Decision Intelligence Market by Offering (Platforms, Solutions (Integrated & Standalone), Services), Type (Decision Automation, Decision Augmentation, Decision Support System (DSS)), Business Function, Vertical and Region - Global Forecast to 2030
[333 Pages Report] The global decision intelligence market is projected to grow from USD 13.3 billion in 2024 to USD 50.1 billion in 2030, at a CAGR of 24.7% during the forecast period. The shift towards data-centric decision-making is evident in various sectors such as finance, healthcare, retail, manufacturing, and more. Companies are investing heavily in robust data infrastructure, analytics tools, and talent to harness the power of data effectively. By leveraging predictive and prescriptive analytics models, organizations can anticipate market trends, optimize operations, mitigate risks, and personalize customer experiences. Moreover, regulatory requirements such as GDPR and CCPA emphasize the importance of responsible data governance practices, further driving organizations to adopt data-centric decision-making approaches. The convergence of data analytics with emerging technologies like the Internet of Things (IoT) and edge computing also expands opportunities for real-time data processing and insights generation.
To know about the assumptions considered for the study, Request for Free Sample Report
To know about the assumptions considered for the study, download the pdf brochure
Decision Intelligence Market Dynamics
Driver: Need to automate and expedite decision-making processes across diverse industries to fuel the growth of the market
Decision intelligence integrates decision support, decision management, and complex systems applications to address pressing digitalization needs and harness the potential of emerging technologies such as AI and ML. These technologies enhance forecasting and predictive capabilities, supporting automated and expedited decision-making processes across diverse industries and use cases. Decision intelligence bridges the gap between data abundance and improved decision-making for organizations navigating complex data landscapes. Key sectors such as financial services, healthcare, and supply chain management stand to benefit significantly from leveraging decision intelligence to optimize AI and ML applications. These industries are currently facing critical challenges in ensuring precise decision-making. ML and AI technologies have enabled providers to gain insights into customer perceptions through a comprehensive multi-source data analysis. Enterprises are now prioritizing delivering seamless customer experiences across all touchpoints and leveraging real-time data analysis of customer purchasing behaviors to offer personalized offers promptly.
Restraint : Relying heavily on decision support systems can contribute to information overload, potentially overwhelming decision-makers with data
The user is uncertain about the criteria for consideration and exclusion as decision intelligence thoroughly analyzes every aspect of a problem. Effective decision-making does not always necessitate complete information; however, when information is available, decision-makers often struggle to filter out irrelevant data. Enterprises integrate decision support systems (DSS) to streamline and expedite routine decision-making processes. Nevertheless, some decision-makers overly depend on automated decision-making systems, neglecting their judgment. This shift in focus may hinder the development of decision-maker skills as they become overly reliant on DSS technologies.
Opportunity: The proliferation of advancements in big data technology is driving the growth of actionable business intelligence
Numerous software tasks related to decision intelligence, commonly utilized on the internet, have been effectively resolved and integrated, including morphological and syntactic analysis. The convergence of decision intelligence and big data analytics presents an opportunity to create robust systems capable of handling vast amounts of data, enabling knowledge discovery, text analysis, opinion mining, and supporting decision-making in business and management contexts. Decision intelligence applied to big data can automate the identification of pertinent information and summarize document content within extensive datasets, fostering collective insights. This approach eliminates the need for users to select precise keywords for information retrieval, allowing them to interact with content using natural language queries. This advancement not only accelerates information access but also speeds up downstream processes reliant on timely information, facilitating real-time actionable business intelligence. Consequently, decision intelligence for big data offers a means to unlock valuable insights from expansive and evolving content repositories, unveiling patterns, connections, and trends across diverse data sets. Positioned as a prominent facet of data analytics, decision intelligence leverages big data to extract valuable information through innovative methodologies, providing insightful perspectives on current or projected market dynamics.
Challenge: The security and privacy concerns surrounding data are expected to impede the broad adoption of decision intelligence solutions
Data, the foundation of decision intelligence solutions, remains a pivotal aspect challenging for many organizations to manage effectively. The complexities of handling vast amounts of data, ranging from exabytes to petabytes, have heightened concerns regarding potential security breaches and data loss incidents. In the contemporary competitive landscape, marketing teams demand real-time access to secure data to deliver exceptional customer experiences. Organizations gather data from diverse touchpoints and analyze them comprehensively, encompassing various data types such as public information, big data sets, and customer-derived small data. This data includes permissions, individual preferences, and updated contact details related to products, services, and communication channels. Therefore, it is imperative for vendors to uphold stringent data security measures to preserve customer trust and confidentiality. Recent cyber threats underscore the importance of collaboration between marketing and IT teams to ensure a thorough understanding of data collection, processing, and utilization protocols across operational workflows. Although significant cyberattacks persistently impede the widespread adoption of decision intelligence across data-intensive industries, ongoing technological advancements are expected to mitigate associated risks over the forecast period, with the benefits of technology adoption outweighing potential security concerns in the long run.
Decision Intelligence Market Ecosystem
The decision intelligence ecosystem is a dynamic and interconnected network of entities that collectively enable seamless communication between machines and devices through satellite networks. This ecosystem encompasses a diverse range of players, each contributing specialized services and solutions to facilitate efficient and global connectivity. The ecosystem of the decision intelligence include solution/services/platform providers, end users, and regulatory bodies.
By vertical, BFSI segment accounts for the largest market size during the forecast period.
The Banking, Financial Services, and Insurance (BFSI) sectors are experiencing significant growth in the decision intelligence market, driven by transformative technologies. Artificial Intelligence (AI) and Machine Learning (ML) algorithms are revolutionizing risk management, fraud detection, and customer insights, enhancing operational efficiencies and personalized services. Big Data analytics platforms handle massive datasets to extract valuable business intelligence, enabling data-driven decision-making across financial institutions. Moreover, adopting cloud computing infrastructure ensures scalable and cost-effective data processing, further fueling innovation and competitiveness in the BFSI sector's decision intelligence landscape.
By business functions, human resources segment is projected to grow at the highest CAGR during the forecast period.
Human Resources (HR) is experiencing substantial growth within the decision intelligence market due to advanced analytics, AI-driven tools, and predictive modeling. Organizations leverage HR data for talent acquisition, retention, and workforce optimization using machine learning algorithms. HR analytics enhances decision-making by providing insights into employee performance, engagement, and skill gaps. This data-driven approach enables companies to align HR strategies with business objectives, improve organizational effectiveness, and drive innovation. With the integration of big data technologies, HR professionals can harness real-time data streams for agile decision-making, fostering a competitive edge in talent management and organizational development within the evolving business landscape.
North America to account for the largest market size during the forecast period.
Key Market Players
The major decision intelligence solution and service providers include IBM (US), Oracle (US), Intel (US), Microsoft (US), Google (US), TCS (INDIA), DOMO (US), Board International (Switzerland), Provenir (New Jersey), Pyramid Analytics (Netherlands), 4CAST(Israel), H20.ai(CA), Remi.AI (Australia), Quantellia (US), Peak.AI (UK), DIWO(US), Cerebra (US), Clarifai (US), FLYR LABS(US), Metaphacts (Germany), Systems Technology Group (US), Paretos(Germany), Course5i(US), Telius (US), Evolution Analytics (US), HyperFinity (UK), Aera Technology (US), Quantexa (UK), Urbint(US), PlanningForce(Belgium), EY(UK). These companies have used both organic and inorganic growth strategies such as product launches, acquisitions, and partnerships to strengthen their position in the decision intelligence market.
Get online access to the report on the World's First Market Intelligence Cloud
- Easy to Download Historical Data & Forecast Numbers
- Company Analysis Dashboard for high growth potential opportunities
- Research Analyst Access for customization & queries
- Competitor Analysis with Interactive dashboard
- Latest News, Updates & Trend analysis
Request Sample Scope of the Report
Get online access to the report on the World's First Market Intelligence Cloud
- Easy to Download Historical Data & Forecast Numbers
- Company Analysis Dashboard for high growth potential opportunities
- Research Analyst Access for customization & queries
- Competitor Analysis with Interactive dashboard
- Latest News, Updates & Trend analysis
|
Report Metrics |
Details |
|
Market size available for years |
2019–2030 |
|
Base year considered |
2023 |
|
Forecast period |
2024–2030 |
|
Forecast units |
USD Billion |
|
Segments Covered |
Offering, Type, Business Function, Vertical, and Region. |
|
Geographies covered |
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America |
|
Companies covered |
IBM(US), Oracle (US), Google (US), Intel (US), Microsoft (US), TCS(INDIA), DOMO(US), Board International (Switzerland), Provenir (New Jersey), Pyramid Analytics (Netherlands), 4CAST(Israel), H20.ai(CA), Remi.AI (Australia), Quantellia (US), Peak.AI (UK), DIWO(US), Cerebra (US), Clarifai (US), FLYR LABS(US), Metaphacts (Germany), Systems Technology Group (US),paretos(Germany), Course5i(US), Telius (US), Evolution Analytics (US), HyperFinity (UK), Aera Technology (US), Quantexa (UK), Urbint(US), PlanningForce(Belgium), EY(UK) |
This research report categorizes the decision intelligence market based on Offerings, Type, Business Functions, Verticals, and Region.
Offering:
- Platform
-
Solution
-
By Integration Level
- Integrated Solutions
- Standalone Solutions
-
By Deployment Mode
- Cloud
- On-Premises
-
By Integration Level
-
Services
-
Professional Services
- Consulting
- Deployment & Integration
- System & Maintenance
- Managed Services
-
Professional Services
By Type:
- Decision automation
- Decision Augmentation
- Decision Support Systems (DSS)
By Organization Size:
- Marketing & Sales
- Finance & Accounting
- Human Resources
- Operations
- Research & Development
By Verticals:
- BFSI
- Retail and eCommerce
- Healthcare and Life Sciences
- Telecommunications
- Energy and Utilities
- Manufacturing
- Government
- Defense
- Others
By Region:
-
North America
- US
- Canada
-
Europe
- UK
- Germany
- France
- Italy
- Spain
- Rest of Europe
-
Asia Pacific
- China
- Japan
- India
- South Korea
- ANZ
- Rest of Asia Pacific
-
Middle East & Africa
- UAE
- Kingdom of Saudi Arabia
- Qatar
- Israel
- South Africa
- Rest of the Middle East & Africa
-
Latin America
- Brazil
- Mexico
- Argentina
- Rest of Latin America
Recent Developments:
- In February 2024, IBM Cloud Pak for Data version 4.8 introduced significant enhancements, offering faster access to distributed data sources, reduced ETL requests, and improved data cataloging capabilities. This update aimed to streamline data management processes, enhance productivity, and enable more efficient organizational decision-making leveraging the platform's features.
- In November 2023, Wonderbox Group collaborated with Board, an intelligent planning solutions provider, to improve sales forecasting and cost optimization. It aimed to streamline budgeting processes, manage P&L more effectively, and boost technical performance through agile and customized processes. With the Board's tools, they can unify data, collaborate efficiently, and make informed decisions for controlling costs.
- In November 2023, Provenir partnered with Tbi bank to enable real-time credit decisions at scale, showcasing the integration of decision intelligence into digital lending processes.
- In September 2023, The Oracle Cloud Infrastructure (OCI) Generative AI service developed, in collaboration with Cohere, enhanced decision intelligence by automating business processes, improving decision-making, and enhancing customer experiences. This service supported large language models (LLMs) to optimize end-to-end processes while ensuring data security and privacy, aligning with the principles of responsible AI deployment.
- In September 2022, Tata Consultancy Services (TCS) announced the latest release of its TCS Connected Intelligence Platform (CIP). The new release of CIP is a low-code decision intelligence platform designed to provide organizations with the next best actions for customers, employees, partners, and business processes in real-time. It offered a graphical, drag-and-drop interface for configuring the next best action strategies using business rules, segmentation, contextual data, and AI/ML models to accelerate the development and deployment of decision intelligence use cases. This update aimed to transform data into a strategic asset that delivers in-the-moment recommendations for informed and intelligent decisions across departments, value chains, and industries.
Frequently Asked Questions (FAQ):
What is Decision intelligence?
AI-based decision intelligence is a capability developed through human-technology collaboration and encompasses data science, Machine Learning (ML), and management decision-making. The decision-making is facilitated through the deployment of Artificial Intelligence (AI) (and its suite of technologies that includes ML, Natural Language Processing [NLP], and computer vision) and advanced analytics (predictive analytics and prescriptive analytics). It enables businesses to make informed decisions about their internal operations/strategic outcomes or resolutions provided to end users.
Which region is expected to hold the highest share in the decision intelligence market?
North America boasts the highest market share in the decision intelligence market due to several factors. Its robust economy, technologically advanced infrastructure, and favorable regulatory environment foster innovation and growth in decision intelligence.
Which are key verticals adopting decision intelligence platform, solutions and services?
Key end users adopting decision intelligence solutions and services include BFSI, retail & eCommerce, healthcare & life sciences, telecommunications, energy & utilities, manufacturing, government, defense, and other verticals (media & entertainment, travel & hospitality, and IT/ITeS).
Which are the key drivers supporting the market growth for decision intelligence market?
The key drivers supporting the market growth for decision intelligence include digital transformation that streamlines corporate lending through rapid tech adoption, customer demand that drives seamless decision intelligence development, and complex financial markets demanding robust risk management in lending platforms.
Who are the key vendors in the market for decision intelligence market?
The key vendors in the global decision intelligence market include IBM (US), Oracle (US), Intel (US), Microsoft (US), Google (US), TCS (INDIA), DOMO (US), Board International (Switzerland), Provenir (New Jersey), Pyramid Analytics (Netherlands), 4CAST(Israel), H20.ai(CA), Remi.AI (Australia), Quantellia (US), Peak.AI (UK), DIWO(US), Cerebra (US), Clarifai (US), FLYR LABS(US), Metaphacts (Germany), Systems Technology Group (US), Paretos(Germany), Course5i(US), Telius (US), Evolution Analytics (US), HyperFinity (UK), Aera Technology (US), Quantexa (UK), Urbint(US), PlanningForce(Belgium), EY(UK). .
To speak to our analyst for a discussion on the above findings, click Speak to Analyst
The research study for the decision intelligence market involved extensive secondary sources, directories, and several journals. Primary sources were mainly industry experts from the core and related industries, preferred decision intelligence solution providers, third-party service providers, consulting service providers, end users, and other commercial enterprises. In-depth interviews were conducted with various primary respondents, including key industry participants and subject matter experts, to obtain and verify critical qualitative and quantitative information, and assess the market’s prospects.
Secondary Research
The market size of companies offering decision intelligence platforms, solutions and services was arrived at based on secondary data available through paid and unpaid sources. It was also arrived at by analyzing the product portfolios of major companies and rating the companies based on their performance and quality.
In the secondary research process, various sources were referred to for identifying and collecting information for this study. Secondary sources included annual reports, press releases, and investor presentations of companies; white papers, journals, and certified publications; and articles from recognized authors, directories, and databases. The data was also collected from other secondary sources, such as journals, government websites, blogs, and vendor websites. Additionally, decision intelligence spending of various countries was extracted from the respective sources. Secondary research was mainly used to obtain key information related to the industry’s value chain and supply chain to identify key players based on platforms, solutions, services, market classification, and segmentation according to offerings of major players, industry trends related to solutions, platforms, services, types, business functions, verticals, and regions, and key developments from both market- and technology-oriented perspectives.
Primary Research
In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief Experience Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and decision intelligence expertise; related key executives from decision intelligence solution vendors, SIs, professional service providers, and industry associations; and key opinion leaders.
Primary interviews were conducted to gather insights, such as market statistics, revenue data collected from solutions and services, market breakups, market size estimations, market forecasts, and data triangulation. Primary research also helped understand various trends related to technologies, applications, deployments, and regions. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Strategy Officers (CSOs), and end users using decision intelligence, were interviewed to understand the buyer’s perspective on suppliers, products, service providers, and their current usage of decision intelligence platforms, solution and services which would impact the overall decision intelligence market.
The following is the breakup of primary profiles:
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
Multiple approaches were adopted for estimating and forecasting the decision intelligence market. The first approach involves estimating the market size by summation of companies’ revenue generated through the sale of platforms, solutions, and services.
Market Size Estimation Methodology-Top-down approach
In the top-down approach, an exhaustive list of all the vendors offering solutions and services in the decision intelligence market was prepared. The revenue contribution of the market vendors was estimated through annual reports, press releases, funding, investor presentations, paid databases, and primary interviews. Each vendor’s offerings were evaluated based on the breadth of offerings, types, business functions, verticals, and regions. The aggregate of all the companies’ revenue was extrapolated to reach the overall market size. Each subsegment was studied and analyzed for its global market size and regional penetration. The markets were triangulated through both primary and secondary research. The primary procedure included extensive interviews for key insights from industry leaders, such as CIOs, CEOs, VPs, directors, and marketing executives. The market numbers were further triangulated with the existing MarketsandMarkets repository for validation.
Market Size Estimation Methodology-Bottom-up approach
In the bottom-up approach, the adoption rate of decision intelligence offerings among different end users in key countries with respect to their regions contributing the most to the market share was identified. For cross-validation, the adoption of decision intelligence solutions and services among industries, along with different use cases with respect to their regions, was identified and extrapolated. Weightage was given to use cases identified in the different areas for the market size calculation.
Based on the market numbers, the regional split was determined by primary and secondary sources. The procedure included the analysis of the decision intelligence market’s regional penetration. Based on secondary research, the regional spending on Information and Communications Technology (ICT), socio-economic analysis of each country, strategic vendor analysis of major decision intelligence solution providers, and organic and inorganic business development activities of regional and global players were estimated. With the data triangulation procedure and data validation through primaries, the exact values of the overall decision intelligence market size and segments’ size were determined and confirmed using the study.
Top-down and Bottom-up approaches
To know about the assumptions considered for the study, Request for Free Sample Report
Data Triangulation
After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Market Definition
According to Peak.AI, decision intelligence is the commercial application of AI to the decision-making process of every area in a business. It is outcome-focused and delivers on commercial objectives. Organizations use decision intelligence to optimize every single department and improve business performance.
Stakeholders
- Decision Intelligence Platform Providers
- Independent Software Vendors (ISVs)
- Investors and Venture Capitalists (VCs)
- Managed Service Providers
- Support and Maintenance Service Providers
- System Integrators (SIs)/Migration Service Providers
- Value-added Resellers (VARs) and Distributors
Report Objectives
- To define, describe, and predict the decision intelligence market by offering, type, business functions, vertical, and region
- To provide detailed information about the major factors (drivers, restraints, opportunities, and challenges) influencing the market growth
- To analyze the opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments with respect to five main regions: North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
- To profile the key players and comprehensively analyze their market rankings and core competencies
- To analyze the competitive developments, such as partnerships, product launches, and mergers & acquisitions, in the decision intelligence market
Available Customizations
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
Product Analysis
- The product matrix provides a detailed comparison of the product portfolio of each company.
Geographic Analysis as per Feasibility
- Further breakup of the North American decision intelligence Market
- Further breakup of the European Market
- Further breakup of the Asia Pacific Market
- Further breakup of the Middle East & Africa Market
- Further breakup of the Latin American decision intelligence Market
Company Information
- Detailed analysis and profiling of additional market players (up to five)
Generating Response ...
Growth opportunities and latent adjacency in Decision Intelligence Market