The overwhelming majority of smartphones shipping today have silicon that drives some integrated Artificial Intelligence (AI) capabilities. The industry is moving fast to embrace next-generation chips that will drive new and exciting features and interaction modes.

IDC defines “next-gen AI smartphones” as devices with a system-on-a-chip (SoC) capable of running on-device Generative AI (GenAI) models more quickly and efficiently leveraging a neural processing unit (NPU) with 30 Tera operations per second (TOPS) or more performance using the int-8 data type. These new devices are generating a lot of interest amongst consumers and OEMs, making AI the focal marketing message at recent flagship launches, with more to follow this year.

IDC’s latest forecast estimates that GenAI smartphone shipments will grow 364% year-over-year in 2024, reaching 234.2 million units, growing to 912 million units in 2028 implying a compound annual growth rate (CAGR) of 78.4% for 2023-2028.

While AI will impact all device categories, smartphones will lead the charge from a pure reach and volume perspective, quickly outpacing the forecasted volumes of AI PCs. What follows is IDC’s initial definitions around AI smartphones and an early look at the impact we expect it to have on the market.

AI Smartphone Definition

Smartphones capable of running on-device AI have existed for nearly a decade; however, more recently, the term AI smartphone has come into play to describe some of the latest flagship devices with on-device GenAI capabilities that are creating increased interest and excitement in the industry. IDC categorizes AI smartphones into two distinct groups, with these newer AI smartphones as the second category below:

Hardware-enabled AI Smartphones (≤30NPU TOPS): These smartphones use accelerators, or specialized processors aside from the main application processors, to run on-device AI at lower power. More recently, this includes a shift to the use of neural processing unit (NPU) cores with up to 30 TOPS performance using the int-8 data type. Examples of on-device AI are natural language processing (NLP) and computational photography. These smartphones have been on the market for nearly a decade.

Next-gen AI Smartphones (>30 NPU TOPS): These smartphones use SoCs capable of running on-device GenAI models more quickly and efficiently and have an NPU with at least 30 TOPS performance using the int-8 data type. Examples of on-device GenAI include Stable Diffusion and various large language models (LLMs). This category of smartphones first hit the market in the second half of 2023.

The smartphone SoCs being designed and marketed by silicon vendors with next-gen AI smartphones in mind will proliferate in the future as they continue to push forward the NPU technology. However, to date, here are a few that qualify based on the definition above:

Apple A17 Pro
MediaTek Dimensity 9300
Qualcomm Snapdragon 8 Gen 3

The AI Smartphone Journey

The first thing to know about on-device AI in smartphones is that on-device AI has been a part of smartphones for years in the form of natural language processing (NLP) and computational photography. The data models to do this are usually smaller than the models that run in the cloud on servers but work well enough to get the job done.

AI is run on devices for speed of response, privacy, and security. On-device GenAI is newer, and the industry’s discussion of AI smartphones is centered around this. IDC will use the term next-gen AI smartphones when referencing these newer AI smartphones focused on device GenAI as defined above.

Next-gen AI smartphones are about performing inferencing on the device and specifically on-device GenAI through the inclusion of LLMs and text-to-image models, among others. However, just like putting a game on a PC does not make it a gaming PC, putting an LLM or two on a smartphone does not make it a next-gen AI smartphone. It is the fact that the smartphone’s SoC is designed with specific accelerators, or specialized processor cores, that are optimized to run LLMs quickly and efficiently with less power consumption than if the main processor cores were the primary workhorse. These specialized cores are called neural processing units (NPUs) typically.

There have been phones on the market with NPU cores already, but typically with fewer cores and less performance. Processors just hit the market in the second half of 2023 with more powerful NPU cores and a greater number of cores since they were designed with on-device GenAI in mind. One could define an AI smartphone based on quantitative specifications such as core count, the aggregate processing power of those cores, or total processing power across all application processor cores and all accelerators. The typically minimum amount of DRAM could be part of the definition, too. However, these are all moving targets and will keep changing. Furthermore, GenAI models can be compressed and quantized further to fit into phones with lesser specifications.

To create a knowable segmentation between hardware-enabled AI smartphones and next-gen AI smartphones, IDC has drawn the line at 30 TOPS. The smartphone SoCs powering today’s next-gen AI smartphones listed above are in the range of 30 to 45 TOPS of NPU performance using the Int-8 data type.

Customer Demand and Future Applications

The sales of many next-gen AI smartphones in the first year or two will likely be driven by the sheer fact that they are flagship phones. But the arrival of phones capable of running GenAI on the device will lead to more application development and next-gen AI smartphones will become increasingly capable. A later evolution could include a very large AI model that is a much more personalized and proactive assistant. This is likely what Google is aiming for with Gemini, Microsoft is aiming for with a future version of Copilot on smartphones, and what Apple is likely also planning. And this is where the excitement of consumers and industry really comes into play, at the untapped potential of what this technology could bring in the next phase of evolution, rather than the basic applications and use cases that exist today.

Hardware Implications – An Opportunity and Challenge for OEMs

Before we get to the next phase, OEMs will need to address the other hardware requirements of next-gen AI smartphones outside of SoCs. One of the biggest variables will be not just the premium cost of the SoC, but the cost of additional DRAM that will be necessary to support the super powerful SoCs of these devices.

Where 16 GB is a large amount of RAM for most smartphones, 16GB is already considered a minimum requirement for next-gen AI smartphones. A general doubling of memory included in these phones will be far more than double the recent historical cost of memory, as the cost of DRAM is increasing. Most flagship phones will tend to be loaded with premium configurations and components, including better screens and cameras that would optimize the use of multi-modal GenAI around imaging.

This means that next-gen AI smartphones will also come with a larger bill of materials (BOM) cost, which presents both an opportunity and a challenge for the OEMs. OEMs can leverage the innovative technology and its obvious benefits to pass the added BOM cost to the end consumer with a higher sticker price and use the opportunity to raise the value of the industry or absorb the additional cost between the channel and OEM.

Learn how to take a data-driven approach to managing and developing the right partnerships in IDC’s recent playbook.

Although a combination of the two is the likely outcome, the good news is that smartphone ASPs have been going up in recent years, and the share of premium devices continues to grow with no signs of slowing down. Consumers are getting used to and even willing to pay more for their smartphones. As flagship smartphone prices increase, increasing availability of multi-year payment plans and other promotions like aggressive trade-in offers, will make it easier for consumers to purchase these higher-priced next-gen AI smartphones.

Looking Ahead

IDC forecasts 170 million next-gen AI smartphones to be shipped in 2024, representing almost 15% of the total smartphone market. This will be a significant leap from the 51 million devices shipped in 2023, more than tripling in volume in just one year. Next-gen AI smartphones will continue to grow rapidly in the coming years as use cases evolve and as the OEMs, silicon vendors, and industry players continue to drive processing power and adjoining hardware specifications to support the growing demand for these intelligent smartphones.

Next-gen AI PCs are expected to take off this year, too, but the scale of the smartphone market means the volume of next-gen AI smartphones will quickly surpass the PC. IDC forecasts AI PCs to ship 167 million units by the end of 2027, while smartphones will cross that number this year alone. Therefore, while AI as a technology will impact all corners of the devices market, smartphones will be the device driving the AI revolution into every home.

Contributing authors:

Phil Solis
Bryan Ma
Tom Mainelli
Ryan Reith

Data is the fuel of digital transformation, but it also comes with challenges of privacy, security and trust. How can you share and analyze data with your partners, customers or competitors without compromising your data assets or exposing sensitive information? How can you mitigate risks of data security and confidentiality?

Data clean room technology is a potential solution that enables secure and privacy-preserving data collaboration across multiple parties enabled by the functions and features of the software. Data Clean Rooms are a trending topic in the technology industry, gaining traction due to their ability to facilitate privacy-preserving sharing of data and data collaboration between multiple parties. They are used in various sectors, including advertising, marketing, healthcare, and financial services.

According to Lynne Schneider, research director of IDC’s Data as a Service and Data Marketplaces area, 88% of data buyers are at least somewhat familiar with the concept of Data Clean Rooms.

However, there are challenges associated with data clean rooms. One of the challenges comes from the term itself, as there is not a clear-cut definition, leading to confusion among vendors and end users. Another challenge is that because data clean rooms are purposefully opaque, it is imperative that the parties participating carefully establish data models, cleanse their data sets, and do other relevant prep work.

IDC estimates that there are more than 500 data clean room instances currently deployed across the globe. IDC has conducted a series of two MarketScapes on this topic, evaluating more than a dozen vendors including Acxiom, AppsFlyer, AWS, Decentriq, Epsilon, Habu, Helios Data, InfoSum, LiveRamp, Optable, Pyte.ai, Snowflake, TransUnion and TripleBlind.

What is Data Clean Room Technology?

Data clean room technology is a software solution that creates a virtual environment where multiple parties can combine and analyze their data without sharing or copying the underlying data. The data clean room technology ensures that each party maintains control over their data and can set rules and limits on how it can be used. The data clean room technology
also protects the privacy of the data and the algorithms that are used to generate insights. The data clean room technology can use various techniques to achieve this, such as encryption, hashing, pseudonymization, noise injection, synthetic data, secure enclaves, or secure multi-party computation.

Data clean room technology can be used for a variety of use cases and industries, such as advertising, marketing, healthcare, life sciences, financial services, public sector, and more. Some of the common applications of data clean room technology are:

Data enrichment: You can enrich your data with external data sources to gain more insights about your customers, markets, or competitors.
Audience creation and activation: You can create and activate audiences based on shared attributes or behaviors across multiple data sources, such as web, app, phone, and physical traffic.
Measurement and attribution: You can measure and attribute the impact of your campaigns or actions on your business outcomes across multiple channels and platforms.
Fraud detection and prevention: You can detect and prevent fraud by collaborating with other parties to identify and block suspicious activities or transactions.
Research and innovation: You can collaborate with other parties to conduct research and innovation projects that require access to sensitive or proprietary data.

What are the Benefits of Data Clean Room Technology?

Data clean room technology can bring many benefits to your business, such as:

Enhanced data value: You can unlock the value of your data by combining it with other data sources and generating new insights that were not possible before.
Improved data privacy: You can protect the privacy of your data and your customers by ensuring that your data is not shared or copied by other parties or by the data clean room provider.
Increased data security: You can secure your data from unauthorized access or misuse by encrypting it, hashing it, or using other techniques that prevent data leakage or exposure.
Reduced data risk: You can reduce the risk of data breaches, compliance violations, or legal disputes by following the rules and limits that you and your data collaborators have agreed on.
Accelerated data innovation: You can accelerate your data innovation by collaborating with other parties that have complementary data, expertise, or resources.

How to choose the right data clean room vendor?

Some of the key dimensions to consider include:

The scalability and performance of the solution. You need a solution that can handle large volumes and variety of data, and provide fast and reliable results. You also need a solution that can scale up or down as your business needs change, and offer flexible pricing models.
The functionality and usability of the solution. You need a solution that can support various types of analyses, such as descriptive, predictive, and prescriptive, and provide actionable insights and recommendations. You also need a solution that is easy to use and integrate with your existing systems and tools, and that offers a user-friendly interface and dashboard.
The security and compliance of the solution. You need a solution that can ensure the privacy and security of your data, and that complies with the relevant data protection regulations. You also need a solution that can offer different levels of access and control, and that can audit and verify the data processing and outcomes.

Action Items

Assess your data collaboration needs and opportunities, and identify the use cases where data clean room technology can help you.
Review the IDC MarketScapes and compare the data clean room technology vendors based on their capabilities and strategies.
Contact the data clean room technology vendors that match your requirements and preferences, and request a demo and client references. Ask questions, give feedback, and explore the possibilities and limitations of each solution. Find out how each vendor can support you throughout the implementation and integration process, and how they can help you achieve your desired outcomes and ROI.

Digital markets for consumer goods and services are inherently inefficient because the vast majority of tech investment is on the sell-side of the market. Despite this, most digital marketers provide highly personalized customer interactions less than 50% of the time, and most digital advertisers still waste an enormous amount of ad dollars on buyers that are not and will never be in-market for their products or services.

For decades, the tech industry has been selling brands and publishers a myth that more data and more analytics can make them omniscient about buyer behavior. While that investment dramatically improved the effectiveness of marketing and advertising, it hasn’t lived up to its potential because consumers are not equal players in the ecosystem. To be optimally efficient both sides of a market must have an equivalent ability to participate.

The emergence of Edge AI that enables data and Generative AI (GenAI) agents to reside on smartphones will flip consumer market models from enabling brands to control engagement with millions of consumers, to enabling consumers to intuitively control engagement with every brand and ad network with a single super-agent, not a cacophony of apps.

This creates the potential for consumer goods and services markets to approach the efficiency of stock markets as buyers will be able to programmatically control purchase intentions, and monetization models for publisher and brands can be based on commissions instead of impressions. Like search, social, and mobile, consumer super agents will transform digital marketing, advertising, and commerce, but will likely be adopted even faster.

According to U.S. Federal Reserve data, it took the Internet roughly 20 years to support $500B in retail sales. It took mobile roughly 15 years after the launch of the iPhone. GenAI could do it in less than 10, as scale accelerates scale.

For consumer super agents to be the universal front end to commerce requires that consumers possess their own data and AI which the next generation of smartphone chips and AI models are expected to support. Super agents can then be proactive market participants that identify products, assess offers, and automate purchases or ask permission to do so. Super agents can be trained with no more effort than managing a Spotify play list and will dramatically simplify consumer shopping. They can support replenishment and considered purchases, from household goods and groceries to fashion; they can make appointments, plan vacations, advise on auto, home, finance, education, and health care. They can curate offers as convergently or divergently as the user desires, consider substitutes or not based on consumer preference, and reveal users’ personal information only as needed (critical features missing from today’s platforms.)

To function, super agents require a rebalancing of consumer marketplaces in three major ways:

Intuitive super agents: Consumers will want one GenAI super agent to manage all their purchasing, not a different agent for every brand, market, or product category. Super-agents will learn by watching organic consumer behavior and through conversation and function as next-gen super apps like WeChat and Alipay.
Irrigating the customer data desert: Ironically, we’re still living in a retail world dominated by paper receipts. Technically there is no reason why consumers shouldn’t already have line-item visibility into all their household shopping regardless of how they pay. But retailers do not provide electronic receipts, nor do banks, payment processors, and credit card providers. Getting over the fear that giving consumers more data would result in less revenue is the greatest mindset shift needed for the market to evolve. Unlocking this data and feeding it though super agents would make markets for goods, services, and advertising far more efficient for both buyers and sellers. It will also inherently protect consumer data.
Autonomous marketplace: Buyer and seller agents will need a global exchange that passes consumer bids to multiple platforms in which all sellers can respond regardless of their ecommerce presence (e.g. Amazon, Shopify, eBay, Etsy, etc.)   

That brings us to two questions:

Who will be the “Spotify” of super agents?
Who will be the “NASDAQ” of AI marketplaces?

The “Spotify” of Super Agents

Spotify use cases are like those of household shopping — we tend to listen to our favorite songs over and over, we tend to like slight variations on song lists, and occasionally we want something special or completely different or a throwback from the past. Songs can be quickly liked and unliked, categories are easy to manage, and recommendations are presented in intuitive ways. It’s all a matter of taste as expressed by organic consumption and discovery behavior. Retail and advertising content is very similar. Consumers tend to repurchase their favorite products, sometimes need something new, or want to discover something completely different no matter how niche.

Super agents can communicate all this to ad networks, e.g. if a “no substitutes” tag is on a product, there’s no reason for a brand to pay to advertise to that buyer. If someone buys a car or truck it may be years before they are back in-market for those products, in the meantime all ads on any medium are a waste for both brands and buyers. GenAI will function as a chief of staff for the lifetime of a consumer across brands, channels, and life stages.

All the usual suspects will vie for dominance in this new era of super agents: Platforms such as Alipay, Amazon, Apple, Baidu, Google, Meta, Microsoft, TenCent, TikTok, WeChat, eCommerce players such as Shopify, customer experience companies such as Adobe and Salesforce. Payments companies such as Mastercard, Visa, and PayPal. AI players like OpenAI. Digital consultancies such as Accenture, Deloitte, Publicis/Sapient, etc. Or any combination thereof.

The winners will wholly embrace the idea that the most important partners to share data with are customers. It is a bold proposition, but as the tech industry has proven again and again, fortune favors the bold.

Buyer Benefits

Inherent privacy and consent: Super agents do not have to reveal why consumers are in the market for any specific item. The data that brands use for targeting such as demographics, click trails, social posts, lookalikes, transaction histories, weather, etc. are all weaker signals than intent. Personal information can be revealed progressively as needed to enhance offers and complete transactions.
Better experience: Super agents provide automated access to the best deals on preferred products, services, and substitutes based on price, availability, delivery, convenience, etc. They will also obviate the need for third party cookies, stalker ads, and irrelevant marketing.
Value-added insights: Examples might include analysis of savings potential across product categories, nutritional analysis from grocery purchases, ESG stats for the brands they patronize.

Seller Benefits

Improved customer experience: Enabling consumers to tell brands when they are in market takes the guesswork out of marketing and brands don’t need to encroach on the private lives of buyers thereby reducing risks of privacy violations and poor customer experiences.
Less tech expense: Brands don’t need massive customer data stores. They don’t need to send millions of emails or waste compute on trillions of personalization decisions when they know exactly who’s in and out of market every millisecond of the day.
Lower go to market costs: Intent-based marketplaces will monetize based on transactions rather than impressions making the market much more transparent and measurable, resulting in lower customer acquisition costs, fraud, cart abandonment, and reliance on third party influencers.

The “NASDAQ” of AI Marketplaces

NASDAQ’s great innovation was to digitize, accelerate, and scale accessibility for stock transactions. It connects buyers and sellers and gives them an equivalent ability to control the terms of their market participation. At the transaction level consumer markets are not significantly different, but they are far more complex logistically. Super agents can advise consumers on the time, cost, and convenience of various delivery options, pick up at store, or how many stores they might have to visit to get desired products at the best deals.

The big advantages of a NASDAQ-like open platform include:

Reduced costs for both buyers and sellers.
Equal participation for sellers of all kinds from global brands to mom-and-pop shops from any platform.

A global AI-powered exchange offers many opportunities for tech companies to find their place in a new infrastructure from agent development, marketplace hosting, offer management, connectivity, security, governance, payments, logistics, and more.

Impact on Marketing and Advertising

Each new digital platform – the Internet, mobile, social, etc. – required new go-to-market practices. However, each of those innovations supported traditional ad models for a human audience. That will not go away, there is massive ad and influencer activity around stocks. But digital ad spend may undergo a major shift as brands and publishers get access to programmatic intent signals from super agents and overweight on paying commissions for transactions rather than fees for impressions.

Brands will have to find creative ways to extend incentive programs to encourage loyalty, advocacy, and lifetime value. Publishers will have to expedite intent pass-through to ad networks. Digital ad networks will have to be extended to traditional mass media. Those that move early at scale will have sustainable advantages. Brands and publishers that respond with the greatest immediacy and relevancy will have advantages. But they will have to make major changes to their go to market mindsets and practices and invest in new capabilities for supporting consumer data residency, dynamic real-time offers, frictionless logistics, and holistic support.

In other words, they’ll need an composable, intelligent infrastructure from intent signal to support call, from back office to front office, from supply chain to door drop. The payoff will be measured in $100Bs of revenue and trillions of dollars of market capitalization.

As customer expectations evolve continuously and competition intensifies, we cannot overstate the importance of sales enablement resources. These resources support sales teams by giving them the information they need to engage with potential customers and close sales. However, managing and updating these resources to ensure they remain relevant and impactful can be a daunting task.

To help sales leaders navigate this challenge, here are ten tips for optimizing sales resources for relevance and impact:

1. The Best Sales Enablement Tools Help You Understand Your Audience

The first step in optimizing sales resources is understanding your target audience – the sales team. What are their pain points? What challenges do they face in their day-to-day activities? Understand your sales team’s needs to provide the right resources and support for increased productivity.

It’s especially crucial to address their concerns about the evolving landscape of B2B buying behavior. As AI becomes more common in the discovery and consideration process, sales reps may fear being sidelined or becoming less relevant. Instead of fearing AI, sales leaders can support their teams by learning how to use AI effectively.

By using AI insights in sales, reps can better understand customer preferences and behaviors, helping them customize their approach. Finally, invest in training programs to enhance their performance and empower them to build thoughtful relationships.

Equipping your team with the best sales enablement tools ensures that they are adeptly poised to navigate the intricacies of modern sales landscapes. Arm your sales force with interactive selling tools that empower them to build relationships and thrive amidst the evolving paradigms of B2B sales.

2. Prioritize Quality (Over Quantity) in Sales Enablement Resources

Rather than inundating the sales team with an abundance of resources, emphasize the delivery of curated materials that offer actionable insights and substantial value. It’s imperative to ensure that your sales enablement tools, content, and resources are finely tuned to address the evolving needs of both the sales representatives and the market.

Keep your sales enablement content updated with the latest industry trends, product enhancements, and competitive intelligence. Engage in periodic assessments to evaluate the effectiveness of your sales enablement resources, seeking feedback from the sales team to pinpoint areas for enhancement and adjustment.

61% of sales reps are not skilled at selling to C-level buyers

Source: IDC 2022 Outcome Selling Advisory IDC Survey on Value Selling Excellence

A strategic blend of educational content, sales aids, and sales engagement tools is paramount. However, don’t overlook the significance of continuous training and support. Sales enablement goes beyond providing resources; it involves giving the sales team the skills and knowledge to use those resources effectively.

3. Tailor Resources to Different Sales Stages for Enhanced Value Selling

Recognizing the nuanced nature of the sales cycle is paramount. Sales representatives operate within distinct stages, each demanding tailored approaches and resources to optimize outcomes. Whether they’re engaged in prospecting, qualifying B2B sales leads, or closing the deal, acknowledging and addressing the specific needs of reps at each stage is essential for effective value selling.

Understanding the diverse requirements across sales stages necessitates a strategic approach to sales enablement. Provide your sales team with the appropriate arsenal of sales enablement tools, designed to empower them at every step of the journey and facilitate the generation of valuable B2B sales leads.

Check out: Building a Value-Based Sales-Enablement Strategy

To refine your sales enablement strategy further, leverage the frontline expertise of your sales team. They possess invaluable insights garnered from their interactions with prospects and customers daily. Establish channels for transparent communication and actively solicit feedback from the sales team regarding the efficacy of existing resources and potential areas for enhancement.

By fostering a collaborative environment where feedback is welcomed and acted upon, you can continuously refine and optimize your sales enablement tools to align seamlessly with the evolving needs of your sales team. Embracing this iterative approach ensures that your resources remain finely tuned to support value-driven interactions, enhance lead qualification processes, and facilitate seamless deal closures in the dynamic landscape of B2B sales.

Optimizing sales resources for relevance and impact requires a strategic and proactive approach. By understanding the needs of your sales team, focusing on quality, keeping content updated, providing training and support, tailoring sales enablement resources to different sales stages, fostering collaboration, and seeking feedback, you can empower your sales team to drive more b2b sales leads in today’s competitive landscape.

Additional Resources:

Ask us about our newest interactive value selling tools
Explore complimentary sales enablement resources from IDC’s Sales Enablement Toolkit

As more and more organizations are advancing on their sustainable transformation journey, their efforts are becoming increasingly complex. Sustainability considerations are becoming more integrated in different functions, and ESG (Environmental & Social Governance) performance must be monitored and reported more continuously. IT has become a critical enabler of these transformations as ESG performance monitoring and management process has evolved from an entirely manual exercise to a much more data-intensive process, necessitating the integration of large-scale data models and management platforms.

Since their maturity levels regarding sustainable transformation are generally still relatively low, many organizations also require a significant amount of help from professional services providers regarding their sustainable business and IT strategy setting, reporting, implementation of enabling technologies, etc. This has led to numerous partnerships between professional services and IT providers that have created joint solutions and go-to-market strategies focusing on generating positive financial and non-financial ROIs for their clients and helping them up to speed on their sustainability journey. Recent IDC data shows that many organizations still struggle with a lack of understanding of available sustainability-focused IT, and with making tangible progress in solving the ESG data challenge. This, in hand with professional services firm’s lack of proven tech-enabled sustainability services, has led to users taking smaller, less impactful steps in their sustainable transformations, thus lengthening the time to transform, and increasing resource costs.

Despite the recent political backlash against ESG, the topic remains a top business priority for business decision-makers globally. For instance, we asked the following question in our annual Future of Industry Ecosystems global survey: considering the collective capital among your partners (people, financial, asset, operational), what are the most important collaborative initiatives? The top answer for three years running, whether you are a CxO (CEO, CIO, CTO, CFO, CDO), business line manager, IT leader, supply chain, or customer-facing executive, is sustainability, or environmental, social, governance (ESG).  Organizations want to and need to work closely with ecosystem partners in support of ESG because this is too complex an issue to address on their own.

In support of these efforts, IDC believes that major global organizations that typically orchestrate industry ecosystems will increasingly form cross-ecosystem teams dedicated to ESG activities and task them with facilitating the resulting sustainable practices throughout the ecosystem and their organizations. In our 2023 Future of Industry Ecosystems FutureScape, we predicted that organizations would begin to build sustainability teams consisting of ecosystem partners: By 2025, 60% of G2000 organizations form cross-ecosystem ESG teams that are accountable for sharing of data, applications, operations, and expertise that facilitates sustainable ecosystem practices. Our recent research shows that this approach is well on its way.

Forming dynamic and reconfigurable cross-ecosystem teams that can quickly adapt new business demands to their industry environment promotes trust, cooperation, and solidarity among industry ecosystem participants. Further, working on ESG within an ecosystem consortium enables companies to collaborate with partners, suppliers, advisors, and regulators in the development, tracking and management of industry-specific standards, performance metrics, and targets. Having a cross-ecosystem team dedicated to the stewardship of ESG standards and practices allows partners to not only share development costs and risks but also address issues with a united front and communicate clearly to all stakeholders.

The Most Advanced With Ecosystems Are Most Advanced With ESG

In our Future of Industry Ecosystems MaturityScape Benchmark report (April 2023), we asked about the ecosystem maturity approach with environmental sustainability, and what this entails. An analysis of survivors (those at levels 1 or 2) and thrivers (those at levels 4 or 5) shows that thrivers go one step beyond meeting regularly with partners to ensure sustainability; they create formal teams of leaders across the ecosystem, that share data, applications, operations, expertise, and knowledge as needed to advance their approach to environmental sustainability.

Collaboration With Industry Ecosystem Partners for ESG a Critical Focus

Which statement best describes your organization’s environmental sustainability strategy and approach to your industry ecosystem?

2024 Multi-Client ESG Ecosystems Research Study

During the first half of 2024, IDC will be fielding a study on ESG best practices and plans with ecosystem partners, including a perception element of current IT and services providers.  We are currently accepting sponsors of this study – which we will look to for guidance on the questions and topics that matter most to you and your business. Contact us to learn more: jhojlo@idc.com, bstengel@idc.com, dversace@idc.com

Contributing authors: Dan Versace and Bjoern Stengel

The Best of Times

For Apple, it is the best of times, thanks to the way it has consolidated its position in its traditional markets and raised its game above that of Android in higher price segments.

In 2023 it became the world’s largest phone maker by volume, surpassing Samsung according to IDC’s Worldwide Quarterly Mobile Phone Tracker.

Volumes and unit share have been creeping up since 2019  (Chart 1 below), and the value of iPhone shipments has close to doubled in a decade.  Various factors have helped Apple achieve this.

Apple increasingly takes the top of the market, creaming off well-heeled consumers in affluent countries for its premium phones. (Chart 2 below)

More specifically, Apple has ridden a wave of consumers preparing to put more money down for their phones and the iPhone 14 and 15 series have resonated with consumers.

The consumer willingness to pay more has pushed Apple even further ahead of its competitors in value terms, and the most expensive Pro models in the new ranges have become the most popular models in its flagship lineup.

Behind Apple’s rising trend are also familiar reasons like the impact of the coronavirus crisis, during which consumers got used to spending more on devices given how much more people use them. 

Apple also continues to leverage mobile operators to great advantage.

In Apple’s top 20 markets by share, nearly two-thirds of iPhones are sold through the telco channel, according to IDC data, a figure which has hardly dropped in the last five years.

Their postpaid financing and trade-in deals drive a lot of the iPhone’s volumes. IDC’s Final Tier Mobile Phone Tracker shows that in the US 88% of iPhones are sold through operator postpaid. Generous buyback offers encourage consumers to trade in for the latest iPhone model, knowing that they will get a good price when they repeat the trade in a couple of years.

These deals have helped Apple in those top 20 markets to increase its share in Price bands above $650 to over three quarters.

Serendipity has played a role in Apple’s rise too – Apple’s share in China jumped after US sanctions in 2019 stopped Huawei from accessing US components necessary to make 5G smartphones, essentially knocking Huawei out of the smartphone race.  Since then, Apple has more than doubled its share in China and became number 1 for the first time ever in 2023. 

A less talked about factor is that Apple has reached this position without much change in its geographical focus. Outside of its growth in China, the majority of its sales remain skewed to the richer parts of the world.  The Top 20 Apple markets by units share account for more than half of total iPhone shipments, but they account for less than 10% of the global population.

Also, four-fifths of iPhones are priced above $800 (Chart 3 below). Catering to richer markets and more affluent consumers also made Apple more resilient to the current macro crisis. The strength of Apple’s ecosystem, its walled garden of apps, its family of devices, and its well-renowned focus on user experience, also helped maintain demand for Apple during recent challenging years.  As did the iPhone’s stronger resale value throughout its life cycle.

Apple has also done well in supply: its superior navigation of the supply chain crisis from Covid-19-related lockdowns enabled its production to escape relatively unscathed, unlike some other industry players.

The Worst of Times

For Samsung on the other hand, it seems like the worst of times in the phone market. It has lost its position as number one in units, a position many in the phone business saw it retaining longer.

As the world’s everything everywhere brand in the phone market, many of Samsung’s difficulties in the last few years have to do with parts of the world, that is most of it, where the iPhone is an aspiration much more frequently than a possession.

It’s not just Samsung which is in the doldrums, it is the global Android market; global Android shipments shrank around 5 percent in 2023 and a total of 20 percent over the last five years.

There were some specific reasons why 2023 was a bad year.

While in the richer world affluence and postpaid deals gave many consumers the choice to ignore the wave of inflation and cost of living pressures, that was far less of an option for vulnerable poorer consumers, who reined in spending on Android smartphones.

So Android sales contracted in many countries, including those of Samsung, since two-thirds of its volume are low-end devices below $400 (Chart 3)

The economic situation in China as it emerged from the coronavirus lockdown dragged down the local market for one and had a knock-on effect on the global market.

But there are more general factors at play.

The motors of the Android market are also much less dynamic than they were. The Chinese 5G boom was over two years ago, and the Indian smartphone market is no longer growing so rapidly or consistently.

The market potential of some emerging markets remains long term, for instance, Africa – where despite smartphone penetration of around 40% according to the GSMA mobile trade body, the market is essentially flat.

Africa has been hit by the global downturn, with falls in several local currencies and new laws imposing import restrictions crashing certain large markets. Emerging markets often suffer badly in a global downturn.

So where has this left Samsung?

In terms of the Android players, it is not doing badly. It has retained its unit market share in Android, in fact it has been level-pegging for several years now.

It has also regained some of the premium smartphone share it lost when it stopped producing its Note series, and it leads in foldable. It has simplified and rationalized its model portfolio, increased its focus on the premium market, and gained 7pts in share from Apple over the last two years (Chart 2).

In the big mid-market economies which are key to the Android market outside China and India – Brazil and Mexico, Thailand and Malaysia – Samsung has in the last couple of years held its own, as it has in larger and poorer Indonesia and the Philippines, and of particular note in India.

Furthermore, Samsung has pushed up its ASP in many of these markets, despite bringing 5G rapidly to lower price points in its portfolio.

So Samsung is not that badly placed if Android-focused markets begin to grow again

These markets are more dependent on the economic cycle than Apple’s key markets, but the economic tide will turn.

Samsung may need to focus its competition in richer Apple markets on foldables, where Apple currently has no product, and reorientate its other flagships towards price brackets affordable in middle-income countries.

Apple meanwhile still faces the challenge of renewed competition from Huawei in China and how to expand into more countries without compromising the premium position of its products.

While Apple has pulled ahead of Samsung in unit sales, for now, they remain close rivals. It is a lopsided contest, in that Apple has the advantage of its own and compelling OS ecosystem while Samsung is limited by Android.

But Samsung is a feisty company, a global consumer electronics player with a worldwide presence, and not about to take playing second fiddle to Apple lightly.

Looking back at 2023, various factors and events come to mind that encapsulate the year: challenges such as economic slowdowns, soft recessions and flat GDP, rising interest rates, and inflation, which, in the tech industry would reflect focusing on controlling costs in areas such as cloud. Geopolitical tensions also surged, sparking new conflicts across global regions, while the relentless impacts of climate change continued to fuel natural disasters.

However, amidst these difficulties, there were also positive strides. COP28’s landmark agreement marked a pivotal shift away from fossil fuels, signaling a collective commitment to combatting climate change. Additionally, the WHO declaration of the end of the COVID-19 global emergency unblocked key trade and economic areas. Scientific and technological advancements were abundant, with the standout being the explosive rise of Generative AI, profoundly influencing investment plans, not just in the tech industry, but permeating other sectors, governments, and institutions. We are entering the AI-everywhere chapter in the Digital Business era.

IDC is not in the business of looking at the past, but rather analyzing how past and ongoing events shape the future digital landscapes. Keeping in mind the main highlights of last year, let’s take a look at the key macro events that are going to shape digital agendas in 2024:

From AI Ambitions to Actions: If 2023 has signaled the beginning of the AI everywhere chapter, 2024 is expected to be its consecration, or is it? The transition from AI aspirations to practical implementation is hindered by many factors: critical infrastructure and skills shortages, rising implementation costs, and rapidly changing infrastructure and data strategies; yet businesses are eager to progress.
The IT Industry AI Pivot: Tech providers are shifting R&D, staffing, and CAPEX investments to AI/automation. This creates a fascinating challenge for IT companies, where possessing the solution allows them to dictate prices, creating a competitive race between cloud, SaaS, major consulting firms, and key infrastructure players in determining the direction of the industry. It will be interesting to see how the 2023 investments will come to fruition in 2024, also in terms of new use cases, applications, and innovations; and, how Technology providers will react to the initial adoption challenges and show the potential of business value to end-users.
The Elections’ Year: EU elections, general elections in the UK and the US, and more than 60 other general elections worldwide are poised to shape the future guidance of global equilibria. These will have repercussions on the digital landscape: a shift in political powers in key regions might cause the readjustment or the halt of ongoing national plans and new priorities in countries’ digital agenda – green initiatives, international relations, investments, and regulations.
Inflation Evolution: the normalization of inflation rates towards the 2% target is likely to have to wait some more time. Despite some positive signs of deflation in the second half of 2023, prices rose again towards the end of the year. As a result, it seems we reached the peak of the interest rate raise, but it’s still uncertain whether we’ll see some cuts in H1 2024 or later on in the year. Ongoing disruptions in supply chains pose an increasing threat to the oil and energy sectors, and in many regions, IT product and service supply chain issues will also continue to affect costs and access to innovations.
Digital Regulations: In 2024, significant developments in IT regulations are anticipated, particularly on AI, with Europe taking the lead through the EU AI Act. This legislation will impact global players, although its effects may not be fully evident until later. The year will be crucial for gauging the timeline, initial consequences, and the enforcement approach of Member States. Other global players are engaged in the race to regulate AI, including the US with its executive order on AI and various legislative proposals in Congress, China and its draft rules on Gen AI, and Brazil’s somewhat EU-inspired rules. Other digital regulations are also going to be key this year, including the EU’s Digital Operational Resilience Act and the CSRD, data privacy regulations in various US states from California to Texas, and more.
Sustainability for Real: after the historic COP28’s agreement on fossil fuels, 2024 marks a pivotal year for sustainability reforms, also in the face of the increasingly frequent natural disasters – directly linked to climate change – that have been affecting the whole world in the last 12 months. Europe is poised to step up, as stringent regulations will be enforced in the region; in the US, the incentive-based approach with the Inflation Reduction Act (IRA) is finally expected to have a greater impact in 2024 and the SEC rules on climate disclosure; China’s strategic emphasis on its green industry to gain competitive advantage in global markets; some APAC countries have stringent climate and ESG regulations, like Australia and South Korea. Digital transformation and technologies will have a key role there, leveraging IT solutions to carry out green initiatives, but also by making the IT industry itself more sustainable and greener. VC funding for climate tech and sustainability innovations slowed down in 2023, but the newly established fund by COP28 will set precedence for further acceleration in this space. 2024 will also be the year when countries and organizations start linking AI investment decisions to the positive and negative implications of meeting sustainability goals.
Ecosystem Evolution Scenario: China’s supply and economic recovery plays a pivotal role in shaping global dynamics. The continued growth and resilience of China’s supply chains have far-reaching implications for the global economy, as the country remains a key player in various industries. As China attempts to recover from economic challenges and adapts its ecosystem, the implications can reshape global trade and IT market dynamics. The rise of digital sovereignty and protectionism, in general, is already redefining global trade and technology markets. Countries are focused on securing their technology supply chains, resulting in heightened competition for critical materials and a push for technological self-reliance. This trend, driven by concerns over national security and economic interests, could fragment the global tech supply chain and reshape the balance of power in emerging industries.
Continued Geopolitical Tensions: The ongoing conflicts in strategic global regions – the invasion of Ukraine and in the Middle East – continue to affect the markets in terms of investments, supply chain disruptions, and volatile oil prices. As we have been increasingly learning in the past couple of years, the IT market is not immune to these shocks: critical data centers are affected, talent is displaced or relocated, and key components procurement flows are disrupted. The supply chain deserves a spotlight, specifically related to disruptions in key worldwide shipping channels that are affected by ongoing conflicts. As things stand, most of the most critical conflicts happening worldwide are unlikely to be resolved in the short term, and their continuation can amplify their unsettling outcomes.

It’s essential to monitor ongoing macroeconomic events and be ready to assess and adjust strategic plans in the face of unexpected shocks. We follow all of this and more in our Digital Economy Strategies research. Get in touch to discover how IDC can support you in this continuously changing environment.