AI-Driven Business Improvement Cases at Silicon Valley Companies

Enterprise AI adoption, with Silicon Valley as its epicenter, clearly shifted phases in 2026 from "proof of concept" to "company-wide deployment." The enterprise AI market reached approximately $185–200 billion (roughly ¥27.75–30 trillion) in 2025 and is projected to exceed $800 billion (approximately ¥120 trillion) by 2030 (McKinsey, IDC). While foundational AI platforms such as ChatGPT Enterprise, Claude, Microsoft Copilot, and Gemini for Google Workspace continue to penetrate the enterprise, a layer beneath them has seen the rapid rise of specialized AI products — including internal knowledge search, meeting AI, contract management, customer support automation, sales intelligence, and workflow automation. "AI-native" startups such as Glean (valued at $4.6 billion / approx. ¥690 billion), Gong (valued at $7.25 billion / approx. ¥1.0875 trillion), Ironclad (valued at $3.2 billion / approx. ¥480 billion), and Cursor (valued at over $9 billion / approx. ¥1.35 trillion+) have achieved multi-billion-dollar valuations and are being deeply embedded into the operational processes of large enterprises. BCG research indicates that only 26% of AI-adopting companies are achieving returns commensurate with their investment; however, what successful companies share in common is the integration of these specialized tools into business processes and deployment in a form that enables clear ROI measurement. In Japan as well, AI startups such as Preferred Networks (valued at over $3.5 billion / approx. ¥525 billion+), Sakana AI (valued at over $1 billion / approx. ¥150 billion+), and Mujin (valued at over $2 billion / approx. ¥300 billion+) are gaining prominence. Simultaneously, domestically developed LLMs including NTT's "tsuzumi" are proliferating, the three major megabanks are rolling out deployments at the scale of tens of thousands of employees, and concentrated AI investment in Japan by AWS, Microsoft, and Google has surpassed a combined ¥3 trillion. This article examines, from multiple angles, an overview of the foundational platforms, the full landscape of specialized AI products that are genuinely transforming corporate operations, their concrete implementation outcomes, and leading case studies from Japanese enterprises.

Enterprise AI Market——Beyond the "Valley of Death of PoC"

The enterprise AI market is entering a period of explosive growth. IDC estimates global AI spending in 2025 at $632 billion (approximately ¥94.8 trillion), of which AI software accounts for $234 billion (approximately ¥35.1 trillion). McKinsey suggests that generative AI alone could create $2.6–4.4 trillion (approximately ¥390–660 trillion) in annual economic value.

However, behind the glamour of these figures lies the "PoC Valley of Death." According to Deloitte's 2025 report, 30% of generative AI projects are abandoned at the proof-of-concept stage, and fewer than half of all projects reach production. BCG research shows that only 26% of companies are achieving "significant financial returns" from AI. The primary causes of failure are not technical issues, but rather data quality, organizational change management, and the difficulty of measuring ROI.

Notably, many of the companies that have broken through the PoC barrier and achieved results are not using general-purpose LLMs as-is, but rather adopting AI products specialized for specific business operations. Marc Andreessen of Andreessen Horowitz (a16z) notes: "AI is following the same pattern as the internet in the 2000s. After the initial hype, the companies that actually transform business operations will be the ones that survive."

Foundational AI Platforms — An Overview of the 4 Major Players

The foundation for enterprise AI product suites rests on four core platforms.

ChatGPT Enterprise (OpenAI) launched in August 2023 and, as of late 2025, serves more than one million business users. It offers SOC 2 Type II compliance, a guarantee that data will not be used for training, and an admin console. In 2025, the Connectors feature enabled real-time integration with SharePoint, Confluence, and Salesforce. Pricing starts at $60 per user per month.

Claude for Enterprise (Anthropic) differentiates itself with a 200K-token (approximately 150,000-word) context window, enabling the processing of large volumes of internal documents in a single pass. Anthropic's annual revenue reached approximately $900 million in 2025, and its safety framework known as "Constitutional AI" is accelerating adoption in heavily regulated industries such as finance, legal, and healthcare.

Microsoft Copilot is integrated across Microsoft 365, GitHub, Azure, and Dynamics 365, and has been deployed by more than 700,000 organizations. Approximately 70% of Fortune 500 companies use it, and its greatest strength is seamless integration with the existing Microsoft ecosystem. AI-related ARR exceeded $13 billion in 2025.

Gemini for Google Workspace is an AI assistant integrated into Gmail, Docs, Sheets, Slides, and Meet. Available as an add-on starting at $20 per month (Business plan), it is offered to more than 9 million paying Google Workspace customers. It embeds AI capabilities across all Google Workspace applications, including document drafting assistance, email summarization, automated spreadsheet analysis, automatic presentation image generation, and meeting summarization and translation. Google reports that "70% of Gemini users experience an improvement in work quality," and early adopters have reported time savings of 30 to 45 minutes per person per day. Google Cloud's Vertex AI platform has also been adopted by companies including Mercedes-Benz (a virtual assistant handling millions of inquiries), Thomson Reuters (tripling the speed of legal AI solution development), and Wayfair (improving product search accuracy by 30%).

Internal Knowledge Search & Information Access — AI Integrates Scattered Knowledge

On top of foundational platforms, a suite of specialized AI products addressing specific enterprise business challenges has emerged. One of the fastest-growing categories is internal knowledge search and integration.

Glean is an AI platform that searches across more than 100 applications including Slack, Google Drive, Confluence, Salesforce, Jira, and ServiceNow. In 2024, it reached a valuation of $4.6 billion in its Series E round, bringing total funding to approximately $360 million. Companies such as Databricks, Duolingo, Grammarly, Palo Alto Networks, and Samsung have adopted it, reducing internal information search time by an average of 50–70%. At Duolingo, it cut one hour per employee per week spent searching for information.

Moveworks is an AI-powered IT support and employee service automation platform. It raised $200 million in its Series C round in 2022, reaching a valuation of $2.1 billion. Broadcom, DocuSign, Palo Alto Networks, Autodesk, and others have deployed it, autonomously resolving 40–60% of IT support tickets within seconds. At Broadcom, 75% of IT issues are resolved automatically.

Guru is a knowledge management platform that delivers reliable answers from internal wikis and various tools; it was acquired by Contentful in 2024. Shopify, Spotify, Airbnb, Square, and others have adopted it, achieving a 60% reduction in information retrieval time and a 30–50% reduction in onboarding time.

Meeting AI — Automation of Minutes & Decision-Making

The AI category transforming "meetings" — which consume a large portion of corporate working hours — is also growing rapidly.

Otter.ai integrates with Zoom, Teams, and Google Meet to transcribe, summarize, and extract action items from meetings in real time. It has processed over 300 million meetings in total and has more than 25 million users. It reduces 30–60 minutes of note-taking time per meeting, and 25% of users have reduced their meeting attendance by reading AI summaries instead.

Fireflies.ai offers meeting transcription and summarization, along with AI-powered cross-search across all meetings, automatic CRM updates, and sentiment analysis. It is used by more than 300,000 organizations and over 16 million people, including Netflix, Nike, Uber, Expedia, and Canva. It saves an average of 32 minutes per meeting and reduces manual meeting minutes creation by 83%.

Fathom is a rapidly growing meeting AI built on a freemium model. It raised $17 million in a Series A round in 2023 and is used by more than 4 million users across over 100,000 companies. Its user base grew 24x in 2023. The model offers core features for free and monetizes through team and enterprise plans.

Workflow Automation — From RPA to AI Orchestration

The automation of routine tasks is evolving from traditional RPA (Robotic Process Automation) to AI-integrated orchestration.

UiPath (NYSE-listed) is a leader in the RPA market with an ARR of approximately $1.3 billion. It integrates AI Document Understanding (automated document reading), process mining (business flow visualization), and Autopilot (generative AI-assisted automation building), and is used by more than 10,800 companies. Deutsche Post DHL has automated more than 200 processes, reducing over 100,000 hours of work annually.

Workato is an enterprise integration and automation platform. It raised $200 million in a Series E round in 2021, reaching a valuation of $5.7 billion. With more than 1,200 app connectors, it is used by over 17,000 companies including Broadcom, Visa, Slack, and GitLab. It deploys 67% faster than traditional integration tools and achieves an average ROI of 300% within six months.

Zapier is a no-code automation platform connecting more than 6,000 apps, used by over 2.2 million companies. Despite being bootstrapped, it has achieved profitability with an ARR of over approximately $250 million. AI features added in 2023 enabled workflow creation via natural language, reducing workflow build time by 60%. It has automated a cumulative total of over 25 billion tasks.

Make (formerly Integromat) is a visual workflow builder that handles more complex automation scenarios. It is used by more than 500,000 organizations including Coca-Cola, Spotify, Cisco, and Adidas. In 2023, it was acquired by Celonis, a leading process mining company.

Customer Support AI — Automating 70% of Human Interactions

Customer support is the area where the operational improvement effects of AI can be most clearly quantified.

Intercom Fin is an AI agent built into Intercom's customer service platform. It not only answers customer questions using help center and internal knowledge resources, but can also execute actions such as order confirmations and refund processing. Used by more than 25,000 companies including Atlassian, Notion, and Anthropic, it resolves 50–70% of customer inquiries without human intervention. First response time has been reduced by 44%.

Ada is an AI-first customer service automation platform. It raised $130 million in a Series C round in 2023, reaching a valuation of $1.2 billion. Adopted by Meta, Verizon, AirAsia, Shopify, Zoom, and others, it achieves a 70% automated resolution rate. For Meta, it reduced cost per conversation by 50%. It supports more than 50 languages and has processed over 4.5 billion customer interactions in total.

Zendesk AI is an AI capability built into Zendesk—which has a customer base of over 100,000 companies and was taken private in 2022 by Permira/Hellman & Friedman for $10.2 billion. AI triage (automated classification and routing) reduces handling time by 30–40%, with intent detection accuracy exceeding 90%. The automated ticket resolution rate by AI agents is 10–20% (growing rapidly), and the company claims it can reduce total cost of service by 20–30%.

Forethought is a customer support AI deployed at Instacart, Upwork, Carta, and others, achieving an average automated ticket deflection rate of 65%. At Instacart, it reduced ticket volume by 20%.

Sales Intelligence & Marketing AI — Revenue-Driven Efficiency

The sales and marketing domain is where AI-driven ROI improvement can be most directly measured.

Gong is a revenue intelligence platform that uses AI to record and analyze all customer touchpoints for sales teams (calls, emails, meetings), providing insights into deal health, pipeline, coaching opportunities, and revenue forecasting. It raised $250 million in a Series E round in 2021, reaching a valuation of $7.25 billion. Over 4,000 companies have adopted it, including LinkedIn, Shopify, HubSpot, PayPal, Zillow, and Paychex. Close rates for coached sales reps improved by 30%, and at LinkedIn, sales rep ramp-up time was cut in half. It delivers revenue forecasting accuracy that is 50% higher compared to traditional CRM-based forecasting.

Clari is an AI-powered pipeline management and revenue forecasting platform. It raised $225 million in a Series F round in 2022, reaching a valuation of $2.6 billion. Adopted by Okta, Zoom, Qualtrics, Adobe, and others, it achieves revenue forecast accuracy of over 95% (within ±5% of actual results). At Okta, forecast accuracy improved by 50%. The cumulative revenue managed on the platform has reached $4 trillion.

6sense is an AI-powered ABM (Account-Based Marketing) and buying intent prediction platform. It detects buying intent from anonymous website visitors and recommends the optimal timing for outreach. Adopted by Cisco, Dell, Cognizant, Snowflake, and others, it has delivered a 2x increase in pipeline, a 40% improvement in close rates, and a 30% reduction in sales cycles.

Writer is an enterprise content generation and governance platform, differentiated by its proprietary LLM (the Palmyra family). It raised $100 million in a Series B round in 2024, reaching a valuation of $1.9 billion. Adopted by Intuit, L'Oréal, Accenture, Uber, Deloitte, and others, it has been deployed to over 5,000 marketers at L'Oréal. It reduced first-draft creation time by 78%.

Contract & Document AI——The Transformation of Legal Tech

Contract management and document processing are areas where AI-driven automation delivers particularly significant impact.

Harvey (legal AI) has been deployed at Allen & Overy (now A&O Shearman), PwC (rolled out to over 40,000 people), and O'Melveny & Myers, among others. In its 2024 Series D, the company raised $300 million, reaching a valuation of over $3 billion. Sequoia Capital and OpenAI are among its investors. It accelerates contract review by 3x and reduces due diligence time by 40%. At Allen & Overy, attorneys save 1–2 hours per day.

Ironclad is an AI-powered contract lifecycle management (CLM) platform. It raised $150 million in a 2022 Series E at a valuation of $3.2 billion. Customers include L'Oréal, Mastercard, OpenAI, Dropbox, and Honda, and it reduces contract processing turnaround time by 80%. At L'Oréal, contract processing time was cut from 30 days to just one day.

DocuSign IAM (Intelligent Agreement Management) goes beyond e-signatures to offer automated contract data extraction, obligation management, and portfolio analysis. Announced as a strategic pivot in 2024, it is rolling out AI capabilities to a customer base of over 1.5 million companies. It reduces contract review time by 90% and aims to expand from the $6 billion e-signature market into the $50 billion-plus contract management market.

AI Coding Tools——A Revolution in Developer Productivity

Software development is one of the domains where AI-driven productivity gains are appearing most dramatically.

Cursor (Anysphere) is an "AI-first" code editor forked from VS Code. It offers inline code generation, simultaneous multi-file editing, and an AI chat that understands the entire codebase. It reached $100M ARR in approximately two years and surpassed a $9 billion valuation in early 2025 — the fastest ARR growth ever recorded for a developer tool. Used by engineers at Shopify, Midjourney, Samsung, and Stripe, with reported coding speed improvements of 30–50%.

GitHub Copilot has the broadest data demonstrating developer productivity gains. A GitHub study (2024) found that Copilot users complete coding tasks an average of 55% faster, with 46% of code being generated from Copilot suggestions. At $19/month, this translates to saving approximately 50 days of coding time per developer per year.

Tabnine is an AI code completion tool with full support for on-premises and air-gapped environments, making it the choice for enterprises with strict security requirements (Samsung, Siemens, Comcast, Cigna). Its key differentiator is fully private deployment with zero data retention.

BI and Data Analytics AI — The Era When Non-Engineers Can Speak the Language of Data

In the realm of business intelligence, AI is also accelerating the "democratization of data."

ThoughtSpot is an AI analytics platform that allows users to ask questions of their data in natural language and instantly obtain charts and dashboards. The company has raised approximately $740 million (around ¥111 billion) in cumulative funding, with a valuation of $4.2 billion (around ¥630 billion). Adopted by Walmart, Hulu, Daimler, CVS Health, Royal Bank of Canada, and others, it delivers insights 10 times faster than traditional BI tools and reduces ad hoc report requests to analytics teams by 80%. At Walmart, thousands of non-technical employees are now able to perform data analysis autonomously.

Hex is a collaborative data platform combining SQL, Python, and AI. In 2022, it raised $52 million (approximately ¥7.8 billion) in a Series B round. Adopted by Notion, Brex, Fivetran, and others, 60% of its users are non-engineers (product managers, marketers). Its AI features reduce query creation time by 30–50%.

RAI Infrastructure — The Foundation Supporting Specialized AI Products

Many of these specialized AI products rely on RAG (Retrieval-Augmented Generation) architecture. The infrastructure supporting those RAG pipelines has also formed its own independent ecosystem.

Pinecone is a managed vector database for AI applications. It raised $100 million in a Series B round in 2023, reaching a valuation of $750 million. More than 30,000 organizations—including Shopify, Notion, Gong, HubSpot, and Zapier—use it, and it surpassed $100 million ARR in 2024. It delivers query latency under 100 milliseconds at the scale of billions of vectors.

LangChain is an open-source framework for building LLM applications, used by more than 100,000 developers, while its commercial platform LangSmith has been adopted by over 5,000 companies. It raised $25 million in a Sequoia-led Series A. It reduces LLM application development time by 40–60%.

Unstructured is an ETL platform that preprocesses unstructured data from more than 40 file formats—including PDFs, images, and HTML—for use with LLMs. Financial institutions such as BlackRock have deployed it, reducing data preparation time by 80%.

Concrete Results — How Specialized AI Tools Are Transforming the Workplace

These specialized AI products have achieved remarkable results in individual deployment cases.

Broadcom × Moveworks: 75% of IT support requests are now resolved automatically. Resolution time, which previously averaged 3 days, has been reduced to under 1 minute for automated tickets. First-year ROI has reached 200–300%.

Deutsche Post DHL × UiPath: Over 200 business processes have been automated, eliminating more than 100,000 hours of manual work annually. AI Document Understanding processes paper-based operations at 5–10x the previous speed.

L'Oreal × Ironclad: A contracting process that previously took 30 days has been reduced to 1 day. Legal team review time has been cut by 50%, and over 50,000 contracts are managed on the platform.

LinkedIn × Gong: Sales representative ramp-up time has been cut in half, and close rates for sales reps who received AI coaching improved by 30%.

Meta × Ada: The cost per customer support conversation has been reduced by 50%. 70% of inquiries are resolved by AI agents alone, with support available in over 50 languages.

Instacart × Forethought: AI-powered automatic ticket classification and routing reduced ticket volume by 20%. Agent ramp-up time was reduced to one-fifth of what it previously was.

Walmart × ThoughtSpot: Thousands of non-technical employees can now perform data analysis autonomously, reducing ad hoc report requests to the analytics team by 80%.

What Separates Successful Companies from Failed Ones

What separates the 26% of companies achieving results from AI investment from the remaining 74%, according to BCG research.

Three common traits of successful companies are as follows. First, executive commitment. In April 2025, Shopify CEO Tobi Lütke issued a company-wide directive requiring proof that a problem cannot be solved with AI before any new hire is approved, resulting in approximately 25% year-over-year productivity improvement per employee. McKinsey research shows that companies with a CEO-led AI task force achieve three times the results of those without one. Second, deep integration into business processes. Rather than simply adopting tools, companies are rebuilding their operations with AI as a foundational assumption — just as Gong transformed the entire sales workflow and Ironclad redesigned the contract process. Third, phased rollout with clear ROI measurement. Running a proof of concept on a specific business process, confirming results, then scaling.

The common pattern among failing companies is "technology first, operations second." Deloitte points out that "the biggest bottleneck in generative AI adoption is not technology but change management."

Andrew Ng (Stanford University professor and founder of Landing AI) has stated: "AI is becoming democratized, but that means 'anyone can use AI' — not 'anyone can produce results with AI.' Achieving results requires both operational understanding and AI literacy."

Japanese Companies — Full-Scale Company-Wide AI Deployment Gains Momentum

Japan's enterprise AI adoption is accelerating in earnest throughout 2025–2026. Among large companies with 1,000 or more employees, the utilization and trial rate of generative AI has surged from approximately 20% in early 2023 to 50–60% by the end of 2024. Japan's AI market is projected to reach approximately ¥3–4 trillion in 2025, growing at an annual rate of 25–30%.

Particularly noteworthy is the rise of Japanese-born AI startups. Preferred Networks (PFN) is one of Japan's largest AI startups, boasting a valuation exceeding $3.5 billion (over ¥525 billion). The company has formed partnerships with Toyota Motor (autonomous driving), Fanuc (factory robotics), and RIKEN (supercomputing), and has developed its own AI chip, the "MN-Core," achieving vertical integration from foundational technology to applications. In the field of "Physical AI"—applying deep learning to the physical world—the company has established a unique position on the global stage.

Sakana AI was founded in Tokyo in 2023 by Llion Jones, a co-inventor of the Transformer. Between 2024 and 2025, it raised a cumulative total of over $300 million (over ¥45 billion), reaching a valuation exceeding $1 billion (over ¥150 billion). The company has developed an evolutionary model merging technique inspired by nature, and the very fact that a world-class AI research lab chose Tokyo as its base demonstrates the gravitational pull of Japan's AI ecosystem.

Mujin is an AI-powered industrial robotics company with a valuation exceeding $2 billion (over ¥300 billion). Its proprietary "MujinController" equips robots with 3D vision and motion planning, enabling picking and palletizing without traditional programming. It has been deployed at Fast Retailing's (UNIQLO) Ariake warehouse and at major logistics companies.

AI inside is an AI-driven OCR and document processing platform listed on the Tokyo Stock Exchange, with widespread adoption among Japanese corporations and local governments. PKSHA Technology (TSE-listed) provides conversational AI and NLP technology to major banks and telecommunications companies, establishing a strong presence in the field of enterprise AI specialized for the Japanese language.

AI deployment by large corporations is also accelerating. NTT launched its proprietary LLM "tsuzumi" for enterprise customers in March 2024. Thanks to its lightweight architecture, it runs on a single GPU and is reported to achieve up to 70 times the cost efficiency of GPT-4 on specific Japanese-language tasks. Panasonic Connect was a pioneer among major Japanese companies, deploying a ChatGPT-based AI assistant to approximately 13,000 employees in 2023, recording approximately 5,000 uses per day. SoftBank has rolled out an in-house generative AI tool to all approximately 20,000 employees and has automated roughly 50% of call center inquiries with AI. The three megabanks are also advancing generative AI deployments—approximately 50,000 employees at MUFG and approximately 45,000 at Mizuho—while SMBC has reduced document processing time for loan screening by approximately 40%.

Vinod Khosla, founder of Khosla Ventures, remarked at a Tokyo conference: "Japan's corporate culture—its attentiveness, precision, and meticulous approach to process—is actually very well-suited to AI adoption." Some analysts note that the Japanese approach of applying the manufacturing kaizen culture to AI adoption—accumulating small, incremental improvements—yields higher sustained adoption rates compared to the American approach of pursuing large-scale transformation all at once. The coexistence of multiple domestically developed LLMs—NTT's "tsuzumi," NEC's "cotomi," and Fujitsu's "Takane"—providing Japanese companies with data sovereignty options is also a structural strength of the Japanese market.

Global tech giants' AI investment in Japan has also reached record levels. AWS approximately ¥2.26 trillion (~$15 billion), Microsoft approximately ¥420 billion (~$2.9 billion), Google over ¥100 billion (~$700 million+)—more than ¥3 trillion in total AI infrastructure investment is concentrated in Japan. This is a testament to global confidence in the growth potential of the Japanese market.

The Next Frontier of Enterprise AI——The Age of AI Agents

In 2026, enterprise AI is evolving from "chatbots" to "agents." AI agents that autonomously execute multiple steps, use tools, and make decisions — rather than responding to a single prompt — are beginning to be embedded into corporate business processes.

Salesforce Agentforce has secured contracts with over 1,000 paying customers since its October 2024 launch, and at Wiley (the publisher), case resolution rates improved by 40%. Microsoft Copilot Studio enables users to build custom agents with no code. Anthropic introduced the "computer use" capability for Claude, opening the door for AI to directly perform computer operations.

a16z partner Matt Bornstein predicts: "2026 is the year of AI agents. Enterprises will transition from mere chatbots to agents that autonomously carry out business processes." Nvidia CEO Jensen Huang declared at CES 2026 that "every company will become an AI factory." The question is no longer "whether to adopt AI," but has entered the phase of "how to adopt it effectively."

Impact on the Industry

First, the primary battleground in enterprise AI competition has shifted from foundational platforms to the layer of specialized AI product suites. "AI-native" companies such as Glean ($4.6B), Gong ($7.25B), Ironclad ($3.2B), and Cursor (over $9B) have secured multi-billion-dollar valuations and are deeply integrated into the operational processes of large enterprises. Meanwhile, products that are little more than thin wrappers around general-purpose LLMs face downward valuation pressure, and the picture is becoming clear: companies with proprietary data moats hold the competitive advantage.

Second, AI-driven operational improvement is advancing not "company-wide all at once," but rather "one business process at a time." Moveworks (75% automated resolution for IT support), Ada (70% automated resolution for customer support), Gong (30% improvement in close rates), Ironclad (contract processing time reduced from 30 days to 1 day)—what these success stories share is deep integration into specific business processes and deployment in a form that allows clear ROI measurement.

Third, an ecosystem of specialized AI product suites is taking shape. RAG infrastructure (Pinecone, LangChain), workflow automation (UiPath, Workato, Zapier), intelligence layers (Gong, Clari, 6sense), and front-ends (Intercom Fin, Ada, Zendesk AI) are interconnecting to form the enterprise AI stack. The average enterprise uses 3–5 specialized AI tools on top of foundational platforms, and budgets for these tools are growing 40–80% year over year.

Fourth, Japan's AI ecosystem is genuinely taking off. The rise of AI startups such as Preferred Networks (valuation over $3.5B), Sakana AI (co-founded in Tokyo by a co-inventor of the Transformer, valuation over $1B), and Mujin (valuation over $2B); the parallel development of domestic LLMs including NTT's "tsuzumi"; and deployments at scale across tens of thousands of employees at all three major megabanks—Japanese enterprises are charting their own course with an approach of "gradual, reliable adoption" drawn from kaizen culture. The combined AI investment in Japan exceeding ¥3 trillion from AWS, Microsoft, and Google signals global confidence in this market's growth potential.

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