> **来源：[研报客](https://pc.yanbaoke.cn)** Global Cross-Discipline Thematic Research Date 16 February 2026 # What AI says about AI eating itself and the world… AI says it is targeting IT and software, finance, customer services, manufacturing and logistics, and media and entertainment The market gyrations of the past two weeks, as fears about Al disruption hit first software and then technology and financial stocks, have left anxious investors wondering: which sector will be next to drop? We went straight to the source, asking our proprietary Al tool dbLumina, which runs on Google's Gemini 2.5 Pro, to do a Deep Research analysis. "You are a sophisticated analyst specialising in the implications of AI for the economy and markets," we said, asking it for "a report of no more than 3,000 words with deep analysis of which global sectors are likely to be most and least disrupted by AI". We specified a number of other parameters and, after some discussion, it generated the report you see below not much more than a minute later. AI is set to increase global GDP and labour productivity, the AI-generated report says. Data-rich sectors with repetitive, pattern-based tasks are most likely to be disrupted, it says. Citing numerous sources from Stanford University, Brookings and the World Economic Forum to Wikipedia, Reddit, blogger Brian Manning and one of our competitors, it singles out information technology and software for disruption, thanks to automation of core tasks and disintermediation. (In the interest of transparency, we are publishing the report completely unedited. For readability, we have not included the links to sources in the original report. Please contact us if you have questions on sourcing.) Other industries ripe for disruption include finance, thanks to the rise of roboadvisers and automation of back-office roles like data processing; customer services; manufacturing and logistics; and media and entertainment, it says. The most insulated sectors require empathy and human connection, like direct patient care and education; those requiring manual dexterity in unpredictable environments such as construction and skilled trades; and those demanding strategic and creative leadership, the report says. Corner-office executives and one-of-a-kind artists are safe for now. Jim Reid Global Head of Macro and Thematic Research +44-20-754-72943 Adrian Cox Research Analyst +44-20-754-17775 We broadly agree with the conclusions, which are a faithful reflection of the current consensus. Given how the model is trained—and the way it generates the output—it is unlikely to deliver genuinely novel insights. Still, it provides a useful synthesis of prevailing views, produced in seconds. That said, we would place more weight on the near-term obstacles to adoption than the report suggests. These range from data quality and governance to operational constraints such as access to energy. Conversely, we think the long-term opportunity is likely even larger than implied—extending well beyond process automation and improved analytics as genuinely new economic and business models emerge. We also think the report goes too far in equating disruption with inherently negative outcomes. New technologies often enable enterprises and individuals to work faster, better, and more enjoyable. Many of the sectors and companies that have sold off in recent days are likely to adapt and ultimately use these capabilities to their advantage, potentially becoming more productive and profitable. Markets, however, tend to sell first and reassess later. The report also cites headline figures—particularly around productivity gains and employment impacts—that read as authoritative but may be drawn from a small number of widely referenced studies. Those estimates can come to dominate the literature through repetition rather than superior rigour, and the report may therefore unintentionally elevate their status. Beyond that, the report generated by dbLumina is well-structured and clear, even if it inevitably lacks a memorable central argument and the writing is rather woolly. Not all of the information is supported by the links cited, and even where it is, there are instances where two sources may be incompatible. But it's a strong starting point, proving its own argument: AI is useful, potentially revolutionary, and here to stay. See what you think. # The Great Rebalancing: An Analysis of AI's Disruptive Impact on Global Sectors An in-depth look at which industries are poised for AI-driven transformation and which are likely to remain bastions of human-centric work, with a focus on recent market shifts in software and wealth management. Report generated by dbLumina in Deep Research mode, using Google's Gemini 2.5 Pro AI model. # Executive Summary Artificial Intelligence is a powerful disruptive force actively reshaping the global economy, creating a great rebalancing where some sectors face profound transformation while others remain relatively insulated. - Most Likely to be Disrupted: Data-rich sectors with automatable tasks are at the forefront. These include Information Technology, where business models are shifting and entry-level roles are impacted; Financial Services, where robo-advisors are growing exponentially; Customer Service, where AI is projected to handle $75\%$ of interactions by 2026; Manufacturing and Logistics, where repetitive physical tasks are being automated; and Media, where AI is changing content creation. - Least Likely to be Disrupted: Industries reliant on uniquely human attributes are more resilient. These include roles requiring deep empathy and human connection (nursing, therapy, teaching), positions that call for strategic and creative leadership, and Construction and Skilled Trades, which involve complex manual dexterity in unpredictable environments. - The Evolving Workforce: The AI era is creating a host of new career opportunities, such as Prompt Engineers, AI Ethicists, and AI Trainers. Success in this new landscape will require a blend of technical skills (e.g., Python, AI frameworks) and AI-complementary soft skills like critical thinking, creativity, and lifelong learning. Global Market Outlook: The Al-driven stock market surge has sparked a fierce debate over a potential bubble, primarily centered on the U.S. market's high valuations and concentration. A global view reveals different investment theses: Japan is experiencing a broad-based rally in its tech and semiconductor firms, while Europe is pursuing an "Al-adjacent" strategy, investing in the industrial "picks and shovels" for the Al revolution. The future will belong to organizations that can navigate this transformation, harnessing Al's power while leveraging the invaluable contributions of human ingenuity and creativity. # Introduction: The Dawn of the Agentic Age Artificial Intelligence (AI) has transitioned from a futuristic concept to a present-day force, actively reshaping global industries. This transformation is not a distant event; it is happening now, with tangible impacts on business models, workforce dynamics, and stock market valuations. The full adoption of generative AI alone is projected to increase global GDP by $7\%$ (equivalent to $7 trillion) over the next decade and boost labor productivity by approximately $15\%$ . This structural shift is expected to create 170 million new jobs while displacing 92 million by 2030, resulting in a net growth of 78 million jobs globally. However, this transition will be disruptive, with estimates suggesting that activities accounting for up to $30\%$ of hours currently worked in the US could be automated by 2030, necessitating as many as 12 million occupational transitions. - Recent market volatility, particularly within the software and wealth management sectors, underscores the immediacy of AI's disruptive potential. The introduction of advanced AI tools, including generative and agentic AI, has sent ripples through the market, prompting a re-evaluation of which sectors are most vulnerable to disruption and which possess inherent resilience. This report provides a deep analysis of the global sectors most and least likely to be disrupted by AI, the evolution of the workforce, and the recent stock market movements that serve as a barometer for investor sentiment in this new AI-driven era. # Sectors on the Front Lines: Most Likely to be Disrupted by AI - The sectors most susceptible to AI disruption are those that are data-rich and have a high degree of repetitive, pattern-based tasks. The availability of vast datasets is a crucial ingredient for training effective AI models, making these industries prime candidates for rapid transformation. Companies deploying AI are already reporting productivity enhancements of $15 - 25\%$ in the functions where it is used, with some staff reporting an $80\%$ improvement in their personal productivity. # 1. Information Technology and Software The very industry creating AI is also one of the first to be profoundly disrupted by it. The irony is not lost on investors, as recent market activity has shown a deep reassessment of the traditional Software-as-a-Service (SaaS) model. Automation of Core Tasks: AI is dramatically reducing the cost and time of software development. Over $85\%$ of developers now use AI coding assistants, with organizations reporting average productivity gains of $40\%$ to $60\%$ . In some cases, programmers have been able to code $126\%$ more projects each week with AI assistance. While this boosts productivity, it also impacts entry-level roles, with research showing a $13\%$ relative decline in employment for early-career workers in AI-exposed occupations since the advent of generative AI. Business Model Disruption and Stock Market Impact: The traditional "per-seat" SaaSlicensing model is under threat as AI automates tasks and increases individual worker productivity, potentially reducing the need for large numbers of software licenses. This has led to a "SaaSpocalypse" narrative among investors. - New Pricing Models: In response, companies are shifting to usage-based and outcome-based pricing. A prominent example is Salesforce, which pivoted from its per-seat model to a "per-conversation" model for its AI assistants, charging $2 for each customer service or sales interaction. Market De-rating: The market has reacted with significant stock price fluctuations. Annual Recurring Revenue (ARR) growth for SaaS companies plummeted from $63\%$ in 2021 to $23\%$ in 2024, while the median revenue multiple fell from a peak of 16x to 6.2x over the same period. Stocks of major players like Adobe and ServiceNow have faced significant sell-offs amid concerns that generative AI could erode their business models. - Agentic AI and Disintermediation: A longer-term threat comes from "agentic AI," which can autonomously execute complex tasks across multiple applications. This could bypass traditional SaaS user interfaces, turning established software platforms into commoditized back-end services. The Opportunity and Role Evolution: Despite the disruption, AI also presents a major opportunity. By 2026, it is expected that more than $80\%$ of companies will have deployed AI-enabled applications. This is creating demand for new roles like Prompt Engineers, AI/Machine Learning Engineers, and Generative AI Specialists. # 2. Financial Services The financial sector, with its vast datasets and reliance on analysis, is a natural fit for AI-driven disruption. Wealth Management: The Rise of Robo-Advisors: The role of the human wealth advisor is being fundamentally challenged by AI. - Explosive Growth: Digital advice platforms, or robo-advisors, have become mainstream since their emergence in 2008. The global robo-advisory market is projected to grow from $7.39 billion in 2023 to$ 72 billion by 2032, with assets under management (AUM) expected to reach $2.33 trillion by 2028. By 2027, AI-driven tools are expected to be the primary source of advice for nearly 80% of retail investors. - The Hybrid Model: The industry is converging on a hybrid model that combines AI's efficiency with the empathy of human advisors. These hybrid models already account for $63.8\%$ of global robo-advisory revenue. This approach uses algorithms for routine portfolio management, freeing up humans for complex planning and emotional support. - Challenges: Trust and Regulation: Significant hurdles remain. A 2023 survey found only $39\%$ of Americans aged $55+$ trust AI-managed investments. Regulators like the SEC are increasing scrutiny over whether algorithms can fulfill a fiduciary duty and are cracking down on "AI washing"—misleading claims about AI capabilities. Banking and Support Roles: AI is being deployed across the banking sector for algorithmic trading, fraud detection, and customer service. Jobs involving structured data processing, such as some forms of accounting, auditing, and paralegal work, are also highly susceptible to automation. # 3. Customer Service The customer service sector is being rapidly transformed by AI-powered automation, leading to significant efficiency gains. Chatbots and Virtual Assistants: AI-driven chatbots now handle initial customer inquiries, answer common questions, and triage issues to human agents. With AI assistance, some support agents can handle $13.8\%$ more inquiries per hour. It is estimated that AI will handle up to $75\%$ of customer service interactions by 2026. - Data-Driven Insights and Cost Savings: AI can analyze customer interactions to identify trends and improve service. This translates to tangible savings; for example, Mindbody's AI-powered support bots saved the company $1.25 million annually by reducing contact volume. # 4. Manufacturing and Logistics While skilled trades show resilience, sectors involving repetitive physical labor are highly vulnerable to AI-powered automation. Manufacturing and Production: Repetitive physical tasks on assembly lines have long been a target for automation, a trend that AI is accelerating. Industrial robots now account for $44\%$ of repetitive manufacturing tasks worldwide, performing jobs like packing, sorting, and assembly. - Transportation and Logistics: The development of autonomous vehicles poses a significant long-term threat to jobs such as truck drivers, taxi drivers, and delivery drivers. # 5. Media and Entertainment The creative industries are also feeling the impact of generative AI, which can create novel content. Content Creation: AI models can now generate text, images, music, and even video. This has the potential to automate aspects of content creation for marketing and entertainment, impacting roles that produce formulaic content. For instance, Quickbase used generative AI to increase its marketing content output by $30\%$ . Personalized Recommendations: Streaming services and media platforms use sophisticated AI algorithms to analyze viewing habits and recommend personalized content, increasing user engagement. # Sectors of Resilience: Least Likely to be Disrupted by AI While AI's reach is broad, certain sectors are more insulated from disruption due to their reliance on uniquely human skills like emotional intelligence, complex manual dexterity in unpredictable environments, and strategic leadership. # 1. Roles Requiring Deep Empathy and Human Connection - Direct Patient Care (Nursing, Therapy): While AI can assist with diagnostics, the human touch in healthcare remains irreplaceable. The empathy, compassion, and critical thinking of nurses, therapists, and social workers are essential for holistic patient care and building trust. - Education (Especially Early Childhood and K-12): The role of a teacher goes far beyond information delivery. It involves nurturing, mentoring, and inspiring young minds, which requires a deep understanding of human development and emotional needs. Social and Mental Health Services: Fields like social work and therapy are fundamentally based on building trust and rapport. The nuanced, empathetic engagement required to help individuals navigate complex personal challenges is a deeply human endeavor. # 2. Construction and Skilled Trades Professions like plumbing, carpentry, and on-site construction require adaptability to unique and often unpredictable physical environments. This sector is distinct from repetitive, factory-based manufacturing. The complex problem-solving and manual dexterity needed on a job site are difficult for current AI and robotics to master. This sector has historically been one of the least digitized, creating significant inertia against AI adoption. Despite this, a new generation of "ConTech" is emerging, with AI being used for project management, cost prediction, and on-site safety monitoring. # 3. Positions Demanding Strategic and Creative Leadership Senior Management and C-Suite Roles: High-level strategic thinking, complex negotiations, and inspirational leadership rely on a blend of experience, intuition, and interpersonal skills that are currently beyond the scope of AI. As AI handles routine tasks, the value of human creativity and complex problem-solving increases. - Original Artistic Creation: While AI can generate art, it does so by learning from existing human-created works. The creation of entirely new artistic styles and the expression of a unique human perspective remain the domain of human artists. Analytical and creative thinking are among the most sought-after core skills by employers in the AI era. # The Evolving Workforce: New Roles and Required Skills The AI revolution is not just about displacement; it's a powerful engine for job creation and role transformation. Success in this new landscape requires a focus on lifelong learning and developing skills that complement AI. # Emerging AI-Centric Professions Prompt Engineer: Often called "AI whisperers," these professionals craft and refine the instructions given to generative AI models to optimize their output. The market for prompt engineering is projected to grow at a CAGR of nearly $33\%$ from 2024 to 2030. - AI Ethicist: As AI becomes more autonomous, these experts guide the responsible and ethical deployment of AI, developing governance frameworks and mitigating biases. AI Trainer: These individuals are essential for "teaching" AI models by creating high-quality training data and rating AI responses to improve accuracy. This role values subject matter expertise over coding skills, opening doors for professionals from diverse fields. AI/Machine Learning Engineers: These highly in-demand professionals design, build, and deploy AI and ML models. The U.S. Bureau of Labor Statistics projects a $32\%$ growth in data science jobs by 2032. # Crucial Skills for the Al Era Technical Skills: Proficiency in programming languages like Python, experience with AI frameworks such as TensorFlow and PyTorch, and a deep understanding of concepts like Large Language Models (LLMs) and Natural Language Processing (NLP) are fundamental. - AI-Complementary Soft Skills: As AI automates routine work, uniquely human skills become more valuable. These include analytical and critical thinking, creativity, complex problem-solving, emotional intelligence, and communication. The World Economic Forum also ranks resilience, flexibility, and agility as top skills for the modern workforce. # Market Tremors: A Global Perspective on the AI Boom Recent stock market activity provides a clear signal of how investors are perceiving Al's disruptive power, sparking an intense debate about a potential Al-driven bubble. # The U.S. Market: Bubble, Boom, or Broadening Rally? - The Case for a Bubble: Concerns center on inflated valuations and extreme market concentration in the "Magnificent Seven" tech giants. This concentration, where the top 10 companies account for about $40\%$ of the S&P 500's market cap, poses systemic risks. Skepticism is also fueled by the immense cash burn on AI infrastructure with uncertain ROI and the phenomenon of "circular" revenue, where cloud providers invest in AI startups that then buy services from the investor. The Case Against a Bubble: Proponents argue the rally is built on the strong fundamentals of highly profitable companies, a key difference from the dot-com era. Federal Reserve Chair Jerome Powell noted these companies "actually have earnings," and analysts argue the surge is supported by "robust and sustained profit growth". # The Global AI Rally: A Tale of Different Markets Japan's Broad-Based Tech Rally: Japan's Nikkei 225 index has surged to record highs, fueled by strong AI optimism. The rally is broad-based, lifting not just tech investor SoftBank Group, but also a range of companies crucial to the AI supply chain, including semiconductor equipment makers like Tokyo Electron and Advantest. - Europe's "Picks and Shovels" Approach: European markets, like the STOXX 600, have also rallied, but with a focus on the industrial and infrastructure backbone—the "picks and shovels"—needed to power the AI revolution. This "AI-proxy" play has boosted companies that provide essential hardware and energy for data centers, such as ASML (lithography machines), Siemens (factory automation), and Prysmian SpA (cabling). # Recent relevant reports from the Deutsche Bank Research Institute Deutsche Bank Research Institute: Technology (public site) Three AI themes for 2026: the honeymoon is over (Jan 20, 2026) Would the real Al bubble please stand up? Boom or bust in 20 slides (Dec 11, 2025) Happy birthday, ChatGPT? OpenAI faces three threats as Altman issues "code red" (Dec 3, 2025) Al 101: Economy: Five ways Al is driving growth (Nov 18, 2025) Al 101: Technology: hype-free guide for users (Oct 2, 2025) # Appendix 1 # Important Disclosures *Other information available upon request *Prices are current as of the end of the previous trading session unless otherwise indicated and are sourced from local exchanges via Reuters, Bloomberg and other vendors. Other information is sourced from Deutsche Bank, subject companies, and other sources. For further information regarding disclosures relevant to Deutsche Bank Research, please visit our global disclosure look-up page on our website at https://research.db.com/Research/Disclosures/FICCDisclosures. Aside from within this report, important risk and conflict disclosures can also be found at https://research.db.com/Research/Disclosures/Disclaimer. Investors are strongly encouraged to review this information before investing. # Analyst Certification The views expressed in this report accurately reflect the personal views of the undersigned lead analyst(s). In addition, the undersigned lead analyst(s) has not and will not receive any compensation for providing a specific recommendation or view in this report. Jim Reid, Adrian Cox. # Additional Information The information and opinions in this report were prepared by Deutsche Bank AG or one of its affiliates (collectively 'Deutsche Bank'). 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