Insights

Amid rising uncertainty and supply chain disruptions, collaborating with AI start-ups offers a strategic advantage for supply chain resilience. An analysis of over 600 AI start-up solutions highlights emerging technologies and provides a framework to guide decisions on building, buying, or partnering. By integrating external innovation, internal expertise, and responsible AI practices, companies can effectively enhance supply chain resilience and secure a competitive edge.
The Role of Start-Ups in AI-Enabled Supply Chain Resilience
Global efforts to manage plastics have lagged compared to the successful Montreal Protocol, which united nations to phase out ozone-depleting substances through shared scientific understanding, aligned politics, and economic incentives. The plastic crisis requires systemic, collaborative global action, including agreement on an initial list of problematic plastics grounded in credible science. Policies must incentivize market shifts towards circular economy models by rewarding reusable and recyclable designs while penalizing waste. Tech tools like digital product passports and AI-driven data sharing can enhance traceability and compliance. Innovation in alternatives and scalable solutions remains crucial, mirroring the Protocol’s focus on viable substitutes for harmful substances.
Health, Financial services
A blueprint for plastics action: 3 lessons from the Montreal Protocol
The Mediterranean is poised to become a key strategic corridor for Europe’s future value chains amid geopolitical shifts, technological advances, and the energy transition, enhancing regional industrial resilience and competitiveness. Using foresight methods including expert insights and scenario planning, four plausible futures for the Mediterranean by 2035 are explored, focusing on its geoeconomic evolution and technological status. The analysis highlights strategic choices and cross-cutting actions that apply across scenarios, offering governments, businesses, and organizations a practical agenda to foster a connected, resilient, and competitive production, energy, and innovation corridor supporting Europe’s next-generation value chains.
Africa
Mediterranean Foresight: Shaping Europe’s Future Value Chains
Sustainability is transitioning from a siloed function to an integrated, company-wide responsibility embedded within core business operations like strategy, risk management, and governance. Regulatory changes, AI's environmental impact, and stakeholder expectations drive this shift. Successful embedding requires deliberate design: aligning sustainability oversight with existing governance cycles, incorporating sustainability risks into enterprise risk management, establishing clear accountability across functions, and linking leadership incentives to outcomes. Without intentional distribution of responsibility, sustainability efforts risk diffusion and lack of accountability. Companies must ensure sustainability is systematically integrated, with transparency and cross-sector collaboration reinforcing accountability beyond isolated teams.
Why sustainability needs to be embedded, not siloed
Global investment in data centre infrastructure, driven by AI growth, could reach $7 trillion by 2030, but sustainability and resilience are critical for long-term viability. Addressing local resource constraints such as electricity, water, and community acceptance, alongside regulatory complexities, is essential. The World Economic Forum's report outlines a framework focused on life-cycle impacts, adaptability, and broader system dependencies beyond operational efficiency metrics like PUE. Coordinated efforts across developers, operators, enterprise customers, financiers, and policymakers are necessary to embed sustainable practices, unlocking $700 billion to $1 trillion in investment by improving project viability and reducing delays.
ICT
The data centre boom won't succeed without sustainability. Here's how to build it in
AI-driven growth demands rapid expansion of digital infrastructure, with global data centre investment expected to reach $7 trillion by 2030 and electricity demand rising over 20% annually. The sustainability and long-term viability of data centres rely on the capacity of local energy, water, and infrastructure systems, alongside host community support. A decision playbook offers a flexible framework—tailored for developers, operators, enterprise customers, financial institutions, and policy-makers—to guide sustainable and resilient choices throughout data centre development and operation. It emphasizes early integration of sustainability to inform capital decisions, minimize redesign risks, build stakeholder confidence, and maintain adaptability amid evolving technologies and resource challenges.
ICT
Data Centre Sustainability and Resilience: A Decision Playbook for AI Infrastructure
Extreme heat threatens over 2.4 billion workers, causing at least 22 million injuries and 18,000 deaths annually and risking $2.4 trillion in productivity losses by 2030. It represents not only a health issue but also a critical business risk impacting operations and resilience. Despite awareness, around 50% of companies have yet to assess heat risks systematically, and only 28% have implemented interventions. A framework developed with Boston Consulting Group guides leaders in identifying high-risk areas, selecting effective actions, and embedding heat resilience into operations. Protecting workers from extreme heat is essential for both risk management and business strategy.
Health
Workforce Heat Resilience: An Actionable Framework to Close the Execution Gap
Financing conditions for emerging East Asian local currency bond markets remained challenging amid Middle East tensions, higher oil prices, and shifts in U.S. monetary policy. Most regional currencies stayed steady while corporate issuance boosted local currency bond markets in Q2 2026, supported by positive sentiment for sustainable bonds. The report highlights potential volatility risks from AI equity repricing and rising energy costs and assesses the impact of stablecoins on the region's financial landscape.
Africa, ASEAN, Latin America | Financial services
Asia Bond Monitor – September 2026
Granting a new licence for the Jackdaw gasfield in the North Sea does not guarantee long-term UK energy security or align with climate goals. Despite arguments that domestic gas production could reduce dependence on imports and support energy transition, natural gas use must decline this decade to meet climate targets. The UK should focus on proven gas reduction methods like insulation, heat pumps, and electrification, alongside developing clean energy storage. Repurposing existing North Sea oil and gas infrastructure for large-scale renewable energy storage, such as hydrogen, offers a more strategic and sustainable path than expanding fossil fuel extraction.
Granting a new gasfield licence does not guarantee energy security
Early adoption of artificial intelligence (AI) by firms depends more on employee skills and digital connectivity than on firm size, especially for generative AI. Research on Turkish firms from 2021 to 2024 shows traditional AI adoption aligns with the size advantage, requiring significant investments and specialist staff. However, generative AI adoption is driven primarily by workforce skills and internet access, with small firms adopting it at higher rates than large ones once skills are accounted for. Firms often start with generative AI before integrating traditional AI, progressing as workforce capabilities grow. Improved broadband infrastructure also plays a critical role by enabling access to cloud-based AI tools, highlighting the importance of skills and connectivity in AI diffusion.
ICT, Education
Why some firms adopt AI before others – skills and connectivity matter more than size
AI is transforming the workplace by changing tasks within jobs rather than eliminating entire positions. Research shows that AI agents are reshaping workplace management, programming, and data handling, enabling companies to undertake work previously unaffordable. This shift highlights AI’s role in evolving job functions and organizational structures rather than causing widespread job loss.
Education
AI Is Changing Jobs, Not Eliminating Them
Extreme heat is increasingly overwhelming critical infrastructure worldwide, causing cascading failures across power grids, hospitals, water systems, and transportation. Rising temperatures, locked in due to past emissions, are pushing infrastructure beyond design limits, straining economies and exacerbating inequalities by disproportionately impacting vulnerable populations. Heat simultaneously increases demand for cooling and water while weakening supply networks, highlighting system interdependence. Effective adaptation requires coordinated, cross-sector planning focused on four key functions: shared operational data combining weather and system loads; centralized governance to manage resource allocation; automatic coordinated responses across sectors; and targeted investments addressing interconnected vulnerabilities. Without swift collective action, infrastructure resilience will continue to degrade as global temperatures rise.
Health
Extreme heat is breaking critical infrastructure. Can we adapt in time?
Medical research and training have historically used male bodies as the default, leading to underrepresentation of females in studies and medical devices like CPR manikins. This bias can delay or reduce life-saving interventions for women, such as bystander CPR during cardiac arrest. Healthcare AI systems trained on sex-biased clinical data may inherit gender disparities, affecting diagnosis and treatment. Women have been excluded from drug trials and lab studies, resulting in less knowledge about sex-specific responses to medications, which can increase adverse reactions. Efforts to improve representation exist, but many studies still fail to analyze data by sex or distinguish between biological and gender influences, complicating equitable healthcare delivery.
Decades of male-focused medical research could bias healthcare AI
The debate over AI consciousness is intensifying and may become a major societal divide akin to abortion or climate change. Surveys show divided public opinion on whether AI can be conscious, with strong convictions on both sides. Recognizing AI consciousness would have profound moral and legal implications, such as rights and protections for AI beings, which could threaten economic interests and human safety. Experts also disagree, complicating public understanding. The debate risks politicization, potentially hindering informed decisions on AI development. Given the high stakes and uncertainty, a balanced, open-minded discourse is essential to navigate the ethical challenges posed by potential AI consciousness.
Why AI consciousness could become the next great societal divide
Rapid changes in supply chain economics are driving US job growth, yet a significant talent shortfall remains, with a projected gap of nearly 1.1 million jobs by 2035. Technology, particularly agentic AI, robotics, and IoT, can address this gap by automating routine tasks and fostering human-machine collaboration, which boosts productivity when technology complements human skills. The World Economic Forum's Human-Machine Collaboration Framework outlines a three-step approach: analyzing task automation and augmentation, identifying changing skill requirements, and redesigning roles to optimize human-machine partnership. This approach encourages reskilling workers and creating new roles such as supply chain intelligence analysts to meet evolving demands.
ICT, Education
3 ways to redesign work to solve the supply-chain talent crisis
Generative artificial intelligence (AI) enhances the quality of creative outputs at all stages but diminishes motivation for sustained effort. In an experiment with illustrators using a text-to-image AI tool, participants completed tasks faster but often stopped earlier, sometimes submitting lower-quality work overall. This suggests that while AI boosts productivity, it may also encourage complacency when outputs reach a "good enough" level. For developing economies aiming to leverage AI to address skill shortages, maintaining incentives and work structures that promote continued effort is crucial to fully realize AI’s productivity benefits.
Education
Better Technology, Worse Motivation: Generative Artificial Intelligence’s Mediocrity Trap
New York City Public Advocate Jumaane D. Williams released the report “Artificially Inevitable,” which examines the role of artificial intelligence in local, state, and federal government and proposes guidelines for its responsible use. The report highlights that power consumption by U.S. data centers is projected to drive nearly half of the growth in electrical demand over the next five years. Additionally, the largest data centers consume up to 5 million gallons of water daily, equivalent to the water use of towns with 10,000 to 50,000 residents. The report emphasizes the government’s responsibility to educate the public about AI and ensure its benefits for New Yorkers.
NYC Public Advocate Releases Report on AI Governance
Rising global seafood demand and threats to ocean health make sustainable fisheries management crucial. Regional fisheries management organizations (RFMOs) are responsible for setting scientifically informed catch limits and regulating fleet activities on high seas. However, monitoring vast international waters poses significant challenges, including the costly and risky nature of deploying human observers on fishing vessels. Enhanced collaboration and the integration of AI technologies offer promising solutions to improve fisheries monitoring, compliance, and sustainability efforts.
How AI – and Increased Collaboration – Can Improve International Fisheries Monitoring
Artificial intelligence is revolutionizing economic measurement by converting unstructured data like text and images into structured variables at low cost, enabling scalable measurement previously infeasible. This progress shifts the main challenge from obtaining any scalable measure to selecting among multiple plausible measures that may lead to differing empirical conclusions. Reliable inference from AI-generated variables requires carefully designed validation anchored to explicit criteria rather than informal assumptions. Validation samples are critical for ensuring credible inference, even when AI predictions contain biases, and alternative strategies exist if random validation samples are unavailable.
Education
The Measurement Revolution? Credible Measurement and Inference in the Age of AI
A recent M.I.T. report highlights that artificial intelligence is causing "cognitive surrender" in education, with students increasingly relying on AI for answers and skipping traditional learning practices like office hours and group study. This reliance can create an illusion of learning and lead to student isolation. Despite these concerns, many university leaders remain enthusiastic about AI’s potential to augment campus work. The report reflects a growing tension between optimistic administrators promoting AI integration and skeptical faculty and students worried about its impact on genuine learning and academic culture.
Education
An M.I.T. Report Warns A.I. Is Causing ‘Cognitive Surrender.’

Forum Spaces

© 2026 All rights reserved
Privacy Policy & Terms of Service