Multimodal BI Assistant Global Market Report 2026

Multimodal business intelligence (BI) assistants are AI-powered analytics tools that allow users to interact with business data using multiple input and output modes, such as text, voice, visuals, and charts. They combine natural language processing, data analytics, and visualization to provide insights from both structured and unstructured data sources. They simplify data analysis, improve insight accessibility, and enable faster, more informed business decision-making.

The primary components of multimodal business intelligence assistants include software, hardware, and services. Software refers to tools that enable organizations to analyze, visualize, and interact with business information using multiple input methods such as text, voice, and images, supporting informed decision-making. These solutions are implemented through on-premises and cloud-based models based on infrastructure and operational needs and are adopted by small and medium enterprises as well as large organizations. The applications involved include data visualization, natural language queries, predictive analytics, reporting, and other uses. The end users of multimodal business intelligence assistant solutions include banking, financial services, and insurance firms, healthcare providers, retail and e-commerce businesses, information technology and telecommunications companies, manufacturing organizations, and other users relying on business intelligence for strategic planning.

Tariffs on servers, analytics hardware, and imported computing infrastructure are indirectly impacting the multimodal BI assistant market by raising deployment and hosting costs. Hardware and on premises deployment segments are more affected than cloud native software layers. Regions dependent on imported high performance servers and storage systems face higher total solution costs. These pressures can slow large scale enterprise rollouts in cost sensitive markets. However, tariffs are also accelerating migration toward cloud based and software first BI assistant platforms that reduce hardware dependency.

The multimodal bi assistant market research report is one of a series of new reports from The Business Research Company that provides multimodal bi assistant market statistics, including multimodal bi assistant industry global market size, regional shares, competitors with a multimodal bi assistant market share, detailed multimodal bi assistant market segments, market trends and opportunities, and any further data you may need to thrive in the multimodal bi assistant industry. This multimodal bi assistant market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The multimodal bi assistant market size has grown exponentially in recent years. It will grow from $3.94 billion in 2025 to $4.99 billion in 2026 at a compound annual growth rate (CAGR) of 26.7%. The growth in the historic period can be attributed to growth of self service bi tools, rising enterprise data volumes, dashboard centric reporting culture, expansion of cloud analytics platforms, demand for faster business insights.

The multimodal bi assistant market size is expected to see exponential growth in the next few years. It will grow to $12.98 billion in 2030 at a compound annual growth rate (CAGR) of 27.0%. The growth in the forecast period can be attributed to increase in conversational analytics adoption, rising non technical data users, demand for real time decision support, integration with enterprise AI copilots, growth of multimodal data interfaces. Major trends in the forecast period include voice driven analytics interfaces, natural language dashboard generation, conversational bi query systems, cross modal insight visualization, embedded AI insight assistants.

The expanding volume of unstructured data is expected to accelerate the growth of the multimodal BI assistant market in the future. Unstructured data refers to information that lacks a predefined data model or organized format, making it challenging to store, process, and analyze using traditional databases. The rise in unstructured data volume is largely attributed to social media platforms, which generate vast amounts of diverse content such as text posts, images, videos, and comments without a fixed structure. Multimodal BI assistants help extract insights from unstructured data by efficiently analyzing text, images, and other formats, converting them into actionable business intelligence. For example, in 2025, according to the Global Skill Development Council (GSDC), a US-based independent, vendor-neutral organization, the total volume of data generated globally is projected to reach 182 zettabytes, increasing from 120 zettabytes in 2023. Therefore, the growing volume of unstructured data is fueling the growth of the multimodal BI assistant market.

The increasing adoption of cloud-based analytics platforms is expected to drive the growth of the multimodal BI assistant market going forward. Cloud-based analytics platforms refer to software solutions hosted in the cloud that allow organizations to collect, store, process, and analyze data in real time without relying on on-premises infrastructure. The growing adoption of cloud-based analytics platforms is mainly driven by the need for scalable, cost-efficient, and flexible data solutions capable of handling expanding data volumes and supporting evolving business requirements. Cloud-based analytics platforms support multimodal BI assistants by delivering scalable real-time data processing and storage, enabling seamless integration of structured and unstructured data from multiple sources for faster and more accurate insights. For instance, in April 2025, according to the American Bar Association, a US-based professional organization, around 75% of attorneys reported using cloud computing for work-related tasks, up from 69% in 2023 and approximately 70% in 2022. Therefore, the rising adoption of cloud-based analytics platforms is driving the growth of the multimodal BI assistant market.

The increasing use of artificial intelligence across enterprises is anticipated to drive expansion in the multimodal BI assistant market in the coming years. Artificial intelligence refers to a field of computer science that enables machines to perform human-like tasks including learning, reasoning, problem solving, perception, and decision-making. The growing adoption of AI is driven by its ability to rapidly process massive datasets, detect patterns, and deliver actionable insights that enhance operational efficiency and business outcomes. AI enables multimodal BI assistants to analyze, interpret, and generate insights from multiple data formats such as text, images, and videos, supporting faster and more informed decision-making. For example, in September 2025, Netguru S.A., a Poland-based software development firm, reported that IT and telecommunications organizations achieved an AI adoption rate of 38% in 2025. As a result, increasing enterprise AI adoption is contributing to the growth of the multimodal BI assistant market.

Major companies operating in the multimodal bi assistant market are Google LLC, Oracle Corporation, Salesforce Inc., Microsoft Corporation, SAP SE, Snowflake Inc., International Business Machines Corporation, MicroStrategy Incorporated, Hex Technologies, Alteryx Incorporated, Zoho Corporation, Databricks Inc., Tableau Software LLC, QlikTech International AB, Domo Incorporated, Sisense Inc., ThoughtSpot Inc., Sigma Computing Inc., GoodData Corporation, Yellowfin International Pty Ltd, Mode Analytics Inc., Tellius Inc., and TIBCO Software Inc.

North America was the largest region in the multimodal BI assistant market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the multimodal bi assistant market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the multimodal bi assistant market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The multimodal business intelligence (BI) assistant market consists of revenues earned by entities by providing services such as natural language query processing, voice-enabled analytics, dashboard generation, data integration and preparation, real-time insight delivery, and decision support services. The market value includes the value of related goods sold by the service provider or included within the service offering. The multimodal business intelligence (BI) assistant market also includes sales of AI-powered analytics tools, voice-enabled BI applications, data visualization modules, multimodal user interfaces, and API-based BI integration products. Values in this market are 'factory gate' values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Multimodal BI Assistant Market Global Report 2026 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses multimodal bi assistant market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for multimodal bi assistant ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The multimodal bi assistant market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

• The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
• The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
• The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
• The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
• The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
• The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
• The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
• The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
• Market segmentations break down the market into sub markets.
• The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
• Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
• The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
• The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.

Scope

• Markets Covered:1) By Component: Software; Hardware; Services
• 2) By Deployment Mode: On-Premises; Cloud
• 3) By Enterprise Size: Small And Medium Enterprises; Large Enterprises
• 4) By Application: Data Visualization; Natural Language Query; Predictive Analytics; Reporting; Other Applications
• 5) By End-User: Banking, Financial Services, And Insurance (BFSI); Healthcare; Retail And E-Commerce; Information Technology (IT) And Telecommunications; Manufacturing; Other End-Users
• Subsegments:
• 1) By Software: Data Analytics And Visualization Software; Natural Language Processing Software; Business Intelligence Dashboard Software; Report Generation And Automation Software; Application Programming Interface Integration Software
• 2) By Hardware: High Performance Computing Servers; Data Storage And Memory Systems; Edge Processing Devices; Networking And Connectivity Equipment; On-Premises Deployment Infrastructure
• 3) By Services: Platform Integration And Deployment Services; Model Training And Customization Services; Maintenance And Support Services; Managed Platform Services; Consulting And Advisory Services
• Companies Mentioned: Google LLC; Oracle Corporation; Salesforce Inc.; Microsoft Corporation; SAP SE; Snowflake Inc.; International Business Machines Corporation; MicroStrategy Incorporated; Hex Technologies; Alteryx Incorporated; Zoho Corporation; Databricks Inc.; Tableau Software LLC; QlikTech International AB; Domo Incorporated; Sisense Inc.; ThoughtSpot Inc.; Sigma Computing Inc.; GoodData Corporation; Yellowfin International Pty Ltd; Mode Analytics Inc.; Tellius Inc.; and TIBCO Software Inc.
• Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain
• Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
• Time Series: Five years historic and ten years forecast.
• Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
• Data Segmentations: country and regional historic and forecast data, market share of competitors, market segments.
• Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
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