Core Insights - Financial institutions are rapidly adopting AI agents for customer-facing processes, significantly transforming interactions with banks and insurers [1][2] - The Capgemini Research Institute predicts that AI agents could generate up to $450 billion in economic value by 2028, highlighting a substantial opportunity for the financial services sector [2][7] - Despite optimism, only 10% of firms have implemented AI agents at scale, indicating a large potential for growth in this area [5][6] Adoption and Implementation - Key processes for AI agent deployment in banks include customer service (75%), fraud detection (64%), loan processing (61%), and customer onboarding (59%) [1] - Insurers also prioritize customer service (70%), underwriting (68%), claims processing (65%), and onboarding (59%) [1] - 80% of financial services firms are in the ideation or pilot stage for AI agent deployment, with 33% developing proprietary agents in-house [5][6] Economic Impact and Investment - Nearly two-thirds of executives (61%) view cloud-based orchestration as critical to their AI strategy, transforming cloud platforms into innovation engines [3] - C-suite executives are aligning investments with AI agent technologies, with nearly two-thirds indicating that up to 40% of their generative AI budget is allocated to these technologies [7] - By 2028, one in four firms expects to increase spending on AI agent solutions by up to 60% [7] Challenges to Adoption - Executives cite a skills gap among business leaders and employees (92%) and regulatory compliance burdens (96%) as major roadblocks to AI adoption [8] - High implementation costs are also a barrier, leading 25% of firms to consider a service-as-a-software model for AI consumption and monetization [9]

Core Insights - Financial institutions are rapidly adopting AI agents for customer-facing processes, transforming interactions in banking and insurance sectors [2][3] - AI agents are projected to deliver up to $450 billion in economic value by 2028, indicating significant opportunities for the financial services industry [3] - A majority of firms are in the ideation or pilot stage of AI agent deployment, with only 10% having implemented them at scale [6] Adoption and Implementation - Key processes for AI deployment in banks include customer service (75%), fraud detection (64%), loan processing (61%), and customer onboarding (59%) [2] - Insurers prioritize customer service (70%), underwriting (68%), claims processing (65%), and onboarding (59%) [2] - 33% of banks are developing proprietary AI agents in-house, while nearly half are creating new roles to supervise these agents [3][8] Benefits and Opportunities - Executives believe AI agents can enhance efficiency in customer onboarding, KYC, loan processing, and claims management, with benefits including real-time decision-making (96%), improved accuracy (91%), and faster turnaround times (89%) [7] - 92% of executives see AI agents facilitating expansion into new geographies without heavy infrastructure costs [9] - 79% believe cloud-native AI agents can enable dynamic pricing and offers, enhancing revenue potential [9] Investment Trends - Nearly two-in-three executives allocate up to 40% of their generative AI budget to agent technologies, with expectations of increasing spending on AI agent solutions by up to 60% by 2028 [10] - A growing number of firms (25%) are considering a service-as-a-software model to manage AI costs effectively [12] Challenges to Adoption - Executives identify a skills gap (92%) and regulatory compliance burdens (96%) as major obstacles to AI adoption [11] - High implementation costs are also a barrier, prompting firms to explore new consumption and monetization models for AI [12]

Core Insights - Financial institutions are rapidly adopting AI agents for customer-facing processes, with significant deployment in customer service, fraud detection, loan processing, and onboarding [1][2][5] - AI agents are projected to deliver up to $450 billion in economic value by 2028, prompting banks and insurers to develop proprietary AI solutions and create supervisory roles [2][7] - The integration of AI and cloud technologies is transforming operational strategies, with a focus on real-time decision-making and improved efficiency [3][4][6] Adoption and Implementation - Currently, only 10% of financial services firms have implemented AI agents at scale, while 80% are in the ideation or pilot stages [5][7] - Executives identify customer onboarding and KYC processes as the most inefficient, with high expectations for AI agents to enhance accuracy and turnaround times [6][10] Economic Impact and Opportunities - 92% of executives believe AI agents will facilitate expansion into new markets without significant infrastructure costs, and 79% see potential for dynamic pricing strategies [8][9] - Nearly two-thirds of leaders allocate up to 40% of their generative AI budget to agent technologies, with expectations of increasing spending by up to 60% by 2028 [9] Challenges to Adoption - Major barriers to AI adoption include a skills gap among employees (92%) and regulatory compliance issues (96%) [10] - High implementation costs are prompting firms to consider a service-as-a-software model, focusing on outcomes rather than traditional licensing [11]

Group 1 - Financial institutions are actively transferring significant customer processes to AI agents, transforming customer interactions with banks and insurance companies [1][4] - Key processes where banks deploy AI agents include customer service (75%), fraud detection (64%), loan processing (61%), and customer onboarding (59%) [1] - Insurance companies also follow a similar trend, with customer service (70%), underwriting (68%), claims processing (65%), and customer integration (59%) being the primary areas of deployment [1] Group 2 - AI agents could generate up to $450 billion in economic value by 2028, indicating substantial opportunities for the financial services sector [2] - 33% of banks are developing their own AI agents internally, while 48% are creating new roles to supervise these agents [2][5] - Only 10% of companies have deployed AI agents at scale, despite 80% being in the design or pilot stages [4][5] Group 3 - Nearly two-thirds (61%) of executives consider cloud orchestration essential to their AI strategy, transforming cloud platforms into innovation engines [3] - The combination of AI and cloud technology allows banks and insurance companies to provide more accurate, faster, and efficient services [4] - Executives see AI agents as capable of real-time decision-making (96%), improved accuracy (91%), and shorter processing times (89%) [6] Group 4 - Major challenges in adopting AI include a lack of skills among executives and employees (92%) and regulatory constraints (96%) [7] - High implementation costs hinder a true return on investment for AI, leading 25% of companies to consider a Service-as-a-Software model in the next 12 to 18 months [8] Group 5 - Executives are optimistic about AI agents helping to expand into new geographic areas without massive infrastructure investments (92%) [11] - 79% believe cloud-integrated AI agents will enable dynamic pricing and personalized offers, maximizing revenue and staying ahead of competition [11] - 75% see opportunities for multilingual support tailored to local regulations and cultural standards [11]

Core Insights - The deployment of the first intelligent humanoid robot, named Hoxo, in the nuclear sector represents a significant technological advancement for the industry [2][3] - This initiative aims to enhance industrial performance and safety by integrating robotics with human operations in challenging environments [4][5] Company Overview - Orano is a leading international operator in nuclear materials, focusing on innovative solutions to address global energy and health challenges, with a workforce of 18,000 employees [7] - Capgemini is an AI-powered global business and technology transformation partner, with nearly 60 years of experience and a workforce of 420,000 across more than 50 countries, reporting global revenues of €22.1 billion in 2024 [8] Technological Innovation - Hoxo is equipped with advanced AI and sensors for real-time perception, autonomous navigation, and interaction, designed to replicate human movements and assist teams in nuclear facilities [3][4] - The project combines robotics, AI, computer vision, and digital twins, redefining human-machine interaction in sensitive environments and pushing the boundaries of industrial automation [6]

Core Insights - Capgemini has successfully closed the acquisition of Cloud4C, enhancing its leadership in cloud managed services and expanding its capabilities in automation and AI-driven solutions [3][5]. Group 1: Acquisition Details - The acquisition of Cloud4C, a provider of automation-driven managed services for various cloud environments, was finalized after meeting all regulatory requirements [3]. - Cloud4C's team of 1,600 specialists will contribute to Capgemini's growth in the cloud managed services market, particularly in developing industry-specific frameworks and generative AI solutions [3][4]. Group 2: Strategic Implications - The integration of Cloud4C will bolster Capgemini's offerings in SAP services, particularly in end-to-end SAP services and SAP RISE, by combining Syniti's data expertise with Cloud4C's capabilities [3]. - Capgemini aims to address the increasing demand for AI-powered cloud automation platforms and scalable industry-specific solutions, providing tangible business value to clients [4]. Group 3: Market Context - The global demand for managed services in hybrid cloud environments is rising, with many clients seeking assistance for complex migrations [4]. - Cloud4C's comprehensive service offerings, including consulting, stack migration, and hybrid cloud solutions, will enhance Capgemini's ability to meet client needs in this dynamic market [4]. Group 4: Company Overview - Capgemini is a global business and technology transformation partner with a workforce of 420,000 across more than 50 countries, reporting global revenues of €22.1 billion in 2024 [6]. - The company focuses on delivering end-to-end services leveraging its deep industry expertise and strong partner ecosystem [6].

Core Insights - Capgemini has successfully closed the acquisition of Cloud4C, enhancing its leadership in cloud managed services and expanding its capabilities in automation and AI-driven solutions [2][3][4] Company Overview - Capgemini is a global business and technology transformation partner with a workforce of 420,000 across more than 50 countries, reporting global revenues of €22.1 billion in 2024 [5][6] Acquisition Details - The acquisition of Cloud4C, announced on August 26, 2025, fulfills all regulatory requirements and adds a team of 1,600 specialists in automation-driven managed services for various cloud environments [2][4] - Cloud4C's offerings include consulting, stack migration, and hybrid cloud solutions, which will complement Capgemini's existing services [3] Strategic Implications - The integration of Cloud4C will allow Capgemini to develop industry-specific frameworks and generative AI solutions, enhancing its SAP services and addressing client demand for cloud automation [2][3] - The acquisition is expected to facilitate smoother migrations for clients and provide access to advanced cloud managed services [3]

Core Insights - Siemens and Capgemini are expanding their strategic partnership to co-develop AI-native digital solutions for product engineering, manufacturing, and operations, focusing on 16 high-impact capability areas to enhance production efficiency, time-to-market, quality, and sustainability [1][2] Partnership Details - The collaboration aims to address long-standing challenges in integrating IT and operational systems by leveraging technologies such as industrial AI, digital twins, and next-generation automation [2] - The partnership will utilize orchestrated AI agents to enhance collaboration across engineering and manufacturing silos [2] Leadership Statements - Siemens' CEO Cedrik Neike emphasized the partnership's role in guiding customers through digital transformation with speed and precision, while Capgemini's CEO Aiman Ezzat highlighted the ambition to help clients achieve operational efficiency and tangible business impact [3] Client Case Studies - For Airbus, the partnership is focused on decarbonizing four industrial locations, targeting a 20% reduction in energy consumption and an 85% reduction in Scope 1 and 2 emissions by 2030, utilizing energy system twins for optimal decarbonization roadmaps [3][4] - In the case of Sanofi, the collaboration is standardizing production processes and accelerating the rollout of Manufacturing Execution Systems (MES), resulting in a 70% reduction in review time and an 80% decrease in deviations [4] - For GravitHy, the partnership aims to digitalize industrial processes, targeting a hydrogen production cost reduction of up to 10% [6] Industry Focus - The joint initiative will concentrate on key industries such as aerospace, automotive, and life sciences, as well as emerging markets like hydrogen and water/wastewater [7] - Capgemini plans to expand its pool of certified experts to enhance its Siemens technology capabilities [7] Company Background - Siemens generated revenue of €75.9 billion and net income of €9.0 billion in fiscal 2024, employing around 312,000 people globally [10] - Capgemini reported global revenues of €22.1 billion in 2024, with a workforce of 420,000 team members across more than 50 countries [11]

Core Insights - xtype has launched the 2026 State of ServiceNow Operations Survey at the ServiceNow World Forum in New York, inviting customers to share insights on governance, AI adoption, and platform ROI [1][2] - The survey aims to benchmark the current state of ServiceNow delivery, focusing on managing complexity, enforcing technical governance, and preparing for GenAI [2][3] Survey Objectives - The 2026 survey will help ServiceNow teams benchmark their maturity, identify gaps in technical governance, and learn from peers on scaling safely and delivering faster [3][4] - The previous report highlighted critical technical governance challenges, emphasizing that ServiceNow is an ecosystem of interconnected instances, which requires proper governance to avoid risks and productivity losses [3][4] Operational Focus - The survey will examine operational realities such as environment sprawl, change control, upgrade strategies, and audit readiness [2][4] - Key findings from the previous report indicated that 70% of organizations reported negative impacts on development workflows due to clone-down processes, and only 57% of mature users utilized commercial tools for deployment automation [5] AI Adoption and Governance - 70% of respondents plan to adopt Gen AI within 12 months, indicating significant investment in AI capabilities [5] - Effective technical governance is essential for accelerating delivery while maintaining compliance and security as companies expand their ServiceNow usage [4][5] Participation and Insights - ServiceNow customers are encouraged to participate in the survey, which takes approximately 5 minutes to complete, and participants will receive early access to the report [6] - The insights gained from the survey will assist organizations in navigating operational challenges and building a foundation for AI and beyond [6]

Core Insights - Swiss enterprises are leading the global shift towards an AI-driven workplace, adopting automation and hybrid work practices more rapidly than their European counterparts [1][20] - The transition from AI experimentation to large-scale implementation is evident, with a focus on enhancing productivity and employee well-being [2][3] AI Adoption and Implementation - AI adoption in Switzerland has progressed to large-scale implementation, with organizations automating processes and creating new working methods [2][3] - Enterprises are developing frameworks for responsible AI to build employee trust and ensure sustainable productivity [2][3] Workplace Strategies and Governance - Swiss enterprises are modernizing workplace strategies amid competitive pressures, emphasizing AI governance as a key criterion for selecting service providers [3][4] - Environmental, social, and governance (ESG) requirements are driving the adoption of sustainability practices, including carbon tracking and circular IT [3] Collaboration and User Experience - Collaboration in Swiss enterprises is evolving, shifting focus from traditional service-level indicators to user experience metrics [4][5] - Generative AI platforms are facilitating this transition, leading organizations to establish frameworks for AI readiness and governance [4] Digital Employee Experience - Digital employee experience (DEX) is a central priority, with providers offering AI analytics to proactively address operational issues [5] - Subscription-based device-as-a-service (DaaS) models are being embraced for lifecycle management and cost predictability [5] Market Evaluation and Leadership - The 2025 ISG Provider Lens Future of Work Services report evaluates 40 providers across six quadrants, identifying leaders such as Swisscom, TCS, and Wipro [9][10] - Microland is recognized as the global ISG CX Star Performer for 2025, achieving the highest customer satisfaction scores [12]