道指跌344.31點，跌幅為0.80%，報42931.60點；納指漲50.45點，漲幅為0.27%，報18540.01點；標普500指數跌10.69點，跌幅為0.18%，報5853.98點。 美股周一收盤漲跌不一，道指下跌逾340點。英偉達再創新高。 市場繼續關注美股財報，以進一步判斷美國經濟狀況。達拉斯聯儲行長表示支持「漸進式」降息，稱寬松政策將有助於避免就業市場過度降温，並使通脹迴歸目標。 國際金價再創歷史新高，COMEX黃金期貨上漲8.90美元/盎司，漲幅0.33%，報2738.90美元/盎司。 央行開展證券、基金、保險公司互換便利首次操作 本次操作金額500億元，採用費率招標方式，20家機構參與投標，最高投標費率50bp，最低投標費率10bp，中標費率為20bp。 多家股份行宣佈下調存款掛牌利率 下調幅度與國有大行基本一致 香港：研究推出離岸國債期貨。 中信股份(267)：出售麥當勞中國大陸和香港業務剩余權益。 中國平安 (2318)前三季度營收8618.17億元，同比增長8.7%；歸屬於母公司股東的淨利潤1,191.82億元，同比增長36.1%。截至2024年9月30日，平安個人客戶數2.40億，其中持有集團內4個及以上合同的客戶佔比爲25.1%，留存率達98.0%。 中國移動 (941)第三季度營業收入爲2,447億元，同比下降0.1%；歸屬於母公司股東的淨利潤爲307億元，同比增長4.6%。前三季度營業收入爲7,915億元，同比增長2.0%；歸屬於母公司股東的淨利潤爲1,109億元，同比增長5.1%。 LinkedIn Email Facebook Twitter WhatsApp source

（左起）中原(工商舖) 商舖部董事黃偉基、董事總經理潘志明、寫字樓部董事陳雁樓、工商部董事劉重興。（Ben Yue拍攝） 本港第三季整體投資氛圍信心不足，工商舖市場於第二季輕微回暖後後勁不繼，令工商舖市場交投轉趨疲弱。據中原(工商舖)資料顯示，第三季工商舖買賣價量齊跌，共錄得約696宗工商舖買賣成交，較上季跌約21%，按年對比亦跌約14%，為連續第五個季度跌穿1,000宗成交水平。然而9月份美國減息周期啟動，加上内地政府接連推出多項大力振市政策，令股票市場表現水漲船高，最新公佈的香港施政報告中，按揭鬆綁上限至七成，為物業投資市場帶來提振作用，預測第四季度整體市場氣氛會顯著改善，表現會谷底回升，但礙於市場積存貨量高企，相信平均呎價及租金仍會有約5%至10%的下調空間。 舖位買賣按季價量續跌 政府積極推動消費，振興經濟，惟市民及訪港旅客消費模式都仍趨保守，商戶開業情況未如理想。中原(工商舖)商舖部董事黃偉基表示，據中原(工商舖)統計，2024年第三季共錄得約175宗商舖買賣成交，較第二季數字下跌約30%，與2023年同期相比，亦下挫約15%，第三季內總成交金額則錄得約32.9億元，對比上一季跌約21%，創下2021年以來最低，按年同期對比相差達約37%。 寫字樓按季買賣創2021年來新低 隨著香港商廈市場供應量持續增加，供過於求的局面已經對寫字樓的租賃及買賣表現帶來明顯的壓力。尤其在2024年第三季，寫字樓市場進一步陷入低迷，買賣交投創下2021年以來按季新低。 工廈按季買賣跌租賃升 季内工廈投資氣氛疲弱，工商物業買賣交投及呎價表現亦有所影響。中原(工商舖)工商部董事劉重興表示，第三季工廈物業買賣交投驟減，季内錄得買賣約400宗，按季跌約兩成，按年跌約14%。成交金額方面，第三季錄得約37.73億元成交，按季大跌約48%，按年亦跌約兩成。至於租賃方面，第三季共錄得約1,680宗工廈租務，按季微跌約6%，但按年則大增約31%，租賃成交金額亦同見上漲，錄得約5,349萬元，按季及按年分別上升約21%及約32%。 中原(工商舖)董事總經理潘志明表示，適逢美國減息周期啟動，中國政府推出大力振經濟措施，最新港府施政報告亦加入支持物業投資市場，料氣氛會逐步轉熾熱。目前市場上醖釀的成交數量眾多，不少投資者已密鑼緊鼓吸納低價物業，而港股9月份的突出表現，亦利好資產市場氣氛和工商業的經營環境，投資者風險胃納增加，相信可帶動更多資金出爐，形成連鎖財富效應，長遠利好房地產。減息、國家著力振興經濟、港府施政措施看重物業市場，三管齊下預料第四季整體投資氣氛會見升溫，工商舖買賣表現會谷底反彈。   LinkedIn Email Facebook Twitter WhatsApp The post 中原(工商舖)：工商舖呎價料再跌5到10% appeared first on VeriMedia. source

Screenshot 生產力局於8月發布的渣打銀行「香港中小企領先營商指數」顯示，本港中小企對環球經濟前景持謹慎態度，最新一季綜合營商指數為42.5，是自2022年第三季以來最低。 作為中小企最強後盾，生產力局及其轄下的「中小企資援組」(資援組)早前透過逾63,000人次諮詢內，整合出中小企四大痛點，希望在本月底(10月29至30日)與工業貿易署合辦的「政府資助及科技博覽2024」中對症下藥，結合政府資助資訊、科技方案、專家諮詢及成功案例分享，一站式協助中小企擊退痛點、提升競爭力。 生產力局「中小企資援組」:中小企常見痛點成升級轉型阻滯資援組在過去四年多，一直為中小企提供一對一詻詢服務，接觸超過63,000人次、逾10,000個單對單諮詢，深入了解企業面臨的挑戰，經整合、分析後，中小企目前面臨的主要痛點如下: 1. 誤以為政府資助申請困難:政府現時為中小企提供多項資助計劃，惟有中小企誤以為政府資助申請 手續與過程繁複或不清楚是否合資格，亦有部分中小企在過程中因文件準備不足而未能成功申請。 2. 品牌創建困難:中小企面對轉型挑戰，除了資金不足，對於建立品牌的資訊、發展方向、品牌故事及策劃，甚至申請專利及商標等亦未完全掌握。 3. 技術升級和數碼轉型挑戰:中小企缺乏技術和資源，在尋找技術供應商時遇到難題，如怎樣設立網上銷售平台、跨境電商、社交媒體推廣或KOL帶貨等。 4. 缺乏對ESG的認知:不少中小企誤以為ESG僅是大企業的發展方向，忽視了其提升品牌形象和市場競爭力的重要性。欠缺資金、技術及對ESG的認識，窒礙了中小企升級轉型以至業務拓展。 有見及此，資援組為企業提供各類型的支援肦增強企業的持續發展能力，如「求FUND」專員的「一對一諮詢」及「睇Form」服務等，旨在協助企業尋找合適的政府資助;而近年推出的「技術支援諮詢」服務，更能幫助企業找到適合的技術解決方案， 過去已令不少中小企受惠。 為了進一步支持中小企發展，資援組將於10月29日至30日一連兩日與工業貿易署在生產力大樓合 辦「政府資助與科技博覽2024」，結合政府資助資訊、科技方案、專家諮詢及成功案例分享，協助中小企解 決資金、技術、市場拓展、ESG等方面的問題，以把握市場先機。 博覽會亦為業界提供了一個互動交流及業 務發展的一站式平台，讓中小企與初創企業互相認識，開展合作商機。過往兩屆博覽會合共超過16,000人 次參與 ，為超過8,000中小企進行即場諮詢，可見需求殷切。 生產力局首席市場總監兼新世代企業及技能發展部總經理馮嘉寶女士表示:「面對挑戰，中小企若希望將拓展業務 ，創新和合作是關鍵。生產力局希望透過這次規模龐大、內容全面的博覽會，不僅為中小企提供資訊和資源，更重要的是打造一個匯聚政府、業界和科技公司精英的跨行業合作平台。生產力局盼成為中小企的最強後盾，繼續發揮橋樑作用，幫助他們升級轉型，提升持久及整體競爭力。」 今年，會場將有超過60個不同展位，來自資助計劃秘書處及科技服務供應商，而當中的五大展區包括「求 FUND專區」(Fun FUND)、「電商直播展示區」(eCommerce LIVE) 、「數碼升級轉型專區」(Go Digital)、「業 務拓展專區 (內地及東盟)」( Business Expansion-Mainland & ASEAN) 及ESG專區，中小企可按需要探訪不同展區，即場了解最新市場資訊。此外，會場亦提供即場展示，讓中小企體驗創新技術及其實際應用，包括展示擴增實境攝影、商用機械人等的「數碼互動專區」、數碼領航系統，以及今年新增設的電子商務KOL直 播及AI人工智能直播等。 博覽會另設八大專題研討會，邀請不同行業專家分享如商會領袖、銀行、業界代表等，參加者可與專家即場進行諮詢，研討會涵蓋多個對中小企相當實用的主題，包括: ● 「求FUND秘技」— 了解熱門政府資助包括「BUD專項基金」「中小企業市場推廣基金(EMF)」、「科技券 (TVP)」、「新型工業化資助計劃(NIFS)」等申請成功要訣 ● 「求FUND大使」與中小企心聲共享 — 申請政府資助個案分享 ● 「數碼升級轉型」— 分享市場大熱科技應用技術，如何將傳統業務進行數碼轉型 ● 「跨境電子商貿」— 讓中小企了解電子商貿市場新興趨勢、平台選擇、社交媒體及營銷策略等，助中小企有效拓展大灣區及內地市場 ● 「衝出香港開拓市場」— 分享如何善用數碼轉型協助港商出海，協助中小企拓展內地及東盟市場 ● 「資訊網絡安全」— 讓中小企掌握網絡安全的最新資訊及實踐小貼士，避免網上陷阱 ● 「ESG」— 探討中小企有效地實行ESG可持續發展的升級轉型方案 ● 「公營機構採購需求」— 由研發中心及公營機構分享在技術方面的採購需求，讓初創企業及中小企掌握最新資訊，共創合作商機。 生產力局期望吸引更多中小企業參加博覽會，從豐富的政府資助資訊、專家諮詢和成功案例分享中，找到切實可行的解決方案和發展出路，提升競爭力，在充滿挑戰的經濟環境中穩步前行。 博覽會將免費開放登記，查詢或報名可聯絡「中小企資援組」:熱線 (852) 2788 6868;電郵: [email protected]。 活動詳情: 日期:10月29日至30日(星期二至三) 時間:上午9時30 分至下午6時 地點:九龍達之路78號生產力大樓 入場:免費(需預先登記) 活動詳情及登記: http://u.hkpc.org/zh-edm-FUNDfair2024 查詢:「中小企資援組」熱線 (852) 2788 6868; 電郵: [email protected] 立即報名: https://campaigns.hkpc.org/zh-hk/registration-sme-reachout-fund-fair-plus-tech-sourcing-2024 LinkedIn Email Facebook Twitter WhatsApp The post 生產力局10月29至30日舉辦「政府資助及科技博覽2024」 appeared first on VeriMedia. source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI, the artificial intelligence powerhouse behind ChatGPT, has taken another step in its quest for ubiquity by releasing a Windows desktop application for its popular AI chatbot. The move, announced Thursday, follows the earlier launch of a macOS client and marks a significant push by OpenAI to embed its technology more deeply into users’ daily workflows. The new Windows app, currently available in preview to ChatGPT Plus, Enterprise, Team, and Edu subscribers, allows users to access the AI assistant via a keyboard shortcut (Alt + Space) from anywhere on their PC. This seamless integration aims to boost productivity by making AI assistance readily available without the need to switch to a web browser. OpenAI’s new ChatGPT desktop application for Windows, showing a user interface with conversation history. (Credit: OpenAI) OpenAI’s desktop strategy: More than just convenience OpenAI’s strategy of platform expansion goes beyond mere convenience. By creating native applications for major operating systems, the company is positioning ChatGPT as an indispensable tool in both personal and professional environments. This move serves multiple purposes: it increases user engagement, facilitates more extensive data collection for model improvement, and creates a sticky ecosystem that could be challenging for competitors to displace. The desktop app approach also reveals OpenAI’s ambition to become the de facto AI assistant for knowledge workers. By integrating ChatGPT more deeply into users’ workflows, OpenAI is not just improving accessibility but potentially reshaping how people interact with computers and process information. Enterprise ambitions: ChatGPT as the new office suite? The Windows release comes at a critical juncture for OpenAI, as the company faces increasing competition in the AI space and scrutiny over its rapid growth and influential position. Recent reports suggest that OpenAI is exploring partnerships beyond its well-known Microsoft alliance, including discussions with Oracle for AI data center infrastructure and pitches to the U.S. military and national security establishment. OpenAI’s aggressive expansion into desktop environments signals a potential shift in the enterprise software landscape. The company appears to be positioning ChatGPT as a fundamental productivity tool for businesses, potentially disrupting traditional enterprise software providers. This move, coupled with the recent partnership expansion with Bain & Company to sell ChatGPT to businesses, suggests OpenAI is not content with being merely an AI research lab but is actively pursuing a dominant position in the commercial AI sector. The implications of this strategy are huge. If successful, ChatGPT could become the new “operating system” for knowledge work, fundamentally changing how businesses operate and potentially displacing or absorbing functions currently served by separate software suites. Balancing Act: Innovation, ethics, and commercialization However, OpenAI’s rapid growth and increasing influence have not been without controversy. The company’s AI models have faced scrutiny over potential biases and the societal implications of widespread AI deployment. Additionally, OpenAI’s dual status as a capped-profit company with significant commercial interests has raised questions about its governance and long-term objectives. As OpenAI continues to expand its reach, the company faces a delicate balancing act. It must navigate the tensions between its stated mission of ensuring artificial general intelligence benefits humanity and its increasingly commercial focus. The Windows app release, while a seemingly straightforward product expansion, represents another step in OpenAI’s complex journey of shaping the future of AI in both consumer and enterprise contexts. The success of this desktop strategy could cement OpenAI’s position as the leading AI company, but it also increases the urgency of addressing ethical concerns and potential monopolistic practices. As ChatGPT becomes more deeply integrated into daily work and life, the stakes for getting AI right — in terms of safety, fairness, and societal impact — have never been higher. source

In today’s crowded marketing landscape, the 4-O Marketing Matrix offers a critical upgrade from the traditional 4 Ps model (Product, Price, Place, Promotion). While the 4 Ps remain foundational, they fall short in addressing the complexities of modern customer engagement. The 4-O Matrix—encompassing Online, Offline, Onsite, and Offsite strategies—provides a comprehensive framework that aligns with shifting consumer behaviors and preferences. The 4-O Marketing Matrix encourages marketers to diversify their promotional tactics across Online, Offline, Onsite, and Offsite channels. This approach not only broadens the scope of engagement opportunities but also aligns more closely with the multifaceted journeys of today’s consumers. By integrating this matrix with the traditional 4 Ps, organizations can enhance their promotional outreach, drive higher conversion rates, and build greater trust with their prospects and clients. In an era where single-format promotional efforts (typically email marketing) dominate the landscape, the necessity for a more expansive and empathetic marketing model is clear. The 4-O Marketing Matrix represents a pivotal evolution in marketing strategy, urging marketers to leverage a variety of tools and technologies to engage with audiences in a more meaningful and impactful way. Adopting the 4-O Marketing Matrix is not just about expanding the promotional mix; it’s about embracing a more holistic and customer-centric approach to marketing that resonates with the complexities of the modern market. Thinking Outside the (In)box Relying too heavily on email has limited the reach and effectiveness of many organization’s efforts and simultaneously overlooks consumers’ changing preferences. Once the cornerstone of digital outreach, email has become a comfort zone, leading to inbox overload and diminishing returns as consumers grow disinterested in repetitive messages. This focus fails to recognize the importance of personalization and relevance in terms of both content, channel, and context. Consumers today crave authentic connections and personalized experiences. Email campaigns, often impersonal and detached due to both their content and the nature of the medium, fail to meet these expectations.  By concentrating too much on email, businesses miss out on opportunities offered by social media, messaging apps, and other digital platforms that facilitate meaningful connections. The limited diversity in contemporary marketing outreach is a consequence of the industry’s own oversights. Martech vendors, influenced by the preferences of marketing users, especially non-marketing executives, have emphasized readily quantifiable and commonly referenced funnel metrics, like Marketing Qualified Leads (MQLs). This focus on simple metrics obstructs a holistic understanding of the “Real” customer journey and pushes marketers towards myopic email-centric campaigns.  Modern tools that track lead scores based on limited activities miss critical insights from the ‘real’ customer journey, including interactions on competitors’ sites, analyst assessments, peer reviews, and user communities. This focus on short-term, funnel-based MQL targets inspired the creation of the 4-O Marketing Matrix, which encourages organizations to adopt a more holistic approach and engage prospects throughout their entire lifecycle. Exploring the 4-O Marketing Matrix The 4-O Marketing Matrix is a revolutionary model that encourages marketers to broaden their promotional approaches beyond traditional methods. This model is divided into four components: Online, Offline, Onsite, and Offsite. Each of these elements plays a crucial role in creating a comprehensive marketing strategy that addresses the diverse needs and preferences of today’s consumers. Online and Offline: Bridging Digital and Physical Worlds The Online component focuses on digital interactions that occur through various electronic devices, offering marketers a vast playground for digital campaigns, social media engagement, and more. In contrast, Offline marketing involves physical, in-person experiences that can create lasting impressions through human touch and personal interaction. Balancing these two aspects allows marketers to cover the entire spectrum of consumer engagement, from the convenience of digital to the authenticity of face-to-face encounters. Onsite and Offsite: Reaching customers where they are Onsite marketing refers to promotional activities conducted on a brand’s platforms, such as its website, physical store, or other “owned” environments. These efforts are directly under the brand’s control and provide a space to fully express the brand’s message. Offsite marketing, however, takes place on external platforms, reaching consumers where they spend their time outside of the brand’s direct influence. This could include social media, third-party websites, or even physical locations not owned by the brand. By leveraging both Onsite and Offsite marketing, brands can ensure they are not only drawing consumers into their own controlled environments but also engaging with them in spaces where they already exist and feel comfortable. This dual approach maximizes visibility and interaction opportunities, making it easier to connect with a wider audience. The Power of the 4-O Marketing Matrix By integrating Online, Offline, Onsite, and Offsite elements, the 4-O Marketing Matrix helps marketers move beyond traditional tactics to create dynamic, impactful campaigns. This holistic approach not only enhances brand visibility but also builds deeper connections and trust with consumers. The 4-O Matrix is more than a theoretical model—it’s a practical guide for developing customer-centric strategies that adapt to the evolving marketing landscape. Embracing the 4-O Marketing Matrix allows marketers to craft strategies that are not only comprehensive but also deeply resonant with the modern consumer’s lifestyle. It’s about enriching the dialogue, understanding their journey, and being present in ways that are both meaningful and impactful. Navigating the Future of Marketing with the 4-O Framework The 4-O Marketing Matrix stands out as a novel and crucial framework for organizations seeking to deepen market engagement and build meaningful connections. This model emphasizes a balanced approach across Online, Offline, Onsite, and Offsite dimensions, offering a comprehensive blueprint for moving beyond traditional promotional tactics. The 4-O Marketing Matrix guides marketers to transcend conventional strategies and adopt a more nuanced understanding of customer engagement. It enables organizations to navigate modern marketing complexities with agility, optimizing every touchpoint for maximum impact. By integrating this matrix, businesses can engage customers more successfully through innovative Offline events, impactful Online campaigns, or effective Onsite and Offsite strategies. This approach fosters a holistic and adaptable engagement strategy, unlocking new opportunities for growth, customer loyalty, and market leadership. Embracing the 4-O Marketing Matrix ensures that organizations not only keep up with the

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More PlayVS has partnered with Omnic.AI, a self-service platform that helps gamers player smarter with AI feedback. The partnership allows players to receive an analysis of their in-game performance, matches them with pro players that have similar gaming styles, and provides them with detailed match analysis data, said Jon Chapman, PlayVS CEO, in an interview with GamesBeat. The goal for PlayVS and Omnic.AI is to help students develop key transferable skills including critical thinking, adaptability, and effective communication. This is aimed at redefining the next generation of gamers, helping them reach their full potential.  PlayVS is focused on middle school and high school esports leagues, and it is targeting such students with the Omnic.AI analytics tools and insights. Back in September, it launched a digital-first esports competition platform to widen its reach. Omnic.AI helps players perform and communicate better in esports. Focuses on esports player performance data and analytics, Omnic.AI uses AI and machine learning to gather insights and a detailed analysis of gameplay for users. The flagship platform, Omnic Forge, analyzes gaming footage and provides players with feedback and statistics to improve their performance in titles including Valorant, Fortnite, Rocket League, Overwatch2 and soon Madden. Omnic.AI provides two kinds of insights. The first is AI coaching insights, which provides tips on team communication, performance, and on the match. An example is here on the website. The other type is advanced analytics, which can help with things such as aim analysis, match recap and stats to other players, and round by round performance summaries. Omnic.AI also has the AI Chat, which is a personalized chatbot that helps with instant coaching advice, gameplay tips, etc., as well as customized results, based on your most recent analyzed match. About 85% of coaches have seen improvement in communication skills among their players, according to last year’s Esports Impact Report from PlayVS. And 83% of coaches agree that their players have improved their leadership skills as a result of esports. It also helps on a broader academic front. The companies also said 60% of coaches have found an improvement in grades and/or attendance among their players. About 45% of PlayVS students reported feeling more excited to go to school after joining an esports team. And 30% of students said they feel more committed to school and academics. In this way, the partnership is about more than just playing games better. “We made a decision earlier this year that we really wanted to find ways to continue to create a resource, and we’re calling it the PlayVS Collective that helps support our community of users, especially those in our leagues at schools,” Chapman said. “Those resources can be a lot of different things. They could be access to curriculum with the connections that can be made between gaming and STEM education.” The PlayVS Collective refers to a thriving partner community that is focused on providing students, coaches and schools with the resources that enrich their esports and gaming experiences.  It could also mean access to the community and infrastructure resources and the equipment a school needs to set up a competitive esports environment. PlayVS organizes esports leagues at schools. “The other dimension that we thought about was how we provide tools that optimize player performance,” said Chapman. “That’s where I got introduced to Shaun Meredith, the CEO of Omnic.Ai, a few months ago. He was really interested in offering their Omnic Forge product, which is essentially an AI tool that analyzes game performance in a number of titles that kids can play in our platform.” The new partnership will bring this technology to PlayVS’ community of gamers at no cost to high school students, helping them gain a competitive edge in their scholastic leagues.  Through Omnic, Forge players can upload five matches at a time and receive two insights per match. They can also match with pro players who share their gaming style and receive detailed match analysis data. PlayVS will also assist in the initial training of Omnic Forge AI through esports coaches that will consult on the platform’s insights. “We’re excited to collaborate with PlayVS to bring our gaming analysis capabilities to a broader audience,” said Shaun Meredith, Omnic.AI CEO, in a statement. “This partnership aligns perfectly with our mission to help gamers improve their skills, win more games and have fun.”  Omnic.AI was founded in 2021 in Maine by MIT alumnus and former nuclear engineer Meredith and former Apple director Chuck Goldman. I asked what distinguishes Omnic.AI from the competition. The company said it is one of the first AI-driven platforms that provides analytics uniquely to competitive gaming, especially on the B2B level. The technology provides customizable insights for individual player performance as well as team performance, which is very interesting and attractive to scholastic teams. Omnic is also focused on social impact, which is very aligned with PlayVS’ values. The Omnic.AI cofounders actually met while working together on a campaign to put a laptop in the hands of every middle school student and teacher in Maine. Their team is committed to bettering the lives of players, designers, coaches, etc. and furthering their careers and success, which is important to PlayVS as well. PlayVS’ mission is to increase accessibility to the positive benefits of esports for all students, so they are very much aligned in their vision of how they can build the industry further, the company said. PlayVS wants to make esports more accessible to youth, while also providing students with valuable skill building opportunities in science, technology engineering and math (STEM) and leadership. Through its partnership with Omnic.AI, PlayVS aims to enhance the player experience by helping them better understand their in-game performance and integrate real-time feedback. This approach not only improves their gameplay, but also equips them with transferable skills such as critical thinking, adaptability, and effective communication—skills that are essential both in and out of the game. “Teaming up with Omnic.AI represents a significant leap

Earlier this year, I published a report exploring the decline of global brands in China’s consumer market, and the concurrent rise of domestic ones. In my latest report, Midyear Review 2024: Global Brands’ Performance In China, our analysis from global brands’ earnings reports reveals that competing in China’s consumer market remains an uphill battle. Five brands in three industries, including Apple, Starbucks, and Tesla, reported negative growth in China due to slower economic growth and intense local competition (see Figure 1).   Despite these challenges, most global brands are optimistic about long-term growth in China: Starbucks believes there’s “abundant white space ahead”, and Nike remains “confident in its competitive position in China in the long term”. Apple shares similar sentiments, citing its confidence in its long-term opportunity in China.   Global Brands Can Learn From Peers’ Positive Measures  Despite shrinking performance for most brands we analyzed, there were still some effective strategies, including:   Localizing strategy. We found that global brands with deep localization strategies performed best in the last quarter. For example, Adidas deepens connections with local consumers through tailored products and experiences in a local-for-local approach. Tesla and Volkswagen outperformed other global automotive brands with their localization efforts – Telsa has a wholly foreign-owned car plant in China, and Volkswagen adopts an “in China, for China” approach.   Retaining core brand value. Starbucks struggles with economic value against cheaper competitors like Luckin Coffee. Despite avoiding a price war, it uses limited discounts to maintain its premium positioning, focusing on experiential value. Initiatives like a tiered rewards scheme and partnerships with Marriott Bonvoy and Hilton Honors boosted Starbucks Rewards members from 1.6 million to 22 million.  Leveraging local partners’ cost advantages. Global brands in the electric vehicle sector face intense price competition due to heavy price pressures and consumers’ price sensitivity. It’s crucial for global brands to remain cost-competitive with local firms; they can seek to do so by deepening local partnerships to improve cost efficiency.  Surviving Fierce Local Competition Requires More Than Brand Salience Or Winning Price Wars  Many global brands are losing in China because local competitors are more effective at capturing market share. While almost every global brand we tracked cited intense price pressure from local competitors, only a few, like Volkswagen, recognized local players’ high level of innovation. Domestic brands excel in the Chinese consumer market because of their localized offerings, level and speed of innovation, as well as aggressive marketing. Global brands wishing to succeed in China must keep pace with an offensive localized strategy and have greater ambitions for product innovation and bold marketing.   Forrester clients can access the full report or schedule an inquiry or guidance session for a deeper dive into examples and insights on how global brands can succeed in China.    source

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Anthropic, the artificial intelligence company behind the popular Claude chatbot, today announced a sweeping update to its Responsible Scaling Policy (RSP), aimed at mitigating the risks of highly capable AI systems. The policy, originally introduced in 2023, has evolved with new protocols to ensure that AI models, as they grow more powerful, are developed and deployed safely. This revised policy sets out specific Capability Thresholds—benchmarks that indicate when an AI model’s abilities have reached a point where additional safeguards are necessary. The thresholds cover high-risk areas such as bioweapons creation and autonomous AI research, reflecting Anthropic’s commitment to prevent misuse of its technology. The update also brings more detailed responsibilities for the Responsible Scaling Officer, a role Anthropic will maintain to oversee compliance and ensure that the appropriate safeguards are in place. Anthropic’s proactive approach signals a growing awareness within the AI industry of the need to balance rapid innovation with robust safety standards. With AI capabilities accelerating, the stakes have never been higher. Why Anthropic’s Responsible Scaling Policy matters for AI risk management Anthropic’s updated Responsible Scaling Policy arrives at a critical juncture for the AI industry, where the line between beneficial and harmful AI applications is becoming increasingly thin. The company’s decision to formalize Capability Thresholds with corresponding Required Safeguards shows a clear intent to prevent AI models from causing large-scale harm, whether through malicious use or unintended consequences. The policy’s focus on Chemical, Biological, Radiological, and Nuclear (CBRN) weapons and Autonomous AI Research and Development (AI R&D) highlights areas where frontier AI models could be exploited by bad actors or inadvertently accelerate dangerous advancements. These thresholds act as early-warning systems, ensuring that once an AI model demonstrates risky capabilities, it triggers a higher level of scrutiny and safety measures before deployment. This approach sets a new standard in AI governance, creating a framework that not only addresses today’s risks but also anticipates future threats as AI systems continue to evolve in both power and complexity. How Anthropic’s capability thresholds could influence AI safety standards industry-wide Anthropic’s policy is more than an internal governance system—it’s designed to be a blueprint for the broader AI industry. The company hopes its policy will be “exportable,” meaning it could inspire other AI developers to adopt similar safety frameworks. By introducing AI Safety Levels (ASLs) modeled after the U.S. government’s biosafety standards, Anthropic is setting a precedent for how AI companies can systematically manage risk. The tiered ASL system, which ranges from ASL-2 (current safety standards) to ASL-3 (stricter protections for riskier models), creates a structured approach to scaling AI development. For example, if a model shows signs of dangerous autonomous capabilities, it would automatically move to ASL-3, requiring more rigorous red-teaming (simulated adversarial testing) and third-party audits before it can be deployed. If adopted industry-wide, this system could create what Anthropic has called a “race to the top” for AI safety, where companies compete not only on the performance of their models but also on the strength of their safeguards. This could be transformative for an industry that has so far been reluctant to self-regulate at this level of detail. The role of the responsible scaling officer in AI risk governance A key feature of Anthropic’s updated policy is the expanded responsibilities of the Responsible Scaling Officer (RSO)—a role that Anthropic will continue to maintain from the original version of the policy. The updated policy now details the RSO’s duties, which include overseeing the company’s AI safety protocols, evaluating when AI models cross Capability Thresholds, and reviewing decisions on model deployment. This internal governance mechanism adds another layer of accountability to Anthropic’s operations, ensuring that the company’s safety commitments are not just theoretical but actively enforced. The RSO has the authority to pause AI training or deployment if the safeguards required at ASL-3 or higher are not in place. In an industry moving at breakneck speed, this level of oversight could become a model for other AI companies, particularly those working on frontier AI systems with the potential to cause significant harm if misused. Why Anthropic’s policy update is a timely response to growing AI regulation Anthropic’s updated policy comes at a time when the AI industry is under increasing pressure from regulators and policymakers. Governments across the U.S. and Europe are debating how to regulate powerful AI systems, and companies like Anthropic are being watched closely for their role in shaping the future of AI governance. The Capability Thresholds introduced in this policy could serve as a prototype for future government regulations, offering a clear framework for when AI models should be subject to stricter controls. By committing to public disclosures of Capability Reports and Safeguard Assessments, Anthropic is positioning itself as a leader in AI transparency—an issue that many critics of the industry have highlighted as lacking. This willingness to share internal safety practices could help bridge the gap between AI developers and regulators, providing a roadmap for what responsible AI governance could look like at scale. Looking ahead: What Anthropic’s Responsible Scaling Policy means for the future of AI development As AI models become more powerful, the risks they pose will inevitably grow. Anthropic’s updated Responsible Scaling Policy is a forward-looking response to these risks, creating a dynamic framework that can evolve alongside AI technology. The company’s focus on iterative safety measures—with regular updates to its Capability Thresholds and Safeguards—ensures that it can adapt to new challenges as they arise. While the policy is currently specific to Anthropic, its broader implications for the AI industry are clear. As more companies follow suit, we could see the emergence of a new standard for AI safety, one that balances innovation with the need for rigorous risk management. In the end, Anthropic’s Responsible Scaling Policy is not just about preventing catastrophe—it’s about ensuring that AI can fulfill its promise of transforming industries and improving lives without leaving destruction in its wake.

2024 beherrschten KI-Fehler die Schlagzeilen, da weltweit ihre Nachteile offenbart wurden – von wettbewerbswidrigen Fällen in der Big-Tech-Branche bis hin zu Wahlmanipulation und Desinformation in sozialen Medien. Während die Mängel von KI und Emerging Technologies Schlagzeilen machten und Unternehmen vor sich hertrieben, wurden weiter die Weichen für die Zukunft gestellt. Führungskräfte lernen täglich neue Lektionen über KI und technologische Verantwortung – alles, um das Vertrauen der Verbraucher und Kunden zu gewinnen. Aber nicht alle Länder haben die gleichen (oder überhaupt) Vorschriften für KI. Das heißt, dass nicht für alle Unternehmen dieselben Spielregeln gelten. Die weltweit uneinheitlichen KI-Standards und -Vorschriften werden dazu führen, dass es einigen Unternehmen besser gelingt als anderen, Vertrauen aufzubauen und zu bewahren. Während Führungskräfte nach dem richtigen Umgang mit diesem ungleich verteilten Vertrauen suchen, prognostiziert Forrester für das Jahr 2025 Folgendes: Das Vertrauen in Regierungen wird nach den Wahlen 2024 um 10 % steigen – kurzfristig. 2024 stehen verschiedene wichtige politische Entscheidungen an: Fast die Hälfte der Weltbevölkerung ist zu nationalen Wahlen aufgerufen. Desinformation und soziale Manipulation durch ausländische staatliche Akteure haben das Misstrauen gegenüber demokratischen Institutionen geschürt. In neun der elf von uns untersuchten G20-Länder gab die Mehrheit der erwachsenen Online-Nutzer an, nicht auf eine Einlösung von Regierungsversprechen zu vertrauen. Nach einem Wahljahr, das von politischer Unsicherheit und heftigen Kontroversen geprägt ist, werden 2025 verschiedene Machtwechsel das Vertrauen in die Regierungen weltweit wiederherstellen. Dieser Vertrauenszuwachs wird jedoch nur von kurzer Dauer sein. Der Glanz des vermeintlichen Aufbruchs wird schnell verblassen, sobald sich die neu gewählten Regierungen mit ernsthafteren Problemen auseinandersetzen müssen, für die es keine schnellen Lösungen gibt. Das Vertrauen in regulierte und unregulierte Branchen variiert stark. Es werden sich zwei Arten von Vertrauen herauskristallisieren: erzwungenes Vertrauen und erarbeitetes Vertrauen. Regulierte Branchen wie Finanzdienstleistungen und das Gesundheitswesen leben in einem Umfeld erzwungenen Vertrauens, in dem staatliche Vorschriften und Aufsichtsbehörden die Standards für Transparenz und Rechenschaftspflicht setzen. Dagegen operieren unregulierte Branchen in einem Umfeld, in dem sie sich Vertrauen durch ihre Leistung erarbeiten müssen, da sie gesetzlich nicht zu vertrauensbildendem Handeln verpflichtet sind. Ihre Motivation beruht allein darauf, dass sie Markenschädigung, eine Verurteilung durch die Öffentlichkeit und andere potenzielle finanzielle Verluste fürchten. Für das Jahr 2025 prognostiziert Forrester starke Unterschiede bei dem Vertrauen, das den beiden Arten von Branchen entgegengebracht wird: Während die regulierten Branchen das derzeitige Vertrauensniveau beibehalten, werden die unregulierten Branchen ein sinkendes Vertrauensniveau verzeichnen. KI-gestützte Skill Intelligence und Karrieretools werden das Vertrauen der Mitarbeiter in KI stärken. Eine Erkenntnis, die Unternehmen im Zuge des KI-Hypes gewonnen haben, ist, dass ein großer Teil ihrer Mitarbeiter eine Umschulung (das Erlernen völlig neuer Fähigkeiten für neu entstehende Arbeitsplätze) oder eine Weiterbildung (das Erlernen zusätzlicher Fähigkeiten für ihre bestehenden Arbeitsplätze) benötigt. Die Daten von Forrester aus dem Jahr 2024 zeigen, dass Fähigkeiten im Bereich Daten und Analytik zu den Fähigkeiten gehören, die Business- und Tech-Fachkräfte weltweit am meisten benötigen, um die Modernisierung ihres Unternehmens in den nächsten 12 Monaten zu unterstützen. Fortschrittliche Unternehmen werden KI nutzen, um Daten zu den Fähigkeiten ihrer Mitarbeiter zu analysieren und mithilfe dieser Erkenntnisse komplexe Herausforderungen zu lösen, wie z. B. der Einsatz von Talenten für andere Aufgaben oder Weiterbildungs- bzw. Umschulungsmaßnahmen. KI wird auch Initiativen zur Verbesserung der Mitarbeitererfahrung unterstützen, die derzeit einen hohen manuellen Aufwand erfordern. So wird durch Vertrautheit Vertrauen entstehen. Wenn Sie Kunde von Forrester sind, steht der Report Predictions 2025: Trust (auf Englisch) für Sie bereit. Dort können Sie unsere fünf Prognosen für das Jahr 2025 vollständig lesen und erfahren, was sie für Sie und Ihr Unternehmen im kommenden Jahr bedeuten. Vereinbaren Sie ein Beratungsgespräch mit Forrester, um mit uns zu besprechen, wie Sie diese Prognosen und Best Practices anwenden können, damit Sie auch im Jahr 2025 in puncto Vertrauen die Nase vorn haben. Wenn Sie noch kein Forrester-Kunde sind, besuchen Sie unseren Hub für Prognosen 2025, um sich für Webinare anzumelden und einen unserer kostenlosen Guides zu Prognosen herunterzuladen. NB: Dieser Blog wurde aus dem Englischen übersetzt. source

Forrester has just released its inaugural evaluation, The Forrester Wave™: Vector Databases, Q3 2024, marking a significant milestone in this rapidly evolving category. The vector database market is buzzing, and nearly all other database vendors are racing to offer vector support. While native vector databases have had a head start over the past few years, traditional database vendors are now setting aggressive timelines to catch up. We haven’t witnessed this level of excitement in the database landscape in decades. Vector databases are becoming essential for businesses, and Forrester anticipates that most organizations will have them in production by 2026. Vector databases are attracting significant attention thanks to the rise of generative AI (genAI), resulting in a surge of new use cases. They play a vital role in delivering reliable and enriched data to support genAI applications, enhancing the accuracy and contextual relevance of responses from large language models. Additionally, vector databases provide an effective means of detecting data anomalies by analyzing deviations from expected norms and generating valuable insights. Forrester expects widespread growth in vector database initiatives across diverse industries, including financial services, retail, healthcare, manufacturing, and energy in the coming years. Choosing A Vector Database Requires Looking Beyond Basic Capabilities There are two main types of vector databases: native and multimodel. Native vector databases are purpose-built to excel at managing complex, multidimensional vector data at scale. In contrast, multimodel databases were not originally designed for vectors but are now increasingly integrating vector capabilities, such as vector storage, indexing, and querying. In our recently released Forrester Wave evaluation, we closely examined 14 leading vector databases from over 100 available in the market. While we currently have two vendors recognized as Leaders, we anticipate that more will emerge next year as their solutions mature. Organizations should also consider other vendors in the Strong Performers category that align with their specific requirements, particularly regarding performance, scale, hybrid search, and integration with non-vector data. To meet current and future needs, organizations should focus on three key differentiators of vector databases — specifically, their ability to: Ensure comprehensive core vector capabilities. Look for vector database vendors that provide advanced indexing, diverse distance metrics, real-time vector updates and deletion, extensive dimensionality support, flexible metadata storage, and hybrid search functionality. Streamline data management for vectors. Look for vector vendors with extensive data management capabilities that accommodate both vector and non-vector data. Additionally, prioritize those that provide a user-friendly, persona-based interface to simplify deployments, along with robust APIs for agile development. Deliver performance and scale at the speed of your business. Look for vendors offering a range of indexing algorithms, including hierarchical navigable small world (HNSW), IVF, and DiskANN, tailored to your specific workload. Additionally, consider those that provide GPU integration, which can deliver significant performance improvements over regular CPUs. Since many vector databases are still evolving their ability to scale, speak to customers or conduct benchmarks if your use cases require 100 million vectors or more. Vector capabilities are coming to a database near you. Kick off 2025 with a pilot project that leverages retrieval-augmented generation use cases to enhance conversational AI, customer service applications, content creation and summarization, enterprise search, and personalized recommendations. The Forrester Wave evaluation will provide insights into how 14 vector database vendors compare across 25 criteria, including functionality, strategy, and market presence. Readers can also customize the Wave scorecard to align with their specific priorities. Forrester clients can schedule a guidance session or inquiry with us to discuss vendor selection and trends in this market. source