AI in IoT Market Size, Share & Growth Forecast by 2033

Research Methodology – AI in IoT Market

At Straits Research, we adopt a rigorous 360° research approach that integrates both primary and secondary research methodologies. This ensures accuracy, reliability, and actionable insights for stakeholders. Our methodology for the AI in IoT Market comprises the following key stages:

Market Indicator & Macro-Factor Analysis

Our baseline thesis for the AI in IoT Market is developed by integrating key market indicators and macroeconomic variables. These include:

1 Factors considered while calculating market size and share

The number of IoT devices in use that are capable of incorporating AI technology.
Current and projected market spending on AI and IoT technologies.
Number of businesses or industries that are likely to implement AI in IoT applications.
The rate of AI technological advancement and its application in IoT.
The level of global and regional adoption of AI in IoT technology.
Revenue generated from AI in the IoT market.

2 Key Market Indicators

AI in IoT market trend figures and forecasts.
Funding or investment in AI in IoT startups and existing companies.
Development and adoption rates of AI and IoT technologies.
The number of patents related to AI in IoT.
Increasing industrial demand for AI applications in IoT systems.
Market economics such as pricing structures and cost analysis of AI in IoT technologies.

3 Growth Trends

Increased adoption of AI technologies in IoT security solutions.
Growth in autonomous vehicles requiring AI in IoT.
Increase in the demand for smart homes and smart cities driving AI in IoT market growth.
AI integration in IoT for personalized advertising and marketing.
Greater use of AI in IoT for effective data management and analytics.
Healthcare industry's increasing adoption of AI in IoT for remote patient monitoring.

Secondary Research

Our secondary research forms the foundation of market understanding and scope definition. We collect and analyze information from multiple reliable sources to map the overall ecosystem of the AI in IoT Market. Key inputs include:

Company-Level Information

Annual reports, investor presentations, SEC filings
Company press releases and product launch announcements
Public executive interviews and earnings calls
Strategy briefings and M&A updates

Industry and Government Sources

Country-level industry associations and trade bodies
Government dossiers, policy frameworks, and official releases
Whitepapers, working papers, and public R&D initiatives
Relevant Associations for the AI in IoT Market

Market Intelligence Sources

Broker reports and financial analyst coverage
Paid databases (Hoovers, Factiva, Refinitiv, Reuters, Statista, etc.)
Import/export trade data and tariff databases
Sector-specific journals, magazines, and news portals

Macro & Consumer Insights

Global macroeconomic indicators and their cascading effect on the industry
Demand–supply outlook and value chain analysis
Consumer behaviour, adoption rates, and commercialization trends

Primary Research

To validate and enrich our secondary findings, we conduct extensive primary research with industry stakeholders across the value chain. This ensures we capture both qualitative insights and quantitative validation. Our primary research includes:

Expert Insights & KOL Engagements

Key Opinion Leader (KOL) Engagements
Structured interviews with executives, product managers, and domain experts
Paid and barter-based interviews across manufacturers, distributors, and end-users

Focused Discussions & Panels

Discussions with stakeholders to validate demand-supply gaps
Group discussions on emerging technologies, regulatory shifts, and adoption barriers

Data Validation & Business POV

Cross-verification of market sizing and forecasts with industry insiders
Capturing business perspectives on growth opportunities and restraints

Data Triangulation & Forecasting

The final step of our research involves data triangulation ensuring accuracy through cross-verification of:

Demand-side analysis (consumption patterns, adoption trends, customer spending)
Supply-side analysis (production, capacity, distribution, and market availability)
Macroeconomic & microeconomic impact factors

Forecasting is carried out using proprietary models that combine: