During a 2024 global survey, a little more than one-quarter – or 26 percent – of responding consumers said they trusted brands generally to use artificial intelligence (AI) responsibly.

When surveyed in 2024, more than half (55 percent) of consumers across 31 countries and territories trusted AI to collect and combine product information. Meanwhile, less than a quarter of consumers trusted artificial intelligence to provide legal advice. As an overall trend, the less risky or impactful an activity, the more likely consumers were to trust AI to do the activity in place of a human being. Consumers lack trust in AI Consumers of all ages are skeptical of AI. Only a quarter of adults in the United States trust AI to provide accurate information, and even fewer trust the technology to make unbiased or ethical decisions. The percentage of adults who trust AI to provide accurate information is comparable to the percent of those who would trust AI to execute financial transactions. Assessing risk Despite skepticism, surveyed consumers did not expect the severity of adverse outcomes of AI technology to be particularly high in 2024. As the statistics show, adults do not trust AI to participate in activities they consider risky, nor do they expect adverse outcomes from the use of AI technologies.

According to a survey conducted in February 2023, 34 percent of consumers in the United States trusted influencer content generated by artificial intelligence (AI) the same amount as they trusted content generated by human influencers themselves. Another 22 percent of U.S. consumers distrusted the same type of content a little more than the human-generated one.

Research Hypothesis:

The hypothesis is that service quality and trust significantly influence customer satisfaction with Telkomsel’s Veronika chatbot. Key dimensions include reliability, responsiveness, and empathy in service quality, and trust based on the chatbot's ability, benevolence, and integrity.

Data and Data Collection:

Data for this study were collected from Generation Z users who have experience using Telkomsel’s Veronika chatbot. A structured questionnaire was administered to 240 respondents, 52.9% of whom were female and 47.1% male, with ages ranging from 18 to 22 years. The data collection occurred between May and June 2024, and the questionnaire was distributed via social media platforms such as Instagram, Line, and WhatsApp. Non-probability sampling methods, specifically purposive and quota sampling, were used to ensure that only those familiar with the chatbot were surveyed.

The questionnaire comprised 31 questions designed to assess three key variables: service quality, trust, and customer satisfaction. A five-point Likert scale, ranging from "Strongly Disagree" to "Strongly Agree," was employed for all questions. Service quality was evaluated using the SERVQUAL model, while trust was measured through dimensions of ability, benevolence, and integrity. Customer satisfaction was assessed using items adapted from the Customer Satisfaction Index (CSI).

Key Findings:

1.Service Quality: A significant positive impact on customer satisfaction was found (β = 0.496, p < 0.001), with reliability and responsiveness being key factors. The highest loading (0.837) was on Veronika’s ability to provide alternative solutions.

2.Trust: Trust was also a significant predictor (β = 0.337, p < 0.001), with confidentiality being the most important trust factor (outer loading = 0.835).

3.Customer Satisfaction: Satisfaction was strongly influenced by both service quality and trust, with outer loadings from 0.908 to 0.918, particularly in terms of the chatbot's clarity and communication effectiveness.

Data Interpretation:

Both service quality and trust are essential to customer satisfaction, with service quality being a stronger predictor. Users value reliability and responsiveness more than trust, though both are necessary for high satisfaction. The reliability of the questionnaire was confirmed with high Cronbach’s alpha values, such as 0.938 for service quality.

Conclusion and Implications:

Improving service quality, especially reliability and responsiveness, will enhance user satisfaction. Strengthening trust, particularly in data security, is also crucial. Future research should explore broader demographics and long-term effects, while qualitative studies could offer more insights into user experiences.

When surveyed in 2024, less than than half (42 percent) of consumers in Ireland trusted AI to collect and combine product information. Even fewer Irish consumers (15 percent) trusted artificial intelligence to provide legal advice, and 23 percent of Irish consumers did not trust AI to complete any activity in place of human interaction.

During a March 2024 survey among adults in the United States, around 38 percent of respondents reported either strongly or somewhat agreeing that they trusted product recommendations from general artificial intelligence (AI) applications like ChatGPT or Gemini (formerly known as Bard). Around 48 percent disagreed.

According to Cognitive Market Research, the global Artificial Intelligence in Retail market size is USD 4951.2 million in 2023and will expand at a compound annual growth rate (CAGR) of 39.50% from 2023 to 2030.

Enhanced customer personalization to provide viable market output
Demand for online remains higher in Artificial Intelligence in the Retail market.
The machine learning and deep learning category held the highest Artificial Intelligence in Retail market revenue share in 2023.
North American Artificial Intelligence In Retail will continue to lead, whereas the Asia-Pacific Artificial Intelligence In Retail market will experience the most substantial growth until 2030.

Enhanced Customer Personalization to Provide Viable Market Output

A primary driver of Artificial Intelligence in the Retail market is the pursuit of enhanced customer personalization. A.I. algorithms analyze vast datasets of customer behaviors, preferences, and purchase history to deliver highly personalized shopping experiences. Retailers leverage this insight to offer tailored product recommendations, targeted marketing campaigns, and personalized promotions. The drive for superior customer personalization not only enhances customer satisfaction but also increases engagement and boosts sales. This focus on individualized interactions through A.I. applications is a key driver shaping the dynamic landscape of A.I. in the retail market.

January 2023 - Microsoft and digital start-up AiFi worked together to offer Smart Store Analytics. It is a cloud-based tracking solution that helps merchants with operational and shopper insights for intelligent, cashierless stores.

Source-techcrunch.com/2023/01/10/aifi-microsoft-smart-store-analytics/

Improved Operational Efficiency to Propel Market Growth

Another pivotal driver is the quest for improved operational efficiency within the retail sector. A.I. technologies streamline various aspects of retail operations, from inventory management and demand forecasting to supply chain optimization and cashier-less checkout systems. By automating routine tasks and leveraging predictive analytics, retailers can enhance efficiency, reduce costs, and minimize errors. The pursuit of improved operational efficiency is a key motivator for retailers to invest in AI solutions, enabling them to stay competitive, adapt to dynamic market conditions, and meet the evolving demands of modern consumers in the highly competitive artificial intelligence (AI) retail market.

January 2023 - The EY Retail Intelligence solution, which is based on Microsoft Cloud, was introduced by the Fintech business EY to give customers a safe and efficient shopping experience. In order to deliver insightful information, this solution makes use of Microsoft Cloud for Retail and its technologies, which include image recognition, analytics, and artificial intelligence (A.I.).

Source-www.ey.com/en_gl/news/2023/01/ey-announces-launch-of-retail-solution-that-builds-on-the-microsoft-cloud-to-help-achieve-seamless-consumer-shopping-experiences

Market Dynamics of the Artificial Intelligence in the Retail market

Data Security Concerns to Restrict Market Growth

A prominent restraint in Artificial Intelligence in the Retail market is the pervasive concern over data security. As retailers increasingly rely on A.I. to process vast amounts of customer data for personalized experiences, there is a growing apprehension regarding the protection of sensitive information. The potential for data breaches and cyberattacks poses a significant challenge, as retailers must navigate the delicate balance between utilizing customer data for AI-driven initiatives and safeguarding it against potential security threats. Addressing these concerns is crucial to building and maintaining consumer trust in A.I. applications within the retail sector.

Impact of COVID–19 on the Artificial Intelligence in the Retail market

The COVID-19 pandemic significantly influenced artificial intelligence in the retail market, accelerating the adoption of A.I. technologies across the industry. With lockdowns, social distancing measures, and a surge in online shopping, retailers turned to A.I. to navigate the challenges posed by the pandemic. AI-powered solutions played a crucial role in optimizing supply chain management, predicting shifts in consumer behavior, and enhancing e-commerce experiences. Retailers lever...

In 2024, 55 percent of people answering a worldwide survey trusted artificial intelligence to replace human interaction when it came to assemble and present product information before a purchase. Another 50 percent of them believed AI could effectively provide product recommendations.

During a March 2024 survey among adults in the United States, around 51 percent of respondents reported either somewhat or strongly agreeing that they trusted product recommendations from a specific store or website's artificial intelligence (AI) tools based on their purchase history. Almost 40 percent disagreed.

This dataset contains survey responses collected to examine the impact of AI-driven chatbot affordances on purchase intention in the e-commerce sector in Sri Lanka. It includes data on key mediators such as customer engagement, trust, and satisfaction, along with demographic variables such as age, gender, employment type, and online shopping frequency. The dataset is structured using a 5-point Likert scale and supports analyses using PLS-SEM. It is valuable for researchers exploring consumer behavior, AI applications, and digital marketing strategies in online retail.

According to a worldwide study conducted by Capgemini in 2023, respondents from Spain, Canada, and the United States had the highest level of trust in medical advice and suggestions from generative AI. Globally, 67 percent of respondents trusted medical opinions from generative AI to be helpful, and there was no significant variation on the country level.

In a 2022 survey conducted among consumers in the Asia-Pacific region, 35 percent of the respondents in India expected AI to improve their consumer experience a lot. In comparison, consumers in New Zealand had less positive expectations, with 31 percent expecting AI to not improve consumer experience.

The emergence of artificial intelligence (AI) has changed traditional methods of value co-creation. Diverging from traditional methods, this study discusses the influencing factors of AI-supported consumer value co-creation from the perspective of human-to-non-human interactions. This study adopts the stimulus–organism–response framework with consumer engagement (CE) as the intermediary to explore the impact of consumers’ personal subjective factors, community factors, and perceptions of AI technology on their value co-creating behaviors. Data were collected from 528 respondents from the Huawei Huafen Club, Xiaomi BBS, Apple China Virtual Brand, Micromobile Phone, and Lenovo communities. SPSS Amos software was used for statistical analysis, revealing that perceived personalization, autonomy, community identity, trust in AI, and self-efficacy are motivational factors that have significant effects on consumer value co-creation behaviors, in which CE plays a significant intermediary role. Our study contributes to the literature on consumer value co-creation supported by AI technology. We also offer important insights for developers of AI-enabled products and service managers.

AI Content Detector Market size is growing at a moderate pace with substantial growth rates over the last few years and is estimated that the market will grow significantly in the forecasted period i.e. 2024 to 2031.

Global AI Content Detector Market Drivers

Rising Concerns Over Misinformation: The proliferation of fake news, misinformation, and inappropriate content on digital platforms has led to increased demand for AI content detectors. These systems can identify and flag misleading or harmful content, helping to combat the spread of misinformation online.

Regulatory Compliance Requirements: Stringent regulations and legal obligations regarding content moderation, data privacy, and online safety drive the adoption of AI content detectors. Organizations need to comply with regulations such as the General Data Protection Regulation (GDPR) and the Digital Millennium Copyright Act (DMCA), spurring investment in AI-powered content moderation solutions.

Growing Volume of User-Generated Content: The exponential growth of user-generated content on social media platforms, forums, and websites has overwhelmed traditional moderation methods. AI content detectors offer scalable and efficient solutions for analyzing vast amounts of content in real-time, enabling platforms to maintain a safe and healthy online environment for users.

Advancements in AI and Machine Learning Technologies: Continuous advancements in artificial intelligence and machine learning algorithms have enhanced the capabilities of content detection systems. AI models trained on large datasets can accurately identify various types of content, including text, images, videos, and audio, with high precision and speed.

Brand Protection and Reputation Management: Businesses prioritize brand protection and reputation management in the digital age, as negative content or misinformation can severely impact brand image and consumer trust. AI content detectors help organizations identify and address potentially damaging content proactively, safeguarding their reputation and brand integrity.

Demand for Personalized User Experiences: Consumers increasingly expect personalized online experiences tailored to their preferences and interests. AI content detectors analyze user behavior and content interactions to deliver relevant and engaging content, driving user engagement and satisfaction.

Adoption of AI-Powered Moderation Tools by Social Media Platforms: Major social media platforms and online communities are investing in AI-powered moderation tools to enforce community guidelines, prevent abuse and harassment, and maintain a positive user experience. The need to address content moderation challenges at scale drives the adoption of AI content detectors.

Mitigation of Online Risks and Threats: Online platforms face various risks and threats, including cyberbullying, hate speech, terrorist propaganda, and child exploitation content. AI content detectors help mitigate these risks by identifying and removing harmful content, thereby creating a safer online environment for users.

Cost and Resource Efficiency: Traditional content moderation methods, such as manual review by human moderators, are time-consuming, labor-intensive, and costly. AI content detectors automate the moderation process, reducing the need for human intervention and minimizing operational expenses for organizations.

This dataset accompanies the research study titled "The Future of U.S. Retail Banking – A Comparative Analysis of AI versus Human Interaction Driving Service Excellence and Customer Satisfaction." It contains survey responses from 50 undergraduate and graduate students at the Raj Soin College of Business, Wright State University. The data captures participant insights on the role of AI and human interaction in customer service within the U.S. retail banking sector.

Key metrics include customer preferences, satisfaction levels, perceived efficiency, trust factors, and expectations from AI-driven and human-assisted banking experiences. The dataset aims to support analysis on the effectiveness of generative AI (GenAI) in transactional efficiency versus the necessity of human interaction in fostering trust, empathy, and personalized financial guidance. Findings from this dataset will contribute to recommendations for an optimized, hybrid approach in retail banking customer service.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5133933

According to Cognitive Market Research, The Global AI (Artificial Intelligence) Speaker market size is USD 5812.5 million in 2023 and will expand at a compound annual growth rate (CAGR) of 26.50% from 2023 to 2030.

The demand for AI (Artificial Intelligence) Speakers is rising due to the increasing adoption of smart home devices and advancements in natural language processing (NLP).
Demand for Wi-Fi Connection remains higher in the AI (Artificial Intelligence) Speaker market.
The living room scene category held the highest AI (Artificial Intelligence) Speaker market revenue share in 2023.
North American AI (Artificial Intelligence) Speaker will continue to lead, whereas the Asia-Pacific AI (Artificial Intelligence) Speaker market will experience the most substantial growth until 2030.

Integration of Virtual Assistants and Smart Home Control to Provide Viable Market Output

The increasing focus on sustainability and cruelty-free practices in the AI (Artificial Intelligence) Speaker market reflects growing consumer demand for eco-friendly and ethically produced cosmetics. Brands that prioritize sustainable sourcing and eco-friendly packaging and avoid animal testing align with consumer values. This trend not only promotes environmental responsibility but also enhances brand reputation and attracts socially-conscious customers, driving market growth towards more ethical and eco-conscious choices.

Advancements in Natural Language Processing (NLP)to Propel Market Growth

Another crucial driver is the continuous advancements in Natural Language Processing (NLP), a fundamental aspect of AI that enables machines to understand and respond to human language. Improved NLP capabilities empower AI speakers to interpret and respond to user queries more accurately, fostering a more natural and intuitive interaction. As AI speakers become more proficient in understanding context, user preferences, and even emotions, they offer enhanced user experiences. The ongoing progress in NLP technology drives the market by making AI speakers more user-friendly, thereby expanding their adoption among a broader audience.

SAS and Basserah partnered to deliver leading data analytics and Al solutions to Saudi businesses. With this partnership, both companies are focusing on data and robotics process automation for growth opportunities in the Kingdom of Saudi Arabia..

(Source:www.zawya.com/en/press-release/companies-news/sas-and-basserah-partner-to-deliver-leading-data-analytics-and-ai-solutions-to-saudi-businesses-hs4933j4)

Market Restraints of the AI Artificial Intelligence Speaker

Privacy Concerns and Data Security Restrict Market Growth

One significant restraint in the AI (Artificial Intelligence) Speaker market revolves around privacy apprehensions and data security issues. As these smart speakers continuously listen for voice commands, users often express concerns about the potential misuse or unauthorized access to their private conversations. Addressing and alleviating these privacy concerns is crucial for the sustained growth of the AI Speaker market. Companies must implement robust security measures, transparent data practices, and user-friendly privacy settings to build and maintain consumer trust in the use of AI speakers in their homes.

Impact of COVID–19 on the AI Artificial Intelligence Speaker Market

The AI (Artificial Intelligence) Speaker market experienced a mixed impact from the COVID-19 pandemic. On one hand, the increased focus on remote work and the adoption of smart home technologies during lockdowns positively influenced the demand for AI speakers. Consumers sought devices that could enhance their home environment, leading to a surge in interest and sales. On the other hand, supply chain disruptions, manufacturing slowdowns, and economic uncertainties resulted in challenges for the market. The pandemic affected the production and distribution of AI speakers, causing delays and shortages in some regions. Additionally, with economic uncertainties, consumers became more cautious in their spending, impacting discretionary purchases, including smart home devices. Despite these challenges, the overall resilience of the AI Speaker market, driven by the increased relevance of smart home solutions during the pandemic, contributed to its ongoing growth trajectory. Introduction of AI Artificial Intelligence Speaker

The AI (Artificial Intelligence) Speaker Mark...

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Artificial Intelligence (AI) In BFSI Sector Market Size 2025-2029

The artificial intelligence (AI) in BFSI sector market size is forecast to increase by USD 101.35 billion, at a CAGR of 54.2% between 2024 and 2029.

The Artificial Intelligence (AI) market in the BFSI sector is witnessing significant growth, driven by the increasing need for enhanced operational efficiency. AI technologies, such as machine learning and natural language processing, are revolutionizing various BFSI processes, including fraud detection, risk assessment, and customer service. Moreover, the rise of cloud-based AI solutions is enabling smaller financial institutions to adopt these advanced technologies, thereby expanding the market's reach. Deep learning algorithms and machine learning models enhance risk management and algorithmic trading, while AI governance and infrastructure support big data processing and cloud computing.
Ensuring data security and privacy is another significant challenge, given the sensitive nature of financial data. Furthermore, integrating AI systems with existing legacy systems and ensuring seamless data transfer can be a complex process, requiring substantial resources and expertise. Effective management of these challenges will be crucial for companies seeking to capitalize on the market's opportunities and stay competitive in the rapidly evolving BFSI landscape.

What will be the Size of the Artificial Intelligence (AI) In BFSI Sector Market during the forecast period?

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In the BFSI sector, Artificial Intelligence (AI) is revolutionizing business operations and driving significant market trends. AI-powered customer onboarding streamlines the process, reducing costs and enhancing the customer experience. In capital markets, AI-driven customer segmentation and investment optimization provide data-driven insights for personalized financial recommendations. AI-powered financial modeling and portfolio management increase efficiency, while real-time fraud detection and cybersecurity threat prevention ensure security.
Furthermore, AI-powered payment processing and lending leverage data-driven risk management and automated underwriting to provide personalized services and improve overall customer satisfaction. Overall, AI is transforming the BFSI sector by automating processes, enhancing decision making, and providing personalized services, leading to increased efficiency and competitiveness. AI-powered investment banking and regulatory reporting automate complex processes, improving accuracy and reducing manual errors. AI-powered insurance underwriting and claims processing enable faster and more accurate risk scoring and claims management. Enhanced decision making is possible through AI-powered wealth management, trade finance, and lending.

How is this Artificial Intelligence (AI) In BFSI Sector Industry segmented?

The artificial intelligence (AI) in BFSI sector industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  Banking
  Investment and securities management
  Insurance


Solution

  Software
  Services


Type

  Fraud detection and prevention
  Customer relationship management
  Data analytics and prediction
  Anti-money laundering
  Others


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By End-user Insights

The banking segment is estimated to witness significant growth during the forecast period. In the banking sector, Artificial Intelligence (AI) is revolutionizing business operations and customer experiences. Banks are adopting AI strategies to automate decision-making processes, develop cognitive models, and deploy predictive analytics for fraud detection and investment management. Speech recognition technology enables virtual assistants to handle customer queries, while computer vision and image recognition facilitate personalized banking services. AI ethics and data privacy are essential considerations in model development and deployment. Financial inclusion is a priority, with AI-powered solutions offering access to banking services through digital identity verification and open banking. Biometric authentication and blockchain technology ensure data security and anti-money laundering compliance.

Explainable AI (XAI) is crucial for transparency and trust. Digital transformation continues to shape the banking industry, with AI innovation driving customer service, loan origination, financial advisory, and loan origination. Data analytics and predictive analytics enable banks to gain valuable insights and make informed decisions. AI adoption is a critical trend, with bank

During an October to November 2023 survey, 64 percent of responding consumers from the United States stated that advertising that disclosed the usage of artificial intelligence (AI) was appealing, as opposed to 43 percent of consumers who found ads that did not disclose AI usage appealing. Overall, ads with a noticed disclosure statement generated a 96 percent boost in company trust on the consumer side.

Personalization and trust In the marketing realm, long before ChatGPT’s hype hit the world, AI-powered chatbots were used to provide customer service and answer questions. In 2023, the leading area, next to coding, in which B2B marketing professionals were deploying AI was precisely chatbots. With the development of technology, chatbot tools are now more efficient and personalize experiences at a greater scale. In turn, this fosters a sense of efficiency and care on the consumer side.

Transparency and trust It is important, however, for companies that use AI and chatbots to understand that transparency is key in the generation of brand trust. Disclosure of AI usage in any marketing material must be of utmost priority if brands wish to remain relevant. Consumers can easily lose their liking if they are not informed whether they are interacting with a machine or a human, or whether the content they are engaging with is “real” or synthetic. In 2023, 40.5 percent of creators globally agreed that there should be a mandatory reveal of AI usage in marketing content.

According to Cognitive Market Research, The Global AI in Fashion market size is USD 1125.2 million in 2023 and will expand at a compound annual growth rate (CAGR) of 41.50% from 2023 to 2030.

The demand for Ai in Fashions is rising due to personalized customer experiences and supply chain optimization.
Demand for solutions remains higher in the AI Fashion market.
The product recommendation category held the highest AI in Fashion market revenue share in 2023.
North American AI in Fashion will continue to lead, whereas the Asia-Pacific AI in Fashion market will experience the most substantial growth until 2030.

Enhanced Personalization Capabilities to Provide Viable Market Output

In the AI Fashion market, a pivotal driver is the capability of artificial intelligence to enhance personalized experiences for consumers. AI algorithms analyze vast amounts of customer data, including preferences, purchase history, and browsing behavior, enabling fashion brands to offer tailored recommendations, personalized styling advice, and targeted promotions. This heightened level of personalization not only enhances customer satisfaction and loyalty but also contributes to increased conversion rates, driving the adoption of AI technologies across the fashion industry as brands seek to deliver more individualized and engaging experiences to their customers.

October 2022: A new member of the Cisco Digital Solutions Integrator (DSI) Program is Delta Bravo Artificial Intelligence Inc. From Cisco's global partner network, the DSI Program chooses strategic partners that can offer distinct value and insights to Cisco's most significant clients.

(Source: deltabravo.ai/partnership-announced-between-cisco-systems-csco-and-delta-bravo-artificial-intelligence-ai/)

Optimized Supply Chain Management to Propel Market Growth

Another key driver in AI in the fashion market is the optimization of supply chain management through artificial intelligence. AI-powered tools facilitate demand forecasting, inventory management, and production planning, helping fashion companies streamline their supply chains. This is particularly crucial in an industry that experiences rapid shifts in trends and consumer preferences. AI algorithms enable more accurate predictions, reducing the risk of overstock or stockouts, improving overall operational efficiency, and contributing to cost savings. The emphasis on a responsive and efficient supply chain positions AI as a fundamental driver for fashion brands aiming to navigate the complexities of the industry and meet evolving market demands.

In July 2022, SAS and Basserah partnered to deliver leading data analytics and AI solutions to Saudi businesses. With this partnership, both companies are focusing on data and robotics process automation for growth opportunities in the Kingdom of Saudi Arabia.

(Source: www.zawya.com/en/press-release/companies-news/sas-and-basserah-partner-to-deliver-leading-data-analytics-and-ai-solutions-to-saudi-businesses-hs4933j4)

Increasing demand for up and coming fashion trends of the moden age is propelling market growth 

Market Dynamics Of AI in Fashion

Data Privacy Concerns to Restrict Market Growth

In the AI Fashion market, a prominent restraint revolves around data privacy concerns. As AI relies heavily on consumer data for personalized recommendations and experiences, fashion companies face growing scrutiny over how they collect, store, and utilize this information. Heightened awareness of data breaches and privacy violations has led to increased regulatory scrutiny and consumer demands for transparency. Balancing the benefits of AI-driven personalization with stringent data protection measures poses a challenge, impacting the industry's ability to fully leverage AI capabilities while maintaining consumer trust.

Impact of COVID-19 on the AI in the Fashion Market

The COVID-19 pandemic had a multifaceted impact on AI in the fashion market. On the one hand, disruptions in the supply chain and manufacturing processes led to a heightened interest in AI technologies for optimizing inventory management, production forecasting, and supply chain resilience. The need for contactless experiences and the surge in online shopping during lockdowns accelerated the adoption of AI-driven virtual try-on solutions, personalized recommendations, and augmented reality experiences. On the ot...

The insurance sector faces a myriad of challenges. Insurtechs are disrupting the industry, drawing on AI, cloud services, and IoT to offer lower-cost and personalized insurance coverage, via seamless digital platforms. COVID-19 has hastened the shift towards digital insurance, and providers with superior online offerings are attracting new customers. Falling profitability is another issue, with greater competition driving down prices, and insurers facing an influx of claims due to COVID-19. Technology, and specifically AI, will play a role in improving the efficiency of existing operations while helping insurers to expand product lines and customer service.
GlobalData’s Emerging Technology Trends Survey 2020 found that 80% of insurance executives expect AI to play a role in helping their companies weather the pandemic.
Bigger insurance companies have led the way, but AI adoption is becoming more widespread, with use cases extending further than the basic conversational platforms that were initially deployed. As cloud-based operating systems become more popular, even legacy insurers will begin to implement compatible AI tools. The growing emergence of several specialist tech vendors will further facilitate AI adoption in the sector, presenting a cost-effective approach to using AI versus developing and curating in-house expertise.
Machine learning (ML), computer vision, and conversational platforms hold the most potential across the insurance value chain. These technologies can help with customer service, claims processing, and underwriting. More advanced applications of AI technology include the use of data science and context-aware computing to enhance risk profiling.
Innovation is greater in general insurance lines as products are less complex and easier to underwrite.
While insurtechs continue to disrupt the insurance sector, incumbents hold an advantage as they have access to swathes of historic customer data on which to train AI models, resulting in superior decision-making outputs. Nonetheless, explainable AI practices and algorithmic transparency will need to be integrated into the early stages of AI deployment to safeguard consumer trust. Read More