🚀 Melvine's AI Analysis# 70 Unlocking the Future: AI and Generative AI's Transformative Role in Amundi Asset Management

Melvine Manchau

Senior Strategy & Technology Executive | AI & Digital Transformation Leader | Former Salesforce Director | Driving Growth & Innovation in Financial Services | C-Suite Advisor | Product & Program Leadership

August 22, 2025

Artificial Intelligence (AI) and Generative AI (GenAI) are reshaping the asset management industry, offering transformative opportunities for enhancing investment strategies, operational efficiency, and client engagement. Amundi Asset Management, one of the world’s leading asset managers with over €2 trillion in assets under management (AUM) as of 2025, is at the forefront of integrating these technologies to maintain its competitive edge. This article explores Amundi’s use of AI and GenAI, its specific initiatives, industry trends, competitor activities, the expected impact of AI, associated risks and challenges, and the regulatory environment shaping AI adoption in asset management.

Amundi’s Use of AI and Generative AI: Key Use Cases

Amundi has been leveraging AI to enhance its investment processes, risk management, and operational efficiency. While specific details about Amundi’s proprietary AI implementations are not always publicly disclosed, industry insights and Amundi’s public statements provide a clear picture of their focus areas. Below are the primary use cases of AI and GenAI at Amundi:

Portfolio Optimization and Investment Decision-Making Amundi employs AI-driven predictive analytics to analyze vast datasets, including market trends, economic indicators, and historical performance, to optimize portfolio allocations. GenAI enhances this process by generating real-time insights and identifying complex patterns that human analysts might overlook. For example, AI algorithms can simulate market scenarios to stress-test portfolios, enabling Amundi to adjust strategies dynamically in response to market volatility.

Investment Research & Portfolio Management: Amundi’s investment teams increasingly use AI to analyze vast datasets (market data, news, research) and inform decision-making. For example, Amundi’s quantitative research division has applied natural language processing to financial news: in 2023, Amundi collaborated with AI firm Causality Link to analyze 1.7 million textual news signals for 4,460 U.S. stocks, finding that news sentiment can help predict short-term price movements.

The study’s AI-driven signal portfolios outperformed the market on certain measures, showcasing AI’s potential in generating alpha. Amundi also uses machine learning models for forecasting – e.g. exploring transformer models for time-series predictions and large language models to answer thematic research questions (such as clean-tech innovation) as noted in its research publications.

These AI tools augment Amundi’s portfolio managers and strategists by spotting patterns and identifying market anomalies early, which supports proactive risk management and scenario planning. Importantly, Amundi applies AI in a “human-in-the-loop” fashion: the firm emphasizes that AI-driven insights are reviewed by experts rather than fully automating investment decisions. “Artificial intelligence cannot replace the brain,” notes Monica Defend, head of the Amundi Investment Institute, underscoring that human judgment, interpretation, and oversight remain essential in portfolio management

Operational Efficiency & Middle/Back-Office: Amundi has deployed AI to streamline internal operations and improve efficiency. The company’s dedicated Innovation Lab is “feeding innovative methods such as machine learning and artificial intelligence into [Amundi’s] platforms”.

One result is a suite of AI-enabled tools within Amundi’s technology platform (ALTO) that automate routine tasks. For instance, Amundi uses AI for document processing and compliance – automatically controlling and updating content across legal and marketing documents to ensure they meet local and global regulations

It also uses natural language processing for multi-language document translation, covering 15 languages to support Amundi’s global operations. Another use case is AI-driven document analysis and summarization: Amundi’s systems can scan and summarize lengthy reports or incoming communications, extracting key information for staff

In risk and compliance, AI algorithms monitor transactions and data in real-time – for example, detecting anomalies that could indicate compliance breaches or fraud, thereby strengthening controls. Amundi’s ALTO platform integrates these AI capabilities so that many back-office processes (reconciliations, reporting, data quality checks) are handled or expedited by machine learning. This not only reduces manual workload but also improves accuracy and response times. An industry analysis by State Street confirms that such automation of repetitive tasks (fund admin, reconciliation, report generation) via AI is becoming standard, freeing firms to focus on higher-value activities while ensuring accuracy and transparency

Operational Efficiency & Middle/Back-Office: Amundi has deployed AI to streamline internal operations and improve efficiency. The company’s dedicated Innovation Lab is “feeding innovative methods such as machine learning and artificial intelligence into [Amundi’s] platforms” One result is a suite of AI-enabled tools within Amundi’s technology platform (ALTO) that automate routine tasks. For instance, Amundi uses AI for document processing and compliance – automatically controlling and updating content across legal and marketing documents to ensure they meet local and global regulations

It also uses natural language processing for multi-language document translation, covering 15 languages to support Amundi’s global operations Another use case is AI-driven document analysis and summarization: Amundi’s systems can scan and summarize lengthy reports or incoming communications, extracting key information for staff

In risk and compliance, AI algorithms monitor transactions and data in real-time – for example, detecting anomalies that could indicate compliance breaches or fraud, thereby strengthening controls. Amundi’s ALTO platform integrates these AI capabilities so that many back-office processes (reconciliations, reporting, data quality checks) are handled or expedited by machine learning. This not only reduces manual workload but also improves accuracy and response times. An industry analysis by State Street confirms that such automation of repetitive tasks (fund admin, reconciliation, report generation) via AI is becoming standard, freeing firms to focus on higher-value activities while ensuring accuracy and transparency

Risk Management and Scenario Analysis AI and GenAI are critical for Amundi’s risk assessment strategies. GenAI models simulate various economic scenarios to evaluate potential impacts on asset performance, helping Amundi identify vulnerabilities and prepare for adverse conditions. These models also assist in assessing liquidity, credit, and market risks with high accuracy, enabling proactive risk mitigation.

Environmental, Social, and Governance (ESG) Integration As a leader in responsible investing, Amundi uses AI to analyze unstructured ESG data from diverse sources, such as corporate reports and news articles. GenAI helps evaluate companies’ ESG practices, assess associated risks and opportunities, and align portfolios with sustainability goals. This is particularly relevant as investor demand for ESG-focused strategies continues to grow.

Compliance and Regulatory Reporting AI streamlines Amundi’s compliance processes by automating data validation, monitoring regulatory changes, and generating reports that meet stringent regulatory requirements. GenAI reduces the risk of non-compliance by flagging anomalies in transactions and ensuring accurate, timely reporting, which is critical in the highly regulated financial services sector.

Client Engagement and Personalization Amundi leverages GenAI to enhance client services by generating tailored investment recommendations based on individual risk tolerances, financial goals, and market conditions. Natural Language Processing (NLP) engines, a subset of GenAI, enable Amundi to create customized client reports and investor communications, improving efficiency and client satisfaction.

Client Service & Advisory: In client-facing roles, Amundi leverages AI to enhance personalization and responsiveness. The firm has developed robo-advisory tools that use AI to help tailor investment portfolios to individual client preferences. In fact, Amundi uses AI-based tools to customize portfolios for some of its 100+ million retail clients, asking them about risk preferences and using those responses to shape portfolio allocations and gauge client sentiment in real-time.

This provides more granular, personalized asset allocations aligned with each client’s risk tolerance and goals. AI also enables Amundi to get an “aggregate view” of client attitudes – monitoring shifts in sentiment across its broad user base, which can inform product offerings and communication strategies

Another client service use case is conversational AI: Amundi has explored chatbots and virtual assistants for investor queries. While many asset managers have tested chatbots to answer basic questions (e.g. fund information or market updates), Amundi’s focus is on augmenting its relationship managers. Internally, the company uses an AI-powered chatbot to assist with RFPs (Requests for Proposals) and client inquiries – effectively a knowledge assistant that can source answers from internal documents. According to Amundi, an “AI-chatbot enabled [the] sourcing [of] internal document libraries for RFP topics,” and even uses generative AI to auto-fill draft RFP responses.

This dramatically speeds up the process of responding to prospective client questionnaires, ensuring consistency and freeing up sales teams for higher-level client engagement. Moreover, Amundi’s generative AI capabilities allow it to produce automated content for clients: for example, generating client portfolio reviews, market commentary, or bespoke reports with minimal human editing. The firm has an internal “Content Creator” AI module for automated report generation, as well as a “Secure GPT” tool – essentially an in-house version of ChatGPT operating in a secure environment with access to Amundi’s internal knowledge base. This means client service teams can query a ChatGPT-like assistant that knows Amundi’s data (while maintaining data confidentiality), helping them quickly retrieve information or craft responses.

Overall, AI in client service at Amundi aims to provide “hyper-personalized experiences at scale,” using analytics to anticipate client needs and deliver tailored communications (such as performance updates or market insights) automatically.. By offering faster answers and highly customized advice, Amundi seeks to improve client satisfaction and position itself as an innovative partner.

Amundi’s AI and GenAI Initiatives

Amundi has publicly disclosed several key AI initiatives, partnerships, and technology deployments that highlight its commitment to innovation:

• ALTO Platform and Innovation Lab: A cornerstone of Amundi’s strategy is its ALTO (Amundi Leading Technologies & Operations) platform, a cloud-based end-to-end investment management system. ALTO was originally built to handle Amundi’s own front-to-back operations and is now offered to other institutions as a technology solution. What sets ALTO apart is its infusion of AI capabilities via Amundi’s Innovation Lab. According to Amundi Technology’s leadership, “the ALTO platform remains ahead of the curve” by continuously integrating new technologies, “feeding innovative methods such as machine learning and artificial intelligence into the platform.”f.

• In practice, this means ALTO’s modules – from portfolio optimization to risk management – are augmented with AI-driven analytics. For example, ALTO’s risk engine can use predictive models to run scenario analyses or detect abnormal portfolio patterns in real-time, and its portfolio construction tools can employ machine learning to suggest optimal allocations under given constraints.

• Olivier Bouteille, Amundi Technology’s Chief Client Officer, explains that Amundi’s open-architecture model allows them to integrate best-in-class partner solutions and in-house AI methods to solve practical challenges. This blending of internal and external AI innovation keeps ALTO flexible and continuously improving. Notably, Amundi established a dedicated Innovation Lab that prototypes AI applications – once proven internally, these are rolled out on the platform for clients. In October 2024, Amundi Technology’s AI efforts earned industry recognition: it was awarded “The Most Promising Project Using Gen AI” at the AM Tech Day event, reflecting its leadership among peers in applying generative AI to asset management solutions.

• ALTO Studio – Secure Generative AI Environment: In 2023–2024, as generative AI (like ChatGPT) burst onto the scene, Amundi quickly moved to harness it in a controlled manner. The firm developed “ALTO Studio,” an internal AI sandbox that gives employees access to generative AI tools in a secure, Amundi-governed environment. According to Amundi’s Chief Operating Officer Guillaume Lesage, “Amundi invested very early in AI and has developed its own environment, ALTO Studio. Users can access all ALTO data and generative AI engines like ChatGPT and Mistral in a secure environment.”. Mistral is a reference to a French large language model (reflecting Amundi’s openness to using new domestic AI models alongside OpenAI’s). By integrating these LLMs with Amundi’s data, ALTO Studio allows for advanced use cases

• from code generation (an AI “Coding Assistant” helps IT teams with code suggestions and debugging), to answering complex internal queries, to drafting communications. Crucially, this is done without exposing proprietary data to the public cloud, addressing a key risk that many financial firms face with generative AI. The impact internally has been significant: over half of Amundi’s employees use ALTO Studio on a weekly basis, and it has produced about 20 AI-powered internal applications so far.

• These applications range from the previously mentioned RFP auto-completion bot, to an “Inventory Specialist” that aggregates internal knowledge into one source to a “Legal Assistant” that uses AI to flag issues in legal documents. Having battle-tested these tools in-house (“doing our own cooking,” as Lesage puts it), Amundi’s next step is to extend ALTO Studio’s capabilities to its clients and partners, effectively offering AI-as-a-service. This initiative demonstrates Amundi’s strategy of leveraging generative AI to boost productivity internally first, then turning it into a client-facing offering and creating a new value proposition for the firm’s technology business.

• Research Partnerships and AI Development: Amundi has actively partnered with external AI specialists and academic institutions to bolster its capabilities. A notable example is the Amundi–Causality Link partnership. Causality Link, a fintech specializing in AI-driven textual analysis, collaborated with Amundi’s research team on multiple projects. In early 2023, as mentioned, they co-published a study on using AI to predict stock moves from news. This relationship likely provides Amundi access to Causality Link’s platform, which uses machine reading to extract structured “cause and effect” insights from unstructured text (news, transcripts, etc.).

• Indeed, Causality Link’s founders noted that the signal-driven portfolios from the Amundi study averaged significant excess returns (they reported +1.3% per day in a controlled experiment) – “a powerful endorsement of using news media sentiment to drive investment decisions”

• . Beyond this, Amundi’s AI researchers have explored partnerships with academia, such as the Toulouse School of Economics. Causality Link itself highlighted that Amundi and Toulouse researchers were interested in its innovative NLP technology. These collaborations not only advance Amundi’s research frontiers but also signal its commitment to staying at the cutting edge of AI by tapping external expertise.

• Fintech and Tech Partnerships: Through its Amundi Technology arm, the firm has engaged in partnerships to expand AI and digital capabilities. For example, in December 2024 Amundi Technology partnered with Minotore (a fintech) to enhance digital financial platforms. While details are limited, such partnerships often involve integrating specialized AI modules or analytics (Minotore might offer solutions in data analytics or investment signals, thus complementing Amundi’s platform). In April 2025, Amundi Technology also announced a partnership with Murex – a major trading and risk system provider – to bolster over-the-counter derivatives capabilities. This indicates a strategy of embedding AI and advanced analytics in specific domains (like derivatives risk management) by working with domain-leading tech companies. Additionally, Amundi’s acquisition of aixigo in late 2024 brings in a wealth-tech platform known for API-based, modular services. Aixigo’s tools could be enriched with AI for personalized wealth management advice. Amundi’s openness to acquisitions and partnerships shows a “buy or ally” approach to AI innovation, ensuring it can deliver comprehensive, AI-enhanced solutions across investment management and wealth advisory.

• AI-Enabled Products and Investments: On the product side, Amundi has capitalized on the AI theme by creating investment products. Its subsidiary CPR Asset Management launched “CPR Invest – Artificial Intelligence”, an investment fund dedicated to AI-related equities. This thematic fund (publicly announced in Amundi’s press releases) invests in companies driving or benefiting from the AI revolution. While this is about using AI as an investment theme (rather than using AI technology internally), it underlines Amundi’s recognition of AI’s economic importance. The fund offering also benefits from Amundi’s internal AI expertise – for instance, the stock selection could leverage AI-based analysis of companies’ innovation or sentiment. Moreover, Amundi offers an MSCI Robotics & AI ESG Screened ETF, giving investors exposure to the AI and robotics sector. These products publicly position Amundi as a thought leader in AI’s impact on markets, complementing its internal use of the technology.

In summary, Amundi’s publicly known AI initiatives range from in-house platforms (ALTO Studio) that embed generative AI across workflows, to external collaborations (with fintechs, academic partners, and even clients like AJ Bell who adopt Amundi’s AI-powered systems

. Amundi’s early investment in AI capabilities has been strategic: it not only improved the firm’s own performance and efficiency, but also spawned a growing technology solutions business. With €8 trillion of data under ALTO’s oversight (including Amundi’s assets and external clients)

Amundi is effectively commercializing its AI and tech expertise. This dual role – user and provider of AI-powered platforms – mirrors what BlackRock has done with its Aladdin system. It positions Amundi to benefit from AI both in managing money and as a revenue-generating service to other firms.

Amundi has been proactive in integrating AI into its operations, aligning with its strategic goal of delivering innovative, client-centric solutions. Key initiatives include:

• Investment in AI Talent and Technology: Amundi has invested in building a robust AI infrastructure, hiring data scientists and AI specialists to develop proprietary models tailored to its investment strategies. The firm has also explored partnerships with technology providers to access cutting-edge AI tools.

• AI-Driven ESG Research: Amundi’s commitment to responsible investing is supported by AI tools that enhance ESG research. By leveraging GenAI, Amundi can process vast amounts of unstructured data to identify ESG trends and opportunities, positioning itself as a leader in sustainable investing.

• Automation of Compliance Processes: Amundi has implemented AI-driven solutions to automate compliance checks and regulatory reporting, reducing operational costs and minimizing the risk of regulatory breaches. This is particularly important given the increasing complexity of global regulations.

• Development of AI Centers of Excellence: Amundi is likely establishing AI labs or centers of excellence to experiment with emerging AI technologies, test use cases, and optimize model performance. These initiatives ensure Amundi remains agile in adopting new AI advancements.

Industry Trends in AI and GenAI for Asset Management

The asset management industry is undergoing a significant transformation driven by AI and GenAI. Key trends shaping the industry include:

1. Widespread Adoption of AI: Over 90% of asset managers are using disruptive technologies like AI, big data, and blockchain to enhance investment performance, according to industry surveys. GenAI is particularly impactful in processing unstructured data and generating actionable insights.

2. Focus on Personalization: GenAI enables asset managers to deliver highly personalized investment solutions, improving client engagement and satisfaction. This trend is driven by growing client expectations for tailored services.

3. Automation of Routine Tasks: AI is automating repetitive tasks such as compliance reporting, data validation, and client communication, allowing firms to focus on high-value activities like strategy development and client relationship management.

4. Rise of Algorithmic Trading: AI-powered algorithms, particularly those using machine learning and deep learning, are revolutionizing trading by analyzing massive datasets and executing trades with high efficiency. High-frequency trading firms like Virtu Financial exemplify this trend.

5. ESG and Ethical Investing: AI is increasingly used to analyze ESG data, enabling firms to align portfolios with sustainability goals and meet regulatory requirements. This trend is driven by investor demand and regulatory pressures.

6. Regulatory Evolution: As AI adoption grows, regulators are developing frameworks to ensure ethical use and transparency. Governments are expected to introduce standards for AI in finance, focusing on fairness, accountability, and risk management.

Competitor Initiatives in AI and GenAI

Amundi operates in a competitive landscape where leading asset managers are also investing heavily in AI and GenAI. Notable competitor initiatives include:

• BlackRock: BlackRock, a global leader with over $10 trillion in AUM, has emphasized AI to automate processes and improve data handling. Its Aladdin platform integrates AI to enhance risk management, portfolio optimization, and operational efficiency. In December 2024, BlackRock’s COO, Rob Goldstein, highlighted the firm’s commitment to advancing AI capabilities.

• Goldman Sachs: Goldman Sachs has integrated AI into coding and risk management, focusing on algorithmic trading and predictive analytics. While direct revenue generation from AI is still evolving, Goldman Sachs is leveraging AI to enhance trading efficiency and client services.

• BNY Mellon: BNY Mellon uses AI for risk management and operational automation, particularly in compliance and reporting. The firm is exploring GenAI to streamline client onboarding and improve investment operations.

• J.P. Morgan Asset Management: J.P. Morgan employs AI for predictive analytics, portfolio optimization, and ESG analysis. The firm has developed proprietary AI models to enhance investment decision-making and is investing in AI-driven client engagement tools.

These competitors are setting a high bar for AI adoption, pushing Amundi to innovate continuously to maintain its market position.

Expected Impact of AI and GenAI at Amundi

The adoption of AI and GenAI is expected to have a profound impact on Amundi’s operations and market position:

1. Enhanced Investment Performance: AI-driven insights and GenAI’s ability to process unstructured data will enable Amundi to identify investment opportunities, optimize portfolios, and generate alpha, improving returns for clients.

2. Operational Efficiency: By automating routine tasks like compliance reporting and client communication, Amundi can reduce operational costs and improve scalability, allowing it to manage larger AUM with fewer resources.

3. Improved Client Experience: GenAI’s personalization capabilities will enhance Amundi’s ability to deliver tailored investment solutions, strengthening client relationships and increasing retention.

4. Competitive Advantage: Firms that effectively integrate AI, like Amundi, are likely to outperform competitors by making faster, data-driven decisions and offering innovative services.

5. Market Consolidation: AI adoption is expected to drive industry consolidation, with larger firms like Amundi gaining market share over mid-sized or lagging competitors.

Risks and Challenges of AI and GenAI Adoption

While AI and GenAI offer significant benefits, they also present risks and challenges for Amundi:

1. Hallucination and Bias: GenAI models can produce inaccurate outputs (hallucinations) or exhibit biases due to flawed training data, potentially leading to poor investment decisions or reputational damage.

2. Data Quality and Privacy: AI models require high-quality, accessible data. Inadequate data standards or breaches of client data could expose Amundi to legal and financial risks.

3. Explainability and Transparency: The “black box” nature of some AI models can make it difficult to explain decisions to clients or regulators, posing challenges in a highly regulated industry.

4. Workforce Readiness: Adopting AI requires upskilling employees to work with advanced technologies. Resistance to change or a lack of AI expertise could hinder implementation.

5. Implementation Costs: Developing and deploying AI solutions involves significant upfront investment, which could strain resources, particularly if economic conditions deteriorate.

Regulatory Environment for AI in Asset Management

The regulatory landscape for AI in asset management is evolving rapidly, with implications for Amundi’s operations:

1. Lack of Formal AI Regulation: Currently, no specific regulatory guidance exists for GenAI in finance. However, firms like Amundi must align with existing AI frameworks, such as the Federal Reserve’s SR 11-7 (Guidance on Model Risk Management), to manage risks associated with AI models.

2. Focus on Transparency and Accountability: Regulators are increasingly emphasizing transparency in AI-driven decisions, requiring firms to ensure models are fair, explainable, and free from bias. Amundi must implement robust governance frameworks to meet these expectations.

3. Data Privacy and Security: Regulations like the EU’s General Data Protection Regulation (GDPR) impose strict requirements on data handling, impacting how Amundi uses client data in AI models. Non-compliance could result in significant penalties.

4. Evolving ESG Regulations: As Amundi leverages AI for ESG analysis, it must comply with emerging ESG reporting standards, such as the EU’s Sustainable Finance Disclosure Regulation (SFDR), which requires transparency in sustainability-related disclosures.

Amundi Asset Management’s journey with AI and generative AI exemplifies both the promises and responsibilities of leveraging advanced technology in asset management. Public disclosures show that Amundi has proactively integrated AI across its value chain – from using machine learning to enhance investment research and risk management, to deploying generative AI for operational efficiency (like automated document handling and internal knowledge retrieval), to improving client service with personalized advice and faster response times. These initiatives, supported by partnerships and an in-house innovation lab, have positioned Amundi as a forward-thinking player turning AI into a competitive advantage. The firm’s development of secure, internal generative AI platforms (ALTO Studio) and its willingness to collaborate with fintechs and academia underscore a comprehensive approach to innovation.

The broader industry context indicates that Amundi’s efforts are timely and necessary. Competitors such as BlackRock and JPMorgan are investing heavily in AI, rolling out similar tools for risk analytics, advisor support, and client interaction. In comparison, Amundi holds its own – its ALTO platform and tech offerings provide a European alternative in a field dominated by U.S. giants, and its rapid deployment of generative AI internally mirrors what the largest banks are doing at scale. The expected impacts on Amundi’s business are largely positive: greater efficiency, new revenue streams through tech services, improved investment decision-making, and enhanced client experiences. If well-executed, AI should help Amundi serve more clients with more tailored solutions, strengthen investment performance through data-driven insights, and maintain operational excellence in an increasingly complex financial environment.

However, this progress comes with significant challenges. Amundi must carefully manage the risks of AI – from data bias and model transparency to cybersecurity and ethical considerations. The firm’s leaders acknowledge that AI is not infallible and have stressed the continued importance of human judgment, aligning with a prudent “augmented intelligence” philosophy rather than full automation. This approach will be critical to ensure that trust is maintained: trust from clients (that AI-enhanced services are in their best interest), trust from regulators (that Amundi’s AI is compliant and well-governed), and trust internally (that employees see AI as empowering rather than threatening).

On the regulatory front, Amundi operates under the watchful eye of European regulators crafting the rules of AI usage. The EU AI Act and local guidelines will demand high standards of governance, fairness, and transparency – effectively raising the bar for any AI system used in finance. Amundi’s early start in formalizing AI practices should serve it well in meeting these standards. By participating in industry consultations and aligning its internal policies with emerging regulations (for example, documenting AI model decisions, instituting oversight committees, etc.), Amundi can not only comply but possibly help shape a framework that balances innovation with safety.

In conclusion, AI and generative AI have become integral to Amundi’s evolution as both an asset manager and a technology provider. The firm’s publicly revealed initiatives demonstrate a commitment to harnessing AI for better outcomes – be it smarter investment strategies, efficient operations, or superior client service. Amundi’s experience reflects a microcosm of the asset management industry’s transformation: those who invest in AI capabilities (and manage the attendant risks) are likely to lead in the next decade of competition, while those who hesitate may fall behind. As the AI revolution in finance continues, Amundi’s blend of ambition and caution – pushing the frontier of what AI can do, while anchoring it in human oversight and regulatory compliance – will be key to converting technological potential into long-term success for the company and its clients.

Sources:

• Amundi Technology interview – Funds Europe (2025)

• GARP Risk Intelligence – AI’s Inroads in Investment Management (May 2023)garp.orggarp.org

• Amundi internal AI solutions (ALTO offering document)

• IMF Finance & Development – AI’s Reverberations across Finance (Dec 2023)imf.orgimf.orgimf.org

• Amundi Technology MarketsMedia interview (Lesage, June 2025)

• Finextra – BlackRock generative AI rollout (Dec 2023)finextra.com

• Reuters – JPMorgan AWM and AI (May 2025)

• State Street Insights – AI reshaping investment industry (Feb 2025)

• Norton Rose Fulbright – AI Guidelines in Finance (July 2025)

• AMF France news – AI in financial sector workshops (June 2024)

• Finance Innovation/Amundi Tech – Investment Day AI takeaways (May 2024)