Mercado de aprendizaje automático: mapeo competitivo y perspectivas estratégicas para 2031

  • Report Code : TIPTE100000804
  • Category : Technology, Media and Telecommunications
  • Status : Published
  • No. of Pages : 221
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Se espera que el mercado del aprendizaje automático crezca de 1.582,9 millones de dólares en 2017 a 39.986,7 millones de dólares en 2025; se estima que crecerá a una tasa compuesta anual del 49,7% entre 2017 y 2025.

La disponibilidad de una gran cantidad de datos se atribuye al crecimiento del mercado. La disponibilidad de cantidades masivas de datos de diferentes fuentes es una de las razones clave que ha impulsado el crecimiento de la tecnología de aprendizaje automático. Este enorme aumento en la cantidad de datos que crece exponencialmente año tras año se debe a la proliferación de sensores que miden una gran cantidad de datos en diferentes parámetros. De manera similar, con el avance de la IoT, que permitió la conectividad a Internet a una amplia gama de dispositivos con tecnología integrada para comunicarse e interactuar con el entorno externo, los dispositivos conectados están aumentando exponencialmente. Estos dispositivos conectados se comunican y generan continuamente una enorme cantidad de datos cada segundo.


Además, con el avance de la tecnología informática y de almacenamiento, la potencia informática se ha multiplicado durante la última década. Esto ha creado nuevas capacidades para gestionar y computar grandes conjuntos de datos y, cuando se combina con la tecnología de aprendizaje automático, ha brindado los mejores conocimientos a las empresas.

regiones lucrativas en la máquina Mercado del aprendizaje

Perspectivas del mercado: mercado del aprendizaje automático

Adopción de la automatización de procesos robóticos< /h3>

La creciente demanda de aprendizaje automático está alineada con la progresión del mercado global de (RPA). Esto se debe principalmente a que se prevé que RPA, junto con otros disruptores digitales que incluyen mano de obra digital y automatización de software avanzado, impulsen significativamente la nueva generación de instalaciones basadas en la nube que ofrecen fuerza laboral virtual. Además, también se espera que el aprendizaje automático habilitado por RPA lleve los servicios empresariales a la eliminación de la mano de obra en las grandes empresas. escalar y compartir: reducción de mano de obra a escala, acompañada de una reducción sustancial de costos.

Información basada en soluciones

Basado en la solución, el mercado del aprendizaje automático se segmenta en servicios de software. El segmento de software tuvo la mayor cuota de mercado en 2016.

Información estratégica

Los actores que operan en el mercado del aprendizaje automático se centran principalmente en el desarrollo de productos avanzados y eficientes.

  • En 2017, Amazon Web Services lanzó una nueva región AWS UE (París). Esto permite a los usuarios ejecutar las aplicaciones y almacenar contenidos en centros de datos disponibles en Francia. AWS también tiene 49 zonas de disponibilidad en sus 18 regiones de infraestructura tecnológica.
  • En 2017, FICO se alió con UBS Card Center (Suiza) para detener el fraude con la ayuda de la inteligencia artificial y el aprendizaje automático. El desafío se resolvió con la ayuda de FICO Falcon Platform, que es la solución líder contra el fraude con tarjetas al proteger 2,6 mil millones de tarjetas de pago.

El mercado del aprendizaje automático se ha segmentado de la siguiente manera:

Mercado de aprendizaje automático:

Mercado de aprendizaje automático: por solución

  • Software
  • Servicios

Mercado de aprendizaje automático: por tipo de implementación                                             

  • Nube/MLaaS
  • On-Premises

Mercado de aprendizaje automático: por el usuario final    

  • BFSI
    • Fraude y fraude Gestión de riesgos
    • Análisis predictivo de clientes
    • Comercio con algoritmos
    • Otros
  • Comercio minorista
    • Experiencia del cliente y experiencia Insight
    • Suministro y distribución Planificación de la demanda
    • Otros
  • Atención sanitaria
    • Sistemas de diagnóstico y tratamiento
    • Análisis de imágenes y análisis de imágenes Diagnóstico
    • Otros
  • Fabricación
    • Mantenimiento predictivo
    • Gestión de la cadena de suministro
    Europa
    • Francia
    • Alemania
    • Italia
    • España
    • Reino Unido
  • Asia Pacífico (APAC)
    • Japón
    • China
    • Australia
    • India
  • H2O.ai
  • Hewlett Packard Enterprise
  • IBM Corporation
  • Microsoft Corporation
  • SAP SE
  • Instituto SAS Inc.
Report Coverage
Report Coverage

Revenue forecast, Company Analysis, Industry landscape, Growth factors, and Trends

Segment Covered
Segment Covered

This text is related
to segments covered.

Regional Scope
Regional Scope

North America, Europe, Asia Pacific, Middle East & Africa, South & Central America

Country Scope
Country Scope

This text is related
to country scope.

The List of Companies - Machine Learning Market

1. Amazon Web Services, Inc.
2. Fair Isaac Corporation
3. Google, Inc.
4. Hewlett Packard Enterprise
5. IBM Corporation
6. Microsoft Corporation
7. SAP SE
8. BigML, Inc.
9. H2O.ai
10. SAS Institute Inc.

The Insight Partners performs research in 4 major stages: Data Collection & Secondary Research, Primary Research, Data Analysis and Data Triangulation & Final Review.

  1. Data Collection and Secondary Research:

As a market research and consulting firm operating from a decade, we have published and advised several client across the globe. First step for any study will start with an assessment of currently available data and insights from existing reports. Further, historical and current market information is collected from Investor Presentations, Annual Reports, SEC Filings, etc., and other information related to company’s performance and market positioning are gathered from Paid Databases (Factiva, Hoovers, and Reuters) and various other publications available in public domain.

Several associations trade associates, technical forums, institutes, societies and organization are accessed to gain technical as well as market related insights through their publications such as research papers, blogs and press releases related to the studies are referred to get cues about the market. Further, white papers, journals, magazines, and other news articles published in last 3 years are scrutinized and analyzed to understand the current market trends.

  1. Primary Research:

The primarily interview analysis comprise of data obtained from industry participants interview and answers to survey questions gathered by in-house primary team.

For primary research, interviews are conducted with industry experts/CEOs/Marketing Managers/VPs/Subject Matter Experts from both demand and supply side to get a 360-degree view of the market. The primary team conducts several interviews based on the complexity of the markets to understand the various market trends and dynamics which makes research more credible and precise.

A typical research interview fulfils the following functions:

  • Provides first-hand information on the market size, market trends, growth trends, competitive landscape, and outlook
  • Validates and strengthens in-house secondary research findings
  • Develops the analysis team’s expertise and market understanding

Primary research involves email interactions and telephone interviews for each market, category, segment, and sub-segment across geographies. The participants who typically take part in such a process include, but are not limited to:

  • Industry participants: VPs, business development managers, market intelligence managers and national sales managers
  • Outside experts: Valuation experts, research analysts and key opinion leaders specializing in the electronics and semiconductor industry.

Below is the breakup of our primary respondents by company, designation, and region:

Research Methodology

Once we receive the confirmation from primary research sources or primary respondents, we finalize the base year market estimation and forecast the data as per the macroeconomic and microeconomic factors assessed during data collection.

  1. Data Analysis:

Once data is validated through both secondary as well as primary respondents, we finalize the market estimations by hypothesis formulation and factor analysis at regional and country level.

  • Macro-Economic Factor Analysis:

We analyse macroeconomic indicators such the gross domestic product (GDP), increase in the demand for goods and services across industries, technological advancement, regional economic growth, governmental policies, the influence of COVID-19, PEST analysis, and other aspects. This analysis aids in setting benchmarks for various nations/regions and approximating market splits. Additionally, the general trend of the aforementioned components aid in determining the market's development possibilities.

  • Country Level Data:

Various factors that are especially aligned to the country are taken into account to determine the market size for a certain area and country, including the presence of vendors, such as headquarters and offices, the country's GDP, demand patterns, and industry growth. To comprehend the market dynamics for the nation, a number of growth variables, inhibitors, application areas, and current market trends are researched. The aforementioned elements aid in determining the country's overall market's growth potential.

  • Company Profile:

The “Table of Contents” is formulated by listing and analyzing more than 25 - 30 companies operating in the market ecosystem across geographies. However, we profile only 10 companies as a standard practice in our syndicate reports. These 10 companies comprise leading, emerging, and regional players. Nonetheless, our analysis is not restricted to the 10 listed companies, we also analyze other companies present in the market to develop a holistic view and understand the prevailing trends. The “Company Profiles” section in the report covers key facts, business description, products & services, financial information, SWOT analysis, and key developments. The financial information presented is extracted from the annual reports and official documents of the publicly listed companies. Upon collecting the information for the sections of respective companies, we verify them via various primary sources and then compile the data in respective company profiles. The company level information helps us in deriving the base number as well as in forecasting the market size.

  • Developing Base Number:

Aggregation of sales statistics (2020-2022) and macro-economic factor, and other secondary and primary research insights are utilized to arrive at base number and related market shares for 2022. The data gaps are identified in this step and relevant market data is analyzed, collected from paid primary interviews or databases. On finalizing the base year market size, forecasts are developed on the basis of macro-economic, industry and market growth factors and company level analysis.

  1. Data Triangulation and Final Review:

The market findings and base year market size calculations are validated from supply as well as demand side. Demand side validations are based on macro-economic factor analysis and benchmarks for respective regions and countries. In case of supply side validations, revenues of major companies are estimated (in case not available) based on industry benchmark, approximate number of employees, product portfolio, and primary interviews revenues are gathered. Further revenue from target product/service segment is assessed to avoid overshooting of market statistics. In case of heavy deviations between supply and demand side values, all thes steps are repeated to achieve synchronization.

We follow an iterative model, wherein we share our research findings with Subject Matter Experts (SME’s) and Key Opinion Leaders (KOLs) until consensus view of the market is not formulated – this model negates any drastic deviation in the opinions of experts. Only validated and universally acceptable research findings are quoted in our reports.

We have important check points that we use to validate our research findings – which we call – data triangulation, where we validate the information, we generate from secondary sources with primary interviews and then we re-validate with our internal data bases and Subject matter experts. This comprehensive model enables us to deliver high quality, reliable data in shortest possible time.

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