請用繁體中文，幫我摘要出重點：usiness leaders believe the development and release of gen AI tools is too slow in their organizations.McKinsey & CompanyToo slowAbout rightToo fast47459Talent skill gapsResourcing constraintsComplex approval processTechnical complexity463888 
13 Hayden Field, “OpenAI’s active user count soars to 300 million people per week,” CNBC, December 4, 2024.
14 Krystal Hu and Dawn Chmielewski, “OpenAI’s Altman pitches ChatGPT Enterprise to large firms, including some Microsoft customers,” Reuters, April 12, 2024.
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Business leaders are trying to meet the need for speed by increasing investments in AI. Of the executives surveyed, 92 percent say they expect to boost spending on AI in the next three years, with 55 percent expecting investments to increase by at least 10 percent from current levels. But they can no longer just spend on AI without expecting results. As companies move on from the initial thrill of gen AI, business leaders face increasing pressure to generate ROI from their gen AI deployments.
We are at a turning point. The initial AI excitement may be waning, but the technology is accelerating. Bold and purposeful strategies are needed to set the stage for future success. Leaders are taking the first step: One quarter of those executives we surveyed have defined a gen AI road map, while just over half have a draft that is being refined (Exhibit 7). With technology changing this fast, all road maps and plans will evolve constantly. For leaders, the key is to make some clear choices about what valuable opportunities they choose to pursue first—and how they will work together with peers, teams, and partners to deliver that value.
Exhibit 7Not identi_edHave not yet identi_ed gen AI use cases for revenue generation or cost reductionMinimally identi_edHave only just begun exploring how gen AI can drive revenue or reduce costPartially identi_edHave identi_ed a few use cases, but more exploration is neededto map to valuegenerationMostly identi_edHave several promising gen AI use cases,but there is still room for discovery andoptimizationFully identi_edReady to implement value-generating gen AI use cases, with no plans for other use casesWeb <2025><Superagency>Exhibit <9> of <21>Presence of a de_ned gen AI road map, % of US C-suite respondentsLevel of identifying revenue-generating use cases for gen AI, % of US C-suite respondentsNote: Figures may not sum to 100%, because of rounding.Source: McKinsey US CxO survey, Oct–Nov 2024 (n = 118) Most C-suite respondents have road maps to guide their gen AI strategies and have begun identifying use cases.McKinsey & CompanyNo, but oneis in progressNo, there is no road map yet 0Yes, but it isstill being re_nedYes, a comprehensiveroad map is in place215338391211025 
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The dilemma of speed versus safety
There’s a spanner in the works: Regulation and safety often continue to be seen as insurmountable challenges rather than opportunities. Leaders want to increase AI investments and accelerate development, but they wrestle with how to make AI safe in the workplace. Data security, hallucinations, biased outputs, and misuse (for example, creating harmful content or enabling fraud) are challenges that cannot be ignored. Employees are well aware of AI’s safety challenges. Their top concerns are cybersecurity, privacy, and accuracy (Exhibit 8). But what will it take for leaders to address these concerns while also moving ahead at light speed?
Exhibit 8Web <2025><Superagency>Exhibit <10> of <21>Share of US employees citing risk as a concern associated with gen AI, %Source: McKinsey US employee survey, Oct–Nov 2024 (n = 3,002)Employees have concerns about gen AI—namely cybersecurity risks, inaccuracies, and data leaks.McKinsey & CompanyCybersecurityInaccuracyPersonalprivacyIntellectual propertyinfringementWorkforcedisplacementExplainabilityEquity andfairnessRegulatorycomplianceNationalsecurityOrganizationalreputationEnvironmentalimpactPhysicalsafetyPoliticalstability51504340353428241615141330 
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Empl，列出一個500字段落給我，盡可能不要遺漏任何資訊, (我是金融業的策略幕僚，請盡可能往金融分析資訊蒐集與影像去分析)