{"id":860,"date":"2025-12-04T14:26:20","date_gmt":"2025-12-04T06:26:20","guid":{"rendered":"https:\/\/www.chain258.com\/?p=860"},"modified":"2025-12-04T14:26:26","modified_gmt":"2025-12-04T06:26:26","slug":"china-and-u-s-ai-spending-growth-in-2026-will-focus-on-different-priorities","status":"publish","type":"post","link":"https:\/\/www.chain258.com\/index.php\/2025\/12\/04\/china-and-u-s-ai-spending-growth-in-2026-will-focus-on-different-priorities\/","title":{"rendered":"China and U.S. AI Spending Growth in 2026 Will Focus on Different Priorities"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><strong>57% of U.S. enterprises expect providers to pre-build agents, while 54% of Chinese enterprises prefer customizable agent building.<\/strong>According to\u00a0<em>Caijing Tuya<\/em>, a corporate intelligence expert, on December 2, Rick Villars, Vice President of IDC Global Research, delivered a keynote speech titled\u00a0<em>\u201cToward a New Era of Intelligence: Three Drivers Reshaping the Global IT Industry\u201d<\/em>at the\u00a0<em>IDC FutureScape 2026: China ICT Market Prediction Forum<\/em>.He noted that the global technology industry is entering an era of expansion. By 2027, total spending on servers and storage will exceed\u00a0<strong>700<em>bi<\/em><em>ll<\/em><em>i<\/em><em>o<\/em><em>n<\/em>\u2217\u2217,<em>an<\/em><em>d<\/em><em>so<\/em><em>f<\/em><em>tw<\/em><em>a<\/em><em>res<\/em><em>p<\/em><em>e<\/em><em>n<\/em><em>d<\/em><em>in<\/em><em>g<\/em><em>w<\/em><em>i<\/em><em>ll<\/em><em>s<\/em><em>u<\/em><em>r<\/em><em>p<\/em><em>a<\/em><em>ss<\/em>\u2217\u221716.7 trillion<\/strong>. However, only\u00a0<strong>13.6% of North American enterprises<\/strong>\u200b and\u00a0<strong>2.4% of Asia-Pacific enterprises<\/strong>\u200b are able to achieve measurable benefits from the majority of their AI projects, highlighting that\u00a0<strong>value realization remains a key challenge<\/strong>.\u201cTo break through the next barrier in AI application, enterprises need to establish enterprise-level AI strategies, build AI-ready workforces, and construct AI-ready technology stacks,\u201d Rick Villars emphasized.Overall,\u00a0<strong>both China and the United States are driving advancements in AI<\/strong>, but with different emphases. The U.S. is a major force behind AI expansion, primarily driven by\u00a0<strong>AI infrastructure and software<\/strong>, while\u00a0<strong>China\u2019s growth is more infrastructure-driven<\/strong>.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Breaking Through the Next Barrier in AI Application: Three Key Directions<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">When it comes to&nbsp;<strong>AI spending<\/strong>, the growth priorities of China and the U.S. in 2026 will vary significantly.Specifically:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u2022<strong>In the U.S.<\/strong>, efforts will focus on:\n<ul class=\"wp-block-list\">\n<li>\u2022Building\u00a0<strong>AI agents<\/strong>\u200b to automate business processes (<strong>expected growth: 48%<\/strong>),<\/li>\n\n\n\n<li>\u2022Enhancing\u00a0<strong>network recovery and resilience<\/strong>\u200b (<strong>33%<\/strong>),<\/li>\n\n\n\n<li>\u2022And\u00a0<strong>modernizing enterprise data center infrastructure<\/strong>\u200b (<strong>31%<\/strong>).<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>\u2022<strong>In China<\/strong>, priorities include:\n<ul class=\"wp-block-list\">\n<li>\u2022Modernizing\u00a0<strong>core enterprise applications<\/strong>\u200b (<strong>39%<\/strong>),<\/li>\n\n\n\n<li>\u2022Migrating\u00a0<strong>applications from public infrastructure to on-premises infrastructure<\/strong>\u200b (<strong>36%<\/strong>),<\/li>\n\n\n\n<li>\u2022And moving\u00a0<strong>applications from on-premises to the cloud<\/strong>\u200b (<strong>34%<\/strong>).<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Measurable AI Benefits Remain Limited<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Globally, only&nbsp;<strong>13.6% of North American enterprises<\/strong>\u200b are able to derive measurable benefits from&nbsp;<strong>more than 75% of their AI projects<\/strong>. Over the past two years, the average proportion of AI projects that have produced measurable outcomes stands at&nbsp;<strong>47%<\/strong>.Key challenges hindering enterprises from fully realizing the value of their AI investments include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u2022<strong>Resource competition between AI and other IT\/digital initiatives<\/strong>\u200b (36%),<\/li>\n\n\n\n<li>\u2022<strong>Resistance to the process changes required for AI integration<\/strong>\u200b (33%),<\/li>\n\n\n\n<li>\u2022<strong>Regulatory uncertainty affecting AI investment decisions<\/strong>\u200b (29%),<\/li>\n\n\n\n<li>\u2022And\u00a0<strong>difficulty in quantifying and demonstrating ROI to stakeholders<\/strong>\u200b (28%).<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">In the&nbsp;<strong>Asia-Pacific region<\/strong>, the percentage of enterprises gaining measurable benefits from over 75% of AI projects is even lower, at just&nbsp;<strong>2.4%<\/strong>, with the average proportion of projects delivering measurable results at&nbsp;<strong>38%<\/strong>\u200b over the past two years.Challenges specific to the region include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u2022<strong>Lack of clarity around ownership and accountability for AI outcomes<\/strong>\u200b (31%),<\/li>\n\n\n\n<li>\u2022<strong>Difficulty in quantifying and demonstrating AI ROI to stakeholders<\/strong>\u200b (30%),<\/li>\n\n\n\n<li>\u2022<strong>Resource competition with other IT\/digital initiatives<\/strong>\u200b (30%),<\/li>\n\n\n\n<li>\u2022And\u00a0<strong>resistance to process changes needed for AI integration<\/strong>\u200b (30%).<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Three Key Directions to Break Through the Next AI Barrier<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Rick outlined&nbsp;<strong>three strategic directions<\/strong>\u200b to overcome the next barrier in AI application:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>1.<strong>Developing an enterprise-level AI strategy<\/strong>\u200b to identify core business areas and prioritize transformation.<\/li>\n\n\n\n<li>2.<strong>Building an AI-ready workforce<\/strong>\u200b by planning and promoting necessary organizational changes.<\/li>\n\n\n\n<li>3.<strong>Constructing an AI-ready technology stack<\/strong>\u200b by optimizing the technological architecture to support AI and agent workflows.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cGoing forward,&nbsp;<strong>CIOs will bear the highest responsibility (46%) for driving their companies\u2019 AI transformations<\/strong>, while Chief AI Officers and CEOs account for only about&nbsp;<strong>18% and 16%<\/strong>, respectively,\u201d he pointed out.He added that in 2026, corporate priorities will include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u2022Identifying key business areas requiring transformation,<\/li>\n\n\n\n<li>\u2022Aligning investments and roadmaps with strategic goals,<\/li>\n\n\n\n<li>\u2022And establishing core teams to coordinate cross-company initiatives.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Over 1 Billion Active Agents by 2029<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cAgent workflows are reshaping the employee lifecycle, and companies need to rethink future work models,\u201d Rick said.By&nbsp;<strong>2026<\/strong>,&nbsp;<strong>40% of jobs<\/strong>\u200b will involve collaboration with AI agents, redefining traditional roles at junior, mid-level, and senior levels.By&nbsp;<strong>2027<\/strong>, the usage of agents among the&nbsp;<strong>Global 2000 companies<\/strong>\u200b is expected to grow&nbsp;<strong>10x<\/strong>, with invocation loads increasing&nbsp;<strong>1,000x<\/strong>. Agent selection, orchestration, and optimization will become core responsibilities. Without a high-quality, AI-ready data foundation, companies risk a&nbsp;<strong>15% productivity loss<\/strong>\u200b due to suboptimal performance of generative AI and agentic systems.<strong>In terms of agent sources:<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u2022<strong>57% of U.S. enterprises<\/strong>\u200b expect application providers to deliver\u00a0<strong>pre-built agents<\/strong>,<\/li>\n\n\n\n<li>\u2022While\u00a0<strong>54% of Chinese enterprises<\/strong>\u200b prefer the ability to\u00a0<strong>customize agents themselves<\/strong>.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cBy&nbsp;<strong>2025<\/strong>, there will be approximately&nbsp;<strong>28.8 million agents<\/strong>\u200b globally. By&nbsp;<strong>2029<\/strong>, the number of active agents will exceed&nbsp;<strong>1 billion<\/strong>, a more than&nbsp;<strong>40x increase<\/strong>\u200b from 2025\u2014of which&nbsp;<strong>39% will be unique, low-code\/no-code custom agents<\/strong>.\u201dRick further noted:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u2022In\u00a0<strong>2025<\/strong>, agents will perform\u00a0<strong>120 million actions per day<\/strong>; by\u00a0<strong>2029<\/strong>, this will rise to nearly\u00a0<strong>217 billion actions per day<\/strong>, a\u00a0<strong>1,798x increase<\/strong>, with\u00a0<strong>38% completed by custom agents<\/strong>.<\/li>\n\n\n\n<li>\u2022In terms of\u00a0<strong>Tokens\/Calls<\/strong>, daily token delivery in 2029 will surpass\u00a0<strong>3.7 trillion<\/strong>, a\u00a0<strong>2,626,000x increase<\/strong>\u200b from 2025, with\u00a0<strong>40% generated by custom agents<\/strong>.<\/li>\n\n\n\n<li>\u2022By 2029, the\u00a0<strong>average token\/call delivery cost per agent action<\/strong>\u200b will be\u00a0<strong>87% lower<\/strong>\u200b than in 2025.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cIn the new era of intelligence, the focus will be on designing for orchestration, delivering at scale, and governing for trust,\u201d Rick emphasized.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h3 class=\"wp-block-heading\">Recommendations for Enterprises<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">To thrive in this new paradigm, Rick advised enterprises to focus on the following:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>1.<strong>Ensure data integrity<\/strong>\u200b and invest in\u00a0<strong>AI governance, observability, and interoperability<\/strong>.<\/li>\n\n\n\n<li>2.<strong>Embrace modularity and interoperability<\/strong>, collaborating across ecosystems to build\u00a0<strong>open agent frameworks<\/strong>.<\/li>\n\n\n\n<li>3.<strong>Design for scale and sustainability<\/strong>, creating architectures capable of handling the exponential growth in the number of agents, interactions, and token\/call demands.<\/li>\n\n\n\n<li>4.<strong>Reassess pricing and delivery models<\/strong>, moving beyond traditional per-seat or per-license models toward\u00a0<strong>outcome-based and usage-driven approaches<\/strong>\u200b that reflect ongoing autonomous operations.<\/li>\n\n\n\n<li>5.<strong>Adopt a responsibility-oriented approach<\/strong>, establishing safeguards and compliance mechanisms to\u00a0<strong>build trust with both enterprises and the public<\/strong>.<\/li>\n<\/ol>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>In summary, as AI agents become ubiquitous, organizations worldwide must prepare for a future where intelligent automation reshapes workflows, data strategies, and business models\u2014requiring not only technological readiness but also governance, scalability, and trust at scale.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>57% of U.S. enterprises expect&hellip;<\/p>\n","protected":false},"author":2,"featured_media":861,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8,3],"tags":[24,227,78],"class_list":["post-860","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-deep-tech","category-investment","tag-ai","tag-china","tag-usa"],"_links":{"self":[{"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/posts\/860","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/comments?post=860"}],"version-history":[{"count":2,"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/posts\/860\/revisions"}],"predecessor-version":[{"id":863,"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/posts\/860\/revisions\/863"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/media\/861"}],"wp:attachment":[{"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/media?parent=860"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/categories?post=860"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.chain258.com\/index.php\/wp-json\/wp\/v2\/tags?post=860"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}