의사결정 인텔리전스 시장 예측(-2034년) : 구성요소, 도입 형태, 기업 규모, 용도, 최종사용자, 지역별 세계 분석

According to Stratistics MRC, the Global Decision Intelligence Market is accounted for $20.6 billion in 2026 and is expected to reach $87.5 billion by 2034 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.

Market Dynamics:

Driver:

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.

Restraint:

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.

Opportunity:

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.

Threat:

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.

Covid-19 Impact:

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.

Region with largest share:

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.

Region with highest CAGR:

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.

Key Developments:

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.

Components Covered:

• Services
• Solutions
• Platform

Deployment Modes Covered:

• Cloud
• On-premise
• Other Deployment Modes

Enterprise Sizes Covered:

• Small and Medium-sized Enterprises (SMEs)
• Large Enterprise

Applications Covered:

• Demand Forecasting
• Logistics Optimization
• Discovering Cause
• Other Applications

End Users Covered:

• IT and Telecom
• Energy and Utilities
• Healthcare
• Government
• Retail and Consumer Goods
• Other End Users

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2023, 2024, 2025, 2026, 2027, 2028, 2030, 2032 and 2034
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 Application Analysis
• 3.7 End User Analysis
• 3.8 Emerging Markets
• 3.9 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global Decision Intelligence Market, By Component

• 5.1 Introduction
• 5.2 Services
• 5.3 Solutions
• 5.4 Platform

6 Global Decision Intelligence Market, By Deployment Mode

• 6.1 Introduction
• 6.2 Cloud
• 6.3 On-premise
• 6.4 Other Deployment Modes

7 Global Decision Intelligence Market, By Enterprise Size

• 7.1 Introduction
• 7.2 Small and Medium-sized Enterprises (SMEs)
• 7.3 Large Enterprise

8 Global Decision Intelligence Market, By Application

• 8.1 Introduction
• 8.2 Demand Forecasting
• 8.3 Logistics Optimization
• 8.4 Discovering Cause
• 8.5 Other Applications

9 Global Decision Intelligence Market, By End User

• 9.1 Introduction
• 9.2 IT and Telecom
• 9.3 Energy and Utilities
• 9.4 Healthcare
• 9.5 Government
• 9.6 Retail and Consumer Goods
• 9.7 Other End Users

10 Global Decision Intelligence Market, By Geography

• 10.1 Introduction
• 10.2 North America
  • 10.2.1 US
  • 10.2.2 Canada
  • 10.2.3 Mexico
• 10.3 Europe
  • 10.3.1 Germany
  • 10.3.2 UK
  • 10.3.3 Italy
  • 10.3.4 France
  • 10.3.5 Spain
  • 10.3.6 Rest of Europe
• 10.4 Asia Pacific
  • 10.4.1 Japan
  • 10.4.2 China
  • 10.4.3 India
  • 10.4.4 Australia
  • 10.4.5 New Zealand
  • 10.4.6 South Korea
  • 10.4.7 Rest of Asia Pacific
• 10.5 South America
  • 10.5.1 Argentina
  • 10.5.2 Brazil
  • 10.5.3 Chile
  • 10.5.4 Rest of South America
• 10.6 Middle East & Africa
  • 10.6.1 Saudi Arabia
  • 10.6.2 UAE
  • 10.6.3 Qatar
  • 10.6.4 South Africa
  • 10.6.5 Rest of Middle East & Africa

11 Key Developments

• 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 11.2 Acquisitions & Mergers
• 11.3 New Product Launch
• 11.4 Expansions
• 11.5 Other Key Strategies

12 Company Profiling

• 12.1 International Business Machines Incorporation
• 12.2 Oracle
• 12.3 Intel Corporation
• 12.4 Pyramid Analytics Bv
• 12.5 Google LLC
• 12.6 Pace Revenue
• 12.7 Microsoft
• 12.8 Provenir
• 12.9 Diwo.ai
• 12.10 Metaphacts GmbH
• 12.11 Paretos