（2017年7月28日， / HRoot.com/）全球人才解決方案的領導者遨聚士（Allegis Group）最近對300多名人力資源專業人士（高級經理及以上級別）進行了調查， 面對人工智慧對未來工作產生的影響， 他們喜憂參半。 受訪者認為人工智慧是令人興奮的（21%）， 產生的干擾和助力並存（17%）， 但少數人力資源專業人士表明人工智慧沒有被足夠快地採納（8%）。 此外， 該調查結果表明， 少數人（9%）認為人工智慧將在10年內取代大部分工作。 該報告名稱為《AI與工作世界：接受承諾和現實》。
人力資源專家盤點人工智慧
當被問及從人工智慧中獲益最多的人才管理領域時， 人力資源專業人員的回答是：人才培訓（26%）、人才篩選（24%）和勞動力規劃（22%）。
對於最容易實行自動化的技能類型， 人力資源專業人員的回答是：資料收集/處理（36%）、可預測的、物理性工作（27%）、分析/定量技能（23%）和客戶服務/管理（22%）。
採用人工智慧的最大障礙包括需要升級或維護人工智慧（32%）、缺乏獎勵或管理人工智慧的人才（26%）以及培訓人工智慧技術（24%）。
總的來說， 調查結果表明人工智慧不會取代對專業人才的需求， 相反， 它將改變人才成功所工作的性質。
遨聚士（Allegis Group）研究表明， 採用人工智慧對整個市場的影響包括：
·預計對人工智慧技能的需求將增加：雖然人工智慧正在取代人類的很多技能， 但新的就業機會也將出現。 很可能包括對管理與人工智慧相關的風險、責任及其透明度需求的人工智慧倫理學家候選人的需求。
·制約因素將影響創新的速度：機器學習驅動的人工智慧系統需要人工指導和程式設計， 而缺乏這種指導的技能可能阻礙發展。 此外， 今天的人工智慧系統需要大量的資料和資訊。 雖然資料豐富， 但並非都能夠支援人工智慧應用程式。 其他制約因素包括成本、購買、採納的需要以及規章制度。
·新的挑戰將影響人工智慧的有效性：通過利用現有資料系統中的漏洞或使用低質量數據， 是否會阻礙人工智慧的發展？雖然存在這些問題，
Allegis Group Study Outlines Status of HR-Related Artificial Intelligence Initiatives
（Jul.28,/HRoot.com/）Allegis Group, the global leader in talent solutions, recently surveyed more than 300 human resources (HR) professionals, senior-manager level and above, who reported mixed feelings about AI and its impact on the future of work. Survey participants see AI as something to be excited about (21%) and as both disrupting and enabling (17%), yet a low number of HR professionals indicate that AI is not being adopted fast enough (8%). Additional findings indicated that a low number (9%) believe AI will displace most jobs in 10 years.
These findings, coupled with insight on AI's implications for tomorrow's talent and workforce strategies, are available in a new research report, "AI and the World of Work: Embracing the Promises and Realities."
HR Professionals Take Stock of AI
When asked to identify areas of talent management that will benefit from AI, top responses from HR professionals surveyed included training talent (26%), screening talent (24%) and workforce planning (22%).
Regarding the skill types most susceptible to automation, HR professionals pointed to data collection/processing (36%), predictable, physical work (27%), analytical/quantitative skills (23%) and customer services/administration (22%).
The top roadblocks to adoption include budgets needed to upgrade or maintain AI (32%), a lack of people to build or manage AI (26%) and training the AI (24%).
Overall, findings indicate AI will not replace the need for talent professionals; instead, it will change the nature of what they need to do to succeed.
Additional trends regarding the adoption of AI that expand to the market as a whole include:
·Expect Increased Demand for AI Skills: While AI is taking on many skills formerly attributed to humans, new jobs will emerge. Likely candidates include AI ethicists to manage the risks and liabilities associated with AI, as well as transparency requirements. Needs will also emerge for AI trainers, and individuals to support data science, the Internet of Things (IoT), as well as capabilities related to modeling, computational intelligence, machine learning, mathematics, psychology, linguistics and neuroscience.
·Constraints Will Influence the Pace of Innovation: Machine learning-driven AI systems require human guidance and programming, and a shortage of skills to provide this guidance may hinder progress. Also, today's AI systems require deep sets of data and information. While data is abundant, it is not always available in pools that can be used to support an AI application. Other constraints include cost, the need for buy-in and adoption, and regulation.
·New Challenges Will Influence AI's Effectiveness: Can AI be prevented from exploiting vulnerabilities in existing data systems or stopped from acting on low-quality data? While these issues, coupled with the impact of failure, product liability, perpetual obsolescence and malicious use are concerns, the research holds that most of these near-term issues will be solved or mitigated over time.