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EY Megatrends

How superfluid enterprises reshape organizations for competitive edge play_circle_filled Play video video Matt Barrington

EY Americas Chief Technology Officer; EY Global AI Activation Leader

27 minute read 12 Nov 2025 Related topics EY wavespace™ COO agenda Supply-chain "> Link Copied Autonomous AI, smart contracts and digital twins will enable superfluid enterprises — flat networks that eliminate operating frictions.\r\n"}}" id="rich-text-9f53f76c67aa" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> Autonomous AI, smart contracts and digital twins will enable superfluid enterprises — flat networks that eliminate operating frictions. Read More Read Less In brief

\r\n\r\nThe shift to superfluidity will involve three stages — AI-assisted operations, collaborative autonomy and fully superfluid enterprises.\r\nAutonomous systems will handle routine execution while human leaders focus on strategic direction, ethical boundaries and ecosystem relationships.\r\nLeaders need to build hybrid governance, transform talent strategies and redefine competitive advantage for an era of machine-driven operations.\r\n\r\n"}}" id="rich-text-f79967dc6c73" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> In brief

The shift to superfluidity will involve three stages — AI-assisted operations, collaborative autonomy and fully superfluid enterprises.Autonomous systems will handle routine execution while human leaders focus on strategic direction, ethical boundaries and ecosystem relationships.Leaders need to build hybrid governance, transform talent strategies and redefine competitive advantage for an era of machine-driven operations. Read More Read Less This article is part of the first set of insights in the new EY Megatrends series: Preparing for the human-machine hybrid era.

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This article is part of the first set of insights in the new EY Megatrends series: Preparing for the human-machine hybrid era.

Read More Read Less Sara, the Chief Operations Officer (COO) at a global manufacturing firm, is starting her Monday in the not-so-distant future. Instead of a flood of emails and meetings, she reviews an overnight report from her company's autonomous artificial intelligence (AI) systems. While she slept, three supply chain issues were automatically resolved through smart contract partnerships, two new supplier agreements were negotiated and implemented, and predictive maintenance algorithms helped avert four potential equipment failures by pre-ordering parts and scheduling technicians. Her weekend was uninterrupted, yet her company operated at peak efficiency nonstop.

\r\nSara's role has significantly changed. She no longer handles daily crises or arranges endless meetings between departments. Instead, she directs strategic decisions within a flexible network of autonomous partners, setting high-level objectives while AI agents manage the complex coordination that used to take up 60% of her time.

\r\nThis isn't science fiction, it's the rising reality of what we call the superfluid enterprise. In a superfluid organization, operational frictions have been all but eliminated, enabling data, talent and capital to flow smoothly and speedily across former silos. Departments collaborate seamlessly, external partners integrate effortlessly, and value moves at the speed of digital execution. These enterprises are increasingly autonomous, running 24/7 through autonomous AI agents and smart contracts, allowing them to adapt instantly to market changes while humans focus on strategy, creativity and judgment. The result is an organizational structure that is flat and organized around networks rather than hierarchical org charts, enabling the company to reshape itself as quickly as circumstances demand, and flow around obstacles that would have paralyzed traditional hierarchies.

\r\nFor generations, successful organizations have excelled at managing friction: the many barriers that slow decision-making, hinder coordination and raise operational costs. But what happens when that friction vanishes? The convergence of several emerging technologies — agentic AI, quantum computing, blockchain-enabled smart contracts and decentralized autonomous organizations (DAOs) — are starting to eliminate these traditional barriers. This will ultimately build organizations where information, decisions and value flow with little resistance across what were once significant sources of friction.

\r\nThe economic case for this change is both urgent and compelling. Gallup's 2024 State of the Global Workplace Report shows that employee disengagement costs the global economy $8.8 trillion each year in lost productivity, which amounts to about 9% of global GDP.1 US companies alone lose around $2.1 billion every day — over $766 billion annually — due to workplace incivility, including unnecessary meetings, duplicated processes and communication breakdowns.2 Internal friction —such as ineffective meetings, redundant approvals, and information silos — costs companies an average of $15,000 per employee each year, while data silos alone cause organizations to lose 20-30% of their revenue because of operational inefficiencies.3

\r\n"}}" id="rich-text-47f134b58051" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> Sara, the Chief Operations Officer (COO) at a global manufacturing firm, is starting her Monday in the not-so-distant future. Instead of a flood of emails and meetings, she reviews an overnight report from her company's autonomous artificial intelligence (AI) systems. While she slept, three supply chain issues were automatically resolved through smart contract partnerships, two new supplier agreements were negotiated and implemented, and predictive maintenance algorithms helped avert four potential equipment failures by pre-ordering parts and scheduling technicians. Her weekend was uninterrupted, yet her company operated at peak efficiency nonstop.

Sara's role has significantly changed. She no longer handles daily crises or arranges endless meetings between departments. Instead, she directs strategic decisions within a flexible network of autonomous partners, setting high-level objectives while AI agents manage the complex coordination that used to take up 60% of her time.

This isn't science fiction, it's the rising reality of what we call the superfluid enterprise. In a superfluid organization, operational frictions have been all but eliminated, enabling data, talent and capital to flow smoothly and speedily across former silos. Departments collaborate seamlessly, external partners integrate effortlessly, and value moves at the speed of digital execution. These enterprises are increasingly autonomous, running 24/7 through autonomous AI agents and smart contracts, allowing them to adapt instantly to market changes while humans focus on strategy, creativity and judgment. The result is an organizational structure that is flat and organized around networks rather than hierarchical org charts, enabling the company to reshape itself as quickly as circumstances demand, and flow around obstacles that would have paralyzed traditional hierarchies.

For generations, successful organizations have excelled at managing friction: the many barriers that slow decision-making, hinder coordination and raise operational costs. But what happens when that friction vanishes? The convergence of several emerging technologies — agentic AI, quantum computing, blockchain-enabled smart contracts and decentralized autonomous organizations (DAOs) — are starting to eliminate these traditional barriers. This will ultimately build organizations where information, decisions and value flow with little resistance across what were once significant sources of friction.

The economic case for this change is both urgent and compelling. Gallup's 2024 State of the Global Workplace Report shows that employee disengagement costs the global economy $8.8 trillion each year in lost productivity, which amounts to about 9% of global GDP.1 US companies alone lose around $2.1 billion every day — over $766 billion annually — due to workplace incivility, including unnecessary meetings, duplicated processes and communication breakdowns.2 Internal friction —such as ineffective meetings, redundant approvals, and information silos — costs companies an average of $15,000 per employee each year, while data silos alone cause organizations to lose 20-30% of their revenue because of operational inefficiencies.3

Read More Read Less Open image description Close image description This chart illustrates the measurable business impact of adopting AI-powered automation and smart contract governance. Companies report 2–3x ROI on AI investments, 35–50% operational cost savings, and 50–70% reduction in cycle times.
Companies that successfully reduce this friction through AI-powered automation and smart contract governance report remarkable returns: two to three times ROI on AI investments, 35-50% operational cost savings, and cycle time reductions of 50-70%.4

\r\nAlthough the economic case for superfluidity has existed for decades, it is now becoming real and urgent due to underlying trends in technology, sustainability and geopolitics. Technological advancements are allowing companies to eliminate operational frictions in ways that were previously impossible. This includes rapid progress in AI, the maturation of blockchain and quantum computing — all accelerated by an environment where technology is evolving quickly and can suddenly reach tipping points that catch companies off guard (such as AI’s “ChatGPT moment”). Additionally, resource scarcity and an increasingly urgent climate crisis require more efficient supply chains, while geopolitical volatility raises the need for operational structures that can respond swiftly to changing events, all of which make superfluid enterprises more appealing.

\r\nThe question facing leaders today isn't whether this transformation will happen, but whether their organization will lead it or be swept along by competitors who embrace superfluidity first.

\r\nThis transformation is critically important for Chief executive officers (CEOs) seeking a competitive edge, Chief Marketing Officers (CMOs) managing decentralized go-to-market efforts, Chief Operating Officers (COOs) streamlining complex processes, Chief Technology Officers (CTOs) developing scalable infrastructure, and Chief Risk Officers (CROs) safeguarding resilience in volatile markets. Each role faces unique challenges: CEOs must position their organizations for a significantly different competitive environment, CMOs need autonomous systems to coordinate global sales and partnerships, COOs require continuous operations to remove coordination bottlenecks, CTOs have to design platforms enabling 24/7 autonomous execution, and CROs must implement adaptive frameworks that sustain governance while allowing rapid reconfiguration. For boards overseeing long-term strategy, understanding the concept of superfluidity is crucial to assessing whether management is building organizations prepared for the next decade of business.

\r\n"}}" id="rich-text-237be7c6777e" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> Companies that successfully reduce this friction through AI-powered automation and smart contract governance report remarkable returns: two to three times ROI on AI investments, 35-50% operational cost savings, and cycle time reductions of 50-70%.4

Although the economic case for superfluidity has existed for decades, it is now becoming real and urgent due to underlying trends in technology, sustainability and geopolitics. Technological advancements are allowing companies to eliminate operational frictions in ways that were previously impossible. This includes rapid progress in AI, the maturation of blockchain and quantum computing — all accelerated by an environment where technology is evolving quickly and can suddenly reach tipping points that catch companies off guard (such as AI’s “ChatGPT moment”). Additionally, resource scarcity and an increasingly urgent climate crisis require more efficient supply chains, while geopolitical volatility raises the need for operational structures that can respond swiftly to changing events, all of which make superfluid enterprises more appealing.

The question facing leaders today isn't whether this transformation will happen, but whether their organization will lead it or be swept along by competitors who embrace superfluidity first.

This transformation is critically important for Chief executive officers (CEOs) seeking a competitive edge, Chief Marketing Officers (CMOs) managing decentralized go-to-market efforts, Chief Operating Officers (COOs) streamlining complex processes, Chief Technology Officers (CTOs) developing scalable infrastructure, and Chief Risk Officers (CROs) safeguarding resilience in volatile markets. Each role faces unique challenges: CEOs must position their organizations for a significantly different competitive environment, CMOs need autonomous systems to coordinate global sales and partnerships, COOs require continuous operations to remove coordination bottlenecks, CTOs have to design platforms enabling 24/7 autonomous execution, and CROs must implement adaptive frameworks that sustain governance while allowing rapid reconfiguration. For boards overseeing long-term strategy, understanding the concept of superfluidity is crucial to assessing whether management is building organizations prepared for the next decade of business.

Read More Read Less About EY Megatrends This article is part of EY Megatrends series. Megatrends are global, cross-sector macroeconomic disruptions, driven by the intersection of two or more “primary forces”—technology, demographics, sustainability and geopolitics. In an operating climate that is increasingly defined by change that is nonlinear, accelerated, volatile and interconnected (NAVI), megatrends help clients scan broadly, explore interconnections, and take a longer-term perspective while building a bridge to near-term actions.

\r\nFor more, see ey.com/megatrends

\r\n"}}" id="rich-text-cf79d57b4c3c" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> This article is part of EY Megatrends series. Megatrends are global, cross-sector macroeconomic disruptions, driven by the intersection of two or more “primary forces”—technology, demographics, sustainability and geopolitics. In an operating climate that is increasingly defined by change that is nonlinear, accelerated, volatile and interconnected (NAVI), megatrends help clients scan broadly, explore interconnections, and take a longer-term perspective while building a bridge to near-term actions.

For more, see ey.com/megatrends

Read More Read Less Methodology The EY Megatrends series features future-facing perspectives based on a combination of qualitative and quantitative research. The selection and refinement of megatrends topics was developed through a series of workshops and consultations with subject matter experts, including:

\r\n\r\nA crowdsourcing exercise with six futurists and executives/entrepreneurs exploring how the nature of disruption and innovation have changed.\r\nA workshop with approximately 15 futurists, leading academics and EY client-serving leaders, exploring the NAVI concept and its implications for business leaders.\r\nTwo workshops with more than 20 EY analysts and professionals to nominate, co-develop and prioritize megatrends topics.\r\nDevelopment of scenarios within the primary forces—technology, geopolitics, demographics and sustainability—and mapping these scenarios to the “Four Futures” framework developed by Prof. Jim Dator. This effort was led by four analyst teams, in consultation with multiple EY Leaders and subject matter experts.\r\n\r\nThe article built on this foundation through research that included:

\r\n\r\nSubject matter expert interviews with technology leaders and human augmentation specialists with experience and expertise in topics ranging from venture capital, artificial intelligence, the future of work, and entrepreneurship.\r\nAnalysis of enterprise implementations of AI-powered automation, smart contract governance, and ecosystem coordination strategies across Fortune 500 companies, using data obtained from the Coinbase "State of Crypto" report (Q2 2024) and Plug and Play Tech Center’s research on Fortune 500 AI governance, for insights into transformation patterns and business outcomes.\r\nReview of venture capital investment trends in agentic AI, blockchain infrastructure, and enterprise automation technologies between 2023-2025, analyzing market maturity and commercial viability indicators for autonomous operation technologies. The data for this analysis was drawn from EY quarterly VC investment reports, Crunchbase News quarterly funding analyses, and publicly reported figures from Mintz analysis.\r\nSynthesis of data from multiple EY surveys: \r\nCIO Sentiment Study of 500 US-based CIOs, surveyed in March 2024\r\nCEO Outlook Study with global survey of 1,200 CEOs globally conducted in July-August 2024\r\nTwo Responsible AI Pulse Surveys of 975 C-suite leaders surveyed in March-April 2025 and July-August 2025\r\nGovernment and Public Services Data and AI Survey of nearly 500 senior government executives surveyed in 2024-2025\r\n\r\n\r\n\r\n"}}" id="rich-text-6876ef6f5162" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> The EY Megatrends series features future-facing perspectives based on a combination of qualitative and quantitative research. The selection and refinement of megatrends topics was developed through a series of workshops and consultations with subject matter experts, including:

A crowdsourcing exercise with six futurists and executives/entrepreneurs exploring how the nature of disruption and innovation have changed.A workshop with approximately 15 futurists, leading academics and EY client-serving leaders, exploring the NAVI concept and its implications for business leaders.Two workshops with more than 20 EY analysts and professionals to nominate, co-develop and prioritize megatrends topics.Development of scenarios within the primary forces—technology, geopolitics, demographics and sustainability—and mapping these scenarios to the “Four Futures” framework developed by Prof. Jim Dator. This effort was led by four analyst teams, in consultation with multiple EY Leaders and subject matter experts. The article built on this foundation through research that included:

Subject matter expert interviews with technology leaders and human augmentation specialists with experience and expertise in topics ranging from venture capital, artificial intelligence, the future of work, and entrepreneurship.Analysis of enterprise implementations of AI-powered automation, smart contract governance, and ecosystem coordination strategies across Fortune 500 companies, using data obtained from the Coinbase "State of Crypto" report (Q2 2024) and Plug and Play Tech Center’s research on Fortune 500 AI governance, for insights into transformation patterns and business outcomes.Review of venture capital investment trends in agentic AI, blockchain infrastructure, and enterprise automation technologies between 2023-2025, analyzing market maturity and commercial viability indicators for autonomous operation technologies. The data for this analysis was drawn from EY quarterly VC investment reports, Crunchbase News quarterly funding analyses, and publicly reported figures from Mintz analysis.Synthesis of data from multiple EY surveys: CIO Sentiment Study of 500 US-based CIOs, surveyed in March 2024CEO Outlook Study with global survey of 1,200 CEOs globally conducted in July-August 2024Two Responsible AI Pulse Surveys of 975 C-suite leaders surveyed in March-April 2025 and July-August 2025Government and Public Services Data and AI Survey of nearly 500 senior government executives surveyed in 2024-2025 Read More Read Less Glossary Agentic AI: AI systems that autonomously manage complex, multi-step tasks, making decisions and adapting to changing conditions without human intervention for routine operations.

\r\nAutonomous operations: business processes that operate continuously with minimal human intervention, where AI manages routine decisions while humans concentrate on strategic oversight and creative problem-solving.

\r\nBlockchain: distributed ledger technology that records transactions across multiple computers, enabling transparent, secure coordination between organizations and providing the foundation for smart contracts.

\r\nContext engineering: the human skill of framing problems and setting parameters that allow AI systems to function effectively while staying aligned with organizational values.

\r\nDAOs (Decentralized Autonomous Organizations): organizations governed by smart contracts and code instead of traditional hierarchy, allowing coordination across distributed networks without central authority.

\r\nDigital twins: virtual replicas of physical objects or systems that offer real-time visibility into autonomous operations, allowing human oversight through auditable models that forecast outcomes with 90-95% accuracy.

\r\nEcosystem coordination: orchestrating value creation across networks of partners and stakeholders instead of controlling resources internally, becoming a key source of competitive advantage.

\r\nFriction costs: economic losses caused by organizational barriers that hinder decision-making and increase operational costs.

\r\nHuman-AI partnership: collaborative approach that leverages complementary human and AI capabilities, resulting in increased creativity compared to humans working alone.

\r\nNetwork effects: phenomenon where products or services become more valuable as more participants join, creating positive feedback cycles that grow over time.

\r\nSmart contracts: self-executing digital agreements where terms are coded and automatically enforced when predefined conditions are met, enabling business processes to run at algorithmic speed.

\r\nSuperfluidity: an organizational state where operations flow seamlessly with minimal friction across boundaries, allowing for 24/7 operation through autonomous systems and instant adaptation to market changes.

\r\nSuperfluid enterprise: an organization that has eliminated operational friction using agentic AI, smart contracts, and ecosystem coordination, enabling information, decisions, and value to flow with minimal resistance.

\r\n"}}" id="rich-text-4e9bcdd8111a" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> Agentic AI: AI systems that autonomously manage complex, multi-step tasks, making decisions and adapting to changing conditions without human intervention for routine operations.

Autonomous operations: business processes that operate continuously with minimal human intervention, where AI manages routine decisions while humans concentrate on strategic oversight and creative problem-solving.

Blockchain: distributed ledger technology that records transactions across multiple computers, enabling transparent, secure coordination between organizations and providing the foundation for smart contracts.

Context engineering: the human skill of framing problems and setting parameters that allow AI systems to function effectively while staying aligned with organizational values.

DAOs (Decentralized Autonomous Organizations): organizations governed by smart contracts and code instead of traditional hierarchy, allowing coordination across distributed networks without central authority.

Digital twins: virtual replicas of physical objects or systems that offer real-time visibility into autonomous operations, allowing human oversight through auditable models that forecast outcomes with 90-95% accuracy.

Ecosystem coordination: orchestrating value creation across networks of partners and stakeholders instead of controlling resources internally, becoming a key source of competitive advantage.

Friction costs: economic losses caused by organizational barriers that hinder decision-making and increase operational costs.

Human-AI partnership: collaborative approach that leverages complementary human and AI capabilities, resulting in increased creativity compared to humans working alone.

Network effects: phenomenon where products or services become more valuable as more participants join, creating positive feedback cycles that grow over time.

Smart contracts: self-executing digital agreements where terms are coded and automatically enforced when predefined conditions are met, enabling business processes to run at algorithmic speed.

Superfluidity: an organizational state where operations flow seamlessly with minimal friction across boundaries, allowing for 24/7 operation through autonomous systems and instant adaptation to market changes.

Superfluid enterprise: an organization that has eliminated operational friction using agentic AI, smart contracts, and ecosystem coordination, enabling information, decisions, and value to flow with minimal resistance.

Read More Read Less 1

Chapter 1

The journey to the superfluid enterprise

AI and other technologies are transforming organizations—removing friction, boosting agility, and empowering leaders to build truly superfluid enterprises.

Representative transformation pathway\r\nThe evolution toward superfluid enterprises will likely progress through three distinct phases, each building capabilities essential for the next. Understanding these stages assists organizations in planning the investments and navigating the cultural shifts needed for success. To see how this unfolds in practice, let's follow Sara's journey through each of the horizons.

\r\n"}}" id="rich-text-d7e2f08e1c27" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> Representative transformation pathway The evolution toward superfluid enterprises will likely progress through three distinct phases, each building capabilities essential for the next. Understanding these stages assists organizations in planning the investments and navigating the cultural shifts needed for success. To see how this unfolds in practice, let's follow Sara's journey through each of the horizons.

Read More Read Less Open image description Close image description A three-tiered diagram illustrating the progression toward a superfluid enterprise through three horizons or stages, starting with Foundation building in Horizon 1, progressing to Autonomous coordination in Horizon 2, and ending in Full superfluidity in Horizon 3.
Each horizon indicates how the role of a leader named Sara evolves, moving from "Strategic Decision Maker" to "Strategic Orchestrator" and finally to "Creative Visionary".

Supply chain reinvention

Supply Chain Reinvention helps clients effect a fundamental change in their performance to support sales growth, become more cost-competitive, minimize risk and improve operational resilience.

Read more Horizon 1: Foundation building Sara arrives at work to find her AI assistant has prepared a briefing on overnight activities. Her company has deployed smart contracts for routine supplier payments, but she still needs to approve any contracts above US$50,000. Three AI agents have flagged potential supply chain risks based on weather patterns and geopolitical news, including tariff negotiations; Sara reviews their recommendations and decides which backup suppliers to activate. Her morning includes three video calls: one with the AI governance committee to review agent performance metrics, another with plant managers to discuss human-AI collaboration training results and a third with the tax function to discuss the tax implications of using backup suppliers.

Foundation-building organizations develop AI-native capabilities while maintaining familiar business structures. Their focus is on building infrastructure, conducting smart contract pilots, and improving human-AI collaboration skills. Sara's day is 40% shorter than it used to be, with AI handling routine coordination, but she remains deeply involved in strategic decisions and exception handling.

Success hinges on meeting specific metrics: 70% employee adoption of AI tools, a 30% reduction in process cycle times, and over 150% ROI on pilot programs. Organizations deploying comprehensive AI automation exemplify this systematic approach, with 78% of global organizations now using AI in at least one business function and 71% regularly using generative AI. The journey shows careful scaling from proof-of-concept to enterprise-wide transformation through structured governance, pipeline management, and resilient architecture design.5

Financial services organizations dominate this landscape due to their data-driven operations and complex risk management needs. Santander's One Pay FX uses blockchain to ensure transaction accuracy and security, offering customers faster and cheaper international payments while positioning the bank as a leader in blockchain adoption across European markets.6 Decentralized finance platforms now manage over US$214 billion in assets, demonstrating significant market appetite for automated financial services.7

Horizon 2: Autonomous coordination Sara's Monday morning routine has changed significantly. She reviews an overnight dashboard showing her AI agents have independently resolved 15 operational issues, adjusted production schedules to accommodate a supplier delay, and negotiated better rates with three vendors through automated smart contract bidding. This enables Sara to focus her time on strategic partnerships, ethical review of AI decisions, and working with ecosystem partners across industries. When a complex quality problem arises that falls outside AI’s scope, the system automatically escalates it to Sara with full context and suggested solutions from multiple AI agents.

The second horizon marks the shift from "humans in the loop" to "humans on the loop," where organizations adopt quantum-enhanced AI systems for complex optimization while implementing hybrid governance models that combine human oversight with algorithmic decision-making. Sara's role has changed from operational manager to strategic orchestrator, with AI agents managing 80% of routine decisions while humans focus on exceptions, creativity and ethical oversight.

Goals include 80% autonomous decision-making for routine tasks, 50% faster responses to market changes, and over 200% ROI from ecosystem coordination. Healthcare transformation focuses on this horizon through integrated care ecosystems that coordinate patient outcomes across traditionally fragmented providers. Blockchain-based health records allow patients to control how their information is shared while ensuring privacy and security, with healthcare representing a target of 15% blockchain market penetration by 2030.8

Manufacturing firms, like Sara's company, approach this frontier through adaptive production networks that dynamically coordinate capacity, expertise and market access across traditional organizational boundaries. Distributed manufacturing platforms allow for rapid product development and market entry without requiring large investments in production infrastructure, cutting time-to-market by 50-70% and reducing capital requirements by 60%.9

Horizon 3: Full superfluidity Sara's role has become almost unrecognizable from her 2025 position. She now focuses on strategic vision, creative problem-solving, and ensuring the company's autonomous operations align with human values and social impact goals. The company's AI systems manage full end-to-end operations — from customer acquisition to product delivery — while keeping transparency through digital twins that Sara can inspect anytime. Her Monday mornings involve reviewing the AI systems' strategic recommendations for entering new markets, and assessing ethical implications of autonomous decisions including seamless analysis of global and local tax laws and regulations, as well as collaborating with other human leaders across the ecosystem on challenges that need uniquely human judgment, empathy and creative thinking.

The question isn't whether machines can make decisions—it's how we maintain human agency over the decisions that matter most.

Sinclair Schuller

EY Americas Responsible AI Leader

The third horizon signifies enterprise-wide autonomous operations, with humans focusing on strategic guidance, creative innovation and ethical oversight. Advanced AI systems handle real-time organizational reconfiguration while maintaining human accountability for purpose and values. Organizations achieve over 90% autonomous operations while creating new forms of human value through creativity, storytelling and strategic thinking.

\r\nSinclair Schuller, EY Americas Responsible AI Leader, describes this as the "governance at the speed of algorithms" challenge: "We need AI systems capable of policing other AIs through sophisticated frameworks that operate automatically while ensuring human accountability for strategic decisions. The question isn't whether machines can make decisions — it's how we maintain human agency over the decisions that matter most."

\r\nThis horizon remains mostly theoretical, but early signs suggest that organizations mastering the first two horizons will be prepared to lead this ultimate transformation when advanced AI capabilities become sufficiently mature to support fully autonomous business operations.

\r\nThe transformation of Sara's role illustrates the fundamental shift from managing operational friction to orchestrating autonomous networks. In Horizon 1, she learned to collaborate with AI as an assistant. In Horizon 2, she became a strategic conductor of AI agents. In Horizon 3, she evolved into a creative visionary, ensuring that autonomous operations serve human purposes. Her weekend stays uninterrupted across all three horizons, but the scope and complexity of autonomous work grow from routine tasks to entire business ecosystems.

\r\nHow the superfluid enterprise could drive superfluid markets and economies\r\nAlmost nine decades ago, economist Ronald Coase established that firms exist to remove operating frictions. Yet, firms have also benefited by perpetuating some sources of external friction—such as switching costs or information asymmetries, which built economic moats, giving them more market power and competitive advantage.

\r\nWith the move to superfluidity, these friction-based advantages will turn into strategic vulnerabilities, meaning that superfluid enterprises could have effects beyond company walls, and make markets and economies superfluid as well.

\r\nConsider three key shifts that are changing competitive dynamics:

\r\n\r\nThe erosion of switching costs: Traditional switching costs — such as data migration complexity, retraining requirements, and integration challenges — are diminishing as AI systems become capable of automatically translating between any platforms. Smart contracts can automate even the most complex vendor transitions, lowering switching costs from millions of dollars and months of effort to thousands of dollars and days of automated migration.\r\nThe democratization of information: Many successful companies have built defenses by controlling how information flows and keeping information asymmetries. Today, AI systems make market intelligence, pricing data and operational insights accessible to more people. What used to take specialized analysts weeks to gather can now be generated, examined and acted on by AI agents instantly.\r\nThe automation of coordination: Complex supplier networks, regulatory requirements and multi-stakeholder coordination once created natural barriers to entry. Organizations with superior coordination capabilities enjoyed sustainable advantages. In a superfluid enterprise, autonomous AI agents will excel at these coordination tasks, reducing the salience of coordination complexity as an entry barrier.\r\n\r\nJPMorgan Chase's blockchain-based payment platform, Kinexys (formerly Onyx), exemplifies this core shift in reducing payment friction. By utilizing blockchain technology for cross-border payments, the platform offers 24/7 real-time settlements in minutes rather than the traditional two to three days required by correspondent banking systems. Since its launch, Kinexys has processed over $1.5 trillion in transaction volume and now manages more than $2 billion in daily transactions, with payment volumes increasing 10 times year-over-year. The platform enables near-instant cross-border FX transactions in USD, EUR, and GBP, creating competitive advantage that attracts new business and fosters innovative service models.10

\r\nCompanies succeeding in this shift aren't trying to keep friction-based defenses — they're aiming to remove friction first, building network effects and ecosystem benefits that grow in the opposite way. As more partners join their superfluid platforms, these companies become more valuable to everyone, creating positive feedback cycles that traditional friction-based strategies can't compete with.

\r\nSector pathways to superfluidity: varied timelines and distinct approaches\r\nThe journey to superfluidity will vary across sectors depending on regulatory frameworks, data requirements, competitive forces and technological development. Recognizing these patterns helps organizations forecast changes and discover cross-industry innovation opportunities. Here are a few examples:

\r\n"}}" id="rich-text-60ccea903e0e" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> The third horizon signifies enterprise-wide autonomous operations, with humans focusing on strategic guidance, creative innovation and ethical oversight. Advanced AI systems handle real-time organizational reconfiguration while maintaining human accountability for purpose and values. Organizations achieve over 90% autonomous operations while creating new forms of human value through creativity, storytelling and strategic thinking.

Sinclair Schuller, EY Americas Responsible AI Leader, describes this as the "governance at the speed of algorithms" challenge: "We need AI systems capable of policing other AIs through sophisticated frameworks that operate automatically while ensuring human accountability for strategic decisions. The question isn't whether machines can make decisions — it's how we maintain human agency over the decisions that matter most."

This horizon remains mostly theoretical, but early signs suggest that organizations mastering the first two horizons will be prepared to lead this ultimate transformation when advanced AI capabilities become sufficiently mature to support fully autonomous business operations.

The transformation of Sara's role illustrates the fundamental shift from managing operational friction to orchestrating autonomous networks. In Horizon 1, she learned to collaborate with AI as an assistant. In Horizon 2, she became a strategic conductor of AI agents. In Horizon 3, she evolved into a creative visionary, ensuring that autonomous operations serve human purposes. Her weekend stays uninterrupted across all three horizons, but the scope and complexity of autonomous work grow from routine tasks to entire business ecosystems.

How the superfluid enterprise could drive superfluid markets and economies Almost nine decades ago, economist Ronald Coase established that firms exist to remove operating frictions. Yet, firms have also benefited by perpetuating some sources of external friction—such as switching costs or information asymmetries, which built economic moats, giving them more market power and competitive advantage.

With the move to superfluidity, these friction-based advantages will turn into strategic vulnerabilities, meaning that superfluid enterprises could have effects beyond company walls, and make markets and economies superfluid as well.

Consider three key shifts that are changing competitive dynamics:

The erosion of switching costs: Traditional switching costs — such as data migration complexity, retraining requirements, and integration challenges — are diminishing as AI systems become capable of automatically translating between any platforms. Smart contracts can automate even the most complex vendor transitions, lowering switching costs from millions of dollars and months of effort to thousands of dollars and days of automated migration.The democratization of information: Many successful companies have built defenses by controlling how information flows and keeping information asymmetries. Today, AI systems make market intelligence, pricing data and operational insights accessible to more people. What used to take specialized analysts weeks to gather can now be generated, examined and acted on by AI agents instantly.The automation of coordination: Complex supplier networks, regulatory requirements and multi-stakeholder coordination once created natural barriers to entry. Organizations with superior coordination capabilities enjoyed sustainable advantages. In a superfluid enterprise, autonomous AI agents will excel at these coordination tasks, reducing the salience of coordination complexity as an entry barrier. JPMorgan Chase's blockchain-based payment platform, Kinexys (formerly Onyx), exemplifies this core shift in reducing payment friction. By utilizing blockchain technology for cross-border payments, the platform offers 24/7 real-time settlements in minutes rather than the traditional two to three days required by correspondent banking systems. Since its launch, Kinexys has processed over $1.5 trillion in transaction volume and now manages more than $2 billion in daily transactions, with payment volumes increasing 10 times year-over-year. The platform enables near-instant cross-border FX transactions in USD, EUR, and GBP, creating competitive advantage that attracts new business and fosters innovative service models.10

Companies succeeding in this shift aren't trying to keep friction-based defenses — they're aiming to remove friction first, building network effects and ecosystem benefits that grow in the opposite way. As more partners join their superfluid platforms, these companies become more valuable to everyone, creating positive feedback cycles that traditional friction-based strategies can't compete with.

Sector pathways to superfluidity: varied timelines and distinct approaches The journey to superfluidity will vary across sectors depending on regulatory frameworks, data requirements, competitive forces and technological development. Recognizing these patterns helps organizations forecast changes and discover cross-industry innovation opportunities. Here are a few examples:

Read More Read Less Open image description Close image description A carousel of content describing the journey to superfluidity for financial services, government and public services, healthcare, life sciences, manufacturing, media and entertainment, mining and retail.
2

Chapter 2

Building blocks of the superfluid enterprise

Building superfluid enterprises requires combining multiple technologies and rethinking the human-machine hybrid partnership.

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Read more A confluence of technologies Superfluid enterprises utilize three core technologies working in synchronized harmony:

1. Agentic AI for coordination In a superfluid enterprise, advanced AI agents do more than automate individual tasks, they coordinate complex, multi-step processes across organizations. These agents understand context, make decisions within set parameters, and adapt to changing conditions without human intervention.

Real-world implementations demonstrate this potential. CrewAI's enterprise adoption platform, now adopted by 60% of Fortune 500 companies, allows AI agents to work together on complex projects, with some implementations replacing entire departments' coordination tasks. Teams report spending 60% more time on creative problem-solving and 40% less time on status updates and administrative coordination.11 JPMorgan's autonomous payment systems coordinate multiple banking functions that previously required extensive human coordination.12

2. Smart contracts for governance Blockchain-based smart contracts replace traditional contracts that require human interpretation and enforcement. They execute automatically when predefined conditions are met, enabling business processes to run at algorithmic speed with perfect consistency and transparency. Enterprise adoption is growing rapidly, with large organizations (10,000+ employees) representing 60% of smart contract usage and 90% of global organizations having started adopting blockchain technology.13

Power Ledger's blockchain platform showcases this potential in the energy sector. The system enables peer-to-peer energy trading through smart contracts that automatically match buyers and sellers, process payments, and optimize renewable energy distribution. Platform participants are saving 15-25% on energy costs while boosting renewable energy usage by 40% — outcomes that would be impossible to achieve through traditional utility coordination systems.14

3. Digital twins for visibility Digital twins — dynamic, virtual replicas of a company’s physical objects, processes or systems — offer unmatched transparency and control for autonomous operations. When AI agents run the vast majority of a finance function, digital twins can generate real-time, auditable models of those processes, maintaining human oversight even in fully autonomous operations. Advanced implementations of digital twins reach 90-95% predictive accuracy compared to 60-70% for traditional monitoring systems.15

Organizations that can unlock enterprise data securely and compliantly while enabling autonomous coordination will achieve superfluidity first. The winners won't just be those with the best AI—they'll be those who can orchestrate AI, smart contracts, and human creativity into seamless networks that adapt faster than traditional hierarchies can respond.

The human quotient: building hybrid human-AI partnerships The most effective superfluid transformations focus not on replacing humans but on forming partnerships that enhance human abilities in ways that pure automation cannot reach. Research consistently shows that hybrid human-AI approaches perform better than either humans or AI working alone.

The combination of humans, AI and narrative leads to a 265% boost in creativity compared to humans alone, while AI alone achieves just 120% of human-only performance.

Bryan Cassady

CEO of the Global Entrepreneurship Alliance and author of The Generative Organization.

Research by Bryan Cassady, CEO of the Global Entrepreneurship Alliance and author of The Generative Organization, reveals compelling patterns: “The combination of humans, AI and narrative — the distinctly human ability to create meaning, context, and strategic direction from data and turn AI-generated insights into compelling stories — leads to a 265% boost in creativity compared to humans alone, while AI alone achieves just 120% of human-only performance.”16 This finding challenges the common belief that AI's value lies in replacing human labor; rather, the greatest benefit comes from complementary capabilities that neither humans nor AI can achieve alone.

\r\nThree human skills are becoming increasingly important in superfluid organizations:

\r\n\r\nContext engineering: While AI excels at processing information within set boundaries, humans will remain vital for framing problems, setting limits and establishing success criteria across complex, multi-stakeholder ecosystems. Context engineering involves turning strategic goals into frameworks that AI agents can carry out while staying aligned with organizational values and stakeholder expectations.\r\nStrategic thinking: Humans excel at asking the crucial question: "Are we solving the right problems?" As AI systems continuously optimize within set parameters, human strategic thinking shifts toward meta-iteration — the ability to step back, evaluate system performance, and redirect automated processes toward higher-value goals. This involves recognizing patterns across multiple domains and knowing when to redirect systems that optimize for the wrong goals.\r\nStory-driven innovation: Human storytelling abilities become major catalysts when paired with AI analysis. Stories independently increase human creativity by 45%, but when combined with AI-generated insights, they enable breakthrough innovations that pure data analysis cannot reach.17 The key is that humans can take AI-generated data points and transform them into compelling business cases that motivate teams, secure funding, and drive strategic change. Humans who can interpret AI insights and turn them into compelling narratives become "mega-experts": individuals who excel at human-AI collaboration, with organizations reporting that 55% of businesses admit making wrong decisions about AI-related employee redundancies, highlighting the importance of strategic human roles in AI transformation.18\r\n\r\nDr. Terri Horton, work futurist, stresses that successful human-AI collaboration requires treating AI systems as sophisticated tools rather than human-like partners, while ensuring both humans and AI contribute to clearly defined business objectives.

\r\nOrganizations successfully navigating this transition understand that the goal isn't just efficiency through replacement, it's about amplification through collaboration. The companies that see the highest returns on AI investment are those that redesign work to leverage uniquely human capabilities while letting AI handle coordination, analysis, and execution tasks that machines do more effectively.

\r\nRedefining competitive advantage in a transparent world\r\nIf superfluid enterprises enable unprecedented transparency and universal access to AI capabilities, how do organizations build sustainable competitive advantage? The answer lies not in controlling information or maintaining barriers, but in mastering three new sources of differentiation.

\r\n\r\nSpeed of adaptation: While all companies may access similar technologies, competitive advantage goes to those who can reconfigure the fastest. Organizations that excel at quickly coordinating AI agents, smart contracts and human creativity can respond to market changes in hours rather than months, creating temporal advantages that grow over time.\r\nNetwork orchestration: Success increasingly relies on coordinating complex ecosystems rather than controlling internal resources. Companies that become central nodes in valuable networks, attracting top partners, suppliers and talent through superior coordination, build positions that are hard to duplicate even with similar technology.\r\nPurpose-driven innovation: In a world where operational excellence becomes a commodity due to AI, competitive advantage shifts toward human-centred value creation. Organizations that blend adaptable capabilities with inspiring missions, ethical principles and creativity-led innovation foster loyalty and differentiation that pure efficiency cannot achieve.\r\n\r\nThe defining characteristic of success in superfluid markets isn't technological advantage — it's the organizational ability to constantly blend human creativity with AI coordination to generate unique value for connected stakeholder networks.

\r\n"}}" id="rich-text-262c94b3b92a" data-up-is="rich-text" data-up-translation-read-more="Read More" data-up-translation-read-less="Read Less" data-up-translation-aria-label-read-more="Read more button, press enter to activate, or use Up arrow key to learn more about this content" data-up-translation-aria-label-read-less="Read less button, press enter to activate, or use Up arrow key to learn more about this content" class="up-rich-text cmp-text" data-up-analytics="rich-text"> Research by Bryan Cassady, CEO of the Global Entrepreneurship Alliance and author of The Generative Organization, reveals compelling patterns: “The combination of humans, AI and narrative — the distinctly human ability to create meaning, context, and strategic direction from data and turn AI-generated insights into compelling stories — leads to a 265% boost in creativity compared to humans alone, while AI alone achieves just 120% of human-only performance.”16 This finding challenges the common belief that AI's value lies in replacing human labor; rather, the greatest benefit comes from complementary capabilities that neither humans nor AI can achieve alone.

Three human skills are becoming increasingly important in superfluid organizations:

Context engineering: While AI excels at processing information within set boundaries, humans will remain vital for framing problems, setting limits and establishing success criteria across complex, multi-stakeholder ecosystems. Context engineering involves turning strategic goals into frameworks that AI agents can carry out while staying aligned with organizational values and stakeholder expectations.Strategic thinking: Humans excel at asking the crucial question: "Are we solving the right problems?" As AI systems continuously optimize within set parameters, human strategic thinking shifts toward meta-iteration — the ability to step back, evaluate system performance, and redirect automated processes toward higher-value goals. This involves recognizing patterns across multiple domains and knowing when to redirect systems that optimize for the wrong goals.Story-driven innovation: Human storytelling abilities become major catalysts when paired with AI analysis. Stories independently increase human creativity by 45%, but when combined with AI-generated insights, they enable breakthrough innovations that pure data analysis cannot reach.17 The key is that humans can take AI-generated data points and transform them into compelling business cases that motivate teams, secure funding, and drive strategic change. Humans who can interpret AI insights and turn them into compelling narratives become "mega-experts": individuals who excel at human-AI collaboration, with organizations reporting that 55% of businesses admit making wrong decisions about AI-related employee redundancies, highlighting the importance of strategic human roles in AI transformation.18 Dr. Terri Horton, work futurist, stresses that successful human-AI collaboration requires treating AI systems as sophisticated tools rather than human-like partners, while ensuring both humans and AI contribute to clearly defined business objectives.

Organizations successfully navigating this transition understand that the goal isn't just efficiency through replacement, it's about amplification through collaboration. The companies that see the highest returns on AI investment are those that redesign work to leverage uniquely human capabilities while letting AI handle coordination, analysis, and execution tasks that machines do more effectively.

Redefining competitive advantage in a transparent world If superfluid enterprises enable unprecedented transparency and universal access to AI capabilities, how do organizations build sustainable competitive advantage? The answer lies not in controlling information or maintaining barriers, but in mastering three new sources of differentiation.

Speed of adaptation: While all companies may access similar technologies, competitive advantage goes to those who can reconfigure the fastest. Organizations that excel at quickly coordinating AI agents, smart contracts and human creativity can respond to market changes in hours rather than months, creating temporal advantages that grow over time.Network orchestration: Success increasingly relies on coordinating complex ecosystems rather than controlling internal resources. Companies that become central nodes in valuable networks, attracting top partners, suppliers and talent through superior coordination, build positions that are hard to duplicate even with similar technology.Purpose-driven innovation: In a world where operational excellence becomes a commodity due to AI, competitive advantage shifts toward human-centred value creation. Organizations that blend adaptable capabilities with inspiring missions, ethical principles and creativity-led innovation foster loyalty and differentiation that pure efficiency cannot achieve. The defining characteristic of success in superfluid markets isn't technological advantage — it's the organizational ability to constantly blend human creativity with AI coordination to generate unique value for connected stakeholder networks.

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简介：在日常的学习、工作、生活中，大家都不可避免地会接触到作文吧，作文一定要做到主题集中，围绕同一主题作深入阐述，切忌东拉西扯
2026-02-26 19:19:08 视频成功标题：送给月亮的情书第83集红豆剧场_在线播放[高清流畅]_爽文短剧
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2026-02-26 19:19:36 视频成功标题：京栀玉叶第85集完结_在线播放[高清流畅]_爽文短剧
简介：爽文短剧_京栀玉叶剧情介绍：京栀玉叶是由内详执导,内详等人主演的,于2025年上映,该剧情讲述的是&l@a片快播@t@中
2026-02-26 19:42:41 综合成功标题：Guide: PS5 Safe Mode - Learn How To Put The PS5 In Safe Mode And Much More - PlayStation Universe
简介：Learn how to start your PS5 in Safe Mode with our handy Play
2026-02-26 16:50:16 综合成功标题：R星球的科学城四年级作文
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2026-02-26 18:17:29 综合成功标题：AI智能索引
简介：lun8.com
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简介：爽文短剧_遥相思剧情介绍：遥相思是由内详执导,内详等人主演的,于2025年上映,该古装讲述的是
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简介：Hersteller: Alfa Laval Moatti OEM Nr. :Alfa Laval Moatti 180
2026-02-26 16:39:50 教育成功标题：改变初中作文(集锦15篇)
简介：在平时的学习、工作或生活中，许多人都写过作文吧，作文是人们以书面形式表情达意的言语活动。那么你有了解过作文吗？下面是小编
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简介：在平时的学习、工作或生活中，大家最不陌生的就是作文了吧，作文一定要做到主题集中，围绕同一主题作深入阐述，切忌东拉西扯，主
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简介：在生活、工作和学习中，大家都有写作文的经历，对作文很是熟悉吧，借助作文可以宣泄心中的情感，调节自己的心情。还是对作文一筹
2026-02-26 19:35:19 综合成功标题：Historical Projects, 1972-1999 - Sir Robert McAlpine
简介：From Sellafield to Canary Wharf, Hampden Park to the Millenn
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简介：新笔趣阁收录了当前最火热的网络小说，免费提供高质量的小说最新章节，是广大网络小说爱好者最值得收藏的网络小说阅读网,精彩小
2026-02-26 18:30:21 视频成功标题：鉴宝大师第73集河马短剧_在线播放[高清流畅]_爽文短剧
简介：爽文短剧_鉴宝大师剧情介绍：鉴宝大师是由内详执导,内详等人主演的,于2025年上映,该都市讲述的是&@战地狮吼电视@姐姐
2026-02-26 18:39:58 综合成功标题：一天的作文描写一天的作文关于一天的作文素材-作文网
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2026-02-26 18:11:00 教育成功标题：二年级家乡作文六篇
简介：在日常学习、工作或生活中，大家都经常接触到作文吧，借助作文可以宣泄心中的情感，调节自己的心情。写起作文来就毫无头绪？下面
2026-02-26 16:51:17 教育成功标题：[热门]二年级作文300字
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2026-02-26 16:00:10 教育成功标题：写爷爷奶奶的作文
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2026-02-26 17:49:01 综合成功标题：高中书信作文700字高中700字书信作文大全-作文网
简介：作文网优秀高中书信700字作文大全，包含高中书信700字作文素材，高中书信700字作文题目、美文范文，作文网原创名师点评
2026-02-26 19:42:34 综合成功标题：Cubby's Inc.
简介：Cubby
2026-02-26 17:46:21 工具成功标题：《私家法医第一季》第13集快播资源高清全集在线观看-迅雷下载-最新美剧-美剧网
简介：私家法医第一季剧情介绍：私家法医第一季是由理查德·谢帕德执导,摩里斯·切斯塔特,詹娜·利·奥提兹,洛莱妮·图桑特,多米尼
2026-02-26 19:37:23 综合成功标题：水先人が選ぶ優秀船舶「ベストクオリティーシップ2022」を当社グループ管理船2隻が受賞日本郵船株式会社
简介：水先人が選ぶ優秀船舶「ベストクオリティーシップ2022」を当社グループ管理船2隻が受賞のページです。日本郵船グループは
2026-02-26 18:55:11 综合成功标题：QA to improve telecom software products quality
简介：Facing problems with the quality of your telecom software pr