市场调查报告书
商品编码
1423713
到 2030 年决策智慧市场预测:按组件、部署型态、公司规模、应用程式、最终用户和地区进行的全球分析Decision Intelligence Market Forecasts to 2030 - Global Analysis By Component (Services, Solutions and Platform), Deployment Mode, Enterprise Size, Application, End User and By Geography |
根据Stratistics MRC预测,2023年全球决策智慧市场规模将达到120亿美元,预计2030年将达到424亿美元,预测期内复合年增长率为19.8%。
决策智慧 (DI) 市场是指一个快速成长的行业,它利用先进技术、资料分析和人工智慧来增强组织内的决策流程。包括各种旨在优化决策工作流程并为策略规划、业务效率和风险管理提供可行见解的解决方案。决策智慧整合了机器学习演算法、预测分析和资料视觉化工具,帮助企业做出及时、明智的选择。
根据 Gartner 预测,到 2025 年,创业投资(VC) 和早期投资者将在超过 75% 的高阶主管评估中使用人工智慧 (AI) 和资料分析。根据 Gartner 最近的一项民意调查,80% 的高阶主管认为自动化可用于制定所有类型的业务决策。随着数位业务和自动化变得更加一体化,这项民意调查揭示了公司如何在自动化工作中利用人工智慧 (AI)。
商业环境日益复杂
在科技快速进步、全球化和复杂互联的时代,组织正在应对多方面的挑战。决策者面临着来自不同来源的大量资料,这使得手动破解模式、预测趋势和得出可行的见解变得越来越困难。决策智慧透过利用高阶分析、人工智慧和机器学习从庞大的资料集集中提取有意义的资讯来解决这种复杂性。此外,它还使您能够识别相关模式、发现机会并敏捷地应对复杂的决策环境。
缺乏熟练的专业人员
决策智慧领域需要独特的专业知识融合,包括资料科学、人工智慧、机器学习和特定领域的知识。缺乏具有这些多学科技能的专业人员阻碍了组织内决策智慧工具的有效采用和利用。对熟练人才的需求往往超过供应,导致人才竞争加剧。然而,这种短缺不仅增加了实施所需的时间和资源,也增加了人事费用。
人工智慧 (AI) 和机器学习 (ML) 的进步
人工智慧和机器学习技术的进步为决策支援系统提供了前所未有的分析大量复杂资料集的能力。这些技术使演算法能够随着时间的推移进行学习、适应和改进,从而提高决策流程的准确性和效率。决策智慧利用这些功能,为组织提供预测性和指示性分析,以即时做出明智的选择。此外,决策智慧与人工智慧/机器学习之间的协同效应不仅优化了业务效率,而且还开启了从资料中提取有价值的见解的新可能性。
资料隐私问题
由于决策在很大程度上依赖普遍的资料分析,企业面临确保遵守 GDPR 等严格资料保护条例的挑战。整合决策智慧通常涉及收集和资料,从而引发对潜在违规和未授权存取的担忧。在提取有意义的见解和保护个人隐私之间取得微妙的平衡变得至关重要。组织必须投资于强有力的安全措施和透明的做法,以解决这些问题并建立相关人员的信任。
疫情带来的复杂性和不确定性增加,加强了对决策智慧所提供的先进分析和预测能力的需求。组织寻求优化营运、供应链和策略规划,以因应快速变化的环境。但经济的不确定性导致一些公司重新考虑预算,并将眼前的需求置于长期技术投资之上。然而,疫情也凸显了决策演算法中道德考量和透明度的重要性。
预计解决方案产业将在预测期内成为最大的产业。
由于对促进资料主导决策的先进工具和技术的需求不断增加,预计解决方案产业在预测期内将占据最大份额。各行各业的组织都在积极寻求全面的决策智慧解决方案,以应对日益复杂的商业环境。这些解决方案包含预测分析、机器学习演算法和资料视觉化工具等各种功能,为决策者提供可行的见解。
预计云细分市场在预测期内复合年增长率最高
云端领域预计在预测期内将出现最高的复合年增长率,因为它为部署高阶分析和决策支援解决方案提供可扩展且灵活的基础架构。云端基础的决策智慧平台使组织能够灵活地即时存取和处理大量资料,从而更快地制定决策。云端服务的可扩展性使企业能够根据需求扩展或收缩运算资源,从而优化成本。此外,云端解决方案促进协作和可访问性,使决策者能够从任何地方获取见解,从而促进更分散和敏捷的决策流程。
该地区先进的技术基础设施,加上整个行业的高度数位化,为采用复杂的决策智慧解决方案创造了肥沃的土壤,使北美成为估计期间市场上最大的地区,预计将占据很大的份额。北美企业,特别是金融、医疗保健和技术等行业的企业,越来越认识到资料主导的决策对于获得竞争优势至关重要。此外,主要市场参与者的存在和有利于创新的商业环境也有助于该地区在塑造决策智慧市场方面的主导地位。
欧洲地区在预测期内正在快速成长。以一般资料保护规范 (GDPR) 等框架为代表的严格监管环境正在迫使企业采用先进的决策智慧解决方案来实现资料的合规性和道德处理。强调资料隐私和安全的法规是催化剂,促使公司投资先进的决策支援系统,以确保遵守这些标准。此外,随着欧洲政府继续收紧资料保护条例,公司将需要整合决策智慧工具,这些工具不仅可以提高业务效率,还可以展示决策流程的透明度和课责。我是。
According to Stratistics MRC, the Global Decision Intelligence Market is accounted for $12.0 billion in 2023 and is expected to reach $42.4 billion by 2030 growing at a CAGR of 19.8% during the forecast period. Decision Intelligence (DI) Market refers to the burgeoning industry that leverages advanced technologies, data analytics, and artificial intelligence to enhance decision-making processes within organizations. It encompasses a range of solutions designed to optimize decision workflows, providing actionable insights for strategic planning, operational efficiency, and risk management. Decision Intelligence integrates machine learning algorithms, predictive analytics, and data visualization tools to empower businesses in making informed and timely choices.
According to Gartner, Inc., artificial intelligence (AI) and data analytics will be used to inform more than 75% of venture capital (VC) and early-stage investor executive assessments by 2025. According to a recent Gartner, Inc. poll, 80% of executives believe automation can be used in every kind of business decision. As digital business becomes more integrated with automation, the poll uncovered how companies are adapting their usage of artificial intelligence (AI) in automation initiatives.
Increasing complexity of business environments
In an era marked by rapid technological advancements, globalization, and intricate interconnections, organizations grapple with multifaceted challenges. Decision-makers face a deluge of data from diverse sources, making it increasingly challenging to decipher patterns, anticipate trends, and derive actionable insights manually. Decision Intelligence addresses this complexity by leveraging advanced analytics, artificial intelligence, and machine learning to distill meaningful information from vast datasets. Moreover, it enables businesses to discern relevant patterns, identify opportunities, and navigate intricate decision landscapes with agility.
Lack of skilled professionals
The field of Decision Intelligence requires a unique blend of expertise in data science, artificial intelligence, machine learning, and domain-specific knowledge. The scarcity of professionals possessing this interdisciplinary skill set hampers the effective implementation and utilization of Decision Intelligence tools within organizations. The demand for skilled talent often outstrips the available supply, resulting in increased competition for qualified individuals. However, this shortage not only extends the time and resources required for implementation but also leads to higher labor costs.
Advancements in artificial intelligence (AI) and machine learning (ML)
Advancements in AI and ML technologies empower decision support systems with unprecedented capabilities to analyze vast and complex datasets. These technologies enable algorithms to learn, adapt, and improve over time, enhancing the accuracy and efficiency of decision-making processes. Decision Intelligence leverages these capabilities to provide organizations with predictive and prescriptive analytics, enabling them to make informed choices in real-time. Additionally, the synergy between Decision Intelligence and AI/ML not only optimizes operational efficiency but also unlocks new possibilities for uncovering valuable insights from data.
Data privacy concerns
With decision-making heavily reliant on extensive data analysis, organizations face the challenge of ensuring compliance with stringent data protection regulations, such as GDPR. The integration of Decision Intelligence often involves the collection and processing of vast amounts of personal and business data, raising apprehensions about potential breaches and unauthorized access. Striking a delicate balance between extracting meaningful insights and safeguarding individual privacy becomes crucial. Organizations must invest in robust security measures and transparent practices to allay these concerns and build trust among stakeholders.
The increased complexity and uncertainty brought about by the pandemic amplified the demand for advanced analytics and predictive capabilities offered by Decision Intelligence. Organizations sought to optimize their operations, supply chains, and strategic planning in response to rapidly changing circumstances. However, economic uncertainties led some businesses to reevaluate budgets and prioritize immediate needs over long-term technology investments. However, the pandemic also highlighted the importance of ethical considerations and transparency in decision-making algorithms.
The solutions segment is expected to be the largest during the forecast period
Due to the escalating demand for advanced tools and technologies that facilitate data-driven decision-making, Solutions segment is expected to hold the largest share during the forecast period. Organizations across diverse sectors are actively seeking comprehensive Decision Intelligence Solutions to navigate the increasing complexity of business landscapes. These solutions encompass a spectrum of capabilities, including predictive analytics, machine learning algorithms, and data visualization tools, empowering decision-makers with actionable insights.
The cloud segment is expected to have the highest CAGR during the forecast period
Cloud segment is expected to have the highest CAGR during the forecast period as it offers scalable and flexible infrastructure for deploying advanced analytics and decision support solutions. Cloud-based Decision Intelligence platforms provide organizations with the agility to access and process large volumes of data in real-time, enabling faster decision-making. The scalability of cloud services allows businesses to expand or contract their computing resources based on demand, optimizing costs. Moreover, cloud solutions facilitate collaboration and accessibility, allowing decision-makers to access insights from anywhere, fostering a more distributed and agile decision-making process.
Due to the region's advanced technological infrastructure, coupled with a high level of digitalization across industries, creates a fertile ground for the adoption of sophisticated decision intelligence solutions, North American region is expected to hold the largest share of the market over the extrapolated period. North American enterprises, particularly in sectors like finance, healthcare, and technology, are increasingly recognizing the imperative of data-driven decision-making to gain a competitive edge. Additionally, the well-established presence of key market players and a conducive business environment for innovation contribute to the region's dominance in shaping the Decision Intelligence Market.
Europe region is growing at a rapid pace over the projection period. The stringent regulatory landscape, exemplified by frameworks like the General Data Protection Regulation (GDPR), compels businesses to adopt advanced decision intelligence solutions for compliant and ethical handling of data. The regulatory emphasis on data privacy and security acts as a catalyst, prompting organizations to invest in sophisticated decision support systems that ensure adherence to these standards. Furthermore, as European governments continue to strengthen data protection regulations, businesses are compelled to integrate decision intelligence tools that not only enhance operational efficiency but also demonstrate transparency and accountability in decision-making processes.
Key players in the market
Some of the key players in Decision Intelligence market include International Business Machines Incorporation, Oracle, Intel Corporation, Pyramid Analytics Bv, Google LLC, Pace Revenue, Microsoft, Provenir, Diwo.ai, Metaphacts GmbH and Paretos.
In June 2022, IBM acquired Databand.ai. Through the acquisition, Databand.ai will be able to increase the scope of its observability capabilities enabling deeper connections with more open source and for-profit products that drive the modern data stack, with the additional resources made available by this purchase. Additionally, businesses will have complete control over how Databand.ai is used, whether as a software-as-a-service (SaaS) or a selfhosted subscription.
In April 2022, Sopra Steria and IBM launched the Sopra Steria Alive Intelligence (SSAI) offering. The IBM Watson Assistant, a customizable virtual agent for all fields, powers the Sopra Steria Alive Intelligence (SSAI) solution. This data is utilized to enhance decisionmaking and create new services that are tailored to the needs of consumers and users.
In March 2022, Provenir with Francisco Franch declared to assist the rising number of financial services businesses looking for AI-powered risk decisioning tools. Franch will oversee managing Spain's sales operations, company growth, and marketing plans.