Market Definition and Introduction
The Global AI in Tourism Market, valued at USD 3,373 million in 2024, is forecast to reach a monumental USD 432,339.66 million by 2035, expanding at a remarkable CAGR of 26.7% over the forecast period 2025-2035. With AI technologies that once appeared like future novelties-there is a paradigm shift taking place in the tourism industry. From dynamic pricing algorithm application changes for air ticketing strategy to AI-powered concierge services that provide hyper-personalized itineraries, the industry is reshaping customer engagement with the help of data-driven intelligence that redefines the efficiency of operations within organizations.
As global travel finally resumes its upward trajectory post-pandemic, AI plays a pivotal role in helping tourism enterprises understand demand, optimize resources, and elevate services. Being an international traveller, one could access AI-powered translation tools that would break linguistic barriers, while predictive analytics would help hotel providers to identify and anticipate needs for guests before checking in. Then there's some convergence between AI and these immersive technologies like augmented reality (AR) and virtual reality (VR), which are really enhancing destination marketing and pre-travel experience, such as allowing one to actually explore places before going there.
From a supply-side perspective, machine learning models and cloud-based AI platforms are being aggressively adopted by the stakeholders in the industry. Streamlined workflows help drive down operational costs and serve the global scaling of services. Travel technology organizations have developed AI-enabled chatbots and voice assistants to provide round-the-clock customer assistance. Moreover, transportation providers are embedding AI to manage their fleets, ensuring real-time tracking and maintenance. Heightened competition in the tourism ecosystem makes organizations realize that AI is not an optional enhancement-it's a strategic necessity for survival in the increasingly personalized and digitally-savvy market.
Recent Developments in the Industry
- In October 2024, IBM busted a move and entered into a partnership with Amadeus IT Group SA to further develop solutions for integrating critical IBM Watson Applications within global travel platforms and eventually lead the personalization of bookings and itinerary optimization for millions of travelers worldwide in real time.
- In August 2024, Google LLC launched a feature inside Google Maps that allows planning trips from an individual point of view based on past travel behavior and the Live location of activity with the input of creating really adaptive dynamic multi-stop itineraries.
- In June 2023, Microsoft Corporation introduced the artificial intelligence-powered carbon-emission monitoring sustainability dashboard for hotels and resorts, with which vacationers can benefit through eco-travel packages.
Market Dynamics
The rapid rise of artificial intelligence is becoming the traveler experience across the entire value chain.
The first adoption of AI into different tourism touchpoints-from booking to post-trip engagement, quickened. Now that the importance of AI to personalize smooth client experiences is acknowledged, businesses have begun implementing it. With machine learning algorithms, the travel provider can now predict guest preferences from historical behavior and thus maximize the upselling opportunities and satisfaction.
Strategic Investment in AI Infrastructure-Driving Market Growth
The investment in AI-powered tourism innovations sees considerable capital flow as companies are trying to find the competitive edge in an unprecedentedly fast-changing market. Heavyweights are now ploughing money into cloud infrastructure, AI analytics engines, and natural language processing tools to obtain real-time insights into customer behavior and operational metrics.
Shift Towards Automation and Contactless Solutions-Lessons Learned from the Pandemic
The pandemic brought such a change: it permanently modified traveler expectations. The accelerated adoption of contactless check-ins powered by AI, biometric verification in airports, and automated concierge services is in full swing. All are said to improve safety, operational efficiency, and a drop in labor overheads.
Automated Demand Forecasting Surged And AI-Powered Predictive Analytics
Predictive analytics are being applied by tourism operators to foresee shifts in demand and seasonality, to optimize pricing, and resource allocation. The empirical orientation helps businesses mitigate risks and respond quickly to market realities.
Attractive Opportunities in the Market
- Hyper-Personalized Travel Planning - AI algorithms delivering bespoke itineraries and tailored destination experiences.
- Smart Mobility Solutions - AI-powered fleet optimization and predictive maintenance for transport providers.
- AI in Destination Marketing - Immersive AR/VR tours boosting pre-travel engagement and conversion rates.
- Revenue Optimization - Dynamic pricing models for airlines and hotels, maximizing profitability.
- Sustainable Tourism Solutions - AI tools tracking and minimizing the environmental footprints of travel operators.
- Multilingual AI Support - Real-time translation services enhance global traveler accessibility.
- Autonomous Transportation - Self-driving shuttles and AI-assisted navigation are revolutionizing local transit.
- Travel Fraud Detection - Machine learning models preventing booking scams and payment fraud.
Report Segmentation
By Offering: Solution, Services
By End Use: Transportation & Mobility Services, Travel Technology Platforms & Solution Providers
By Region: North America (U.S., Canada, Mexico), Europe (UK, Germany, France, Spain, Italy, Spain, Rest of Europe), Asia-Pacific (China, India, Japan, Australia, South Korea, Rest of Asia-Pacific), LAMEA (Brazil, Argentina, UAE, Saudi Arabia (KSA), Africa Rest of Latin America)
Key Market Players: IBM Corporation, Google LLC, Microsoft Corporation, Amazon Web Services Inc., Salesforce Inc., Amadeus IT Group SA, SAP SE, Oracle Corporation, Sabre Corporation, Adobe Systems Inc.
Report Aspects
Base Year: 2024
Historic Years: 2022, 2023, 2024
Forecast Period: 2025-2035
Report Pages: 293
Dominating Segments
The service segment dominates the AI in tourism market as travel technology companies, consulting agencies, and service providers are specialized.
AI offers end-to-end solutions from AI integration to the deployment of predictive analytics that are highly needed by hospitality groups, airlines, and mobility providers, focusing on delivering personalized experiences even while managing complex digital infrastructures.
Solutions are rapidly becoming adopted as the travel trade deploys AI-powered platforms.
Segment is now witnessing exponential growth as tourism companies spend on AI software platforms, dynamic pricing engines, and chatbot solutions for customer engagement. These platforms empower real-time decision-making and operational efficiency for global travel networks looking to unify customer experiences across the various touchpoints.
Key Takeaways
- AI Transformation - Integration of AI across booking, travel, and post-trip phases redefining the tourism experience.
- Services Lead - Outsourced AI expertise dominates due to complex implementation requirements.
- Solutions Surge - Travel platforms adopt AI for operational optimization and customer engagement.
- Predictive Analytics Boom - Data-driven forecasting reshaping pricing and capacity planning.
- Immersive Tech Synergy - AI convergence with AR/VR enhancing destination marketing.
- Mobility Evolution - AI-driven transport solutions enhancing safety, reliability, and efficiency.
- Sustainable Travel Push - AI tools supporting carbon tracking and eco-friendly operations.
- Fraud Prevention Gains - Machine learning mitigating risks in digital travel transactions.
- APAC Growth - Rapid digitization and tourism recovery are boosting AI adoption.
- Regulatory Considerations - Data privacy and AI ethics shaping industry deployment strategies.
Regional Insights
North America Leads AI in Tourism Adoption Due to Strong Technology Ecosystem
North America occupies the leading position in the AI in tourism market, owing to an advanced technology infrastructure, very high consumer adoption rates, and the presence of major AI and travel technology companies. The U.S. thrives with a robust startup ecosystem for travel companies and giants and emerges as a hub of innovation for AI-influenced solutions for the hospitality and mobility sectors.
Europe Leverages AI for Sustainable and Cultural Tourism Experience Enhancement
Europe has plenty of market presence, such as in the UK, Germany, and France, where AI is readily applied to improve traveler experiences towards sustainable tourism. Because the continent boasts a rich cultural heritage and prides itself on being an eco-friendly travel destination, AI can meet the personalized itinerary-building needs and resource optimization.
Asia-Pacific Poised for Fastest Growth by Expanding Tourism Infrastructure and Government Support
Asia-Pacific is expected to register the highest growth rate during the forecast period because of increasing disposable incomes and huge investments in massive tourism infrastructure projects undertaken by governments that encourage the adoption of AI in travel. China, India, and Japan lead this growth as they undertake key investments in smart airports, AI-city tours, and multilingual digital assistance.
LATAM and MEA Slowly Engaging AI into Their Tourism Frameworks
Slowly but surely, Latin America and the Middle East & Africa are integrating AI into their tourism strategies, focused mainly on the security aspect, marketing outreach, and upgrading hospitality services. They are still at very early stages, but as AS tourism starts reviving and digital transformation hightens, there will surely be an increase in adoption rates.
Key Benefits for Stakeholders
- The report offers a quantitative assessment of market segments, emerging trends, projections, and market dynamics for the period 2024 to 2035.
- The report presents comprehensive market research, including insights into key growth drivers, challenges, and potential opportunities.
- Porter's Five Forces analysis evaluates the influence of buyers and suppliers, helping stakeholders make strategic, profit-driven decisions and strengthen their supplier-buyer relationships.
- A detailed examination of market segmentation helps identify existing and emerging opportunities.
- Key countries within each region are analysed based on their revenue contributions to the overall market.
- The positioning of market players enables effective benchmarking and provides clarity on their current standing within the industry.
- The report covers regional and global market trends, major players, key segments, application areas, and strategies for market expansion.
Chapter 1. Market Snapshot
1.1. Market Definition & Report Overview
1.2. Market Segmentation
1.3. Key Takeaways
1.3.1. Top Investment Pockets
1.3.2. Top Winning Strategies
1.3.3. Market Indicators Analysis
1.3.4. Top Impacting Factors
1.4. Industry Ecosystem Analysis
1.4.1. 360- Analysis
Chapter 2. Executive Summary
2.1. CEO/CXO Standpoint
2.2. Strategic Insights
2.3. ESG Analysis
2.4 Market Attractiveness Analysis
2.5.key Findings
Chapter 3. Research Methodology
3.1 Research Objective
3.2 Supply Side Analysis
3.2.1. Primary Research
3.2.2. Secondary Research
3.3 Demand Side Analysis
3.3.1. Primary Research
3.3.2. Secondary Research
3.4. Forecasting Models
3.4.1. Assumptions
3.4.2. Forecasts Parameters
3.5. Competitive breakdown
3.5.1. Market Positioning
3.5.2. Competitive Strength
3.6. Scope of the Study
3.6.1. Research Assumption
3.6.2. Inclusion & Exclusion
3.6.3. Limitations
Chapter 4. Industry Landscape
4.1. Market Dynamics
4.1.1. Drivers
4.1.2. Restraints
4.1.3. Opportunities
4.2. Porter's 5 Forces Model
4.2.1. Bargaining Power of Buyer
4.2.2. Bargaining Power of Supplier
4.2.3. Threat of New Entrants
4.2.4. Threat of Substitutes
4.2.5. Competitive Rivalry
4.3. Value Chain Analysis
4.4. PESTEL Analysis
4.5. Pricing Analysis and Trends
4.6. Key growth factors and trends analysis
4.7. Market Share Analysis (2025)
4.8. Top Winning Strategies (2025)
4.9. Trade Data Analysis (Import Export)
4.10. Regulatory Guidelines
4.11. Historical Data Analysis
4.12. Analyst Recommendation & Conclusion
Chapter 5. Global AI in Tourism Market Size & Forecasts by Offering 2025-2035
5.1. Market Overview
5.1.1. Market Size and Forecast By Offering 2025-2035
5.2. Solution
5.2.1. Market definition, current market trends, growth factors, and opportunities
5.2.2. Market size analysis, by region, 2025-2035
5.2.3. Market share analysis, by country, 2025-2035
5.3. Services
5.3.1. Market definition, current market trends, growth factors, and opportunities
5.3.2. Market size analysis, by region, 2025-2035
5.3.3. Market share analysis, by country, 2025-2035
Chapter 6. Global AI in Tourism Market Size & Forecasts by End Use 2025-2035
6.1. Market Overview
6.1.1. Market Size and Forecast By End Use 2025-2035
6.2. Transportation & Mobility Services
6.2.1. Market definition, current market trends, growth factors, and opportunities
6.2.2. Market size analysis, by region, 2025-2035
6.2.3. Market share analysis, by country, 2025-2035
6.3. Travel Technology Platforms & Solution Providers
6.3.1. Market definition, current market trends, growth factors, and opportunities
6.3.2. Market size analysis, by region, 2025-2035
6.3.3. Market share analysis, by country, 2025-2035
Chapter 7. Global AI in Tourism Market Size & Forecasts by Region 2025-2035
7.1. Regional Overview 2025-2035
7.2. Top Leading and Emerging Nations
7.3. North America AI in Tourism Market
7.3.1. U.S. AI in Tourism Market
7.3.1.1. By Offering breakdown size & forecasts, 2025-2035
7.3.1.2. By End Use breakdown size & forecasts, 2025-2035
7.3.2. Canada AI in Tourism Market
7.3.2.1. By Offering breakdown size & forecasts, 2025-2035
7.3.2.2. By End Use breakdown size & forecasts, 2025-2035
7.3.3. Mexico AI in Tourism Market
7.3.3.1. By Offering breakdown size & forecasts, 2025-2035
7.3.3.2. By End Use breakdown size & forecasts, 2025-2035
7.4. Europe AI in Tourism Market
7.4.1. UK AI in Tourism Market
7.4.1.1. By Offering breakdown size & forecasts, 2025-2035
7.4.1.2. By End Use breakdown size & forecasts, 2025-2035
7.4.2. Germany AI in Tourism Market
7.4.2.1. By Offering breakdown size & forecasts, 2025-2035
7.4.2.2. By End Use breakdown size & forecasts, 2025-2035
7.4.3. France AI in Tourism Market
7.4.3.1. By Offering breakdown size & forecasts, 2025-2035
7.4.3.2. By End Use breakdown size & forecasts, 2025-2035
7.4.4. Spain AI in Tourism Market
7.4.4.1. By Offering breakdown size & forecasts, 2025-2035
7.4.4.2. By End Use breakdown size & forecasts, 2025-2035
7.4.5. Italy AI in Tourism Market
7.4.5.1. By Offering breakdown size & forecasts, 2025-2035
7.4.5.2. By End Use breakdown size & forecasts, 2025-2035
7.4.6. Rest of Europe AI in Tourism Market
7.4.6.1. By Offering breakdown size & forecasts, 2025-2035
7.4.6.2. By End Use breakdown size & forecasts, 2025-2035
7.5. Asia Pacific AI in Tourism Market
7.5.1. China AI in Tourism Market
7.5.1.1. By Offering breakdown size & forecasts, 2025-2035
7.5.1.2. By End Use breakdown size & forecasts, 2025-2035
7.5.2. India AI in Tourism Market
7.5.2.1. By Offering breakdown size & forecasts, 2025-2035
7.5.2.2. By End Use breakdown size & forecasts, 2025-2035
7.5.3. Japan AI in Tourism Market
7.5.3.1. By Offering breakdown size & forecasts, 2025-2035
7.5.3.2. By End Use breakdown size & forecasts, 2025-2035
7.5.4. Australia AI in Tourism Market
7.5.4.1. By Offering breakdown size & forecasts, 2025-2035
7.5.4.2. By End Use breakdown size & forecasts, 2025-2035
7.5.5. South Korea AI in Tourism Market
7.5.5.1. By Offering breakdown size & forecasts, 2025-2035
7.5.5.2. By End Use breakdown size & forecasts, 2025-2035
7.5.6. Rest of APAC AI in Tourism Market
7.5.6.1. By Offering breakdown size & forecasts, 2025-2035
7.5.6.2. By End Use breakdown size & forecasts, 2025-2035
7.6. LAMEA AI in Tourism Market
7.6.1. Brazil AI in Tourism Market
7.6.1.1. By Offering breakdown size & forecasts, 2025-2035
7.6.1.2. By End Use breakdown size & forecasts, 2025-2035
7.6.2. Argentina AI in Tourism Market
7.6.2.1. By Offering breakdown size & forecasts, 2025-2035
7.6.2.2. By End Use breakdown size & forecasts, 2025-2035
7.6.3. UAE AI in Tourism Market
7.6.3.1. By Offering breakdown size & forecasts, 2025-2035
7.6.3.2. By End Use breakdown size & forecasts, 2025-2035
7.6.4. Saudi Arabia (KSA AI in Tourism Market
7.6.4.1. By Offering breakdown size & forecasts, 2025-2035
7.6.4.2. By End Use breakdown size & forecasts, 2025-2035
7.6.5. Africa AI in Tourism Market
7.6.5.1. By Offering breakdown size & forecasts, 2025-2035
7.6.5.2. By End Use breakdown size & forecasts, 2025-2035
7.6.6. Rest of LAMEA AI in Tourism Market
7.6.6.1. By Offering breakdown size & forecasts, 2025-2035
7.6.6.2. By End Use breakdown size & forecasts, 2025-2035
Chapter 8. Company Profiles
8.1. Top Market Strategies
8.2. Company Profiles
8.2.1. IBM Corporation
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.2. Google LLC
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.3. Microsoft Corporation
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.4. Amazon Web Services Inc.
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.5. Salesforce Inc.
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.6. Amadeus IT Group SA
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.7. SAP SE
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.8. Oracle Corporation
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.9. Sabre Corporation
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
8.2.10. Adobe Systems Inc.
8.2.1.1. Company Overview
8.2.1.2. Key Executives
8.2.1.3. Company Snapshot
8.2.1.4. Financial Performance
8.2.1.5. Product/Services Port
8.2.1.6. Recent Development
8.2.1.7. Market Strategies
8.2.1.8. SWOT Analysis
Research Methodology
Kaiso Research and Consulting follows an independent approach in making estimations to provide unbiased business intelligence. Our studies are not limited to secondary research alone but are built on a balanced blend of primary research, surveys, and secondary sources. This methodology enables us to develop a comprehensive 360-degree understanding of the industry and market landscape.
Supply and Demand Dynamics:
A. Supply Side Analysis:
We begin by assessing how suppliers contribute to overall market revenue growth. Our research then delves into their product portfolios, geographical reach, core focus areas, and key strategic initiatives. As most of our reports are based on a top-down approach, we begin by conducting interviews across the value chain. In the first round, we engage with manufacturers and companies, speaking with professionals from supply chain management, production, and sales. These discussions allow us to gather detailed insights into revenue generation, measured in millions or billions, segmented by type, platform, end-user, region, and other key parameters. This helps identify how companies are driving their products into mainstream markets and influencing the overall industry structure.
As the final step, we conduct a Pareto analysis to evaluate market fragmentation and identify the key players influencing industry structure. On the supply side, we evaluate how industry players contribute to overall market growth and revenue generation.
This includes an in-depth review of:
- Product Offerings β range, categories, and applications covered.
- Geographical Presence β regions of operation and market penetration.
- Strategic Initiatives β new product development, product launches, distribution channel strategies, and key application areas.
B. Demand Side Analysis:
Once supply dynamics are assessed, we then examine demand-side factors shaping the market. This involves mapping demand across applications, geographies, and end-user groups. On the demand side, we conduct interviews with a network of distributors from the organised market to gain a deeper understanding of demand dynamics. This analysis covers revenue generation segmented by type, platform, end-user, and region.
Each subsegment is interconnected to understand patterns in:
- Revenue contribution
- Growth rate
- Adoption levels
By aggregating demand from all subsegments, we estimate the magnitude of market-driving forces. Comparing supply and demand enables us to forecast how these dynamics influence future market behaviour.
Forecast Model (Proprietary Kaiso Engine):
Building on quantitative rigor, Kaiso integrates a Forecast Model that blends statistical precision with strategic scenario planning. Unlike generic projections, this model adapts dynamically to evolving market signals.
Our proprietary forecast engine incorporates the following layers:
- Baseline Projection: Derived using historical patterns, econometric baselines, and validated macroeconomic inputs.
- Scenario Forecasting: Optimistic, conservative, and base-case outlooks built with dynamic weighting of influencing variables (e.g., policy shifts, raw material volatility, supply chain disruptions).
- AI-Augmented Predictive Analytics: Machine learning algorithms detect emerging weak signals, nonlinear patterns, and correlation anomalies that standard models may overlook.
- Sector-Specific Modules: Tailored sub-models for fast-evolving industries (e.g., clean energy adoption curves, healthcare regulatory cycles, AI penetration trends).
- Resilience Testing: Shock modeling to evaluate market response under βblack swanβ or disruption scenarios such as pandemics, trade wars, or technology breakthroughs.
Deliverable outcomes of our Forecast Model:
- Granular projections by region, segment, and application (up to 2035)
- Sensitivity-rank matrices highlighting critical drivers and risks
- Dynamic update capability, ensuring forecasts remain current with real-time data
This ensures that our clients donβt just see where the market is heading, but also how robust that trajectory is under different conditions.
Approach & Methodology
At Kaiso Research and Consulting, we adopt an independent, data-driven approach to ensure objective and unbiased insights. Our methodology blends primary research, secondary research, and survey-based validation, giving us a 360Β° market perspective.
Research Phase
| Description
| Key Activities
|
|---|
Secondary Research | Gathering qualitative insights from a variety of credible sources. | Analysis of blogs, articles, presentations, interviews, annual reports, and premium databases such as Hoovers, Factiva, Bloomberg. |
Primary Research Phase 1: CXO Perspective | Interviews with top-level executives to collect strategic insights on trends and market drivers. | Discussions with CEOs, CXOs, industry leaders; interpretation of executive viewpoints. |
Primary Research Phase 2: Quantitative Data Generation | Data collection from key stakeholders along the value chain, segmented by supply and demand. | Step 1: Interviews with manufacturers and supply chain personnel to gauge revenue metrics. Step 2: Interviews with distributors to assess demand-side revenues. |
Primary Research Phase 3: Validation | Ground-level survey research for real-world data validation across the value chain. | Collaboration with local survey companies; engagement with manufacturers, wholesalers, retailers, and end-users. |
On average, for each market:
- 45 primary interviews are conducted covering the entire value chain.
- Interviews last approximately 28 minutes each, including a mix of face-to-face and online formats.
This rigorous methodology guarantees realistic, credible, and unbiased market analysis.
Key Player Positioning
We assess key companies on two major dimensions:
Market Positioning: measured through revenue, growth rate, geographical reach, customer base, strategies implemented, and focus areas.
Competitive Strength: evaluated through product portfolio, R&D investment, innovation, new product introductions, and overall competitiveness.
Conclusion
Our comprehensive methodology enables us to deliver high-quality, objective, and actionable market intelligence. By balancing both supply and demand perspectives, Kaiso Research and Consulting has established itself as a trusted and recognised brand in the research and consulting landscape.