Core Insights - The Capgemini Research Institute report indicates that two-thirds of public sector organizations are currently exploring or using generative AI initiatives to enhance public services, with 90% planning to adopt agentic AI within the next 2-3 years [2][3] - Despite the enthusiasm for AI, public sector organizations face significant challenges related to data readiness, trust, compliance, and data management, which hinder their ability to fully leverage AI technologies [2][5][6] AI Adoption and Expectations - Public sector organizations have high expectations for AI, with 39% planning to evaluate agentic AI feasibility, 45% intending to explore pilot programs, and 6% aiming to scale existing initiatives within the next 2-3 years [3] - The report highlights that 64% of organizations have progressed to pilot or scaled deployments, with higher adoption rates in defense (82%), healthcare (75%), and security (70%) sectors [3] Data Readiness Challenges - A significant barrier to AI adoption is data security concerns (79%) and limited trust in AI outputs (74%), with only 36% of organizations in the EU prepared to comply with the EU AI Act [5] - Only 12% of public sector organizations consider themselves very mature in activating data, and just 21% have the necessary data to train and fine-tune AI models [6][8] Data Sharing and Governance - Data sharing is essential for AI adoption, yet 65% of organizations are still in the planning or pilot stages of data sharing initiatives, complicating the deployment of AI [7] - The rise of Chief Data Officers (CDOs) and Chief AI Officers (CAIOs) reflects the growing importance of data governance, with 64% of organizations having a CDO and 27% appointing a CAIO [9] Research Methodology - The report is based on a survey conducted by the Capgemini Research Institute involving 350 public sector organizations across various segments and levels of government, providing a comprehensive view of AI adoption in the public sector [10]

Investment Rating - The report indicates a positive outlook for service providers that adapt to generative AI (genAI) technologies, suggesting a shift towards asset-based, solution-driven, and outcome-oriented business models [3][7]. Core Insights - Generative AI is significantly disrupting professional services, with providers facing pressure to reduce costs and improve efficiency. Clients are expecting up to 30% price reductions in project costs, prompting providers to innovate their delivery models [3][12]. - The report highlights that service providers must reinvent their business models to remain competitive in the AI era, focusing on automation and AI-powered delivery platforms to enhance productivity and quality [6][21]. - Major investments are being made by service providers in AI capabilities, with companies like IBM, Accenture, and PwC committing billions to enhance their AI service offerings [17][19]. Summary by Sections Disruption and Response - Service providers are on the front lines of genAI disruption, needing to adapt quickly to client demands for faster, cheaper, and higher-quality services [6][11]. - Providers are expected to build genAI-powered delivery platforms to automate tasks and improve service quality, which is crucial for maintaining competitiveness [21][23]. AI-Fueled Factors - Four key factors driving change include client expectations for lower costs, providers' lagging delivery capabilities, the slow emergence of AI computing services, and the need for new business models anchored in AI [11][12][14]. - Providers are making significant investments to build AI ecosystems and partnerships, which are essential for future business models [26][30]. New Service Offerings - The traditional time-and-materials pricing model is being challenged, with a shift towards managed service-as-software offerings that leverage AI to enhance operational efficiency [31][34]. - New AI services are emerging to reengineer business processes, focusing on automation and real-time data optimization [32][34]. Strategic Recommendations - Companies are encouraged to negotiate not just for lower prices but also for value-added services that can enhance their operational capabilities [38][41]. - Emphasis is placed on the importance of developing AI governance and leadership practices to effectively manage AI integration within organizations [42].

Core Insights - Boardwalktech Software Corp. has appointed Miles Ravitz to its corporate advisory board to enhance partnerships and strengthen risk and compliance benefits in its offerings [1][2][3] - Mr. Ravitz brings over 20 years of experience in financial services, focusing on risk management and regulatory compliance, which will support Boardwalktech's growth in the financial sector [2][3] - The company has developed a patented Digital Ledger Technology Platform that allows multiple parties to work on the same data simultaneously, enhancing data management efficiency [4] Company Strategy - The appointment of Mr. Ravitz is part of Boardwalktech's broader strategy to secure partnerships with leading technology and professional services organizations [1] - The company aims to close new license deals with financial institutions by leveraging Mr. Ravitz's expertise and industry connections [2][3] Product Offering - Boardwalktech's digital ledger technology is unique in the market, allowing for collaborative enterprise information management applications with full integration into existing enterprise systems [4] - The platform is currently utilized by Fortune 500 companies for mission-critical applications, indicating its reliability and effectiveness in managing structured and unstructured data [4]

Core Insights - Capgemini is leading a paradigm shift in mainframe modernization with a new automated offering that enables organizations to unlock value from legacy systems at unprecedented speed and accuracy [1][3] - The new approach utilizes generative and agentic AI to convert legacy mainframe applications into modern, agile, and cloud-friendly formats, enhancing cost savings, agility, and data quality [1][2] Group 1: Automated Mainframe Application Refactoring - The automated refactoring process involves using tools to convert legacy applications, such as those written in COBOL, into modern architecture, supported by generative AI assistants and AI agents [2] - This offering includes rigorous automated testing to ensure faster, higher-quality transformations and reduced business risks [2] Group 2: Market Position and Client Success - Capgemini's automated approach provides a comprehensive understanding of an enterprise's legacy landscape, enabling complete refactoring of mainframe applications for greater efficiency [3] - The company has delivered tangible results for blue-chip clients, including a major life insurance firm in the USA, by significantly accelerating the conversion to a modernized Policy Admin System [3] Group 3: Recognition and Experience - Capgemini was named a leader in The Forrester Wave™: Application Modernization and Multicloud Managed Services, Q1 2025 [4] - The company has over 55 years of experience in delivering complex mainframe modernization programs and possesses deep domain knowledge and understanding of industry regulations [3]

Market Overview - The market size of China's human resources digitalization is expected to reach approximately 30.3 billion yuan in 2024, with a year-on-year growth of 13.2%. By 2027, the market size is projected to reach 48.4 billion yuan, with an average compound annual growth rate of 16.9% over the next three years [1][3]. Product Iteration - Leading integrated vendors are inclined to utilize PaaS platforms to build flexible development frameworks that support on-demand customization and rapid iteration [2][3]. - AI applications are expanding from recruitment and assessment to training scenarios, evolving from intelligent interaction to smart suggestions, and from industry models to proprietary enterprise models [2][3]. Current State of HR Management - In most enterprises, the HR department plays a leading role in transformation, shifting its focus towards maximizing the value of human capital [6][7]. Digital Transformation Planning - Currently, 97% of enterprises have begun digital transformation efforts, primarily initiated by HR departments. There is a gradual shift from bottom-up to top-down transformation, indicating a strategic shift from efficiency in talent management to strategic human capital management [7][9]. Focus Areas in Digitalization - The core focus of human resources digitalization is on top-level design and technological implementation, with an emphasis on process innovation and iteration. Over half of the enterprises believe that the key to digitalization lies in system architecture and process optimization, while attention to mid-to-late stage operations remains insufficient [9]. Globalization of HR Systems - For enterprises going overseas, safety and compliance are critical, including personal information protection and adherence to local labor laws. The digitalization of HR should be phased, starting with overseas team expansion and progressing to a hybrid employment model [12][16]. Industry-Specific HR Needs - Retail: The retail industry, characterized by a high proportion of part-time workers (nearly 60%), requires flexible scheduling and real-time training due to seasonal fluctuations in workforce demand [18][20]. - Manufacturing: The manufacturing sector emphasizes rapid onboarding and performance calculation for blue-collar workers, alongside a focus on training for high-level talent due to the low overall digitalization level [24][25]. - Internet: Internet companies benefit from a mature digital infrastructure, requiring agile, integrated talent systems to support rapid business iteration and employee growth [28][29]. Trends in Digitalization - Enterprises are increasingly shifting from personnel management to performance management, with over half planning to increase AI investment by 5-30% annually. The focus is on enhancing employee experience and operational efficiency through automation and personalization [62][65]. Competitive Strategies of Vendors - HR digitalization vendors are focusing on mid-sized enterprises, offering integrated solutions for large enterprises, while niche vendors leverage their scene advantages [38]. The evolution of product matrices involves horizontal integration of product modules and vertical development of PaaS foundations [35].

Core Insights - The Temenos Community Forum (TCF) 2025 will gather over a thousand banking industry representatives to discuss transformative technologies, particularly Generative AI, shaping the future of banking [1][2] - The theme "Leading the Way" will feature over 60 sessions focused on bold ideas, product innovations, and technology to help banks overcome operational challenges [2] - Dr. Jonnie Penn from the University of Cambridge will present insights on Generative AI, including best practices and use cases in banking [3] Industry Participation - Banks such as ABN Amro, Banque Internationale à Luxembourg, and EQ Bank will showcase their experiences in innovation, efficiency, and customer experience [4] - Over 40 Temenos customers, including Commerce Bank, Komerční banka, and Credem, will share insights at the event [4] Partner Ecosystem - The event will feature a wide range of partners, including Platinum sponsors HCLTech and Microsoft, and Gold sponsors Capgemini, Cognizant, IBM, NTT Data, and Tech Mahindra [5] Program Highlights - Attendees will gain insights into Temenos' product roadmap and advancements in core banking, digital, and payments through demos and breakout sessions [6] - Roundtable discussions will cover high-impact topics such as migrating core banking systems, moving to SaaS, and deploying a Generative AI governance model [6] Financial Industry Context - The financial industry spends approximately $650 billion annually on IT, with top performers investing more in growth and innovation [7] - The TCF 2025 presents a unique opportunity for banks to learn from industry leaders and explore the potential of Generative AI and other transformative technologies [7]

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The industry is transitioning from a document-driven KYC process to a data-driven model, emphasizing real-time, structured, and validated data to enhance compliance and operational efficiency [3][4] - A strategic data exchange model is proposed, which incentivizes corporate clients to provide verified data, thereby reducing operational costs and improving KYC compliance for Corporate Investment Banks (CIBs) [6][7][9] - The model aims to address the inefficiencies and high costs associated with traditional KYC processes, which require extensive documentation and lead to compliance fatigue [5][10][11] Summary by Sections KYC Data Acquisition - The traditional KYC process is labor-intensive, requiring corporations to submit numerous documents to multiple banks, resulting in 100 to 200 KYC document requests annually [5] - The new data-driven model leverages premium data aggregators to fulfill 70 to 80 percent of KYC requirements, streamlining compliance efforts [4] Strategic Data Exchange Model - This model is built on a proof-of-work mechanism, allowing clients to provide reliable data and earn incentives from CIBs, while CIBs earn credits from data providers [6][19] - The model enhances data quality and reduces long-term acquisition costs, positioning banks at the forefront of digital transformation [7][30] Benefits of the Model - The strategic data exchange model improves data availability and accuracy, with expected benefits of 95% data availability and 80% data accuracy [29] - It reduces compliance burdens for companies by minimizing redundant document submissions, leading to improved efficiency in banking relationships [32] - The model fosters industry-wide adoption and scalability, creating a standard for KYC data collection [34] Regulatory and Legal Considerations - The model must comply with global data protection laws such as GDPR and CCPA, ensuring that corporate-submitted data is used strictly for KYC purposes [35] - Clear contractual agreements are necessary to define responsibilities among banks, data vendors, and corporate participants [38] Implementation Framework - The implementation strategy includes identifying premium data aggregator partners, establishing API connectivity, and creating incentive structures for corporate clients [42] - Continuous monitoring and optimization of data quality and cost savings are essential for the model's success [42]

Press contact: Sereydana OumTel.: +33 6 61 42 03 59E-mail: sereydana.oum@capgemini.com Capgemini confirms its ESG commitment with an updated policy and enhanced objectives As a responsible organization, Capgemini remains committed to the ESG priorities set out in 2021 while unveiling new ambitious targets Paris, May 6, 2025– Capgemini has updated its ESG policy and objectives set in 2021, reinforcing its commitment to sustainable growth, responsible business practices, and corporate accountability. The upd ...

Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The retail banking environment is rapidly evolving, and leveraging cards as a gateway offering is crucial for increasing wallet share and enhancing reach [5] - Credit and debit cards have grown beyond utility, presenting banks with opportunities for financial and market share advantages, but modern rewards programs are essential for long-term value creation [6] - Customer expectations are shifting towards hyper-personalized experiences, making traditional rewards systems insufficient [7] - A significant portion of cardholders (74%) are dissatisfied, indicating a risk of attrition for banks that do not enhance their loyalty programs [8] Summary by Sections Customer Loyalty and Experience - Banks must address both emotional and rational loyalty drivers to create experiences that motivate customers to prefer one card over another [9] - Purposeful loyalty combines transactional benefits with personalized experiences, leading to a stronger preference for a bank's services [19] Key Ingredients for Building Loyalty - Successful loyalty programs require a customer-centric focus, amplification of both rational and emotional drivers, and advanced digital experiences powered by data and AI [20] Addressing the Experience Gap - Many customers feel rewards programs are insufficiently personalized (73%), and a significant number find their banking experiences confusing [26][27] - Banks need to infuse loyalty programs with hyper-personalized recommendations and ensure seamless experiences across all touchpoints [25] Seven Essential Steps for Loyalty Transformation 1. Create hyper-personalized experiences with a human-centered design [28] 2. Enable customer data sharing and transparency [38] 3. Develop conversational customer journeys and engagement [46] 4. Generate content and offers dynamically [47] 5. Connect experiences across channels [54] 6. Establish new business models [55] 7. Implement a real-time value loop [56] Conclusion - Banks must transform their loyalty strategies to meet the expectations of digital-first customers, integrating AI and dynamic personalization into their rewards ecosystems [61] - By focusing on purposeful loyalty, banks can foster deeper emotional and transactional bonds with customers, ensuring long-term engagement and sustained revenue growth [62]

Financial Data and Key Metrics Changes - Revenue totaled $4.8 billion, down 1% year-over-year due to lower vehicle production in North America and Europe and negative customer mix [5][21] - Operating income reached a record $572 million, an increase of over 5%, reflecting strong operating execution and ongoing cost reduction initiatives [5][21] - Earnings per share hit a record $1.69, a 46% increase from the prior year, driven by higher operating income and share repurchases [5][23] - Operating cash flow totaled $273 million, positioning the company to accelerate its deleveraging plan [5][31] Business Line Data and Key Metrics Changes - Advanced Safety and User Experience (ASUX) segment revenues were flat, with Active Safety revenues increasing by 9% and User Experience down 14% due to the roll-off of legacy programs [25][13] - Engineered Components Group (ECG) revenues increased by 1%, driven by 24% growth in China, offsetting declines in North America and Europe [26][16] - Electrical Distribution Systems (EDS) revenues declined by 3%, primarily due to lower light vehicle production, but bookings included over $1 billion in new business awards [27][18] Market Data and Key Metrics Changes - In North America, revenues were down 2%, while in Europe, revenues decreased by 4% year-over-year [24] - In China, revenues grew by 2% year-over-year, driven by growth with local OEMs, despite significant production volume declines with a specific EV customer [24][26] Company Strategy and Development Direction - The company is focused on the transition to electrified, software-defined, and connected solutions, positioning itself to enable this transition across multiple end markets [7][35] - The separation of the EDS business is on track, expected to create two independent public companies with unique product portfolios and financial profiles [35][19] - The company is proactively adapting its business to evolving trade policies and customer needs, leveraging a localized supply chain and flexible cost structure [10][9] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the long-term growth drivers of the business, despite current uncertainties due to rapid changes in global trade policies [8][9] - The company is closely monitoring demand changes and plans to update its full-year outlook when visibility improves [8][9] - Management highlighted strong cash flow generation and a robust balance sheet, providing flexibility to execute strategic initiatives [31][32] Other Important Information - The company completed a $3 billion accelerated share repurchase program, reducing its share count by 18% [6] - Bookings for the first quarter were nearly $5 billion, with strong traction in China and across various segments [11][12] Q&A Session Summary Question: Outlook and Tariff Impact - Management confirmed that the second quarter guidance is based on current visibility, with a focus on vehicle production schedules and customer pricing strategies [37][41] Question: High-Value Production Relocation - Management indicated that high-value production could potentially move back to the U.S., but this does not include the wire harness business [42][44] Question: Advanced Content Bidding Launches - Management noted that activity levels remain robust, although customer award timelines have been extended due to macro uncertainties [48][49] Question: EDS Spin and Macro Uncertainty - Management affirmed that the plan to separate EDS remains unchanged, focusing on growth and cost minimization [50][51] Question: Volume Decline and Guidance - Management clarified that the guidance reflects a volume question for the second half of the year, with no direct tariff impact expected [54][60] Question: China Market Performance - Management acknowledged strong growth in China, despite being impacted by a significant global EV manufacturer [62][63] Question: Tariff Commentary - Management confirmed that 99% of goods imported are USMCA compliant, implying minimal tariff costs [78][79]