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With the rise of technology sovereignty, major economic regions are aggressively developing self-sufficient ICT industry supply chains with the semiconductor industry as a key focus area. To contain China’s development in semiconductors and technology, in addition to export control and enactment of the CHIPS Act, the United States has also joined forces with the Netherlands, Japan, etc. to restrict China’s acquisition of semiconductor equipment tools (e.g., EUV and DUV), materials, specialty chemicals, software (EDA and IP) capabilities.

Despite this restrictive environment, Chinese vendors continue to adapt, and IDC has observed these key trends that deserve special attention:

  • Mature Manufacturing Processes Development and Government Subsidy Policy Models Transformation

As China is unable to develop its advanced manufacturing processes because of export controls on equipment, mature processes have become its industrial development focus. In the past, to develop semiconductor autonomy, Chinese government subsidies were mostly on the expansion of wafer manufacturing capacity. However, due to the overall environmental impact and the inability to obtain more substantial orders, many plants have become idle, underutilized, and unable to produce sustainable benefits for industrial development. To remedy this, the current government subsidy model was changed. Now based on operating results, wafer factories must obtain orders first and have a certain degree of capacity utilization to obtain government subsidies. This shift has made Chinese wafer fabs more active in attracting customers through different strategies (e.g., low pricing, placing orders first and then returning part of the investment amount later, etc.). Compared with the previous subsidy model, this incentivizes local fabs and IC design companies to expand their business.

China’s wafer fabs are currently self-sufficient in 22/28nm and older process technologies (given the available equipment tools). In the future, through government policies and subsidies, coupled with the support of China’s huge domestic demand market, it is expected that China will have a mature process market in 2030 (≥ 22nm) and will reach nearly 40% share (30% in 2023). China’s influence on the global semiconductor production capacity will also increase as it puts pressure on International Device Manufacturers (IDMs) and foundries focusing on mature nodes.

  • Focus on Wide-Bandgap Semiconductors

Wide-bandgap semiconductors, such as silicon carbide and gallium nitride, have the characteristics of low power leakage, high power, high-temperature resistance, and high voltage resistance. They are especially suitable for high-voltage and high-current environments. Therefore, in the future, wide-bandgap semiconductors will play a key role in applications such as electric vehicles, high-frequency communications, 5G communications, and green energy. At present, Wide-bandgap semiconductors are mostly regarded as national security-level industries. These are also the projects regions are investing in, developing, protecting, and establishing policies to encourage investment and export controls.

Every region expects to maintain technological independence in wide-bandgap semiconductors. China has listed it as a development priority in its 14th Five-Year Plan and hopes to further develop the technology and use it rapidly in new energy vehicles, communication industries, etc. Under this initiative, related applications are the focus. In 2023, China’s capacity of silicon carbide (SiC) crystal growth continued to grow. In addition to joining hands with IDMs, China will also begin to enter the power components market. If the new production capacity is effectively produced in 2024, China SiC wafer’s market share will increase significantly, and its industrial influence cannot be ignored.

  • Actively Lay Out Chiplets

China is also using chiplets to connect chips with different functions and slow down the impact of the restricted development of high-end chips. China has established a chiplet alliance and produced their first chiplet technical standard. In the “Advanced Cost-driven Chiplet Interface(ACC 1.0)” drafted by China ChipLet League in 2023, more emphasis was also placed on optimizing China’s packaging and substrate supply chain through chiplets and expanding related packaging technologies. However, although China actively hopes to break through in this area, not all chips are suitable for chiplets. For example, chips used in consumer electronics, such as mobile phones and laptops, rarely require chiplet designs. In addition, chiplet design requires more IP and usually the use of advanced packaging technology which is costly and not China’s strength. It will take time to see whether chiplets can become a key driver of China’s semiconductor independence in the future.

Bigger Challenges Lie Ahead

In their efforts to further the development of their semiconductor industry, China has seen initial positive results in the mature processes and IC design fields. However, from a long-term development perspective, semiconductor equipment is still an important key. The market for semiconductor equipment and related components and materials is quite fragmented, and the certification process is complex and cyclical. This market is also currently highly concentrated in the United States, Netherlands, and Japan. Hence, it will remain a challenge for China to achieve full autonomy.

Currently, under the ban, China is no longer able to import high-end machines from ASML. How long the existing tools in the facilities supplied by ASML can maintain operation still needs to be evaluated. Although China actively supports local equipment manufacturers, and related manufacturers, such as Northern Huachuang, AMEC, and Shanghai Microelectronics (who are actively expanding their business), these manufacturers still lag by more than 5 generations compared to international first-tier tool manufacturers in terms of product accuracy and performance. Also, although China has invested in dry/wet etching, thin film deposition, and polishing and grinding equipment, there is still a gap in lithography tools. In the latest phase (the third phase) of China’s National Fund’s plan, related news mentioned that one of China’s areas of focus and development is in chip manufacturing equipment, highlighting the important correlation between semiconductor equipment and China’s semiconductor industry development.

China has actively maneuvered through the ban on semiconductor policies in the United States and other countries and has quickly adjusted its policies. However, as semiconductor equipment and related components are still heavily dependent on imports, it will not be easy to achieve full autonomy within five years. Relying on external advanced technology and equipment, we expect China’s semiconductor development will be a gradual process even with the strategy of upgrading technology and gradually increasing manufacturing experience.

On the other hand, China has gained the opportunity and motivation to develop mature processes despite the restrictions comprehensively. Their mature processes can still meet the requirements of current applications, including consumer electronics, automotive electronics, and industrial, among many other applications in the semiconductor market. Despite all these, China is still currently the second-largest semiconductor application market in the world. As their share of mature processes gradually expands in the future and related IC design capabilities gradually improve, China will still play a key role in the development of the global semiconductor industry.

Explore IDC’s Semiconductor Research

Helen Chiang - Country Manager - IDC

Analyst Profile
Helen Chiang is the lead of Asia Semiconductor research and the general manager of IDC Taiwan. She is responsible for analysis, forecast, and research of semiconductor supply chain sectors such as IC design, OSAT, and Asia IC design, AI and automobile semiconductor. Since joining IDC in 2007, Helen conducted numerous research and consulting projects about semiconductor, cloud, AI, IoT, security, emerging technology and vertical market in Taiwan and across Asia Pacific region. She also provided professional market analysis and high-value consulting strategy to C-level managers. She not only leads the team to develop new market opportunities successfully, but also to provide customers with long-term growth capabilities.

A little over a year ago, a new phase of the digital business era began with OpenAI’s launch of ChatGPT. The generative AI (GenAI) boom is expected to roundly influence what comes next: AI Everywhere. AI is expected to become a driving force of our digital future, impacting individual lives, consumers, citizens, workers, businesses, and society.

Henry Ford said, “The only real mistake is the one from which we learn nothing.” What should we learn from the past to determine the way forward?

After the 2023 hype (see Reimagining an AI Everywhere Digital Future: IDC EMEA FutureScape 2024), 2024 is expected to be the year when AI becomes real for organizations. The focus is expected to remain predominantly on GenAI for many organizations through the first half.

When looking at the future, there are urgent actions EMEA organizations should take to accelerate their AI Everywhere readiness. And there are some useful lessons we can learn from the past.

According to IDC’s Future Enterprise Sentiment Survey, in 2022 just 9% of EMEA organizations considered their digital transformation (DX) projects to have been successful. This is a clear indicator of the multiple pitfalls that can plague a DX journey, including organizational silos, lack of ROI, unreasonable time frames for completing the initiative, lack of internal skills and change management, and gaps in infrastructure requirements.

Looking at the DX challenges of past years provides us with a clear indication regarding “things not to do/forget” when charting a successful AI Everywhere road map.

In October 2023, when we asked EMEA CIOs about their spending plans for 2024, 91% confirmed they expect to maintain or increase their budgets in 2024. That investment needs to drive a return.

If you don’t want to follow the organizations that saw digital projects fail in past years, what should (or shouldn’t) you do?

5 Lessons for your AI Business Strategy

  1. Don’t regard AI as an IT tool. It’s a business reimagination. AI should not be seen just as another tool, but as an opportunity to transform the business to become more efficient, deliver new value to customers, and innovate with products and services. Aligning technology and AI investments to business strategy and requirements is critical to achieving higher returns in the age of digital business.

The stakes are high — these decisions will determine the success or failure of businesses. From developing an overarching strategy and identifying the right business use cases, to deciding whether workloads will work best on premises, in the public cloud, or in a hybrid environment, there are numerous decision points. Dealing with the challenges of a potential proliferation of AI applications requires foresight and forward-looking leadership.

As mentioned by the CEO of a Global Professional Service organization, every leader in the organization should engage at least with the “what” of this technology, understanding what the real use cases and opportunities are. Initially, the budget for experimenting with the technology will come from the IT and data department, but business will increasing lead when progressing with the use case road map budget.

With so many decision makers, having a coordinated holistic approach is paramount. Whether through the creation of new roles (e.g., chief AI officer) or within the remit of existing ones, organizations need to manage AI initiatives through a defined organizational structure. There’s a need to have a structured and coordinated approach from the AI strategy to the use cases road map, all surrounded by strong governance to foster a responsible AI deployment.

  1. Don’t forget to measure. Quantify the digital business impact. In the past, we talked about the digital ROI gap — the gap between digital investments and the ability to generate results from them. The greater cautiousness driven by the volatile macroeconomic scenario, combined with tech pricing concerns, imposes a laser focus on ROI. It is imperative for organizations to define the business outcomes they want to achieve with AI, check them against the investments needed, and measure the progress toward their achievement to adjust the tech strategy procurement if needed.
  2. You won’t have three years to show results. Start small, think big. The use case prioritization exercise should factor in the quantification of business value, the cost and capabilities requested, and the risk of the initiative — as well as the time to outcomes. Make sure your use case portfolio is well balanced, with several smaller projects that have a shorter time to market and can better demonstrate business value, and few mid-sized ones that have a slightly longer timeline.

The CEO of a non-profit organization told us, “We have reengineered the technology road map to completely align to business requirements. What have we changed? We reprioritized projects so we are now working on fewer bigger projects and then a lot of small, more innovative projects that are creating value in the in the short term.” Particularly regarding GenAI initiatives focused on productivity, the CIO feedback is that these need to be proven within two to six months.

  1. You won’t go far without the basics. Prioritize building a secure, intelligent architecture and data foundation. If you are looking at AI as an opportunity to transform the business and not another tool to plug and play — which is the way you should approach the AI Everywhere transformation journey — you should not overlook the importance of the required foundations and the alignment with partners and the broader ecosystem.

A successful AI road map can only be realized through a solid, agile and intelligent technology backbone. This must comprise key technology enablers, foundational data and analytics, cloud for scale and agility, security technologies to ensure cyber protection and remediation, as well as regulatory compliance and smart risk mitigation.

A well-governed data system is critical to ensure data quality, trustworthiness, and actionability. According to IDC’s Digital Executive Sentiment Survey (September 2023), only 53% of EMEA organizations have integrated data sets and effectively manage them to deliver returns.

  1. Don’t underestimate the importance of change management. Humans should be at the center. As happened in the past 200 years, industrial revolutions have brought tech closer to humans, unlocking new opportunities. Similarly, we are now undergoing an industrial revolution powered by AI — and the human element should remain central to the process.

A main pitfall companies should avoid is not considering it a change management program. Developing the right culture and skills is critical. This applies to all organizational levels. According to European CEOs, the top skill to be successful in their role is AI proficiency. Engaging all stakeholders from the get-go is key for successful AI projects, as we have seen many digital initiatives fail because of organizational silos.

The CEO of a fintech company, for example, has championed the development of an AI certification program for the entire organization. The program has multiple levels and is mandatory for all employees. As a true change management program, the members of the leadership team actively drove change in the organization. They were the first to complete the certification program and developed guidelines and procedures for a responsible use of the tech.

Similarly, a member of the IDC CIO Advisory Board highlighted the employee journey as one of three critical pillars to be successful on the journey: Build transparency on upcoming tech needs and train the people to adopt and leverage future technologies.

Practical Steps to Move Forward on Your AI Journey

In a nutshell, here’s what you should do:

  • Bring the C-suite dream team together to develop an aligned strategy.
  • Create a road map for use cases.
  • Embed GenAI’s transition into a more comprehensive AI strategy.
  • Measure your AI-enabled business impact.
  • Decide on your next infrastructure approach: Build, buy, amend, or have it managed.
  • Plan for an agile yet secure digital platform with a strong data foundation.
  • Engage employees and build talent for new ways of working.
  • Build strategic and trusted partnerships and ecosystems for co-innovation.

As we have seen since the beginning of DX, IT teams and CIOs will play a central role in the AI Everywhere age. The increasing importance of the CIO role and the opportunities it brings in 2024 are unmistakable.

With the expected increase in IT investments, especially in the field of AI, CIOs face a unique opportunity to position themselves as a driving force behind the next level of transformation. However, it should be emphasized: These investments should not be made lightly.

The transition to the AI world requires careful planning, resource allocation, and implementation, and will likely impact the operating and organizational model. But as a medtech CIO put it, if you can learn from the past and embrace the future, “The future will be bright.”

Andrea Siviero - Senior Research Director, MacroTech, Digital Business, and Future of Work - IDC

Analyst Profile
Andrea Siviero leads IDC's European Digital Business and Future of Work Research group. The group provides market research insights to foster a purposeful and fair adoption of technologies supporting digital societies, businesses and workforce and empower tech providers in strategic decision making, planning and go-to-market activities. Siviero also co-leads the IDC Worldwide MacroTech Research program, focused on the intertwined connection between the Economical and Digital worlds - analyzing the impact key MacroEconomic factors have on the digital landscape and viceversa, how technologies are impacting economies around the world.

To maintain a competitive edge, customers in Latin America are embracing co-managed security solutions, consolidation projects, and cost-efficiency goals. These additional reasons for selecting Managed Detection and Response Services are becoming more and more important.

Are you wondering, what to focus on when it comes to security in the era of Gen AI?, if so, you might be interested in the top 3 reasons for selecting Latin America Managed Detection and Response (MDR) Services, Let’s read more about it.

Well, before thinking it’s better to be alone than in bad company, let’s consider some criteria that could help you to save budget and avoid tough questions from board members.

Have you thought about the top 3 reasons for your organization to select Managed Detection and Response (MDR) Services?

According to respondents, in our latest IDC Latin America: Managed Detection and Response (MDR) Survey, (who were qualified in three waves of rankings), the top 1 in each wave are as follows:

Figure 1
  • 1st: Brand Recognition, this could be interpreted as how well-known the company is in the security service provider market ecosystem, but resist the temptation and focus on their trust, reputation, transparency, and ethics.

” Breaches happen to everyone, and some may fall but remember, transparency builds trust”, Emanuel Figueroa.

  • 2nd: Functional superiority over other competitors, a service provider must be able to achieve the security outcomes desired by the organization, and this is directly related to the timing in the detection and response lifecycle, capabilities in terms of integration to existing ecosystems, and reporting power.

“If they are able to customize their operations to your environment or industry, that means superiority, not just talking about technology features”, Emanuel Figueroa.

  • 3rd: Adjacent capabilities that could be utilized, as security initiatives are always a clean canvas, you must take into consideration that a service provider who could offer advice on how particularly resolve your needs and a robust security offering could reduce the friction caused by areas like purchasing, change management, IT, internal auditing, and risk management and of course finance.

…. But what about cost-effectiveness?

Well, IDC has seen the CISO environment grow in importance to the business, but the more the C-suite gets involved, the more questions CISOs receive about budget efficiency, and the back-and-forth to save resources each year remains one of the biggest challenges.

1 in 3 organizations completely outsource their security tools, with the most challenging tools preferred.

In our recent Managed Detection and Response (MDR) survey, we found that organizations are not only systematically benchmarking direct pricing but also comparing feature sets and costs across vendors (see Figure 1).

IDC knows that all organizations are different – some prefer flexibility over predictability – but we recommend understanding the pricing model, scalability, and time to value before making a decision.

Finally, how do you achieve efficiency and transparency, and manage risk to a level that is acceptable to the board?

By efficiency, we mean increasing operational efficiencies; the faster you and your vendor can resolve issues, detect future incidents, and contain/stop them before they disrupt vital services, the more efficient security will be and the more cyber resilient you will become. 

“Security outcomes must meet your specific needs, remain relevant, and be actionable.”

Other efficiencies include reducing the amount of time your staff spends troubleshooting, reporting changes, or requesting adjustments; the more self-service you implement, the more you improve staff productivity and security analyst workload/alert fatigue.

Keep in mind that a large stack of on-premises and cloud assets may require the same level of protection, so automated responses will help your initiatives succeed, and in some cases will require flexibility from the MDR service provider to scale at your pace.

In terms of transparency, look for service providers that can inherit compliance but also can demonstrate privacy and data residency according to your needs, in terms of technical support, look for providers that can supply interfaces with other customers, especially within your industry peers and consortia; this will enhance your experience and help you understand how well they can integrate into your existing environment.

In terms of risk management, ask your service provider how their service is going to improve your security posture, is there any technology that will help you profile your current and future risk exposure, analytics, incident management and threat hunting alone are features,

Is there a risk management report that could add value to your risk management process? Do they present their findings in business terms?

Key takeaways

  • Assess your MDR needs and opportunities; requesting proof of value can help you address your use cases and determine criteria for appropriate evaluation.
  • Review the IDC Market Glances to understand the competitor’s landscape in the managed security services of Latin America.
  • If you are interested in understanding the vendors’ opinions, feel free to reach out, and do not hesitate to ask them who managed security service providers are better prepared or acknowledged.
Learn More About IDC’s Latin America Security Strategies

Emanuel Figueroa - Senior Research Analyst, Identity and Access Management Security, Worldwide - IDC

Analyst Profile LinkedIn
Emanuel Figueroa serves as a Senior Research Analyst for IDC Identity and Access Management Security. His research scope encompasses a range of critical IT security, risk, and trust-related subjects, with particular emphasis in identity security. Emanuel’s research also emphasizes the effect of continuous change in the IT security market, as well as the trends and challenges currently facing security offices. These challenges include threats, security paradigms, and architectures that are transforming businesses. Prior to joining the global organization, he served as the Latin America Security Market Expert.

Saudi Arabia is making good on its ambition to become a global smart and sustainable tourist destination.

Not long ago, however, such an outcome seemed unlikely. When we traveled from Europe to the kingdom in 2015, for example, we were required to prepare piles of documents months in advance. We also had to make a trip to a Saudi visa application center, which existed in only a handful of European cities.

Getting through passport control at King Khaled International Airport meant standing in line for at least an hour. The quickest way to get to town was via a pre-booked car service, which invariably came in the form of a gas-guzzling SUV. After arrival in Riyadh, the entertainment options were slim.

But now, nine years later, the immigration process and airplane boarding can take literally a blink of an eye. This reflects the Saudi aviation industry’s investments in growth, customer experience, and operational excellence.

Commuting to Riyadh also comes in all shapes and forms of private transportation — and public transit is on the way. The city buzzes with museums, theaters, concerts, sport events, and Michelin star restaurants. It will host, along with partner cities across the country, the Asian Winter Games 2029, as well Formula 1, Formula E, the Dakar Rally, World Expo 2030, and the FIFA World Cup in 2034.

Obviously, these rapid changes did not occur accidentally. They are the fruits of an ambitious vision to enhance the country’s social fabric and lay the foundation for a diversified economy that leverages the full spectrum of its population’s talents and contributions. Saudi Arabia aspires to reduce its dependence on oil and ensure economic resilience by cultivating sectors such as tourism and entertainment.

Bold Vision — Sustainable Execution

The government’s Vision 2030 marks a pivotal chapter in the history of the kingdom, signaling a transformative shift towards the goals of openness, cultural evolution, and economic diversification. Travel, tourism, and entertainment are strategic priorities in this economic diversification and social reform road map.

The Digital Tourism Strategy aims to boost tourism’s contribution to GDP from 3% to 10% by 2030 and to increase the number of foreign visitors from around 60 million to 100 million annually by 2030. Investments are already paying off.

Since the opening of its doors in 2019 to international tourists, the kingdom has become the fastest growing tourism destination in the G20.

But the ambition extends beyond growth of the tourism industry. Giga projects like Neom, Diriyah, and Red Sea — backed by the $600 billion Public Investment Fund (PIF) — are being developed not only to increase capacity to host new residents, visitors, and global events, but also to reimagine the quality of life and the cultural, heritage, leisure experiences, environmental sustainability, and innovation expectations of next-generation tourists.

Saudi Arabia seeks to explore “the art of the possible” in terms of eco-friendly tourism, architectural design, and green technologies. The kingdom seeks to align these developments with the United Nations’ Sustainable Development Goals. The aim is to pioneer a responsible tourism model that safeguards the country’s rich natural and cultural heritage while fostering economic prosperity and improving Saudi quality of life.

By 2030, the kingdom plans to reduce by 50% the carbon emissions generated by the tourism industry. In parallel, it is creating wildlife sanctuaries and developing sustainable tourism initiatives that protect endangered species and the natural landscape. Planned developments at the Red Sea project are an example of authorities’ regenerative environmental approach.

Saudi Arabia largely imports its food from abroad and is running out of water. To address this, Neom plans to become food self-sufficient and source water from carbon-free desalination plants. Some resorts are exploring the concepts of biomimicry and developing nature-based architectural designs.

To accelerate the execution of such an ambitious vision, Saudi public institutions and private investors are working closely with local and global technology companies to empower them to reimagine the visitor experience and operational excellence in a sustainable manner.

Sustainable Tourism: Powered by Tech Innovation

The Saudi Tourism Authority’s (STA) traveler-centric approach and ambition to develop personalized experiences for visitors is a major differentiator from other destinations. Visitors who share their interests and preferences, for example, can receive customized recommendations during their stay in the kingdom. For world sports events like Formula E, guests can enjoy immersive experiences.

Digital technology is also powering Saudi Arabia’s long-standing tradition of hosting the annual religious pilgrimages of Hajj and Umrah, with a range of apps offered to enhance the safety and experience of millions of pilgrims from around the globe.

Plans also call for the building and operation of digital-by-design entertainment facilities that leverage digital twins and metaverse-centric solutions. These require partnering with technology companies that can deliver next-generation digital infrastructure, platforms, and user experience capabilities that align with the kingdom’s sustainable tourism and entertainment agenda.

To execute these ambitious visions, local and global technology vendors need to partner with the senior leaders driving the giga projects, as well as with national authorities like the STA and the Authority for Data and AI (SDAIA), which serves as a strategic decision maker for Saudi aspirations to leverage AI to enhance smart tourism destinations. Technology vendors and advisors can also help the kingdom leverage international best practices, such as the UNWTO framework, and to set the baseline and measure progress against sustainable tourism targets.

From personalized travel experiences to efficient resource management and environmentally and socially responsible engineering and construction supply chains, Saudi Arabia is being watched by global leaders who are also reimagining and developing new standards for sustainable tourist destinations.

Tech innovation will be critical to execute such an ambitious vision while confronting a demographic boom and limited natural resources — all while keeping a human touch that allows tourists as well as citizens to enjoy the fruits of these developments.

“Customer experience”, whether we are discussing discrete and process manufacturing, construction, healthcare, retail, or other industries, is omnichannel, supported by multiple tools, processes, and data models.  These experiences are also supported by interconnected partners working together by sharing the requisite and related customer data & insights, applications, operations, and expertise.

In our (3rd annual) 2023 Future of Industry Ecosystems global survey (n=1288), fielded to CxOs, business line executives, and IT leaders, we strive to determine current and planned approaches to industry ecosystems. More specifically, we ask questions related to strategy, use case focus, and IT investment for industry ecosystem success.

For IT investment, cloud infrastructure and applications as well as cybersecurity remain critical, while customer data platform (CDP) is also a top-three focus. Sharing customer data with ecosystem partners is not something end-user organizations have extensively done in the past – but that is changing, with products, services, and experiences delivered quickly in a blended physical and digital way, innovation expectations high, and end customers that demand personalized experiences. A network of on-demand partners that share mutually beneficial customer data makes this possible and scalable.

Organizations realize that they must work closely with their partners to orchestrate that end-user experience (whether consumer, customer, citizen, or patient) while having this be seamless and substantive. This is true whether the industry is fast-moving consumer goods, industrial manufacturing, or energy distribution. As such, for three years running in our Future of Industry Ecosystems Global Survey, CDPs continue to be a leading IT investment in support of industry ecosystems.

Another key element for engaging customers and consumers across industry ecosystems is the blending of physical and digital approaches to product and service experiences. Better visibility and decision support, clear communication and collaboration, and ensuring a relevant, quality experience for customers and consumers are the reasons why the melding of physical and digital products and services is important to the vibrancy of ecosystems today. This approach also includes the use of digital twins for asset, process, and resource optimization (particularly important and prevalent in the industrial space), which is especially important as organizations digitally extend their way of working across technology and business domains, within the organization, and among ecosystems of partners.

Customers and consumers expect this blending of physical and digital offerings to work together without interruption, which is possible only through a network of industry ecosystem providers. For this interconnected mash-up of physical and digital to function optimally and orchestrate activity across the industry ecosystem, several models, platforms, and digital technologies must be in place, including marketplaces and industry clouds (IC) that are empowered by cognitive, AI, and GenAI-driven systems that help determine the next best product or service action. Across the ecosystem, there will be different business models for the constituents of the ecosystem, with the mash-up between the physical and digital being key to success.

Other points that highlight the importance of industry ecosystems to ensure a good customer experience for the end user:

  • The end customer is considered by most organizations to be among the top two most important ecosystem partners, collaborators, and co-innovators (along with strategic consultants).
  • IoT remains an important investment related to industry ecosystem IT: this is due to the wealth of performance, as well as customer, use data that exists within connected assets, products, and processes.
  • One related point from our Future of Industry Ecosystems global survey is that there is strong interest in leveraging Web3 decentralized technologies and environments (metaverse, DAOs, tokens) to engage more closely with customers – although investment plans for blockchain are relatively low.  This could be due to a lack of knowledge that blockchain is an enabling Web3 tech.
  • We expect continued interest in and investment in CDPs for industry ecosystems, as organizations see the value in establishing a central place for shared customer information, accessible to all industry ecosystem partners.

In 2024, a team of IDC analysts (including me) will be writing on what it takes to be “Experience Orchestrated” in your business – for internal employees, ecosystem partners, and the end customer. My focus is how industry ecosystems enable this: what strategies and business models, technologies required, and use cases to focus on. Be on the lookout for more Experience Orchestrated Ecosystem research from my Future of Industry Ecosystems practice. Explore additional information on this practice including videos, eBooks, and research agenda.

Learn More About the Future of Industry Ecosystems

Jeffrey Hojlo - Research Vice President - IDC

Analyst Profile
As Research Vice President, Future of Industry Ecosystems, Innovation Strategies, & Energy Insights at IDC, Jeff Hojlo leads one of IDC's Future Enterprise practices at IDC - the Future of Industry Ecosystems. This practice focuses on three areas that help create and optimize trusted industry ecosystems and next generation value chains in discrete and process manufacturing, construction, healthcare, retail, and other industries: shared data & insight, shared applications, and shared operations & expertise. Mr. Hojlo manages a group focused on the research and analysis of the design, simulation, innovation, Product Lifecycle Management (PLM), and Service Lifecycle Management (SLM) market, including emerging strategies across discrete and process manufacturing industry such as product innovation platforms and the closed loop digital thread of product design, development, digital manufacturing, supply chain, and SLM. He also manages IDC's North American Energy Insights group, with a focus on key topics such as energy transition & sustainability, distributed energy resource management, and digital transformation in the Oil & Gas and Utilities industries.

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.

Learn More About IDC Mobile Phone Tracker

Contributing authors:

Nabila Popal - Sr. Director, Data & Analytics - IDC

Analyst Profile
Nabila Popal is Senor Director with IDC's Data & Analytics team, specializing in Mobile Phones, PC Monitors and other consumer devices. Ms. Popal is responsible for the global research and quality and timely delivery for her respective technologies, coordinating with regional and worldwide research teams. She continuously engages with global vendors and key market players to discuss the latest industry trends and dynamics. Ms. Popal is also responsible for future product planning and evolution whilst managing client relationships and providing thought leadership and executing custom engagements. She also manages communications with the media and is often published in leading local and international media outlets. Ms. Popal has been with IDC since 2013, and prior to her role with the Worldwide team, she was with IDC MEA, leading the research for Middle East, Africa, and Turkey, based out of Dubai, UAE.

Making government services more people-centric is not a new aspiration, but with fast advances in technology and rising societal expectations, public sector senior leaders are re-imagining how to deliver on that promise.

Since the inception of e-government in the early 2000s (later also known as smart government and digital government), making services available through digital channels became a critical instrument to improve citizen and business experience, as well as to attract investors and tourists, and collaborate with across government entities. These initiatives yielded results in terms of operational efficiency, convenience for and engagement with constituents.

Notwithstanding the progress, siloed processes and systems, forcing people and businesses to experience time-consuming bureaucratic services, and inequality of access to e-government services are still open issues.

Public sector leaders that aim to usher in the next generation of the people-centric services should understand people’s and businesses’ needs and circumstances through intelligent use of data, simplifying and joining up services across programs, partnering with the private sector, making digital services more inclusive, and enabling trusted interactions to make the bureaucracy truly “invisible”.

Reimagining Service Delivery, Operating and Trust Models

Making government bureaucracy invisible means embracing technology-powered innovation to drive proactive operations that will deliver seamless services for empowered people and businesses:

  • Service delivery model. The next generation of invisible services will be seamless. Constituents (citizens, businesses, investors, tourists, etc.) will not realize that public services are being delivered. They will not be asked to interact with the government to know what services they are entitled to or be interrupted in their daily routine because they receive a request to provide data to prove changes in circumstances.
  • Operating model. The next generation of invisible operations will be proactive. Without intruding into people’s and businesses’ daily lives, the government will know enough to understand the events that impact constituents and changes in circumstances. Governments will proactively register constituents for programs that they are entitled to and automatically deliver services.
  • Trust model. The next generation of invisible bureaucracy will shift from enforcement to empowerment. Instead of enforcing compliance after the fact, the government will make compliance easy for constituents through automated, proactive services, and simplified regulations. Government will invest in digital trust through proactive, transparent personalized notifications, and tools to see how personal data is being used across departments.

The Road to Invisible Government Bureaucracy

To accelerate the road towards Invisible Government Bureaucracy, public sector senior leaders should implement changes around the six building blocks:

  1. Building a holistic view of people, businesses, and communities. To avoid asking for the same data again and again, to understand when a change in circumstances offers an opportunity for the government to proactively deliver a service, and to empower open engagement, governments are investing to build a 360° view of people, businesses, communities.
  2. Scaling cognitive processes and services. Governments need to re-engineer processes and embed AI-enabled cognitive capabilities into systems so that they can recognize changes in the circumstances of their constituents, identify root causes and trigger operational workflows or dynamically reconfigure services and programs to satisfy the evolving constituent needs.
  3. Designing and delivering people-centric experience journeys. Increasingly, people will expect to interact with systems through conversational interfaces that can recognize their language, accent, tone of voice, instead of having to scroll through screens and fill forms. Cognitive capabilities will be embedded in every touch points throughout the user experience journey.
  4. Ensuring accessibility and inclusion for all. The non-intrusive and proactive nature of the invisible government bureaucracy will also enhance inclusion by lowering accessibility the barriers. However, as conversational and generative AI, immersive reality solutions become more pervasive, they must be designed with accessibility in mind.
  5. Investing in next-generation trust services. The public sector should invest in digital trust tools that enable citizens to conveniently access digital services across government, without having to remember multiple login credentials. Such tools will help citizens have a transparent understanding on how government use personal data and opt-in or opt-out of data sharing.
  6. Expanding collaboration with third parties. Government are working with private enterprises and community organizations to enable constituents to enjoy the lowest possible number of interactions with the government, to eliminate duplicate request for personal data, and the best possible convenience and proximity when those interactions are needed.

The latest IDC Government Insights study explores how to adapt organizational capacity and competencies, revisit policies, work with the ecosystem, and ensure public trust, to make Invisible Government Bureaucracy a reality.

Massimiliano Claps - Research Director - IDC

Analyst Profile
Massimiliano (Max) Claps is the research director for the Worldwide National Government Platforms and Technologies research in IDC's Government Insights practice. In this role, Max provides research and advisory services to technology suppliers and national civilian government senior leaders in the US and globally. Specific areas of research include improving government digital experiences, data and data sharing, AI and automation, cloud-enabled system modernization, the future of government work, and data protection and digital sovereignty to drive social, economic, and environmental outcomes for agencies and the public.

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.
Learn More

Lynne Schneider - Research Director - IDC

Analyst Profile
Lynne Schneider is Research Director leading IDC's Data Collaboration & Monetization, and Location & Geospatial Intelligence market research and advisory practices. Ms. Schneider's core research coverage in DaaS includes data sourcing and delivery services from traditional and emerging data providers along with evolving data aggregation and dissemination platforms. The breadth of coverage includes services that enable an organization to externally monetize data generated as part of the organization's ongoing operations, value-added information derived from this data, and the marketplace for combining data with other solutions. This research analyzes the supply and demand side business and technology trends of this emerging category.

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.

Learn More

Gerry Murray - Research Director, Marketing and Sales Technology - IDC

Analyst Profile
Gerry Murray is a Research Director with IDC's Marketing and Sales Technology service where he covers marketing technology and related solutions. He produces competitive assessments, market forecasts, innovator reports, maturity models, case studies, and thought leadership research. Prior to his role at IDC, Gerry spent six years in marketing at Softrax Corp. an enterprise financial solutions provider. There, he managed marketing programs that produced 4 million emails a year, multiple websites, interactive tools and product tours, an online game, collateral, and PR. Concurrently, he was Managing Editor at RevenueRecognition.com, a thought leadership site featuring partnerships with IDC and the Financial Accounting Standards Boards (FASB) which was quoted and referenced in leading industry publications such as CFO magazine, BusinessFinance, and others. Gerry spent the first half of his career at IDC advising executives from some of the world's largest software and services providers on market strategy, competitive positioning, and channel management. He was the Director of Knowledge Management Technology and conducted research on a worldwide scale including: market sizing and forecasting, ROI models, case studies, multi-client studies, focus groups, and custom consulting projects.

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.

By 2028, 70% of B2B buyers in the United States will use GenAI to help them discover, evaluate, and select products and services.

IDC FutureScape: Worldwide B2B Sales Leadership 2024 Predictions

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.

Learn More About IDC’s Sales Enablement Resources

Additional Resources:

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