Hyperscalers and SaaS providers are clearly on the front lines of GenAI monetization, but the availability of GenAI services through cloud delivery methods will also accelerate the development of the market.

The Current State of AI Use in Cloud

GenAI adoption is reinforcing one of the strongest value propositions of cloud computing: access to technology. That’s right, even though cloud computing started with a focus on cost — both reducing and delaying costs through an operating expense model versus a capital expenditure model — more recently customers have come to appreciate the access to innovation via cloud models.
 
This cloud-delivered GenAI model is accelerating the pace of investment at scale in the market and will ultimately grow the market more quickly. Most customers are starting with a handful of use cases to gain experience and build the business case for additional GenAI investments. Software development, customer service, procurement, sales and marketing, and strategic ideation are common use cases for enterprises getting started with the technology.
 
Customers are still at a beginning stage of evaluating the costs, benefits and best practices for these early use cases, but we expect maturity to develop quickly throughout 2024. The experience gained throughout this year, including the security, quality and connection to measurable outcomes, will form a critical foundation for growth in adoption and in the market opportunity over the next five years.
 

How Will AI Impact the Cloud Market in 2024?

Torrents of Investment Will Continue

Cloud vendors must invest tens of billions of dollars in 2024 to realize the market opportunity in 2025 and beyond. Core infrastructure to support GenAI service growth is still in short supply, requiring significant data center build across the globe. As each vendor races to establish its AI infrastructure footprint, demand for high-performance silicon will outpace supply, compounding investment demands.
 
Meanwhile, the power held by large language model developers like OpenAI and Anthropic is drawing capital investments across the cloud landscape as vendors vie for their attention and collaboration. These investments will continue to grow and acquisitions are possible as cloud players look to establish a competitive advantage.

Trickles of Returns Will Grow

Premium cloud tiers, GenAI-add ons and pure play vendor revenue streams will grow but be outsized by the amount of investment required to support long-term growth. GenAI is still in its infancy, and a greater proportion of the necessary R&D investment lies ahead for cloud vendors. Customers will need to see tangible value delivered by their GenAI investments, which may not be feasible yet for many future use cases. Over the coming years, the focus will be on contextualizing GenAI around specific use cases to automate workflows and ensure positive ROI is delivered to customers. This will broaden the market opportunity and create a growth driver for players that are able to execute.

Ecosystem Development Continues at a Furious Pace

As is the case with all cloud technologies, the partner ecosystem will be a critical component of vendors’ GenAI strategies. From a technology perspective, relationships between delivery-focused hyperscalers and the model innovators like OpenAI and Anthropic were the initial priority, which is best illustrated by the strategic alliance forged between Microsoft and OpenAI.
 
These partnerships are bringing GenAI to the enterprise and allowing customers to begin experimenting with custom model development. This is where IT services providers will find their opportunities. Global systems integrators and management consultancies have the skills, certifications and competencies needed for GenAI adoption growth, and efforts to support the ecosystem development will occur as a result.

Conclusion

The current state of AI use in cloud computing underscores the shift from a focus solely on cost reduction to embracing innovation accessibility. Cloud providers are investing heavily in GenAI infrastructure, enabling customers to start with free solutions and scale up as needed, particularly in areas like software development, customer service and strategic ideation.
 
While customers are still in the early stages of evaluating the costs and benefits, 2024 is expected to witness significant strides in maturity, including improved security, quality, and measurable outcomes. Looking ahead, investment will continue as cloud vendors race to establish their AI infrastructure footprint, with collaborations and acquisitions likely as players seek a competitive edge.
 
However, returns may grow slowly initially due to the substantial R&D investment required, necessitating a focus on demonstrating tangible value and contextualizing GenAI around specific use cases to ensure positive ROI for customers. Moreover, ecosystem development remains crucial, with partnerships between hyperscalers and AI innovators driving GenAI adoption in enterprises, presenting opportunities for IT service providers to support ecosystem growth.

Within the technology ecosystem, device manufacturers play a specialized role. OEMs operate under different business model constraints, more like traditional industries and less like the software, cloud and “as a Service” economics prevalent across the technology space.

In this blog, we answers the questions device manufacturers are asking in their search for ecosystem partners. Additionally, we highlight the trends TBR believes will shape the devices market over the next few years.

Key Questions Device Manufacturers Ask

Within the business-to-business ecosystem of devices (PC, smart tablet, handheld), are there specific evolving partnership dynamics that are bringing disruption in an era of AI and generative AI (GenAI)?

Not yet, but only because the OEMs find themselves in a strangely fixed universe, in which only two companies make viable x86 chips. NVIDIA’s software and developer head start gives it a stranglehold on AI GPU, and only TSMC (and soon Intel) can manufacture high-end chips.

Additionally, while platform providers Microsoft, Google and Apple carry oversized influence on the chip market, Microsoft’s impartiality with OEMs limits its ability to create specific deals and further complicates the potential for evolving partnerships across the ecosystem.
 

Click the image below to watch: TBR Senior Analyst Ben Carbonneau discusses trend expectations for the Devices industry in 2024 and how TBR’s research will address market activity in the coming year

As a player within the ecosystem — think, Accenture from the IT services perspective, SAP as a software provider or Nokia as a connectivity company — what could they be doing now to be part of the change as device manufacturers prepare for GenAI evolution in PCs and smartphones?

Infosys’ investment in semiconductor design services, as well as similar moves by other IT services vendors, indicates an appreciation across the ecosystem that the hardware components around IT may become less commoditized, surprisingly, as demands for specific capabilities vary widely by industry and applications.

If IT services, software and connectivity vendors previously treated hardware indiscriminately, opportunities to partner more closely or develop expertise and capabilities around hardware — at least semiconductors — could bring meaningful differentiation. The OEMs have flexibility in devices’ physical design, so wherever potential implementations involve nonstandard devices, as in edge and embedded devices, there are useful alliances between customers, their partners and OEMs.

All PC OEMs have embedded systems practices, where PC and server platforms are manifested in medical devices and other nonstandard form factors. Lenovo is especially eager to build diverse devices.

Coming to this challenge from the OEM vendors’ perspective, even with help from the rest of the ecosystem, OEM vendors still face differentiating products that must be standardized. Can an alliance, including go-to-market motions, coinvestment in R&D and even coselling, help OEMs differentiate themselves among other ecosystem players?

While one could speculate about an Accenture-Microsoft-Dell alliance launching a natively GenAI-enhanced laptop aimed at enterprise buyers, this world first require OEMs provide standard platforms so that everything works on everything.

They can vary form factors. They can provide edge devices that are PCs from the software/internal hardware point of view. But any new applications must be capable of running on competitors’ devices, which limits the potential for unique or differentiating services.

If, and when, OEMs form alliances with ecosystem players, those players, such as the IT services vendors, will want their customers to be free to switch hardware vendors at the customers’ discretion, limiting the value of alliances.

Navigating the Future of Device Manufacturing Partnerships

The landscape for device manufacturers, particularly OEMs, is undergoing a complex evolution amid the backdrop of advancing technologies like AI and GenAI. As explored in this blog, the search for ecosystem partners and the quest for differentiation amid standardization pose significant challenges. Current market dynamics, characterized by limited chip options and the dominant influence of platform providers, require OEMs seek innovative strategies to remain competitive.

Collaboration within the ecosystem holds promise for differentiation and adaptation to the GenAI evolution. And navigating these partnerships requires OEMs balance standardization with innovation, ensuring compatibility across diverse devices while also pursuing unique offerings.

Ultimately, like most players not already blessed with a monopoly or wildly dominant market position, the future success of OEMs in the tech ecosystem will hinge on their ability to forge strategic alliances and leverage emerging opportunities amid a rapidly evolving landscape.

GenAI Will Propel Growth in Devices and Associated Businesses

Generative AI (GenAI) will make devices, especially PCs and smartphones, more powerful and easier to use, and that will drive business among device, platform, silicon and software vendors but will not change the structure of the ecosystem. New opportunities in software and services will present themselves, new companies will enter the market, and most new companies will ultimately be acquired.

GenAI has not yet greatly affected the devices market and is not expected to begin to change device usage and requirements until CY2025, with the real impact beginning in CY2026. Right now, devices essentially serve as thin clients for cloud-based GenAI applications. Some PCs run machine learning applications that are helpful but inessential. Both iOS and Android smartphones use neural processing units (NPUs) for computational photography, but so far there are no significant large language model (LLM) applications running on devices.

Vendors and enterprises will spend the next two years evolving LLMs to run efficiently on local devices, expanding the devices to run LLMs, and developing the software to help users be more effective and insightful while making their jobs and lives easier.

Local GenAI Presents the Greatest Opportunity

Devices’ user interfaces (UIs) are the gateways the gateway to all computing; when you improve a device and the device’s software, you improve efficiency and the user experience across the board and you have the greatest possible impact on productivity, leading to optimal business results.

The user interface is not an afterthought or a sidelight; it governs what the user can do with the device and the underlying network. The UI both limits and empowers the user; a UI with GenAI greatly expands what the user can do.

Users spend many hours finding, arranging, organizing, sorting and transforming documents, messages, images, appointments and commitments. GenAI will help enormously in setting up and performing analyses, charting results, and laying out documents and presentations. With GenAI, it will be easier to automate the many tasks that are repeated with minor variations, with obvious benefits.

Device-based GenAI helps users do everything better and more easily; cloud-based GenAI makes individual applications more powerful and easier to use. Local GenAI will have a greater impact, contributing revenue and profit to winning software development companies, to the platform vendors and to the device vendors.

TBR Senior Analyst Ben Carbonneau Discusses Key Predictions for the Devices Market in 2024

The Steps to Local GenAI

It will be challenging to redesign GenAI software, along with PCs and smartphones, to make it possible to run effective and powerful local GenAI applications, but it is necessary because the devices must remain as responsive as they currently are. Users engage with the UI constantly, and delays would completely negate the benefits of an enhanced UI. The round trip to the cloud is unacceptable. Privacy concerns will also require local storage for private business and personal data.

Large language models are, of course, large. While PC memory and fast storage requirements will probably increase, a new architecture of multiple models will be required and is widely under development. The local model “knows” about the user’s data and activities, but it may consult with a company model for broader information and finally with cloud-based models for “knowledge” about the world.

We Still Need Software Development

Vendors will develop and adapt software to leverage GenAI. The conversational chat interface will be available to specify complex tasks, but PC and smartphone applications must have the faster and more conventional UI tools. Underlying the buttons and sliders will be more capable commands, adapted to the user’s needs and preferences.

The platform vendors — Apple, Google and Microsoft — have the advantage here, especially Microsoft, which owns its platform and its primarily horizontal applications. The platform vendors will provide APIs to GenAI resources and services to allow third-party software vendors to take advantage of their platforms. Third-party software vendors include established leaders like Adobe, but there are opportunities for new applications and vendors. Some SaaS vendors will build clients to take advantage of the local AI platform.

One new opportunity for both platform and software vendors is personal GenAI, which consists of private applications for individuals that assist in every aspect of their lives including work, home, family and health. The personal GenAI assistant is a smartphone automated personal assistant. It can shop, make appointments and even answer emails. Apple and Google have the inside track on this important business, and they will use their current voice interfaces, Siri and Google Assistant, respectively, as a starting point. Apple’s high-touch relationships with its customers and corporate emphasis on privacy will help the company’s effort.

The device vendors will benefit from the need for more capable hardware, and the new hardware should evolve more quickly than before, driving faster refreshes. They have few new software and service opportunities, however, as they need to provide standard platforms.

The Devices and Platforms Business Will be Bigger but not Different

The GenAI revolution will not greatly change the relationships that govern the production of devices. There is intense competition among the silicon vendors, but they face the usual array of customers. OEM vendors still face the challenge of differentiating products that must be standardized. Of the three platform vendors, only Microsoft plays well with others, and this situation is unchanged.

With respect to devices, the opportunities are larger but not very different. The invention of applications, leveraging the uniquely novel devices and platforms, is the only new type of opportunity.

What is competitive intelligence, and why is it important. In this blog, we highlight three reasons why CI is crucial to business success and how best to leverage CI I your strategy.

Understanding Competitive Intelligence for Business Success

Competitive intelligence is a broad concept: Think of it as any intelligence that improves your business’s performance in the market. Insight on what, how and where competitors are operating is one aspect of competitive intelligence, but it is also important to include the role of partners and the perspective of end customers to establish an all-encompassing view of the overall market.

Most markets are imperfect, with complexity across regions and verticals as well as the need for a myriad of vendors to work together to create solutions. Due to that market complexity, information on what is occurring in the space and why can be difficult to ascertain. Competitive intelligence is one method to extract points of clarity that can serve as guideposts as you set objectives for your business.
 

Click the image below to hear more about competitive intelligence for business success from TBR Principal Analyst Allan Krans

Why Is Competitive Intelligence Important?

Competitive intelligence can be the best proxy for your own business decisions. Gaining a deeper understanding of individual vendors and the broader set of competitors in the market landscape can inform your decision making in a powerful way.

1. Competitors as a proxy

Anticipating where the market opportunity is moving and how to capitalize on that is a challenging proposition, especially in dynamic, quickly evolving markets like IT. It is difficult to make complicated and/or significant investments, and the risks are always high. In quickly evolving markets, one of the best ways to reduce risk and increase the confidence of the overall organization in making business decisions is to look at how your competitors are handling the same situations. Understanding how and in which markets your peers and competitors are investing can provide a number of benefits.

First, this information validates strategic directions your own business is considering. It may not guarantee the success of an investment but at least it can provide reassurance that competitors are weighing the risk-reward ratio in a similar manner. Second, understanding the intent and strategy behind different decisions can be even more important for competitive intelligence. No two businesses are the same, so this context can allow your business to translate the intent of different competitor strategies into something that works for your business. The third benefit is gaining information about the outcomes of competitor strategies in real financial terms — one of TBR’s specialties. Revenue, expenses and profit margins are concrete metrics that can help you gauge the effectiveness of competitor strategies and understand whether the outcomes align with your business’s overall financial goals.
 

2. Markets inform opportunity

Looking holistically at markets and how different peers and competitors operate within them can provide value competitive intelligence. This broad view can help you gain insights into where and how a group of key competitors operate within a market and with what results. TBR’s benchmark and market forecast reports are examples of this type of competitive analysis, illustrating the size, growth and strategies of a given group of peers within a market segment.
 

3. Competitive intelligence can guide business strategies

A combination of competitive intelligence activities, including deep dives into segment leader strategies, broad coverage of other peers in the space and an analysis of the different objectives for those peers, can be used as a powerful tool for business strategy road mapping. These combined activities can illustrate the objectives, investments, outcomes and landscape against which your business will be competing across different endeavors. Just because your peers are going in a certain direction does not mean that is the best path for your business. Likewise, just because competitors are not making certain decisions does not mean your business should not consider them. However, an awareness of what is occurring can be an important source of intelligence.

Conclusion

There is no perfect customer, no perfectly aligned competitor, and no clear market opportunity, especially in IT. In a world where no perfect decision exists, competitive intelligence can be an informative window into how businesses in similar markets are operating their businesses.

Having market perspectives to consider, strategies to evaluate, and approaches to both emulate and avoid can be valuable. Competitive intelligence can provide these benefits and more, helping organizations plan future investments and reduce overall risk.

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