Explainable AI Market to Grow with a CAGR of 22.4% Globally through to 2028
Global Explainable AI Market is rising due to
increasing demand for transparency and interpretability in AI systems, enabling
better decision-making and regulatory compliance in the forecast period
2024-2028.
According to TechSci Research report, “Global Explainable
AI Market - Industry Size, Share, Trends, Competition Forecast &
Opportunities, 2028”, Global Explainable AI Market has valued at USD 5.4
Billion in 2022 and is anticipated to project robust growth in the forecast
period with a CAGR of 22.4% through 2028. The Global Explainable AI (XAI)
Market is experiencing significant growth as organizations increasingly adopt
artificial intelligence solutions across various industries. XAI refers to the
capability of AI systems to provide understandable and interpretable
explanations for their decisions and actions, addressing the "black
box" challenge of traditional AI. The market is poised for expansion,
driven by the growing need for transparency, accountability, and ethical AI
deployment. XAI is vital in sectors such as finance, healthcare, and autonomous
vehicles, where the ability to understand AI-generated decisions is crucial for
regulatory compliance and user trust. Additionally, the rise of AI-related
regulations and guidelines further propels the demand for XAI solutions. The
market is characterized by innovations in machine learning techniques,
algorithms, and model architectures that enhance the interpretability of AI
systems. As businesses prioritize responsible AI practices, the Explainable AI
Market is set to continue its growth trajectory, offering solutions that not
only deliver AI-driven insights but also ensure transparency and human-centric
AI decision-making processes.
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The global explainable AI market has witnessed
significant growth in recent years, driven by the increasing demand for
transparency and interpretability in AI systems. Explainable AI refers to the
ability of an AI system to provide clear and understandable explanations for
its decisions and actions. This is particularly important in industries such as
finance, healthcare, and legal, where the decisions made by AI systems can have
a profound impact on individuals and society. One of the key drivers of the
explainable AI market is the growing concern over the "black box"
nature of AI systems. Traditional AI models, such as deep learning neural
networks, are often considered to be black boxes because they make decisions based
on complex algorithms that are difficult to interpret. This lack of
transparency has raised concerns about bias, discrimination, and the potential
for AI systems to make incorrect or unfair decisions. To address these
concerns, there has been a growing demand for explainable AI solutions that can
provide clear and understandable explanations for their decisions. These
solutions use techniques such as rule-based systems, symbolic reasoning, and
natural language processing to generate explanations that can be easily
understood by humans. By providing explanations, these AI systems can help
build trust and confidence in their decision-making processes.
The financial industry has been one of the early
adopters of explainable AI solutions. Banks and financial institutions are
using these systems to improve risk assessment, fraud detection, and compliance
monitoring. By providing clear explanations for their decisions, these AI
systems can help financial institutions comply with regulatory requirements and
provide better transparency to their customers. In the healthcare sector,
explainable AI is being used to improve diagnosis and treatment decisions. AI
systems can analyze large amounts of patient data and provide recommendations
for personalized treatment plans. By providing explanations for their
recommendations, these systems can help doctors and healthcare professionals
understand the reasoning behind the AI's decisions and make more informed
decisions.
The legal industry is also embracing explainable AI to
improve legal research and decision-making. AI systems can analyze vast amounts
of legal documents and provide insights and recommendations for legal
professionals. By providing explanations for their recommendations, these
systems can help lawyers understand the legal reasoning behind the AI's
suggestions and make more accurate and informed decisions. The global
explainable AI market is expected to continue its growth trajectory in the
coming years. The increasing adoption of AI across various industries, coupled
with the growing demand for transparency and interpretability, will drive the
market's expansion. However, challenges such as the complexity of AI algorithms
and the need for robust explain ability techniques will need to be addressed to
fully realize the potential of explainable AI.
In conclusion, the global explainable AI market is
witnessing significant growth as industries recognize the importance of
transparency and interpretability in AI systems. The demand for explainable AI
solutions is driven by concerns over bias, discrimination, and the need for
trust and confidence in AI decision-making. Industries such as finance,
healthcare, and legal are early adopters of explainable AI, using it to improve
risk assessment, diagnosis, treatment decisions, legal research, and
decision-making. The market is expected to continue growing as AI adoption
increases, but challenges related to algorithm complexity and explain ability
techniques need to be addressed.
The Global Explainable AI Market is segmented into
Component, Deployment, End-use, Application, regional distribution, and
company.
Based on application, the market is segmented into
fraud and anomaly detection, drug discovery & diagnostics, predictive
maintenance, supply chain management, identity and access management, and
others. Artificial intelligence (AI) plays a crucial role in fraud
management. The fraud and anomaly detection segment accounted for the
largest revenue share of 23.86% in 2022.
Machine Learning (ML) algorithms, a component of AI,
can examine enormous amounts of data to identify trends and anomalies that
could indicate fraudulent activity. Systems for managing fraud powered by AI
can detect and stop various frauds, including financial fraud, identity theft,
and phishing attempts. They can also change and pick up on new fraud patterns
and trends, thereby increasing their detection.
The prominent use of XAI in manufacturing with
predictive maintenance is propelling the market growth. XAI predictive analysis
in manufacturing involves using interpretable AI models to make predictions and
generate insights in the manufacturing industry. Explainable AI techniques are
used to develop models that predict equipment failures or maintenance needs in
manufacturing plants. By analyzing historical sensor data, maintenance logs,
and other relevant information, XAI models identify the key factors
contributing to equipment failures and provide interpretable explanations for
the predicted maintenance requirements.
Moreover, explainable AI models leverage predictive
analysis in quality control processes. By analyzing production data, sensor
readings, and other relevant parameters, XAI models can predict the likelihood
of defects or deviations in manufacturing processes. The models can also
provide explanations for the factors contributing to quality issues, helping
manufacturers understand the root causes and take corrective actions.
Based on region, North America dominated the market
with a share of 40.52% in 2022 and is projected to grow at a CAGR of 13.4% over
the forecast period. Strong IT infrastructure in developed nations such as
Germany, France, the U.S., the UK, Japan, and Canada is a major factor
supporting the growth of the explainable AI market in these countries.
Another factor driving the market expansion of
explainable AI in these countries is the substantial assistance from the
governments of these nations to update the IT infrastructure. However,
developing nations like India and China are expected to display higher growth
during the forecast period. Numerous investments that are appropriate for the
expansion of the explainable AI business are drawn to these nations by their
favorable economic growth.
Asia Pacific is anticipated to grow at the fastest
CAGR of 24.8% during the forecast period. Significant advancements in
technology in Asia Pacific countries are driving market growth. For instance,
in February 2021, a new system built on the 'explainable AI' principle was
developed by Fujitsu Laboratories and Hokkaido University in Japan. It
automatically shows users the steps they need to do to obtain a desired result
based on AI results about data, such as those from medical exams.
Major companies
operating in Global Explainable AI Market are:
- Amelia US LLC
- BuildGroup
- DataRobot, Inc.
- Ditto.ai
- DarwinAI
- Factmata
- Google LLC
- IBM Corporation
- Kyndi
- Microsoft Corporation
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“The global explainable AI market has experienced
significant growth due to the rising demand for transparency and
interpretability in AI systems. Explainable AI refers to the ability of an AI
system to provide clear and understandable explanations for its decisions and
actions, which is crucial in industries like finance, healthcare, and legal.
The concern over the "black box" nature of traditional AI models has
driven the need for explainable AI solutions. These solutions utilize
techniques such as rule-based systems, symbolic reasoning, and natural language
processing to generate explanations that humans can easily comprehend. The
financial industry has been an early adopter, using explainable AI to enhance
risk assessment, fraud detection, and compliance monitoring. In healthcare,
explainable AI aids in improving diagnosis and treatment decisions by providing
understandable recommendations. Similarly, the legal industry benefits from
explainable AI by enhancing legal research and decision-making. The global
explainable AI market is projected to continue growing as AI adoption expands,
although challenges related to algorithm complexity and explain ability
techniques must be addressed to fully realize its potential.,” said Mr. Karan
Chechi, Research Director with TechSci Research, a research-based management
consulting firm.
“Explainable AI Market – Global Industry Size,
Share, Trends, Opportunity, and Forecast, Segmented By Component (Solution,
Services), By Deployment (Cloud, On-Premises), By Application (Fraud &
Anomaly Detection, Drug Discovery & Diagnostics, Predictive Maintenance,
Supply chain management, Identity and access management, Others), By End-use
(Healthcare, BFSI, Aerospace & defense, Retail and e-commerce, Public
sector & utilities, IT & telecommunication, Automotive, Others), By
Region, By Competition”, has evaluated the future growth potential of
Global Explainable AI Market and provides statistics & information on
market size, structure and future market growth. The report intends to provide
cutting-edge market intelligence and help decision makers take sound investment
decisions. Besides, the report also identifies and analyzes the emerging trends
along with essential drivers, challenges, and opportunities in Global
Explainable AI Market.
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