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Tag: Artificial inteligence

  • How AI Voice Agents Work and How Can They Enhance Customer Interactions and Business Operations

    This article has been contributed by Mr. Sarvagya Mishra, Co-founder and Director, Superbot, an AI-powered voice agent startup.

    In today’s hyper-connected world, businesses face growing pressure to deliver personalized and efficient customer service. This demand is particularly pronounced among small and medium-sized enterprises (SMEs), which heavily rely on innovative ways to enhance their customer support offerings. Recognizing this need, voice assistants (Vas) and smart assistants have emerged as transformative tools, revolutionizing the way SMEs interact with their customers.

    As per research conducted by The Capgemini Research Institute, over three-quarters (76%) of businesses have reported experiencing tangible benefits from implementing voice or chat assistant initiatives. Additionally, 58% of businesses stated that these benefits either met or exceeded their initial expectations. These benefits encompassed remarkable reductions in customer service costs, with some experiencing more than a 20% decrease, along with a noteworthy increase of over 20% in consumer utilization of digital assistants.

    Evolution of Voice Technology and Smart Assistants
    How AI Voice Agents Work
    Adoption of AI Voice Agents in Customer Service
    Personalized Assistance
    Efficient Operations
    24/7 Availability
    Enhanced Productivity
    Future of AI Voice Agents

    Evolution of Voice Technology and Smart Assistants

    The journey of AI voice agents traces back to the dawn of computing in 1966, with the emergence of ELIZA, the world’s first chatbot. Designed as a virtual therapist, ELIZA interacted with users through a simple decision tree, offering pre-written responses to simulate human-like conversations. This early experiment laid the groundwork for the evolution of chatbots and voice assistants, paving the way for their integration into various aspects of modern life.

    Building upon the success of ELIZA, chatbots evolved into phone support tools, enabling callers to select options and engage in rudimentary conversations. The development of ALICE (Artificial Linguistic Internet Computer Entity) in 1995 marked a significant leap forward, as it introduced natural language processing (NLP) capabilities, allowing for more contextually relevant interactions. ALICE utilized artificial intelligence markup language (AIML) to engage users in more sophisticated conversations, setting the stage for the integration of AI and machine learning into voice assistants. The convergence of AI and machine learning during the internet boom propelled the transformation of simple chatbots into intelligent virtual companions. These AI voice agents emerged as powerful tools capable of executing tasks, providing information, and engaging in natural language conversations with users.

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    How AI Voice Agents Work

    AI voice agents operate through a sophisticated combination of artificial intelligence (AI) and natural language processing (NLP) technologies. These agents begin by transcribing spoken words into text through speech recognition algorithms, then proceed to interpret the meaning behind the words using natural language understanding (NLU) techniques. By recognizing keywords, phrases, and patterns within the input text, AI voice agents identify the user’s Intent or purpose behind their query. They consider contextual information, previous interactions, and user preferences to generate personalized responses, engaging in dynamic dialogues while managing turn-taking and conversation flow. Continuously learning from user interactions and feedback, AI voice agents adapt and improve their performance over time using machine learning algorithms. Behind the scenes, they integrate with backend systems, databases, and third-party APIs to retrieve information and fulfil user requests in real-time.

    Worldwide Natural Language Processing Market Revenue
    Worldwide Natural Language Processing Market Revenue

    How AI Voice Agents Work

    Today, numerous conversational AI service providers offer user-friendly DIY platforms, empowering both users and businesses to customize their conversational experiences with greater control and flexibility. These platforms simplify the process of creating personalized bots without requiring any coding skills, allowing users to effortlessly drag, connect, and customize their AI agents to deliver desired responses and voice tones within minutes. Remarkably, these platforms often include cloud-based blended contact centres, providing clients with a comprehensive ecosystem for handling calls all within a single platform. Here’s how these AI voice agents offer numerous benefits, enhancing customer interactions and streamlining business operations across various sectors:

    Personalized Assistance

    AI voice agents revolutionize customer support in various industries by providing tailored assistance to address specific needs and preferences. For instance, in the healthcare sector, AI voice agents can guide patients through appointment scheduling, provide medication reminders, and offer personalized health tips based on individual medical histories. Similarly, in sectors such as Direct-to-Consumer (D2C) and E-Commerce, AI voice agents empower businesses with real-time fulfilment capabilities and rapid responses. This functionality helps reduce Return to Origin (RTO) rates, minimize cart abandonment, boost Customer Satisfaction (CSAT), and Decrease Average Handling Time (AHT).

    Efficient Operations

    AI voice agents enhance business operations across various sectors, optimizing processes and boosting efficiency. In banking, for instance, these agents automate routine tasks like balance inquiries, transaction history requests, and payment reminders, alleviating the burden on customer service staff and enhancing response times. Likewise, in the hospitality industry, AI voice agents facilitate hotel reservations, handle check-in/check-out procedures, and provide concierge services, allowing staff to focus on delivering personalized guest experiences.

    24/7 Availability

    AI voice agents ensure round-the-clock support for customers, offering assistance and guidance regardless of time constraints or business hours. In the telecommunications industry, AI voice agents enable subscribers to troubleshoot technical issues, activate new services, and inquire about billing information at any time of day or night, all in multiple languages. In like manner, educational institutions utilize AI-driven voice agents to automate admission counselling processes effectively. This reduces initial interaction times with students to under five minutes and automates lead profiling. As a result, human counsellors can dedicate more time to actual counselling, saving 60% of the time previously allocated to lead profiling.

    Enhanced Productivity

    AI voice agents optimize workflows by automating repetitive tasks, freeing up employees to concentrate on high-value activities. In the legal sector, for instance, AI voice agents can assist lawyers with legal research, document drafting, and case management tasks, freeing up time for attorneys to dedicate to complex legal analysis and client consultations. And when it comes to complex sectors like logistics, AI voice agents effortlessly facilitate order tracking, shipment scheduling, and route optimization, enabling logistics professionals to manage logistics operations more efficiently and effectively.

    Future of AI Voice Agents

    New predictions indicate that AI will play an increasingly central role in customer interactions, with an estimated 95% of interactions expected to be handled by AI without human involvement by 2025. This paradigm shift highlights the growing importance of AI voice agents in shaping the future of customer service and business operations.

    However, as businesses integrate AI voice agents, they must prioritize data privacy, transparency, and ethical usage. Continuous training can ensure seamless collaboration between employees and AI systems, facilitating effective utilization of AI capabilities. Notably, adaptability is crucial for businesses to keep pace with evolving technology and changing consumer expectations, thereby fostering growth and innovation in the digital age.

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  • The Future of Brokerage Platforms: AI Integration and Enhanced Trading Capabilities

    This article has been contributed by Kartik Chhaya, COO of Rupeeseed.

    In today’s rapidly evolving financial landscape, brokerage platforms are undergoing a transformative shift driven by advancements in artificial intelligence (AI) technology. The integration of AI into brokerage platforms is revolutionizing the way brokers and investors engage with financial markets, offering enhanced trading capabilities and unprecedented insights.

    ‘As the financial industry harnesses the potential of AI, brokerage platforms emerge as pioneers of innovation. At Rupeeseed, we recognize the significance of emerging technology trends, such as AI integration, for enhancing trading capabilities and delivering superior experience. Our dedication to staying ahead of technology trends drives continuous innovation and evolution, ensuring our clients benefit from the latest advancements, “says Mr. Kartik Chhaya, COO of Rupeeseed.

    Traditional Data-Powered Insights 
    AI-Powered Data and Its Benefits
    Integration and Challenges for Solution Providers and Brokers
    Current AI Trends Around the Periphery
    Boosted Deliverables Through AI
    Future Trends

    Traditional Data-Powered Insights 

    Data-powered insights have played a vital role in guiding trading decisions on brokerage platforms. Traditional methods of data analysis, relying on manual processing and human interpretation, are increasingly falling short in the face of growing data volumes and market complexities. 

    With the advent of AI integration, brokerage platforms can process and analyze massive datasets with speed and precision, uncovering valuable insights that may have previously gone unnoticed. By harnessing machine learning algorithms, brokers can provide deeper insights of market dynamics, identify trends, and empower traders and investors make more informed decisions. 

    AI-Powered Data and Its Benefits

    The primary benefits of AI-powered data analytics are identifying hidden patterns and multilevel insights in market data that may be imperceptible to human analysis. By processing large volumes of structured and unstructured data sources such as market prices, news articles, social media sentiment, and economic indicators, AI algorithms can identify correlations and relationships that traditional methods may overlook. This enables brokers to equip themselves with effective data, identify high probability opportunities, and mitigate risks more effectively.

    Additionally, AI-powered data analytics enhances the efficiency of trading operations by automating repetitive tasks, streamlining decision-making processes, and providing real-time insights. Ultimately, AI integration empowers brokerage platforms to offer more sophisticated and personalized services to investors, driving greater efficiency, effectiveness, and innovation in the financial industry.

    Integration and Challenges for Solution Providers and Brokers

    While AI enhances trading capabilities and user experiences, its successful integration requires navigating technical, regulatory, and operational challenges. From a technical standpoint, integrating AI solutions requires robust infrastructure and seamless collusion with existing systems in order to handle large data in real-time. AI tools should address scalability concerns to accommodate the growing demands of users and market fluctuations.

    On the regulatory front, brokers must adhere to stringent data privacy regulations and compliance standards when implementing AI solutions. Operationally, investing in staff training and organizational restructuring is necessary to effectively leverage the capabilities of AI technology. Equipping teams with the skills and knowledge to interpret AI-generated insights, optimize trading strategies, and provide value-added services to clients is vital. 

    AI integration is reshaping the financial industry, driving innovation and transforming traditional trading practices. One trend is the increasing adoption of natural language processing (NLP) and sentiment analysis to analyze textual data sources such as news articles, social media posts, and earnings reports. 

    Another prominent trend is the rise of explainable AI (XAI) techniques, enhancing transparency and interpretability in AI-driven decision-making processes. As regulators and investors demand greater accountability and understanding of AI-generated insights, brokers are increasingly integrating XAI methods into their platforms to provide users with clear explanations of AI-driven recommendations and trading strategies.

    Additionally, the convergence of AI with other emerging technologies such as blockchain and edge computing is driving new opportunities for innovation in brokerage platforms. Blockchain technology offers enhanced security and transparency for financial transactions, while edge computing enables real-time data processing and analysis at the edge of the network, reducing latency and enhancing efficiency.

    Boosted Deliverables Through AI

    AI-driven automation streamlines trading processes and enhances operational efficiency for both brokers and investors. Manual and time-consuming tasks such as data analysis, trade execution, and portfolio management are now automated through AI-powered tools.

    AI integration enables personalized services to individual investors based on their preferences, risk profiles, and investment goals. Machine learning algorithms analyze client data to offer customized recommendations and risk management strategies, driving client satisfaction and loyalty.

    Furthermore, AI-powered risk management tools enable brokers to mitigate risks and protect client assets more effectively. By continuously monitoring market conditions and portfolio performance, AI algorithms can identify potential risks and vulnerabilities and implement proactive risk mitigation strategies. This minimizes the impact of market fluctuations and unexpected events on investor portfolios, safeguarding their financial interests.

    Global Online Trading Market from 2020 with Forecasts to 2026
    Global Online Trading Market from 2020 with Forecasts to 2026

    Several trends are expected to shape the trajectory of brokerage platforms and redefine the landscape of the financial industry:

    • Augmented Intelligence: As AI technology matures, Brokers will increasingly employ augmented intelligence, blending human expertise with AI insights. This approach enables informed decisions by combining human intuition with AI analytics.
    • Predictive Analytics: Future platforms will feature predictive analytics, allowing brokers to anticipate market trends accurately. AI algorithms will forecast market movements and identify opportunities, enabling proactive strategy adjustments.
    • Personalized Services: Platforms will prioritize personalized services, leveraging AI to tailor recommendations and strategies to individual investor needs. This enhances client satisfaction and fosters long-term relationships.
    • Quantum Computing: The emergence of quantum computing promises unparalleled computational power, revolutionizing brokerage capabilities. Quantum algorithms will optimize trading strategies and risk management with exceptional efficiency.
    • Ethical AI: With AI integration, brokers will emphasize ethical practices, ensuring transparency and accountability. Ethical AI frameworks will uphold regulatory standards and protect investor interests.

    “As AI technology continues to evolve, brokerage platforms are at the forefront of innovation, reshaping the way investors engage with financial markets. At Rupeeseed, we’re dedicated to delivering robust and scalable capital market solutions to brokers and wealth firms. Our offerings enhance trading capabilities, streamline processes, and deliver personalized experience. The future of brokerage platforms holds immense potential, and we’re eager to lead the way by providing integrated solutions to financial service providers, adapting to the evolving technology trends.”, says Mr. Kartik Chhaya, COO of Rupeeseed.

    In conclusion, the future of brokerage platforms is characterized by the convergence of AI technology, predictive analytics, personalized services, quantum computing, and ethical AI practices. As brokerage platforms continue to evolve, they will play a pivotal role in shaping the future landscape of the financial industry and driving positive outcomes.

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  • The Potential of AI Facial Recognition, From Applications to Ethical Considerations

    This article has been contributed by Vivek Gujar, Director, IndoAI Technologies P Ltd.

    One of few innovations today which gathered attention and interest is AI facial recognition. From empowering marginalized communities to revolutionizing essential services, the applications of this breakthrough technology are as diverse as its impact. This technology involves artificial intelligence and biometrics, and holds promise for a wide range of applications, from improving security measures to revolutionizing the customer experience. However, alongside its transformative potential, AI facial recognition raises significant ethical considerations that require careful consideration and proactive safeguards.

    The Technology: It uses advanced algorithms to analyze and interpret facial features from digital images or video streams. This technology identifies unique facial attributes such as contour, proportion: extract and interpret distinctive facial features such as the distance between the eyes, the shape of the nose, blinking & smile ( liveness factor) and the contour of the jaw and texture by using deep learning models, specifically convolutional neural networks (CNN). Through iterative training on massive datasets, the accuracy of these algorithms continues to improve, enabling accurate facial recognition and verification capabilities.

    Applications in Various Fields
    Applications in Key Sectors
    Access to Healthcare and Telemedicine
    Education
    Agriculture and Rural Development
    Social Distribution
    Employment and Skills
    Women’s Safety and Empowerment
    Access to Government Services
    Ethical considerations are paramount

    Applications in Various Fields

    1. Security and Surveillance:
    • Law Enforcement: AI facial recognition can help identify suspects, locate missing persons, mob moods and prevent criminal activity.
    • Border Control: Airports and border crossings use this technology to enhance security measures and streamline immigration procedures.
    • Critical Infrastructure: Facial recognition process can streamline visitor management for Government building, defence establishment, etc.
    1. Personalization and Customer Experience: 
    • Retail: Retailers are using AI facial recognition to analyze customer demographics and preferences, provide customized product recommendations and improve the shopping experience.
    • Hospitality: Hotels and entertainment venues are using facial recognition for faster check-in, personalized service and increased guest satisfaction.
    1. Public Safety and Health Care: 
    • Contact Tracing: During pandemics and outbreaks, facial recognition helps with contact tracing and identifies people who may have been exposed to an infectious disease.
    • Access Control: Hospitals, healthcare facilities, pharma, etc use facial recognition for secure access control to ensure restricted areas are protected.

    Applications in Key Sectors

    Financial Inclusion at the Bottom of the Pyramid (BoP): 

    • Access to Banking Services for the BoP: AI facial recognition simplifies the bank account opening process for BoP individuals and facilitates extensive documentation.
    • Microfinance: Optimizing loan applications through facial recognition helps people access loans faster, pursue entrepreneurial ventures, and improve their livelihoods.

    Access to Healthcare and Telemedicine

    • Access to Healthcare in Rural Areas: Doctors with the help of Facial recognition technology remotely monitor patients in rural health centers to ensure timely intervention and identify needed Improve access to health services.
    • Telemedicine: Facial recognition improves security during virtual visits and makes telemedicine platforms more accessible and efficient for remote communities.

    Education

    • Access to online learning: Facial recognition technology ensures secure access to digital learning platforms, closing educational gaps and providing equal learning opportunities.
    • Attendance Tracking: Facial recognition reduces administrative burden and increases efficiency by simplifying attendance tracking in schools with limited infrastructure. A group photo of a class in a second can save several hours of roll call.

    Agriculture and Rural Development

    • Fair Trade Practices: Facial recognition verifies farmers’ identities at collection points, ensuring fair prices for agricultural products and increasing transparency in trade practices.
    • Crop Seed Distribution: AI facial recognition assists in crop seed distribution and provides valuable insights into weather conditions to sustainably optimize crop yields.

    Social Distribution

    Direct Benefit Transfer (DBT): Facial recognition can verify the identity of beneficiaries during the distribution of social assistance benefits, reducing losses and ensuring effective use of government initiatives.

    Public Distribution System: Facial data may be key to getting access to essential items such as rice under the public distribution system (PDS).

    Facial Recognition Market Size Worldwide from 2019 to 2032
    Facial Recognition Market Size Worldwide from 2019 to 2032

    Employment and Skills

    • Job Matching: Facial recognition accelerates the employment process by matching BoP job seekers with suitable employment opportunities based on their skills and qualifications, thereby increasing economic empowerment and self-employment.

    Women’s Safety and Empowerment

    • Safety App: Smartphone app with facial recognition technology makes women safer by issuing emergency alerts in stressful situations, providing immediate assistance, and promoting empowerment.

    Access to Government Services

    • Facilitate Government Services: Facial recognition simplifies the authentication process at local e-government centers, allowing seamless access to government programs, land records, and important certificates. eKYC through Facial Recognition helps Senior citizens in pension, health benefits, etc. Government can keep accurate tab of orphans, special people, senior citizens of old age homes.
    • Disaster Relief: Identification and Aid Distribution: During natural disasters, facial recognition allows authorities to quickly identify victims and efficiently distribute aid, ensuring rapid aid to those in need.

    Ethical considerations are paramount

    AI facial recognition has great potential, but its widespread use raises significant ethical concerns that require careful consideration and improvement strategies: 

    1. Privacy and Data Security: 
    • Consent: In the wake of DPDP act, users must be fully informed about what is collected. The storage and use of facial data is subject to explicit consent for each application. The ongoing deepfakes worldwide is worth mention here.
    • Data Protection: Robust encryption protocols and strict access controls are essential to protect facial data from unauthorized access and potential misuse.
    1. Bias and Discrimination: 
    • Algorithmic Bias: Facial recognition algorithms can exhibit biases that lead to inaccurate identification or disproportionate targeting of certain demographic groups.
    • Fairness and Justice: Developers must prioritize fairness and justice in data collection and algorithm design to reduce the risk of perpetuating social bias.
    1. Surveillance and Civil Liberties:
    • Mass Surveillance: The widespread use of facial recognition for surveillance purposes raises concerns about the impact on individual privacy and civil liberties.
    • Regulatory Oversight: Clear regulatory and oversight mechanisms are essential to ensure responsible deployment and use of AI facial recognition systems.

    Navigating the complex landscape of AI facial recognition requires a fine balance between upholding ethical principles and protecting fundamental rights while harnessing the transformative potential of technology is need today. Technologists, policymakers, ethicists, and citizens need to help AI facial recognition become a force for positive change, shaping a future that promotes safety, efficiency and inclusion while respecting individual autonomy and dignity. Through thoughtful debate with society’s cooperation, transparent governance and ethical responsibility, this technology is for progress and prosperity based on principles of justice, equity and respect for human rights.

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  • How AI is Revolutionizing Supply Chain Management: A Deep Dive

    This article has been contributed by Atul Kumthekar, Co-Founder, 3-F Software – a Design Thinking Company.

    The use of artificial intelligence in various fields is increasing day by day. In this context, the supply chain does not fall behind. The supply chain is simply a distribution network that connects brands and consumers through distributors. In this article, let’s learn more about what a supply chain is, areas where AI can be used in the supply chain, how AI can be useful in enhancing the supply chain, and more.

    What Is A Supply Chain
    Problem And Approach So Far
    Areas Where Ai Be Used In Supply Chain?
    What Is Ai From Technological Standpoint?
    How Can Ai Be Useful In Supply Chain?

    What Is A Supply Chain

    If you are a living being, you are part of some supply chain! There is no escaping! Essentially it is a distribution network. From Brand to Consumers via Distributors Products and goods move from Brand to Consumer and Money flows in the reverse order. This is the best simplistic definition of supply chain that I have ever come across.

    This brings in a lot of complexities and the challenges thereby. Complexity is at multiple levels and scale because of various challenges:

    • Scale and affordability at various layers mean plethora of different solutions used from start to end. From excel sheet to SAP like expensive ERP
    • International nature of today’s world
    • Prediction of demand to meet supply in time
    • Management of unsold in case of retail chain
    • Inventory management at various levels
    Supply Chain Management
    Supply Chain Management

    Problem And Approach So Far

    Various integrations and APIs helped intercommunication between Tally like software to SAP and Excel both People have addressed various issues using the latest technologies of the day. Blockchain being a recent example especially for global trade. The blockchain technology proved that the documentation time saving is possible and also that assurance of quality and source can be guaranteed beyond doubt.

    But these technologies and solutions did not address more complex problems like demand predicting, analyzing vast data.

    Now Artificial Intelligence is the new kid in town to help ease out these complexities a bit!

    Areas Where Ai Be Used In Supply Chain?

    Now that we know what was possible so far and some clue to unsolved problems, let us look into the problem areas little more closely. I got following response when I enquired on ChatGPT which was pretty accurate! So, I am going to reproduce the same with my elaborations on interesting ones –

    1. Demand Forecasting: AI algorithms can analyze historical data, market trends, weather patterns, and other variables to predict demand more accurately. This helps in optimizing inventory levels and reducing stockouts or overstock situations.
    2. Inventory Management: AI-driven systems can optimize inventory levels by analyzing factors like lead times, demand variability, and supplier performance. This ensures that inventory is maintained at optimal levels, reducing carrying costs while ensuring products are available when needed.
    3. Route Optimization: AI algorithms can optimize delivery routes considering factors like traffic patterns, weather conditions, and delivery windows. This reduces transportation costs, improves delivery times, and minimizes fuel consumption.
    4. Supplier Relationship Management: AI can analyze supplier performance data to identify trends, assess risk, and predict supplier behaviour. This helps in making informed decisions about supplier selection, negotiation, and risk management.
    5. Warehouse Management: AI-powered systems can optimize warehouse operations by automating tasks such as picking, packing, and sorting. This improves efficiency, reduces errors, and lowers operational costs.
    6. Quality Control: AI can analyze sensor data and visual inspections to detect defects in products or packaging. This ensures that only high-quality products are shipped, reducing returns and improving customer satisfaction.
    7. Supply Chain Visibility: AI can provide real-time insights into the entire supply chain, allowing businesses to track inventory levels, monitor supplier performance, and identify potential bottlenecks or disruptions.
    8. Predictive Maintenance: AI can analyze equipment sensor data to predict when maintenance is needed, reducing downtime and preventing costly equipment failures.
    9. Risk Management: AI can analyze various risk factors such as geopolitical events, natural disasters, and supplier financial stability to identify potential risks to the supply chain. This enables businesses to develop contingency plans and mitigate risks proactively.
    10. Sustainability: AI can optimize supply chain processes to minimize environmental impact, such as reducing carbon emissions through optimized transportation routes or minimizing waste through better inventory management.

    But before I add my elaborations let us peek a bit into what are typical AI techniques

    What Is Ai From Technological Standpoint?

    The word artificial intelligence typically deals with large data. I used to mock AI saying this is our Ajji’s (Grandmother’s) wisdom! What a person gathers over years or our ancient culture have already noted down. But that’s more or less about how humans behave, individually Vs in masses. But let’s not divert there!! May be in some other blog

    It is impossible to make ANY sense out of the vast data that is flowing in today. The producing brands (Manufacturers) need to listen to those in a meaningful way, in order to save any costs and time. You can employ men (and women) power in all the countries you deal with. That is one possible solution. But then there is issue of miscreants and malicious feeds. And even any number of these will not match the scale and capability of technology today. So why not technology, if that is one way?

    The AI basically started with machine learning which rests heavily on statistics. Let’s say you have an excel sheet of student’s marks. And you want to know the distribution. Most likely you will get a Gaussian curve. Meaning most students near about average and few below and few above, the curve tapering down both directions. This is understandable.

    Gaussian Curves Example
    Gaussian Curves Example

    But now consider the problem – can I find out if students have copied? I will leave this problem to you and get back to me on any thoughts!

    Ah ha! Welcome to machine learning.

    A typical approach in machine learning is give enough sample data, ask the algorithm to understand the pattern and apply this learning to test data and judge the output and then think about improving output. Yes, you probably have guessed it right, that the output is probabilistic. You need to get comfortable with this! (And we are not going to quantum mechanics as yet)

    The above paragraph is the essence of Artificial Intelligence. The major differential between machine learning and AI started emerging with Large Language Models (LLM) which started putting chatGPT like tools into public hands. How do they work? Are they the advanced versions of Google search? Well, basically they can address much much much more parameters to analyze. From few hundreds to millions! That is amazing. Even our brains may not be doing so. Take a look at Hugging Face and you will get the picture. The company started with chatbot application and with multiple rounds of funding reached at LLM models. And if you care to read “Attention is all you need” mentioned in references at the end, you will need to look at Transformer architecture (see diagram below)

    Transformer ArchitectureTransformer Architecture - Source: http://rpradeepmenon.medium.com/
    Transformer Architecture – Source: http://rpradeepmenon.medium.com/

    With this, let’s get back to Supply chain problems.

    How Can Ai Be Useful In Supply Chain?

    Let us look at some of the problems mention in the earlier section (“Areas where AI be used in supply chain?”).

    Demand Forecasting is definitely the one. This is not humanely possibly and achievable by employing any number of employees in any number of countries. Will LLM be useful here? Definitely. This is because it fits into the criteria of what LLM kind of models can work on. Basically, millions of parameters.

    Inventory Management is related to Demand Forecasting. For a big brand, it is not just about warehouse but localized inventory to supply quickly to local market. You may have seen Duzo like B2C supplier having small storage locations nearby your area with many biker riders picking things from there and delivering in 10 minutes! What inventory to maintain at such local locations can be better judged only by AI models.

    Route Optimization a well-known problem in industrial engineering and operations research (Traveling salesman problem) The solution to this was once modelled as Simplex algorithm (Narendra Karmarkar) The large parametrization that is possible with LLM models will throw and interesting solutioning scenarios of solving this problem.

    Supplier Relationship Management also known as CRM (Customer Relationship Management) is an important area where sales and support are managed. Salesforce the world leader in this domain is funding good amounts for the growth in Artificial Intelligence and LLM (Large Language Models). Pretty soon we will see a day to day usable output from these efforts.

    Quality Control is an important area. During Covid days, this gained importance and quality people could not reach work location. The usual technique was to deploy cameras, send images which could be checked using AI with possible false positives but reducing the overall load. Radiology is one good example where this is used today.

    Predictive Maintenance is also undergoing big impact due to AI. More the historical data, better is the prediction and preventive measures, which save bigtime in repairs cost. You can send your support technicians for preventive maintenance in time than to fix things! I had personally developed and delivered an IOT solution for X-ray manufacturer to send technician based on number of X-rays taken instead of earlier method of end of year. No AI but you can sense where the next step could be!

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    Important!

    Having seen all this, you must have realized that AI is not a magic wand. Also, it is not an overnight solution. One needs to select an existing model, if not develop a new one, then customize it, play with it and most importantly mature it to predict better and better. All this happens asymptotically. Meaning the gap between actual solution and reality will keep reducing slowly but surely. Keep in mind the dynamics of reality is also dynamic! So, something that worked well may not work equally well in future.

    More importantly…

    All AI solution providers stress importance of human touch. The solution needs to be looked at from human perspective. This means that the output is not harmful to certain section of community, or simply very negative etc. And even in this space there are tools and datasets evolving to improve solution from this perspective.

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  • Medical Advancements and Challenges in AI Yet How Is It Changing the Industry?

    This article has been contributed by Dr. Sravani Reddy G, Founder & CEO, Soprav Health Consulting.

    AI is fundamentally transforming the healthcare industry by revolutionizing various aspects of patient care, diagnosis, treatment, and administrative processes. Through the utilization of advanced algorithms and machine learning techniques, AI enables healthcare providers to analyze vast amounts of data quickly and accurately, leading to improved clinical decision-making. Additionally, AI-powered technologies enhance efficiency in tasks such as medical imaging interpretation, predictive analytics for disease prevention, personalized treatment planning, and drug discovery. Moreover, AI-driven solutions streamline administrative tasks, optimize workflows, and reduce healthcare costs. Overall, AI is catalyzing a paradigm shift in healthcare, driving innovation, improving patient outcomes, and enhancing the overall quality and accessibility of healthcare services.

    The vast realm of artificial intelligence (AI) is rapidly evolving, pushing boundaries, and revolutionizing healthcare. Recent advancements, including improved access to extensive health data, faster computer processing, a growing pool of AI experts, and accessible AI tools, are seamlessly integrating AI into modern healthcare. Despite initial hesitancy, the healthcare sector is embracing AI to address workforce shortages, meet patient expectations, and leverage technological innovations.

    Managing the Intricacies of Healthcare Data
    Interpretability
    Ensuring Ethical Considerations and Patient Privacy
    Integration with Clinical Workflow
    Cost and Resource Constraints

    However, the healthcare sector has traditionally been slow to embrace such technology and it is essential to acknowledge that we are still in the early stages of this journey, with much ground left to cover. Some of the concerns surrounding involve:

    Managing the Intricacies of Healthcare Data

    While access to patient information has improved, AI integration faces a significant hurdle due to the intricacies and complexities of healthcare data. Unlike sectors with abundant and readily available data, healthcare data is diverse, complex, and fragmented across different systems. This presents unique challenges for AI implementation, requiring innovative strategies for integration, interoperability, and standardization.

    Interpretability

    Many AI models, such as deep learning algorithms, are often considered “black boxes” due to their complex nature, making it challenging for healthcare professionals to understand how they arrive at specific conclusions or recommendations. Improving the interpretability of AI systems is crucial for building trust and acceptance among clinicians.

    Ensuring Ethical Considerations and Patient Privacy

    In the healthcare sector, where decisions directly impact patient lives, ensuring ethical considerations and patient privacy is paramount. AI technologies must adhere to rigorous ethical standards and regulatory guidelines to safeguard patient data and maintain trust in healthcare systems. Transparency, accountability, and patient-centric approaches are essential to responsible AI integration.

    Total Data Storage Capacity Compared To The Total Amount Of Healthcare Data
    Total Data Storage Capacity Compared To The Total Amount Of Healthcare Data

    Integration with Clinical Workflow

    While some healthcare sub-sectors have experts familiar with basic AI tools, but many medical practitioners still face workflow issues. Integrating AI seamlessly into existing clinical workflows and EHR systems remains a challenge. Healthcare professionals require user-friendly interfaces and interoperable AI solutions that enhance existing practices without disrupting patient care or workflow efficiency.

    Cost and Resource Constraints

    Developing and implementing AI technologies in healthcare can be costly and resource-intensive, particularly for smaller healthcare facilities or resource-limited settings. Addressing cost barriers and providing adequate training and support for healthcare professionals to use AI tools effectively is essential for ensuring equitable access and adoption across different healthcare settings.

    Although challenges such as data complexity and regulatory obstacles persist, the adoption of AI in healthcare is steadily increasing. As the world becomes more interconnected, particularly through avenues like medical tourism, AI and ML present considerable opportunities to enhance the healthcare journey. It’s widely acknowledged that AI holds the potential to revolutionize patient care, emphasizing precision medicine and personalized services. Moving forward, it’s imperative that the advancement of AI in healthcare remains grounded in a commitment to innovation and empathy, ultimately striving to enhance outcomes and elevate the quality of life for individuals globally.

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  • The Impact of AI on Digital Marketing Campaigns and the Latest AI Technologies Shaping ROI and Campaign Optimisation in the Industry

    This article has been contributed by Prateek Sethi, Founder, Trip Creative Agency.

    The dawn of the 21st century significantly changed people’s personal and professional lives. Among other shifts, new-age technologies have gained considerable traction by altering the dynamics for the better. As a result, artificial intelligence (AI), formerly regarded as a futuristic concept, has established itself as a reality. This technology has revolutionised various industries, with digital marketing being no exception. Thus, this cutting-edge technology has become a necessity rather than a luxury over the years.

    According to a joint analysis by NASSCOM and BCG, India’s AI market is expected to reach $17 billion at a CAGR of 25–35% between 2024 and 2027. This expansion is attributed to various factors, including changing customer behaviour and increased enterprise technology spending, among others. In fact, everyone is familiar with the term artificial intelligence. It refers to the development of computer-generated programs and software capable of performing tasks that would require a human mind. These activities include learning, problem-solving, natural language comprehension, pattern recognition, visual information perception, depth perception and decision-making.

    So, beyond being a buzzword, AI has certainly become a critical tool, reshaping the way companies approach marketing campaigns and bringing in new avenues for creative, personalised, and impactful marketing campaigns that resonate deeply with audiences.

    Impact of AI on Digital Marketing Campaigns
    AI Technologies: Transforming the Future of the Marketing Industry

    Impact of AI on Digital Marketing Campaigns

    From campaign creation to optimisation, AI’s influence extends across the entire digital marketing spectrum.

    • Advanced profiling: Every business understands the need for profiling today. Without a thorough understanding of the target audience, marketers will not be able to develop tailored marketing strategies. Knowing the perfect client profile enables businesses to tailor messages and other information to their specific requirements and expectations. According to Deloitte research, simply putting the customer’s name in their emails can increase open rates by 5.2%, while more tailored communications show a rise of 11%–55%. However, maintaining and calculating every piece of data is time-consuming. Thus, with the ability to analyze vast amounts of customer data, including demographics, online behaviour, and past interactions, AI emerged as a helping hand, executing complicated consumer segmentation activities in real time.
    • Personalise the campaign: A personalised campaign has become a thing of today. Because nobody wants to receive a dull and generic message; the difference between ‘Hi there’ and ‘Hi XYZ’ is tremendous; when anything talks personally, people automatically feel more significant and interested. This is where AI applies customer insights to adapt messaging, content, and offers to specific tastes. Consider receiving product recommendations that are exactly what you need or social media ads that are relevant to your interests. This level of personalisation increases customer engagement and brand loyalty, providing desired outcomes for everyone.
    • Predictive Marketing: What if firms could predict the future and anticipate client requirements before they arise? While AI cannot tell businesses which lottery number to choose, it assists in determining the best marketing plan for a given situation. It accomplishes this by analysing data and evaluating habits to predict what the customer wants and when they want to buy. Thus, AI systems use historical data and user behaviour to forecast future actions. This allows marketers to anticipate client demands and proactively provide relevant information and offers, resulting in higher conversions and revenues.

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    AI Technologies: Transforming the Future of the Marketing Industry

    • AI-powered chatbots: AI chatbots have become critical for modern customer service. With their round-the-clock availability, they serve as virtual representatives, providing prompt and efficient assistance to customers. They can handle a wide range of basic queries, from product information to order status. By taking care of routine tasks, chatbots free up human agents to tackle complex issues, thereby improving the overall efficiency of the team. Furthermore, this not only helps businesses save time and money but also enhances the customer experience, leading to increased customer satisfaction and commitment.
    • AI-powered fraud recognition: AI enables marketers to detect fraudulent actions in real-time. This not only prevents organisations from losing ad revenue due to theft, but it also ensures that campaign measurements are right. AI systems can examine vast amounts of data and spot any suspicious patterns, allowing marketers to respond swiftly and prevent any damage. This new technology has changed the way marketers promote and made the Internet advertising environment more secure.
    • AI-driven A/B testing: When it comes to testing marketing efforts, typical A/B testing can be time-consuming and tiresome. However, with the help of AI, this procedure can be automated and expedited. AI algorithms may analyse various campaign components, such as headlines, pictures, and landing pages, to determine which ones work better than others. Using this iterative technique, AI can continuously recommend campaign modifications and optimise ad spending for optimum impact. This allows firms to get superior results from their marketing efforts more efficiently and effectively.
    Market Value of Artificial Intelligence (AI) in Marketing Worldwide from 2020 to 2028
    Market Value of Artificial Intelligence (AI) in Marketing Worldwide from 2020 to 2028

    It’s a Win-Win for All!

    There is no denying the fact that AI is revolutionising digital marketing by providing unrivalled data-driven insights and automation capabilities. Understanding the impact of AI and embracing strategic AI deployment enables businesses to design intelligent campaigns, forge stronger consumer connections, and achieve optimal results in the ever-changing marketing landscape. Thus, to stay ahead in the competitive world of digital marketing, businesses must embrace AI and use it to their advantage. Although nothing is going to replace the creative human controlling all this information and knowledge, for now.

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  • How Mobicule Utilise AI to Improve Debt Collection Process

    This article has been contributed by Siddharth Agarwal, Founder and Managing Director, Mobicule Technologies Pvt Ltd.

    The recovery of loans is frequently the top priority for lenders in the field of lending because the risk of defaulting is constant. Lenders are increasingly using technology-driven solutions to help in the recovery process as delinquency rates rise, as long as they stay within the bounds of legal regulations.

    Today’s digital age is characterized by a discernible trend away from traditional methods and toward digital services and client interactions. This change is especially noticed in India, where a new frontier in debt collection techniques is being shaped by the adoption of Artificial Intelligence (AI) and machine learning (ML). AI has become a crucial component of debt collection operations, providing opportunities for process optimization and streamlining. Integrating AI and ML technology has become imperative due to the increasing demand for quick and effective debt resolution solutions. These developments are radically changing the dynamics of interactions between lenders and borrowers, which will eventually result in better debt recovery outcomes.

    Mobicule is leading the way in this technological revolution with its all-inclusive debt resolution system that integrates AI and ML technologies. Through the use of these cutting-edge technologies, Mobicule can classify consumers into different risk groups according to a wide range of factors, such as past banking habits and borrower’s past payment patterns. This division makes it easier to create customized plans meant to reduce the risks involved with debt recovery. AI-powered solutions are excellent at focusing on particular customer groups via the best possible channels of communication, which reduces the workload for both the bank and the borrowers. Our platform can also detect early warning signs of possible defaults by using predictive analytics, which lowers bounce rates and prevents possible financial losses.

    Lenders are provided with actionable insights through real-time analytics and customizable dashboards, which facilitate the development and execution of efficient debt resolution plans. Automation features reduce errors and delays that come with manual operations by streamlining communication procedures. Examples include sending payment reminders by SMS, email, WhatsApp, voice bot, and IVR.

    Lenders must make sure that all correspondence complies with legal compliance requirements. AI enables omnichannel interaction by using data to start conversations through favoured channels and at the best moments, therefore maximizing communication tactics. Mobicule’s AI-powered technology customizes resolution techniques to each borrower’s unique scenario, maximizing success, in contrast to traditional one-size-fits-all approaches. The system also effectively handles massive amounts of data, classifying them into relevant legal avenue and expediting the debt resolution procedure. The platform is built intelligently and can be used across delinquency cycle which are pre, early, mid and late delinquency. To sight an example the platform can automate the entire settlement process without any manual intervention if it falls within mandates removing any bias in the processing.

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    Voice bots powered by AI examines communication between borrowers and agents to provide a more comprehensive grasp of the attitudes and preferences of borrowers. In a similar vein, chatbots driven by AI enable direct communication between borrowers and lenders, guaranteeing prompt responses and improved client experiences.

    Artificial intelligence (AI) technologies also provide enhanced security measures by spotting trends that point to previous fraudulent activity and identifying possible threats ahead of time. The re-engagement algorithms powered by AI are essential for promoting borrower compliance since they give priority to contacting borrowers who have interacted with payment links but have not yet fulfilled their obligations. Artificial intelligence (AI) is transforming debt collection procedures by increasing productivity of the team, improving borrower’s experience, working on the engagement rate and eventually deriving better results for lenders.

    Mobicule is a pioneer in products focused on mobile field force and has successfully deployed and managed some of the largest mobile field force implementations across Sales & Distribution, Telecom, and BFSI. With its experience and domain knowledge now spanning 2 decades it has established its niche in Debt Collection, KPI & Gamification, and Digital KYC integrated end to end with internal (core banking, EPR, CRM) and external systems (credit bureaus, govt portals). Backed by a strong R&D and adopting the latest and upcoming technologies it has managed to establish a niche market position. Mobicule’s steadfast vision and commitment to add value to its customers, employees, and all its stakeholders have put it on a rapid growth path to attain a leadership position in the business domains it caters to.

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  • Best AI Presentation Tools: Harnessing AI for Powerful Presentations

    Crafting presentations that captivate and inspire is an art form that combines strategic planning, compelling content, and dynamic delivery. In today’s fast-paced world, the ability to deliver powerful presentations is a skill sought after by professionals across all industries. Whether pitching a new idea, sharing insights, or rallying a team, mastering the art of presentation can elevate your message and leave a lasting impact.

    The advent of artificial intelligence has revolutionised the way we approach presentation development. AI-powered tools can help transform mundane slideshows into compelling visual narratives that engage and resonate with your audience. From design assistance to data analysis and speech coaching, these tools offer a comprehensive suite of features to enhance every aspect of presentation development. These tools can streamline content creation by scouring the internet for relevant information, providing suggestions for graphics and visual aids, and even assisting with speechwriting. They can also help with data analysis, automatically generating charts and graphs that effectively convey complex information visually appealingly.

    In this article, we’ll delve into some of the most powerful AI tools available, exploring how they empower presenters to deliver engaging, memorable presentations with confidence and flair.

    Best AI Presentation Tools

    PopAi
    Beautiful.ai
    SlideSpeak
    Tome
    SlidesAI
    Gamma

    What Is AI? | Artificial Intelligence | What is Artificial Intelligence?

    PopAi

    AI TOOL PopAi
    Launched 2023
    Free Trial available
    PopAi - AI Presentation Tool
    PopAi – AI Presentation Tool

    PopAi is an exceptional platform that harnesses Artificial Intelligence (AI) technology to revolutionise how people interact with digital tools. Its innovative and advanced features transform knowledge acquisition, content generation, and creative processes. 

    With Boosted Answers, Chat with Document, and AI Creation templates, PopAi empowers users to increase their productivity and efficiency, regardless of their field or profession. Boosted Answers provides instant and accurate responses to queries. At the same time, Chat with Document allows users to search for specific content and insights within a document. The AI Creation templates offer tailored solutions to streamline workflows and unlock users’ full potential, whether they are students, professionals, or creatives. 

    PopAi’s user-friendly interface ensures that users stay up-to-date with the latest information, quickly generate engaging content and foster innovation. Users can customise their experience based on their preferences and needs, making PopAi a highly personalised platform. With this, users can achieve their goals and make informed decisions with ease and confidence.

    Pricing

    Plan Pricing
    Basic Free
    Monthly Pro $9.9/month
    Monthly Unlimited $40/month

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    Beautiful.ai

    AI TOOL Beautiful.ai
    Launched 2018
    Free Trial available
    Beautiful.ai - AI Presentation Tool
    Beautiful.ai – AI Presentation Tool

    Beautiful.ai is a versatile online presentation software that simplifies the presentation creation process for individuals and businesses. It focuses on efficiency and visual appeal, offering a wide range of features to enhance productivity and elevate the quality of presentations.

    Users can access hundreds of customisable slides and presentation templates, which saves valuable time and helps jumpstart their ideas. The platform’s intuitive controls and layout variations enable users to create new designs in seconds, ensuring that every presentation is unique and impactful.

    From data visualisation tools to automatic animations and customisable themes, Beautiful.ai provides everything needed to bring ideas to life, maintain brand consistency, and impress the audience. Users can seamlessly collaborate with team members, control slides and branding, and track presentation metrics with viewer analytics. Advanced sharing options and compatibility with various devices empower users to present their best work anytime, anywhere.

    Pricing

    Plan Pricing
    Basic Free
    Pro $12/month
    Team $40/month

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    SlideSpeak

    AI TOOL SlideSpeak
    Launched 2023
    Free Trial available
    SlideSpeak - AI Presentation Tool
    SlideSpeak – AI Presentation Tool

    SlideSpeak offers a robust suite of AI tools designed to enhance productivity and streamline the creation of presentations and documents. Leveraging advanced AI technology, users can precisely summarise PowerPoint, Word, and PDF documents and generate presentations effortlessly based on their content. With the integration of ChatGPT, users can interact with their documents seamlessly, asking questions, requesting summaries, and gaining valuable insights. The platform supports many document types, allowing users to extract essential information efficiently. 

    SlideSpeak’s user-friendly interface makes it easy for individuals and businesses to harness the power of AI to master presentations and documents, ultimately saving time and improving workflow efficiency. SlideSpeak is free, providing users access to cutting-edge AI capabilities without financial commitment.

    Pricing

    Plan Pricing
    Free Plan $0
    Premium $19/month
    Premium Plus $24/month
    ficial intelligence (AI) market size worldwide in 2021 with a forecast until 2029
    Artificial intelligence (AI) market size worldwide in 2021 with a forecast until 2029

    Tome

    AI TOOL Tome
    Launched 2020
    Free Trial available
    Tome - AI Presentation Tool
    Tome – AI Presentation Tool

    Tome is an innovative AI-powered platform that empowers users to create polished presentations and documents quickly and effortlessly. With its intuitive interface and advanced AI features, Tome enables users to add structure and polish to their work, transforming text into compelling narratives with matching images. Whether it’s generating AI presentations, one-pagers, or immersive experiences, users can communicate their ideas effectively with just a few keystrokes. 

    Additionally, Tome offers clever themes, responsive layouts, and seamless integrations with interactive embeds, allowing users to design without constraints and draw viewers in with engaging content. The platform’s mobile-responsive presentation layouts ensure a seamless viewing experience across devices. At the same time, advanced analytics provide insights into audience engagement. From founders and startups to marketers and product teams, Tome caters to diverse users with its versatile capabilities and best-in-class templates. Trusted by industry leaders and praised for its fluidity and intuitiveness, Tome is revolutionising how ideas are shared and communicated in the digital age.

    Pricing

    Plan Pricing
    Basic $0
    Professional $16/month

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    SlidesAI

    AI TOOL SlidesAI
    Launched 2023
    Free Trial available
    SlidesAI - AI Presentation Tool
    SlidesAI – AI Presentation Tool

    SlidesAI offers a user-friendly solution for creating professional and engaging presentations quickly and effortlessly. With its AI-powered platform, users can say goodbye to tedious manual slide creation and generate polished presentations from any text in just a few clicks. The platform requires no design skills and can be set up in seconds, making it accessible to everyone. Users can choose from pre-designed colour and font presets or create custom looks to personalise their presentations. 

    SlidesAI supports over 100 languages, ensuring accessibility for a global user base. Additionally, the platform offers features such as searching citations, customising icons, accessing a premium stock image library, and, soon, exporting slides as videos. With a growing user base of over 10 million downloads and positive testimonials from satisfied customers, SlidesAI is a valuable tool for anyone looking to save time and streamline their presentation creation process. Plus, with a simple and transparent pricing structure, SlidesAI offers affordability and accessibility to users of all levels.

    Pricing

    Plan Pricing
    Basic $0
    Pro $10/month
    Premium $20/month

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    Gamma

    AI TOOL PopAi
    Launched 2023
    Free Trial available
    Gamma - AI Presentation Tool
    Gamma – AI Presentation Tool

    Gamma presents a revolutionary approach to presenting ideas powered by advanced AI technology. With its intuitive platform, users can effortlessly create beautiful presentations, documents, and websites without the need for design or coding skills. Users can access a versatile tool that generates fully functional presentations, documents, and webpages in seconds by signing up for free. This allows users to focus on refining and customising their content rather than starting from scratch. 

    Gamma’s AI generator ensures that presentations and documents are polished and on-brand with just one click, eliminating the need for tedious manual formatting. Users can easily restyle entire decks and work faster with flexible templates. Additionally, Gamma provides context with brevity, offering features such as a present mode for live presentations and nested cards for drilling into details.

    Pricing

    Plan Pricing
    Free $0
    Plus $8/month
    Pro $15/month

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    FAQs

    What are some of the top AI tools for creating presentations?

    Some of the most powerful AI tools for creating presentations include PopAi, Beautiful.ai, SlideSpeak, Tome, SlidesAI, and Gamma.

    Do I need design or coding skills to use AI presentation tools?

    Many AI presentation tools, such as SlidesAI and Gamma, are designed to be user-friendly and accessible even without design or coding skills.

    Can AI presentation tools support multiple languages?

    Yes, some tools like SlidesAI support over 100 languages, making them accessible to a global user base.

  • Revolutionizing Insurance in India: AI Ushers in a New Era

    This article has been contributed by Sanil Basutkar, Co-Founder & Head of Product & Marketing, Bharatsure.

    The Indian insurance sector has the potential to undergo a significant transformation, driven by the power of AI. For decades, the industry has relied on traditional methods that can be slow, cumbersome, and lack the sophistication to fully capture the nuances of individual risk profiles. AI, however, can revolutionize insurance in India, streamlining processes, enhancing accuracy, and ultimately, delivering a superior customer experience.

    Personalized Premiums Powered by AI Analytics
    AI Expedites Claims Processing for Faster Settlements
    AI-powered Tools for Enhanced Accuracy and Fraud Detection
    Challenges and Considerations: Data Privacy and Algorithmic Bias
    The Future of Insurance in India: Embracing AI for Innovation

    Personalized Premiums Powered by AI Analytics

    One of the most exciting applications of AI in insurance is its ability to generate personalized premium quotes. Traditionally, premiums have been based on broad categories and demographics. AI algorithms, however, can analyze vast amounts of data, including driving records, health history, or even social media activity (with consent), to create a more comprehensive understanding of an individual’s risk profile. This allows insurers to offer more accurate and competitive premiums, ensuring that policyholders pay a fair price for their coverage.

    For instance, imagine a young driver in India with a clean driving record and a history of participating in safe driving courses. Through AI analysis, the insurer might recognize this individual’s lower risk profile and offer a lower premium compared to the traditional one-size-fits-all approach. This not only benefits the policyholder but also encourages responsible behaviour.

    AI Expedites Claims Processing for Faster Settlements

    Claims processing has long been a pain point for both insurers and policyholders in India. Manual verification of documents and lengthy investigations can lead to delays in settlements, causing frustration for customers. AI is changing this landscape. By automating repetitive tasks and leveraging technologies like image recognition and natural language processing (NLP), AI can significantly expedite the claims process.

    Imagine a car insurance claim in India. An AI-powered system could analyze photos of the damage submitted by the policyholder, automatically extracting crucial details. NLP could then process the claim form, ensuring accuracy and completeness. This automation frees up human adjusters to focus on complex cases, leading to faster settlements and improved customer satisfaction.

    AI-powered Tools for Enhanced Accuracy and Fraud Detection

    Fraudulent claims can be a significant drain on insurance companies, ultimately impacting premiums for honest policyholders. AI presents powerful tools to combat this issue. Image recognition can identify inconsistencies in damage claims, while NLP can detect fraudulent patterns in claim narratives.

    For example, AI could analyze satellite imagery of a flooded area to verify the extent of damage claimed by a homeowner in India. Similarly, NLP could identify inconsistencies in a medical insurance claim by comparing the patient’s reported symptoms to their medical history. These AI-powered tools help deter fraudulent activity and ensure that claims are settled fairly and efficiently.

    AI use cases in Financial Service Industry Worldwide as of 2020
    AI use cases in Financial Service Industry Worldwide as of 2020

    Challenges and Considerations: Data Privacy and Algorithmic Bias

    Despite its immense potential, AI adoption in the Indian insurance sector comes with challenges. Data privacy is a paramount concern. As AI algorithms rely on vast amounts of personal data, ensuring its secure storage and responsible usage is critical. India’s robust data privacy regulations like the Personal Data Protection Bill (PDP Bill) provide a framework for addressing these concerns.

    Another challenge is algorithmic bias. AI algorithms can perpetuate existing societal biases if trained on incomplete or skewed data sets. Mitigating this requires continuous monitoring and adjustments to ensure AI models are fair and unbiased in their assessments.

    The Future of Insurance in India: Embracing AI for Innovation

    The future of insurance in India lies in embracing AI technologies. By leveraging its capabilities, insurers can drive innovation, enhance risk management, and deliver superior customer experiences.

    Imagine a future where AI-powered chatbots provide personalized insurance advice in local languages like Hindi or Tamil. AI could also play a role in proactive risk prevention, offering safety recommendations to policyholders based on real-time data analysis.

    The Indian insurance sector has an opportunity to become a global leader in AI adoption. By addressing data privacy concerns, mitigating algorithmic bias, and fostering a culture of innovation, insurers can unlock the full potential of AI and redefine the insurance experience for millions of Indian customers.

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  • Indian FMCG Consumer Engagement Revolutionised by AI

    The analysis by the global market research firm EY states that consumer goods companies have enormous opportunities to use AI to improve asset tracking, supply chain management, and consumer experience and engagement. The use of artificial intelligence (AI) technologies to improve customer centricity and operational efficiency is on the rise among Indian merchants. An overwhelming 82% of Indians surveyed by the EY consumer index are optimistic that artificial intelligence will one day make shopping much easier.

    Several industries have jumped on the bandwagon of innovation and adaptation in response to recent tech developments and the expansion of the internet. This trend has been especially accelerated by the fast-moving consumer goods (FMCG) industry’s collaboration with the e-commerce sector. According to McKinsey, E-commerce sales for consumer goods will quadruple from 2016 to 2025, reaching $1.8 trillion. With so much competition and so many brands entering the industry, AI is becoming an important differentiator for brands looking to remain ahead of the curve.

    AI is crucial to draw customers closer to the company. Finding reliable customer insights to improve data-backed decision-making is a persistent problem in the fast-moving consumer goods (FMCG) sector. Insights AI ensures organisations acquire in-depth customer behaviour data by combining powerful AI technologies like Emotion AI, Behaviour AI, and Generative AI. These innovations provide precise data for effective decision-making and aid brands in comprehending the wants and needs of target consumers.

    Customer wants and demands in the fast-moving consumer goods industry (FMCG) are dynamic, just like in any other industry. Thanks to AI’s data-processing prowess, organisations can swiftly and accurately adjust their marketing plans to meet the needs of their target audience. Insights AI has the potential to greatly enhance the quality and affordability of products and services in the Indian fast-moving consumer goods market.

    What are FMCG Products?

    Providing Forecasts to FMCG Companies
    Customised Suggestions

    Providing Forecasts to FMCG Companies

    Through AI, Fast-Moving Consumer Goods (FMCG) companies may better understand their customers’ habits and preferences, which in turn allows them to provide better service and encourages more participation. Artificial Intelligence also allows for substantial process automation, which saves time and money. According to an IBM poll, retail and brand executives expect cognitive automation capabilities to slash operational expenses by seven per cent on average.

    Adapting to the latest developments in data-driven technologies like deep learning, artificial intelligence, and machine learning can greatly benefit FMCG companies. There have been revolutionary shifts in the fast-moving consumer goods (FMCG) industry as a result of Machine learning and deep learning. With the massive amounts of data produced by the FMCG industry, Machine learning approaches help businesses identify and segment their target markets by analysing customer behaviour, preferences, and buying habits. Companies in the fast-moving consumer goods industry can use this information to improve their demand forecasting, personalise their marketing campaigns, and optimise product positioning and pricing tactics.

    Leading FMCG Companies in India by Market Capitalization
    Leading FMCG Companies in India by Market Capitalization

    Customised Suggestions

    AI is having a major impact on consumer choices by providing tailored suggestions. In contrast to 23% worldwide, 48% of Indians trust AI for personalised promotions and sales, according to the EY report.

    Online retailers, media streaming sites, and social media sites all use AI algorithms to sift through customers’ tastes, habits, and online activity. Customers have better shopping experiences, are more satisfied overall, and are likelier to a brand because of AI’s ability to provide personalised product recommendations based on their interests and preferences.

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    Using AI-based technologies to make buying decisions is becoming more and more acceptable to Indian shoppers. While just 58% of people worldwide are receptive to the idea of AI helping them make better purchasing decisions, 82% of Indians are. Indian customers have more faith in AI-generated personalised suggestions and AI-powered targeted marketing and sales. When asked for assistance, 82% of Indians would be willing to use a chatbot.

    Variations in consumer demand contain useful information for fast-moving consumer goods (FMCG) companies due to the many connections and patterns they contain. Discovering these insights is essential for getting ahead in the industry. FMCG companies need to process this data to make informed decisions about product placement, product prioritisation, workflow optimisation, marketing segmentation, pricing and offer launch timings. Applying state-of-the-art tools and algorithms allows for thorough planning and optimisation in the FMCG landscape. As a result, more and more fast-moving consumer goods (FMCG) companies are using AI-powered automation to reimagine the customer service they provide and boost engagement with their brands.

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    FAQs

    What is the future of AI in the FMCG industry in India?

    • AI is expected to play an increasingly important role in all aspects of the FMCG industry, from product development to marketing and sales.
    • As AI technology continues to evolve, we can expect to see even more innovative applications in the FMCG space.

    What are some of the benefits of using AI for FMCG companies in India?

    Some of the benefits of using AI for FMCG Companies are increased customer satisfaction and loyalty, improved operational efficiency, reduced costs and better decision-making.

    How can FMCG companies in India use AI to improve customer experience?

    • AI can provide personalized recommendations based on customer behaviour and preferences.
    • AI-powered chatbots can offer 24/7 customer support.
    • AI can help companies understand customer needs through sentiment analysis.