and the company appears to recognize the value of staying in its own swim lane. Having partners deliver solutions like Fabric that address the upper-level analytics components of the stack and help make MongoDB part of a more complete solution is important and adds a level of differentiation to the Azure-MongoDB relationship that may not exist for other hyperscalers that have yet to adopt Microsoft’s platform-first mindset.
  • Google Cloud: At the event, MongoDB and Google Cloud announced an expansion of their alliance to optimize Google Cloud’s Gemini Code Assist for MongoDB. This announcement comes as Gemini replaces DuetAI throughout the entire GCP portfolio. MongoDB already optimized AWS’ code assistant Code Whisperer by using a customized foundation model so Code Whisperer can make suggestions specific to MongoDB use cases. While the technical relationship is less integrated, the coselling relationship has been well-developed for some time now and is poised for rapid growth given Google Cloud’s audience of born-in-the-cloud developers and increasing focus on empowering developers, the bread and butter of MongoDB.

New MongoDB Services Program Unites Major Players Across the GenAI Stack

One of the top announcements at MongoDB.local was the launch of the MongoDB AI Applications Program (MAAP), a high-touch services offering designed to make it easier for customers to build modern applications. Launch partners include AWS, Microsoft and GCP, as well as LLM providers like Anthropic and Cohere. Collectively, technology partners will align their technology with MongoDB Professional Services through a series of hands-on engagements like prototyping sessions and hackathons, both of which are good ways to engage developers and generate pipeline.

 

Despite all the hype, many customers are still looking for ways to get started with GenAI, and MAAP will be a good way to unite the multiple vendors that MongoDB customers will ultimately use for their GenAI projects. When customers do start taking advantage of GenAI, they will also look to tie the technology to a specific business outcome and work backward from that outcome. This is where the industry and business focus of the SIs come in, and they will undoubtedly play a role in MAAP, supplementing MongoDB Professional Services.

 

MongoDB does work with Tier 1 GSIs like Accenture (NYSE: ACN) and Infosys (NYSE: INFY) but has long adopted a strategy of taking a stake in boutique SIs and scaling them over time. This strategy has a lot of merit, especially as our findings continue to reveal that while the GSIs are excited about the GenAI opportunity, they appear to view data architecture as a pass-through layer to higher-value components of the stack like analytics.

 

This may change as customers recognize the symbiotic relationship between data strategy and GenAI, but GSIs seemingly less interested in dedicating resources to a close-to-the-box data platform will appreciate having a niche SI train Tier 1 consultants on MongoDB. This expected rise in interest level will increase the likelihood that these smaller firms will get acquired by the likes of Accenture, creating new opportunities for MongoDB to expand its relationship with a brand-name professional services firm and tap into its enterprise base.

Conclusion

MongoDB.local NYC told a story of continued product and go-to-market execution, with a meticulous focus on improving developer experiences and driving a more cohesive partner ecosystem inclusive of technology and services players.

 

While the event showcased new partner integrations and Atlas feature updates, it did not highlight any major strategic changes, adding a refreshing and humble tone to the event that suggests MongoDB understands the role it plays and will continue to play in the GenAI revolution.

 

While in some ways waiting for the hyperscalers’ and subsequent customer investments in GenAI to materialize, MongoDB is actively developing and integrating with partners, recognizing that over time, it stands to benefit as customers look for a neutral platform to develop a new set of modern, disruptive applications.

TBR Launches AI & GenAI Technology Market Landscape

HAMPTON, N.H. (May 15, 2024) — Technology Business Research, Inc., is pleased to announce the launch of the AI & GenAI Technology Market Landscape, a new research report focusing on some of the more influential AI startups that are making generative AI (GenAI) a reality for many enterprises as well as for their cloud delivery partners, which play a critical role in this new market.
 
In our initial research we analyze alliance relationships, specifically how AI vendors — including both large language model (LLM) providers and GenAI facilitators — are working with major hyperscalers and SaaS vendors. Additionally, we look at where AI startups are investing; key trends, such as the emergence of multimodal models; and what we can expect from vendors in the coming quarters. Vendors covered include AI21 Labs, Anthropic, Cohere, Databricks, Google, Hugging Face, Meta, OpenAI and Stability AI.
 
The first publication of this semiannual report is now available. If you are a current TBR client and believe you have access to the full research via your employer’s enterprise license, or if would like to learn how to access the full research, click here.

Highlights from the AI & GenAI Technology Market Landscape

Key Trend: Multimodal models

Most foundation model vendors have made multimodal models a strategic priority as they look to expand the number of GenAI use cases
Different from traditional LLMs, multimodal AI can process and interpret several types of data inputs at the same time, such as text, images and sounds. This versatility makes multimodal models critical for expanding the viable use cases for generative AI, specifically to support the creation of marketing content. According to TBR’s 2H23 Cloud Applications Customer Research, this is currently a top five use case for GenAI.
 
Cloud service providers (CSPs) and foundation model vendors alike have made efforts to internally develop multimodal models or form collaborations to harness GenAI’s data interpretation capabilities. Meta launched its open-source multimodal AI model, ImageBind, which can process text, audio, visual, movement, thermal and depth data simultaneously. When connected to sensors, ImageBind can perceive the surrounding environment’s 3D shape, temperature and sound. OpenAI’s newest evolution of its ChatGPT series, GPT-4V, allows users to input text, voice and images into user prompts to create content. Google’s Gemini is also a multimodal foundation model that identifies and generates text, images, video, code and audio. Gemini is known for its ability to perform massive multitask language understanding.
 
TBR believes CSPs and foundation model vendors will drive innovation of multimodal models to improve data interpretation and insights across all business segments.

Explosive AI-driven Demand: Semiconductor and IT Infrastructure Market Expectations

Suppliers of ICT components are often overshadowed by hardware OEMs responsible for delivering finished goods to the market. However, as the importance of semiconductors continues to rise, the market continues to see an expansion of ecosystem partnerships, including between semiconductor vendors and ICT OEMs as well as establishment of government programs and policies that aim to increase domestic chip production, innovation and global market positioning.
 
Over the last several quarters, the rise of generative AI (GenAI) has acted as gasoline on the fire, fueling growth in the semiconductor market. And as new AI workloads and use cases proliferate in the market, cloud service providers, client device OEMs and IT infrastructure OEMs are driving demand for advancements in silicon to support increasingly complex and demanding AI applications.
 
Join TBR Senior Analyst Ben Carbonneau and Principal Analyst Angela Lambert Thursday, June 13, 2024, for an update on the current state of the semiconductor market, including a look at how rapidly increasing demand has supported strong revenue and backlog growth among semiconductor vendors.
 
Additionally, our IT infrastructure experts will discuss findings from TBR’s latest Semiconductor Market Landscape. The semiannual report tracks several key semiconductor vendors, including both fabless companies and integrated device manufacturers, and analyzes portfolio trends, vendor-specific strategies, and end-market trends and implications.

 


 

In This FREE TBR Insights Live Session on AI-driven Demand in the Semiconductor Market You’ll Learn:

  • Key findings from TBR’s latest Semiconductor Market Landscape
  • Update on industry trends and ecosystem partnerships
  • Expectations for the IT infrastructure market

 

TBR Insights Live sessions are held typically on Thursdays at 1 p.m. ET and include a 15-minute Q&A session following the main presentation. Previous sessions can be viewed anytime on TBR’s Webinar Portal.
 
For additional information or to arrange a briefing with our analysts, please contact TBR at [email protected].

Bringing All the AIs Together: Fujitsu Comes at GenAI Through Amalgamated AI

At a new Silicon Valley facility, Fujitsu hosted about 20 industry analysts and over 200 guests for a day of presentations on emerging technologies like quantum computing and AI. The following special report reflects conversations TBR had with Fujitsu leaders and highlights Fujitsu’s role in the technology ecosystem.

Fujitsu’s Superpower: Fusing Compute Power with AI

After a year of relentless hype about the promises of generative AI (GenAI), Fujitsu Research’s leaders structured their presentations during the Fujitsu ActivateNow Technology Summit around a relatively simple and compelling story: GenAI is fundamentally AI, and Fujitsu has successfully deployed a wide range of AI-enhanced solutions.

 

By observing which business challenges can be addressed with AI, and then developing and productizing AI-enhanced solutions, Fujitsu has built an amalgamation of AI solutions, a collection that is worth more than the sum of its parts. The latest fad, GenAI, fits within this collection. According to Fujitsu leaders, the company has delivered over 7,000 AI-enhanced solutions, providing a strong foundation to tap into as GenAI is more widely adopted. TBR recognizes the Japan-centric nature of the majority of Fujitsu’s AI uses cases but sees the value in playing to the company’s strengths.

 

Among these strengths, Fujitsu’s leaders noted that the company’s superpower (TBR’s word, not theirs) comes from fusing compute power with AI. One of the guest speakers reinforced that sentiment by noting that GenAI is feasible only because of the extreme computational power utilized. Fujitsu has recognized that being good at compute is absolutely necessary to be good at GenAI.

 

In TBR’s view, this potentially unique combination of compute power and AI, at scale, could separate Fujitsu from peers as enterprises begin the slow process of recovering from the unfulfilled promises of GenAI hype and implementing the changes needed to progress from pilot to scaled deployments. Fujitsu’s leaders explained that their strategy to accelerate that progress started with the launch of a free AI platform, dubbed Fujitsu Kozuchi (“magic hammer” translated from Japanese), essentially a GenAI sandbox, which the company has now begun to commercialize through a freemium business model.

 

Critically, Fujitsu has tracked activity within the sandbox to determine which AI use cases and associated technologies gained the most client traction and have significant revenue upsides for the company. Fujitsu has been transitioning these uses cases, smartly, from free to use to pay for scale. Fujitsu’s Kozuchi platform spans seven AI areas: GenAI, Predictive Analytics, for Text, AI Trust, XAI, for Vision, and AutoML.

 

In TBR’s view, Fujitsu’s experimentation with AI commercial models while marrying inherent compute power to the potential of GenAI only works because of Fujitsu’s extensive experience with AI and credibility with clients and ecosystem partners. Fujitsu needed a solid foundation in both compute and AI to be well positioned for accelerated growth around GenAI.

 

Additionally, Fujitsu’s broad-based portfolio, including its family of HPCs (high- performance computers) as well as the lower power consumption Fujitsu ARM-based processor — the latest version is scheduled to be released in 2027 — can help the company compete for managing AI workloads, specifically machine learning ones. With security built into the hardware, these processors can also help Fujitsu better appeal to clients in highly regulated industries, including the public sector, emergency response and public safety, healthcare and telco, among others. While built-in security is not a unique feature to Fujitsu, it is a necessary building block as it enables the creation of a strong tech-led AI story around developing and managing large language models.
 

Exactly the Right Time to be Strong in Analytics and AI

TBR’s Voice of the Customer research shows an additional component to Fujitsu’s potential GenAI-related growth. In TBR’s December 2023 Digital Transformation: Voice of the Customer Research, analytics topped the list for priority investments in technologies supporting transformation, displacing cloud and cybersecurity for the first time since TBR started tracking the data six years ago.

 

The report notes: “Analytics is now the top technology buyers choose to support their DT [digital transformation] programs, with AI tools and GenAI ranking in the top six, thus heightening buyers’ expectations for vendors to deliver timely ROI that is tied to ongoing business process and/or IT modernization transformation as implications of technology complexities extend beyond data science, thus creating opportunities for vendors that can manage broad-organizational relationships. Addressing multidisciplinary skills gaps will be key.”

Sustainability and Innovation

Fujitsu’s presence and history in the Silicon Valley, which spans 30 years, enabled the company to develop a deep innovation ecosystem. Fujitsu’s CEO of Research of America, Indradeep Ghosh, and Global CTO, Vivek Mahajan, discussed the expansion of the company’s innovation efforts and how Fujitsu has shifted toward sustainability impacts. At the company’s recently opened facility, Fujitsu remains in close proximity to its key partners, including technology vendors as well as smaller, more specialized firms, which can drive collaboration and innovation efforts.

 

Further, Fujitsu is able to work with universities including Carnegie Mellon University and the nearby Stanford University to deepen its AI, analytics, data utilization and digital twin expertise. Through its innovation efforts, Fujitsu looks to drive social change and leave a positive impact on society, in addition to gathering business intelligence.

 

To contribute to societal change, Fujitsu is prioritizing sustainability with a focus on slowing the impacts of climate change. Fujitsu leverages its expertise and insights to develop technologies and services that benefit the environment and society. Developing sustainability services and solutions in collaboration with U.S.-based universities and companies could encourage local enterprises to establish carbon and energy reduction goals.

 

While sustainability and carbon reduction initiatives have stronger traction in Europe, Fujitsu’s efforts will help transform local clients’ global operations. Fujitsu is considering the long-term impact, which will create new opportunities for the company to drive digital transformation projects across regions outside Japan.

Quantum

Quantum technologies have long been ingrained in Fujitsu’s portfolio and technologies, starting with its in-house development of computing and high-performance computing in the 1990s. Fujitsu has continued to expand the compute power of its quantum technologies enabling the company to address a wider range of challenges, with societal issues the most recent addition. Building out its base and capabilities, in addition to establishing itself as a global technology company, have helped Fujitsu explore the U.S. market. Fujitsu is pursuing two strategies around quantum that will give the company an edge over its technology-centric peers.

 

First, as CTO Mahajan noted during the event, “We [at Fujitsu] are very willing to transfer our IP.” The willingness to give away IP expands Fujitsu’s addressable market. This openness to IP adoption provides both Fujitsu and prospective customers with an advantage, as it raises awareness of the company’s platform and ability to expertly deliver, implement and manage quantum technology.

 

Second, Fujitsu’s plans include the capability to build a quantum computer at a client’s site, actually bringing the hardware to a client rather than providing quantum services from a Fujitsu site. By creating on-site hardware stacks, Fujitsu will be able to integrate with clients’ existing or preferred technologies, enabling the use of new capabilities. With the ongoing convergence of technologies, the ability to work across and with a variety of platforms will strengthen Fujitsu’s overall positioning within the space.

GenAI

Despite possessing the GenAI superpower of fusing the company’s compute power with its AI expertise, Fujitsu has, by its leaders’ own admissions, struggled to gain market recognition as a top player in the overall AI space. One approach Fujitsu has begun pursuing focuses on influencing the wealth of AI startups. TBR’s casual observance of the many startup-affiliated name tags at the ActivateNow event indicated this approach may have generated some early traction.

 

In TBR’s view, focusing on startups reinforces Fujitsu’s corporate culture and mindset, which view technology as central to everything Fujitsu does. The company’s leaders also stressed their efforts to leverage academic research and the broader technology ecosystem as a way to echo Fujitsu’s message of “converging technologies,” a concept that TBR believes hews closely to emerging trends (see TBR’s 2024 Professional Services Predictions and 2024 Digital Transformation Predictions).

 

Applying the company’s blockchain technology to its AI and GenAI assets could strengthen Fujitsu’s position in the space and grow its recognition outside of Japan. The need to regulate AI continues to expand with emerging use cases. Fujitsu’s expertise around blockchain, including Fujitsu Data & Security Technologies for Sustainability Transformation, aligns closely with data protection and regulation, creating the opportunity for the company to apply these capabilities to AI. Fujitsu’s blockchain solutions add a layer of identity and protection to verify real data and information, protecting against external threats.

Sustainability and Consulting as Critical Next Frontiers for Fujitsu

Notably, Mahajan’s first topic was global warming — as he stated, “boiling” — and the opportunity to apply technology to solve climate challenges. His comments conformed with Fujitsu leadership’s sustained message around competing globally and providing something valuable to clients, but TBR cannot recall a similar situation in which the global CTO of a technology-centric company led with global climate change.

 

For the rest of 2024, TBR will listen for similar emphases from CTOs and other C-Suite leaders at the start of technology events. Meanwhile, Fujitsu Uvance provides Fujitsu with resources to develop and deepen the company’s expertise within vertical markets as well as horizontal business areas, allowing the company to drive transformation projects further enhanced by ESG (environmental, social and governance) initiatives.

 

More specifically, Fujitsu can narrow its scope within markets as clients diverge and look to embrace sustainable solutions and achieve outcomes. Leading with the Fujitsu Uvance brand allows Fujitsu to integrate sustainable solutions within specific vertical markets including sustainable manufacturing.

 

Lastly, with increasing client concerns around trusted partners and technology, Fujitsu Uvance’s AI Ethics and Governance Office can help the company establish digital trust in digital transformation projects and help secure Fujitsu’s relationships. Focusing on trust and ethics for the use of AI technologies will allow Fujitsu to use AI more effectively both internally and with clients.

Amalgamation of AIs and Connected Technologies Help Tell Fujitsu’s AI Story

TBR came away from the Fujitsu ActivateNow Technology Summit with two new ideas about Fujitsu and a few questions:

  • First, TBR appreciates that Fujitsu’s combination of compute power and proven AI expertise makes the company a significant competitor and/or alliance partner for nearly every player fighting to turn GenAI hype into revenue. Second, Fujitsu’s vision of “converging technologies” aligns exceptionally well with the more tectonic trends TBR has been observing in the technology space, indicating that Fujitsu’s market positioning is more strategic than transactional or opportunistic.
  • Going forward, will Fujitsu be able to leverage AI startups to shift enterprise buyers’ perceptions about Fujitsu as an AI company? Can Fujitsu successfully bring Japan-centric AI use cases to clients in Europe and North America? And will Fujitsu develop an alliance strategy that plays to its strengths in compute power and emerging technologies while leveraging ecosystem partners’ strengths in other critical component areas for enterprise buyers?

 

TBR anticipates that Fujitsu’s concept around the amalgamation of AI solutions will become a widely shared approach to GenAI. As the hype slows down in 2024 and buyers look to trusted vendors with both scale and proven use cases, as well as the ability to connect existing technologies — especially existing AI-enabled solutions — to GenAI deployments, many of Fujitsu’s peers and alliance partners will be talking about a broader understanding and framing of AI within the enterprise.

 

TBR covers Fujitsu in quarterly reports and as one of 30-plus vendors in TBR’s quarterly IT Services Vendor Benchmark. In addition to this event perspective, TBR has published numerous special reports on Fujitsu events and developments over the last decade.  

U.S. Telecom Operator Outlook: Public Sector Revenue Growth for 2024 [Infographic]

U.S. Telecom Operator Market Overview

TBR estimates public sector revenue from U.S.-based service providers grew 6.1% year-to-year in 4Q23 to $5.4 billion (highlighted in the TBR infographic below). Total public sector revenue growth was driven by wireless revenue, which increased 9% year-to-year to an estimated $2.8 billion. First responder initiatives such as AT&T FirstNet and Verizon Frontline are the main drivers of public sector wireless revenue growth as these units are attracting public safety agencies seeking enhanced reliability to support mission-critical workloads and use cases.

 

TBR estimates network modernization programs such as the General Services Administration’s (GSA) 15-year Enterprise Infrastructure Solutions (EIS) program, which has generated $26.6 billion in business volume since it began in 2017, are driving public sector wireline revenue growth. However, agency migration off legacy contracts such as the GSA’s Networx program is partially offsetting revenue growth from modernization programs such as EIS.

Key 4Q23 Findings on U.S. Operator Market Disruptors and the Competitive Landscape

Market Dominance and Emerging Competition

AT&T, Verizon and Lumen Technologies are still significantly outpacing rivals in total public sector revenue, largely due to the companies’ established footing in the U.S. federal market. AT&T and Verizon also benefit by offering robust portfolios of both wireless and wireline solutions, whereas some competitors, such as Lumen, predominately provide wireline services and others, such as T-Mobile, only offer wireless solutions.

 

Conversely, Charter and Comcast continue to generate the bulk of public sector revenue from U.S. state and local agencies but are gradually gaining traction in the federal market, including by participating in the EIS program via Charter’s partnership with AOC Connect (Core Technologies) and Comcast’s acquisition of Defined Technologies. T-Mobile is also steadily increasing public sector revenue as it is attracting agencies with its 5G capabilities and Connecting Heroes initiative for first responders.

First Responder Initiatives and EIS Migration in the Public Sector

Though TBR expects first responder initiatives will remain a key driver of public sector revenue growth over the next several years, the market is gradually maturing, as evidenced by FirstNet annual customer growth decelerating from 1.4 million new connections in 2022 to 1.1 million new connections in 2023. Conversely, the EIS program provides significant long-term revenue opportunity for contractors but short-term revenue generation has been hampered by many agencies delaying EIS migrations due to factors including uncertainty around long-term budget and technology requirements.

Next Steps: Navigating the U.S. Telecom Public Sector

Dive deeper into TBR’s U.S. telecom operator public sector research at our upcoming TBR Insights Live session. TBR Senior Analyst Steve Vachon will explore overarching market trends and examine the revenue performance and go-to-market strategies of leading U.S. operators competing in the segment. Additionally, he’ll look at key trends and developments at the federal, state and local government levels that are impacting the business performance of these operators.

 

Register now for the May 23 event!

Technology, Travels and TBR: What we Learned on the Road in the First Half of 2024

In the first few months of 2024, TBR’s Professional Services Team traveled to Florida, California (twice), Texas (twice), Boston (twice) and India, meeting with a wide spectrum of IT services vendors and consultancies and hearing firsthand about their strategies, investments, priorities and expectations.

 

Hear Principal Analysts Patrick M. Heffernan and Boz Hristov and Senior Analyst Kelly Lesiczka reflect on ideas, promises and capabilities that stood out; strategies that appear well-suited (or not) to a generative AI (GenAI) age; and what will be changing ― for the IT services vendors and consultancies, their technology partners, and their clients ― over the summer and into 2025.
 


 

In This FREE TBR Insights Live Session You’ll Learn:

  • What technology trends for 2025 are emerging as IT services vendors and consultancies revise their strategies and make new investments
  • Which IT services vendors and consultancies will outpace peers as GenAI moves out of the hype cycle into a more measured phase
  • The biggest surprise in TBR’s travels in the first half of 2024

 

TBR Insights Live sessions are held typically on Thursdays at 1 p.m. ET and include a 15-minute Q&A session following the main presentation. Previous sessions can be viewed anytime on TBR’s Webinar Portal.
 

For additional information or to arrange a briefing with our analysts, please contact TBR at [email protected].