Financial Data and Key Metrics Changes - Total revenue reached approximately €190 million, reflecting a strong performance with a growth of 37% year-over-year, and an organic growth of 9% [4][21] - EBITDA increased to €27.5 million, representing a growth of 57% compared to the same period last year, with an EBITDA margin of 14.6% [4][24] - The gross margin improved from 32.8% in 2024 to 38.2% in the first half of 2025 [22] Business Line Data and Key Metrics Changes - The Smart Solutions division grew by 72%, achieving a top line of €44 million, with an EBITDA margin around 18% [5][6] - Digital Advisory division experienced a growth of 63%, while Software Engineering grew by 22%, mainly due to the integration of the WebGenesis business [6][16] - Overall EBITDA growth was significant across all business lines, particularly in Smart Solutions with a 75% increase [6][21] Market Data and Key Metrics Changes - International revenue accounted for €31 million, representing 16% of total revenue, which is lower than the previous year due to the integration of domestic companies [8] - Strategic areas such as Aerospace and Defense, Banking and Finance, and Public Sector are growing in contribution, while Tech, Industrial, and Automotive sectors are seeing a decrease in their contribution [10] Company Strategy and Development Direction - The company aims to accelerate growth in the Smart Solutions division, which is the most profitable [5] - Continued investment in R&D, totaling €12 million, reflects a 75% increase compared to the same period last year, focusing on innovative technology [7] - The three-year business plan includes a mix of continuity and M&A strategies, targeting a 10% growth rate [18][19] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in achieving an average growth of 5% to 6% for the Software Engineering division despite fluctuations in quarterly performance [39] - The outlook for the second half of the year is positive, with expectations to exceed the defined guidance [18] - The company is scouting for additional M&A opportunities to enhance growth [19][20] Other Important Information - The company made a strategic investment in Altilia, focusing on artificial intelligence, with plans to increase stakes in the future [11][12] - The net debt as of June 2025 stood at €112 million, in line with guidance, and below two times the year EBITDA [9][29] Q&A Session Summary Question: What drove the change in trend for the Software Engineering business? - The Software Engineering business is linked to large projects, leading to variable performance. A strong Q2 last year made it difficult to achieve similar results this year, particularly in the telco industry, which is experiencing low investment [37][38] Question: What is the rationale behind the partial exit from Banco del Fucino? - The strategy remains unchanged; however, market conditions necessitated a two-step approach for the sale due to regulatory constraints on shareholding in banking institutions [40][41] Question: What is the expected timing for new M&A deals? - The company plans to make one to two small acquisitions in 2025, with larger deals anticipated in 2026. Current negotiations are in advanced stages for a small acquisition in the U.S. [43][46]

AI在技术招聘中的影响 - AI作弊服务正在兴起，例如Clu筹集了530万美金的融资，并实现了接近100万美金的年度经常性收入(ARR)[4] - 谷歌和Meta的面试中，有93%的候选人能够成功通过LeetCode题目，表明传统算法题的区分度正在下降[4] - 越来越多的面试中出现了AI助手，这意味着面试实际上是在考察谁拥有最佳的AI编码助手[4] - Salesforce宣布今年将不再招聘软件工程师，因为他们通过使用AI，生产力提高了30%[5] 技术招聘的新方向 - 行业需要寻找具备创造性问题解决能力、协作领导力以及能够与AI协同工作的人才，而不是仅仅擅长LeetCode的人[7][8] - 行业应观察候选人如何与AI队友在实际业务场景中协作，而不是要求他们解决在工作中永远不会用到的难题[8] - 行业应衡量候选人如何委派任务、处理模糊性以及应对需求变更，而不是衡量他们记忆算法的能力[9] - Devday正在重新构想AI时代的技术招聘流程，通过创建真实的工作场所模拟来评估候选人[10][11] - 行业应衡量候选人与AI的协作能力、处理模糊性的能力、技术决策的沟通能力以及指导他人的能力[12][13] 招聘挑战与应对 - 小公司在人才争夺战中面临巨大压力，因为它们无法像谷歌或Meta那样提供高薪和品牌效应[3][7][13] - 招聘到不胜任AI产品开发的人才，可能会给公司带来高达2万到6万美元的损失[14] - 未来的工程岗位需要创造力、协作能力以及根据商业判断进行工作的能力，而不是仅仅编码[15]

Acquisition Overview - Cognition acquired Windsurf, viewing it as a complementary offering in the AI space [4] - The acquisition was structured as a clean cut from Google, with Windsurf's product, IP, go-to-market team, marketing team, and enterprise engineering team remaining intact [6][7] - The deal includes immediate consideration for all Windsurf employees, who are now part of Cognition [9] Strategic Fit and Synergies - Windsurf, an idea that helps developers code faster, complements Cognition's Devon, an AI software engineering agent [13][14] - The integration allows for a workflow where Devon can perform initial project tasks, with developers using Windsurf for finishing touches [14] - Both companies have a clear enterprise focus, with customers like Goldman Sachs, Citibank (rolling out Windsurf), and JP Morgan [2][15] Market Dynamics and Future Outlook - The acquisition aims to address the issue of valuable teams being left behind in aqua-hires [19][21] - Windsurf was previously considered for acquisition by OpenAI, but the deal did not materialize [11][12] - The deal structure resulted in wiping out the investors founder shares, making it an entirely employee owned company [21]

Agent Definition & Requirements - Agents must reliably handle complex, novel work autonomously and proficiently, leveraging reasoning abilities rather than mere copying [1][2] - The core requirement for agents is the ability to work in tandem with professionals like scientists, software engineers, and data scientists, handling tasks effectively [3] Applications Across Industries - Software engineering benefits from agents that can write code, perform QA, conduct unit testing, and automate coding processes [4] - Sales teams can leverage agents to improve efficiency by processing, qualifying, and recommending follow-up steps for a high volume of inbound leads, driving conversions [5] - The concept of agents is generalizable and applicable across various domains beyond enterprise productivity, science, and software engineering [2][5]

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Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - Organizations are beginning to create structures and processes to capture value from generative AI (gen AI), with larger companies leading the way [2] - The use of AI, including both generative and analytical AI, is gaining momentum, with over 75% of organizations reporting AI usage in at least one business function [2] - CEO oversight of AI governance is correlated with higher reported bottom-line impact from gen AI use, particularly in larger organizations [3][5] - The redesign of workflows is identified as the most impactful attribute for organizations to see EBIT impact from gen AI [4][7] - Organizations are increasingly addressing gen-AI-related risks, with a focus on inaccuracy, cybersecurity, and intellectual property infringement [20][23] Summary by Sections Organizational Changes and AI Deployment - Companies are redesigning workflows and elevating governance to drive bottom-line impact from gen AI [2] - 21% of organizations using gen AI have fundamentally redesigned some workflows [7] - CEO oversight is crucial, with 28% of organizations reporting their CEO oversees AI governance [5] AI Governance and Management Practices - Effective AI implementation requires a top-down approach, with C-suite commitment essential for transformation [9][10] - Organizations are selectively centralizing elements of AI deployment, particularly in risk and compliance [12] - Less than one-third of organizations follow most best practices for gen AI adoption and scaling [28][31] Workforce Impact and Hiring Trends - There is a growing need for AI-related roles, with 50% of respondents indicating a need for more data scientists in the next year [40] - Organizations are reskilling employees due to AI use, with expectations for increased reskilling in the next three years [45] - A plurality of respondents expect no immediate change in workforce size due to gen AI, although some functions may see reductions [51][56] AI Usage and Functionality - 78% of organizations report using AI in at least one business function, up from 72% in early 2024 [58] - The most common functions for AI use include IT, marketing and sales, and service operations [66] - Organizations are increasingly using gen AI across multiple functions, with an average of three business functions reported [59] Risk Management and Compliance - Organizations are ramping up efforts to mitigate risks associated with gen AI, particularly inaccuracy and cybersecurity [20][23] - Larger organizations are more likely to manage potential risks effectively compared to smaller ones [23] Future Outlook - The report suggests that organizations that think big and pursue transformative change will gain a competitive advantage from their AI efforts [25][26] - As organizations become more fluent with AI, it is expected to be embedded in all functions, allowing leadership to focus on higher-level tasks [11]