Trending February 2024 # Integrate Eventbrite Using Ai With 1000+ Applications # Suggested March 2024 # Top 7 Popular

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Event management automation is the process of automating the event business processes and simplifying the organizer’s tasks. The event automation helps event marketers, planners, and organizers plan an event and enables them to automate the entire event management process right from the event promotion and registrations to feedback.

Go through this post to learn how to plan an event checklist – The Ultimate Event Planning Checklist.

Now, out of this checklist, here are a few processes that you can automate using event management automation.

Event Planning and Preparation

Execution of Work

Analysis and Reports

Immediate Conduct of the Event


Strategic Thinking and Continuous Improvement

Managing Documents, Creativity, and Ethics

Event marketers can leverage event management automation to automate various other organizational tasks such as communication, control over schedule, risk analysis, optimization, resource allocation, and much more.

In this blog, we will help you understand how you can leverage event automation to make the whole event organization process easier.

Why You Should Automate Your Events?

Event automation is an excellent way to increase your productivity and efficiency. It also helps you extend the coverage of your events.

Before we go ahead and learn major reasons why you should start automating your event management tasks to get a successful event planned, let us check out some stats that can help you learn how event automation can be beneficial for your business.

Ease of Management

Event management automation helps event marketers simplify various event planning processes. With event automation, you can manage ticketing, registrations, event promotion campaigns, email marketing campaigns, etc. all using one common platform.

To get this integration done, you can use this excellent automation software – Appy Pie Connect. Appy Pie Connect helps you integrate multiple software to help you run your tasks smoothly.

Connect This Flow

Reduced Manual Event Tasks

By automating event activities, you free up the event team members’ time and help them focus more on the events. One of the best examples of reducing manual efforts can be automating the registration process and check-ins for the attendees. You can also integrate your event management software with Google Calendar to schedule the invitations, promotions, and much more.

Connect This Flow

Connected Solutions

Automation helps you connect multiple solutions based on promoting and marketing the event. For example, you can integrate your event management software, Eventbrite with Slack, to ease the communication process for the users. So, if they have any questions in their minds, they could right away send you a message and get an instant response.

Connect This Flow

Connect This Flow

Time & Cost Effective

Thinks of having different tools for managing different event planning tasks. Different tools for registrations, ticketing, payments, and much more. Imagine, how easy everything would be if you have one common software in an integrated package to manage all these activities and that too at the fixed price.

Let us take an example of payment automation. You can integrate Eventbrite with PayPal to make it easier for the users to make payments when they buy tickets for your event.

Connect This Flow

Instant customization

Event automation offers a huge room for customizations. Even if you are offering the same theme and features as others are, you can still add a pinch of your own touch to every aspect of your event using event automation. Here, the customization is quicker and instantaneous when compared to other traditional event management software.

Go through this post to come up with new event marketing ideas – Top 5 Event Marketing Strategies & Ideas – with Examples.

Comprehensive Database Generation

With event automation, you can easily generate and maintain a detailed database for everything present in your event checklist. It lets you perform event analytics and automatically generates a detailed report of every aspect integrated with it.

To save all this data somewhere in your database, you can integrate your Eventbrite with Google Drive. With this integration, you can store all your event-related information on your drive and access it whenever you want.

Connect This Flow

Optimized Event Marketing

When it comes to event marketing, there are two major areas that you need to cover – email marketing and social media promotion. To schedule your emails using automation, you can integrate Eventbrite with your Gmail account to send out emails at the fixed time, to a specific list of people.

Connect This Flow


Once you automate your event management tasks, you can plan large-scale events easily. I hope this article will help you implement automation in various aspects of your event checklist. There are many other automation ideas that you can implement in your event marketing and management strategy. Visit our Appy Pie Connect page to learn them better.

You can create an event website for free Appy Pie’s Event Website Builder to help more and more people know about your event. You can also attract more people and help the event attendees stay connected to your brand by posting post-event mages and videos.

You can also create an event app using Appy Pie’s Event App Builder to send your users the real-time event updates and ask for their feedback once the event is over. This helps you improve your upcoming events.

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How To Integrate Chatgpt With Whatsapp

Are you tired of waiting for the ChatGPT website to load every time you want to use it? Do you wish you could access ChatGPT faster by integrating it with your WhatsApp account? If you answered yes to either of these questions, you’re in luck! While there is no official way to directly incorporate ChatGPT into WhatsApp, there are a couple of methods you can try out. Learn How to integrate ChatGPT with WhatsApp, and get started.

Integrating ChatGPT with WhatsApp can help you streamline communication, save time, and improve customer satisfaction. By using the power of artificial intelligence, ChatGPT can handle a high volume of inquiries and provide quick and accurate responses to your customers.

With ChatGPT, you can also reduce the number of customer service agents you need, freeing up your team to focus on more complex issues. ChatGPT can also handle repetitive tasks, making your customer support process more efficient.

Also read: How to Use ChatGPT on WhatsApp

Step 1: Sign up for a ChatGPT account.

Step 2: Download the ChatGPT app from the App Store or Google Play Store.

Step 3: Open the app and sign in with your ChatGPT account.

Step 4: Tap on the “Chats” tab and then “New Chat.”

Step 5: Select “WhatsApp” as the chat type.

Step 6: Enter your WhatsApp number and then tap on “Continue.”

Step 7: You will be prompted to open WhatsApp and then send a message to the ChatGPT bot. Do so and then tap on “Continue.”

Step 8: That’s it! You should now see your WhatsApp messages in the ChatGPT app.

The first method to integrate ChatGPT with WhatsApp involves creating a WhatsApp bot and linking it to ChatGPT. Here’s how you can do it:

Step 1: Register for the WhatsApp Business Programming Interface (API) and create a flow for the chat. Then, use a chat developer to follow your chatbot and put the API chatbot on your phone.

Step 2: Get an OpenAI API. To do this, create an OpenAI account and visit its programming interface key page. Here, you can create a secret key.

Step 3: Use the OpenAI API to connect to the WhatsApp bot you created. However, note that there is a chance WhatsApp may block you if it detects that the integration is not genuine. So, proceed at your own risk.

The second method to integrate ChatGPT with WhatsApp involves using a Python script. Here’s how you can do it:

Step 1: Download the code from GitHub.

Step 3: Execute the “Whatsapp-gpt-principal” file in the terminal.

Step 4: Execute “” record in the terminal.

Step 5: Enter “Is” and hit enter.

Step 6: Enter “python” Your phone will be automatically configured to OpenAI visit page.

Step 7: Verify that you are a human by checking the “I’m a human” box.

Step 8: Go to your WhatsApp account and find OpenAI ChatGPT integrated there.

Before integrating ChatGPT with WhatsApp, there are a few requirements to consider:

API Key: You will need an API key from OpenAI to access ChatGPT and integrate it with WhatsApp.

WhatsApp Business API Account: You will need to have a WhatsApp Business API account set up to integrate ChatGPT with WhatsApp.

Technical Knowledge: Familiarity with APIs and basic coding skills will be helpful in integrating ChatGPT with WhatsApp.

Access to WhatsApp Web: You will need access to WhatsApp Web to set up the integration between ChatGPT and WhatsApp.

Data Privacy & Security: Ensure that you comply with data privacy and security regulations when integrating ChatGPT with WhatsApp.

By taking these requirements into consideration, you can ensure a smooth and successful integration of ChatGPT with your WhatsApp account.

Integrating ChatGPT with WhatsApp can be a game-changer for your customer service process. With the power of AI, you can provide quick, accurate, and personalized responses to your customers, leading to increased trust, loyalty, and satisfaction. By following the steps outlined in this article, you can easily integrate ChatGPT with your WhatsApp account and start reaping the benefits of AI-powered customer service.

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100+ Ai Use Cases & Applications: In

AI is changing every industry and business function, which results in increased interest in AI, its subdomains, and related fields such as machine learning and data science as seen below. With the launch of ChatGPT, interest in generative AI, a subfield of AI, exploded.

According to a recent McKinsey survey, 56% of organizations are using AI in at least one business function. To integrate AI into your own business, you need to identify how AI can serve your business, possible use cases of AI in your business. This article gathers the most common use cases covering marketing, sales, customer services, security, data, technology, and other processes:

Generative AI

Generative AI involves AI models generating output in requests where there is not a single right answer (e.g. creative writing). Since the launch of ChatGPT, it has been exploding in popularity. Its use cases include content creation for marketing, software code generation, user interface design and many others.

For more: Generative AI use cases.

Business Functions General solutions

Analytics Services: Satisfy your custom analytics needs with these e2e solution providers. Vendors are there to help you with your business objectives by providing turnkey solutions.

Automated Machine Learning (autoML): Machines helping data scientists optimize machine learning models. With the rise of data and analytics capabilities, automation is needed in data science. AutoML automates time consuming machine learning tasks, enabling companies to deploy models and automate processes faster.

Specialized solutions

Conversational Analytics: Use conversational interfaces to analyze your business data. Natural Language Processing is there to help you with voice data and more enabling automated analysis of reviews and suggestions.

E-Commerce Analytics: Specialized analytics systems designed to deal with the explosion of e-commerce data. Optimize your funnel and customer traffic to maximize your profits.

Geo-Analytics Platform: Enables analysis of granular satellite imagery for predictions. Leverage spatial data for your business goals. Capture the changes in any landscape on the fly.

Real-Time Analytics: Real-Time Analytics for your time-sensitive decisions. Act timely and keep your KPI’s intact. Use machine learning to explore unstructured data without any disruptions.

Call Analytics: Advanced analytics on call data to uncover insights to improve customer satisfaction and increase efficiency. Find patterns and optimize your results. Analyze customer reviews through voice data and pinpoint, where there is room for improvement. Sestek indicates that ING Bank observed a 15% increase in sales quality score and a 3% decrease in overall silence rates after they integrated AI into their call systems.

Call Classification: Leverage natural language processing (NLP) to understand what the customer wants to achieve so your agents can focus on higher value-added activities. Before channeling the call, identify the nature of your customers’ needs and let the right department handle the problem. Increase efficiency with higher satisfaction rates.

Call Intent Discovery: Leverage Natural Language Processing and machine learning to estimate and manage customer’s intent (e.g., churn) to improve customer satisfaction and business metrics. Sentiment analysis through the customer’s voice level and pitch. Detect the micro-emotions that drive the decision-making process. Explore how chatbots detect customer intent in our in-depth article on intent recognition.

Chatbot for Customer Service (Self – Service Solution): Chatbots can understand more complicated queries as AI algorithms improve. Build your own 24/7 functioning, intelligent, self-improving chatbots to handle most queries and transfer customers to live agents when needed. Reduce customer service costs and increase customer satisfaction. Reduce the traffic on your existing customer representatives and make them focus on the more specific needs of your customers. Read for more insights on chatbots in customer service or discover chatbot platforms.

Chatbot Analytics: Analyze how customers are interacting with your chatbot. See the overall performance of your chatbot. Pinpoint its shortcomings and improve your chatbot. Detect the overall satisfaction rate of your customer with the chatbot.

Chatbot testing: Semi-automated and automated testing frameworks facilitate bot testing. See the performance of your chatbot before deploying. Save your business from catastrophic chatbot failures. Detect the shortcomings of your conversational flow.

Customer Contact Analytics: Advanced analytics on all customer contact data to uncover insights to improve customer satisfaction and increase efficiency. Utilize Natural Language Processing for higher customer satisfaction rates.

Customer Service Response Suggestions: Bots will listen in on agents’ calls suggesting best practice answers to improve customer satisfaction and standardize customer experience. Increase upsells and cross-sells by giving the right suggestion. Responses will be standardized, and the best possible approach will serve the benefit of the customer.

Social Listening & Ticketing: Leverage Natural Language Processing and machine vision to identify customers to contact and respond to them automatically or assign them to relevant agents, increasing customer satisfaction. Use the data available in social networks to uncover whom to sell and what to sell.

Intelligent Call Routing: Route calls to the most capable agents available. Intelligent routing systems incorporate data from all customer interactions to optimize the customer satisfaction. Based on the customer profile and your agent’s performance, you can deliver the right service with the right agent and achieve superior net promoter scores. Feel free to read case studies about matching customer to right agent in our emotional AI examples article.

Survey & Review Analytics: Leverage Natural Language Processing to analyze text fields in surveys and reviews to uncover insights to improve customer satisfaction and increase efficiency. Automate the process by mapping the right keywords with the right scores. Make it possible to lower the time for generating reports. Protobrand states that they used to do review analytics manually through the hand-coding of the data, but now it automates much of the analytical work with Gavagai. This helps the company to collect larger quantitative volumes of qualitative data and still complete the analytical work in a timely and efficient manner. You can read more about survey analytics from our related article.

Voice Authentication: Authenticate customers without passwords leveraging biometry to improve customer satisfaction and reduce issues related to forgotten passwords. Their unique voice id will be their most secure key for accessing confidential information. Instead of the last four digits of SSN, customers will gain access by using their voice.

Data Cleaning & Validation Platform: Avoid garbage in, garbage out by ensuring the quality of your data with appropriate data cleaning processes and tools. Automate the validation process by using external data sources. Regular maintenance cleaning can be scheduled, and the quality of the data can be increased.

Data Integration: Combine your data from different sources into meaningful and valuable information. Data traffic depends on multiple platforms. Therefore, managing this huge traffic and structuring the data into a meaningful format will be important. Keep your data lake available for further analysis. 

Data Preparation Platform: Prepare your data from raw formats with data quality problems to a clean, ready-to-analyze format. Use extract, transform, and load (ETL) platforms to fine-tune your data before placing it into a data warehouse.

Data Visualization: Visualize your data for better analytics and decision-making. Let the dashboards speak. Convey your message more easily and more esthetically.

Data Labeling: Unless you use unsupervised learning systems, you need high quality labeled data. Label your data to train your supervised learning systems. Human-in-the-loop systems auto label your data and crowdsource labeling data points that cannot be auto-labeled with confidence.

Synthetic Data: Computers can artificially create synthetic data to perform certain operations. The synthetic data is usually used to test new products and tools, validate models, and satisfy AI needs. Companies can simulate not yet encountered conditions and take precautions accordingly with the help of synthetic data. They also overcome the privacy limitations as it doesn’t expose any real data. Thus, synthetic data is a smart AI solution for companies to simulate future events and consider future possibilities. You can have more information on synthetic data from our related article.

Finance business function led by the CEO completes numerous repetitive tasks involving quantitative skills which makes them a good fit for AI transformation:

Billing / invoicing reminders: Leverage accessible billing services that remind your customers to pay.

Invoicing: Invoicing is a highly repetitive process that many companies perform manually. This causes human errors in invoicing and high costs in terms of time, especially when a high volume of documents needs to be processed. Thus, companies can handle these repetitive tasks with AI, automate invoicing procedures, and save significant time while reducing invoicing errors.

Employee Monitoring: Monitor your employees for better productivity measurement. Provide objective metrics to see how well they function. Forecast their overall performance with the availability of massive amounts of data.

Hiring: Hiring is a prediction game: Which candidate, starting at a specific position, will contribute more to the company? Machine and recruiting chatbots‘ better data processing capabilities augment HR employees in various parts of hiring such as finding qualified candidates, interviewing them with bots to understand their fit or evaluating their assessment results to decide if they should receive an offer. 

HR Analytics: HR analytics services are like the voice of employee analysis. Look at your workforce analytics and make better HR decisions. Gain actionable insights and impactful suggestions for higher employee satisfaction.

HR Retention Management: Predict which employees are likely to churn and improve their job satisfaction to retain them. Detect the underlying reasons for their motive for seeking new opportunities. By keeping them at your organization, lower your human capital loss.

Performance Management: Manage your employees’ performance effectively and fairly without hurting their motivation. Follow their KPI’s on your dashboard and provide real-time feedback. This would increase employee satisfaction and lower your organization’s employee turnover. Actualize your employee’s maximum professional potential with the right tools.

You can also read our article on HR technology trends.

A 2023 survey conducted among global marketers revealed that 41% of respondents saw an increase in revenue growth and improved performance due to the use of AI in their marketing campaigns.

Marketing can be summarized as reaching the customer with the right offer, the right message, at the right time, through the right channel, while continually learning. To achieve success, companies can leverage AI-powered tools to get familiar with their customers better, create more compelling content, and perform personalized marketing campaigns. AI can provide accurate insights and suggest smart marketing solutions that would directly reflect on profits with customer data. You can find the top three AI use cases in marketing:

Marketing analytics: AI systems learn from, analyze, and measure marketing efforts. These solutions track media activity and provide insights into PR efforts to highlight what is driving engagement, traffic, and revenue. As a result, companies can provide better and more accurate marketing services to their customers. Besides PR efforts, AI-powered marketing analytics can lead companies to identify their customer groups more accurately. By discovering their loyal customers, companies can develop accurate marketing strategies and also retarget customers who have expressed interest in products or services before. Feel free to read more about marketing analytics with AI from this article.

To learn more about AI use cases in marketing, you can check out our complete guide on the topic.


Digital Assistant: Digital assistants are mature enough to replace real assistants in email communication. Include them in your emails to schedule meetings. They have already scheduled hundreds of thousands of meetings.


Sales Forecasting: AI allows automatic and accurate sales forecasts based on all customer contacts and previous sales outcomes. Automatically forecast sales accurately based on all customer contacts and previous sales outcomes. Give your sales personnel more sales time while increasing forecast accuracy. Hewlett Packard Enterprise indicates that it has experienced a 5x increase in forecast simplicity, speed, and accuracy with Clari’s sales forecasting tools.


Sales Data Input Automation: Data from various sources will be effortlessly and intelligently copied into your CRM. Automatically sync calendar, address book, emails, phone calls, and messages of your salesforce to your CRM system. Enjoy better sales visibility and analytics while giving your sales personnel more sales time.

AI-based agent coaching: Both AI and emotion AI can be leveraged to coach sales reps and customer service employees by:

Retail Sales Bot: Use bots on your retail floor to answer customer’s questions and promote products. Engage with the right customer by analyzing the profile. Computer vision will help you to provide the right action depending on the characteristics and mimics of the customer.

Meeting Setup Automation (Digital Assistant): Leave a digital assistant to set up meetings freeing your sales reps time. Decide on the targets to prioritize and keep your KPI’s high.

Prescriptive Sales: Most sales processes exist in the mind of your sales reps. Sales reps interact with customers based on their different habits and observations. Prescriptive sales systems prescribe the content, interaction channel, frequency, price based on data on similar customers.


Conversational AI company Haptik develops sales chatbots for companies, including Fortune 500 ones, to improve their conversational commerce capabilities. For instance, thanks to Haptik’s sales chatbot, Tata Cliq, an e-commerce platform, increased its cart addition rate by 2.4 times in three months.

Sales analytics

As Gartner discusses, sales analytic systems provide functionality that supports discovery, diagnostic, and predictive exercises that enable the manipulation of parameters, measures, dimensions, or figures as part of an analytic or planning exercise. AI algorithms can automate the data collection process and present solutions to improve sales performance. To have more detailed information, you can read our article about sales analytics.

Customer Sales Contact Analytics: Analyze all customer contacts, including phone calls or emails, to understand what behaviors and actions drive sales. Advanced analytics on all sales call data to uncover insights to increase sales effectiveness

Sales Call Analytics: Advanced analytics on call data to uncover insights to increase sales effectiveness. See how well your conversation flow performs. Integrating data on calls will help you to identify the performance of each component in your sales funnels.

Sales attribution: Leverage big data to attribute sales to marketing and sales efforts accurately. See which step of your sales funnel performs better. Pinpoint the low performing part by the insights provided by analysis.

Sales Compensation: Determine the right compensation levels for your sales personnel. Decide on the right incentive mechanism for the sales representatives. By using the sales data, provide objective measures, and continuously increase your sales representatives’ performance.

For more details on how AI is changing sales, you can check out our more comprehensive guide.

No code AI & app development: AI and App development platforms for your custom projects. Your in-house development team can create original solutions for your specific business needs.

Analytics & Predictive Intelligence for Security: Analyze data feeds about the broad cyber activity as well as behavioral data inside an organization’s network to come up with actionable insights to help analysts predict and thwart impending attacks. Integrate external data sources the watch out for global cyber threats and act timely. Keep your tech infrastructure intact or minimize losses. 

Knowledge Management: Enterprise knowledge management enables effective and effortless storage and retrieval of enterprise data, ensuring organizational memory. Increased collaboration by ensuring the right people are working with the right data. Seamless organizational integration through knowledge management platforms.

Natural Language Processing Library/ SDK/ API: Leverage Natural Language Processing libraries/SDKs/APIs to quickly and cost-effectively build your custom NLP powered systems or to add NLP capabilities to your existing systems. An in-house team will gain experience and knowledge regarding the tools. Increased development and deployment capabilities for your enterprise.

Image Recognition Library/ SDK/ API: Leverage image recognition libraries/SDKs/APIs to quickly and cost-effectively build your custom image processing systems or to add image processing capabilities to your existing systems.

Autonomous Cybersecurity Systems: Utilize learning systems to efficiently and instantaneously respond to security threats, often augmenting the work of security analysts. Lower your risk of human errors by providing greater autonomy for your cybersecurity. AI-backed systems can check compliance with standards.

Smart Security Systems: AI-powered autonomous security systems. Functioning 24/7 for achieving maximum protection. Computer vision for detecting even the tiniest anomalies in your environment. Automate emergency response procedures by instant notification capabilities.

Machine Learning Library/ SDK/ API: Leverage machine learning libraries/SDKs/APIs to quickly and cost-effectively build your custom learning systems or to add learning capabilities to your existing systems.

AI Developer: Develop your custom AI solutions with companies experienced in AI development. Create turnkey projects and deploy them to the specific business function. Best for companies with limited in-house capabilities for artificial intelligence.

Deep Learning Library/ SDK/ API: Leverage deep learning libraries/SDKs/APIs to quickly and cost-effectively build your custom learning systems or to add learning capabilities to your existing systems.

Developer Assistance: Assist your developers using AI to help them intelligently access the coding knowledge on the web and learn from suggested code samples. See the best practices for specific development tasks and formulate your custom solution. Real-time feedback provided by the huge history of developer mistakes and best practices.

AI Consultancy: Provides consultancy services to support your in-house AI development, including machine learning and data science projects. See which units can benefit most from AI deployment. Optimize your artificial intelligence spending for the best results from the insight provided by a consultant.


Autonomous things including cars and drones are impacting every business function from operations to logistics.

Driving Assistant: Required components and intelligent solutions to improve rider’s experience in the car. Implement AI-Powered vehicle perception solutions for the ultimate driving experience.

Vehicle Cybersecurity: Secure connected and autonomous cars and other vehicles with intelligent cybersecurity solutions. Guarantee your safety by hack-proof mechanisms. Protect your intelligent systems from attacks.

Vision Systems: Vision systems for self-driving cars. Integrate vision sensing and processing in your vehicle. Achieve your goals with the help of computer vision.

Self-Driving Cars: From mining to manufacturing, self-driving cars/vehicles are increasing the efficiency and effectiveness of operations. Integrate them into your business for greater efficiency. Leverage the power of artificial intelligence for complex tasks.

Course creation


For more: Generative AI applications in education

Creative Design

Virtual try-on

Trend analysis

For more: Generative AI applications in fashion

Patient Data Analytics: Analyze patient and/or 3rd party data to discover insights and suggest actions. Greater accuracy by assisted diagnostics. Lower the mortality rates and increase patient satisfaction by using all the diagnostic data available to detect the underlying reasons for the symptoms.

Personalized Medications and Care: Find the best treatment plans according to patient data. Provide custom-tailored solutions for your patients. By using their medical history, genetic profile, you can create a custom medication or care plan.

Drug Discovery: Find new drugs based on previous data and medical intelligence. Lower your R&D cost and increase the output — all leading to greater efficiency. Integrate FDA data, and you can transform your drug discovery by locating market mismatches and FDA approval or rejection rates.

Real-Time Prioritization and Triage: Prescriptive analytics on patient data enabling accurate real-time case prioritization and triage. Manage your patient flow by automatization. Integrate your call center and use language processing tools to extract the information, priorate patients that need urgent care, and lower your error rates. Eliminate error-prone decisions by optimizing patient care.

Early Diagnosis: Analyze chronic conditions leveraging lab data and other medical data to enable early diagnosis. Provide a detailed report on the likelihood of the development of certain diseases with genetic data. Integrate the right care plan for eliminating or reducing the risk factors.

Assisted or Automated Diagnosis & Prescription: Suggest the best treatment based on the patient complaint and other data. Put in place control mechanisms that detect and prevent possible diagnosis errors. Find out which active compound is most effective against that specific patient. Get the right statistics for superior care management.

Pregnancy Management: Monitor mother and fetus health to reduce mothers’ worries and enable early diagnosis. Use machine learning to uncover potential risks and complications quickly. Lower the rates of miscarriage and pregnancy-related diseases.

Medical Imaging Insights: Advanced medical imaging to analyze and transform images and model possible situations. Use diagnostic platforms equipped with high image processing capabilities to detect possible diseases.

Healthcare Market Research: Prepare hospital competitive intelligence by tracking market prices. See the available insurance plans, drug prices, and many more public data to optimize your services. Leverage NLP tools to analyze the vast size of unstructured data.

Healthcare Brand Management and Marketing: Create an optimal marketing strategy for the brand based on market perception and target segment. Tools that offer high granularity will allow you to reach the specific target and increase your sales.

Gene Analytics and Editing: Understand genes and their components and predict the impact of gene edits.

Device and Drug Comparative Effectiveness: Analyze drug and medical device effectiveness. Rather than just using simulations, test on other patient’s data to see the effectiveness of the new drug, compare your results with benchmark drugs to make an impact with the drug.

Healthcare chatbot: Use a chatbot to schedule patient appointments, give information about certain diseases or regulations, fill in patient information, handle insurance inquiries, and provide mental health assistance. You can also use intelligent automation with chatbot capabilities.

For more, feel free to check our article on the use cases of AI in the healthcare industry.

Manufacturing Analytics: Also called industrial analytics systems, these systems allow you to analyze your manufacturing process from production to logistics to save time, reduce cost, and increase efficiency. Keep your industry effectiveness at optimal levels.

Collaborative Robots: Cobots provide a flexible method of automation. Cobots are flexible robots that learn by mimicking human workers’ behavior.

Network investment optimization: Both wired and wireless operators need to invest in infrastructure like active equipment or higher bandwidth connections to improve Quality of Service (QoS). Machine learning can be used to identify highest ROI investments that will result in less churn and higher cross and up-sell.


This was a list of areas by business function where out-of-the-box solutions are available. However, AI, like software, has too many applications to list here. You can also take a look at our AI in business article to read about AI applications by industry. Also, feel free to check our article on AI services.

It is important to get started fast with high impact applications and generate business value without spending months of effort. For that, we recommend companies to use no code AI solutions to quickly build AI models.

Once companies deploy a few models to production, they need to take a deeper look at their AI/ML development model.

We examined the pros and cons of this approaches in our article on making the build or buy decisions regarding AI.

You can also check out our list of AI tools and services:

These articles about AI may also interest you:

And if you have a specific business challenge, we can help you find the right vendor to overcome that challenge:

Sources: Though most use cases have been categorized based on our experience, we also took a look at some sources before finalizing the list:

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.





Top 10 Ai Use Cases & Applications Insurers Must Know In 2023

According to Deloitte, in order to enhance their operational efficiency, insurers spended the most on AI technology. In 2023, for instance, 74% of insurance executives planned to increase their investment in AI (see Figure 2).

Many insurance operations, such as:

Can be automated by AI technologies such as OCR,  document processing, chatbots, and affective computing. The applicability and flexibility of AI models is the reason why insurance executives are interested in them. 

In this article, we demonstrate the top 10 AI use cases of AI insurance. 

Figure 2:  Insurers’ decisions about their spending on technology investments.

1. Application processing including insurance underwriting

Document capture technologies enable insurance companies to automatically extract relevant data from application documents and accelerate insurance application processes with fewer errors and improved customer satisfaction.

For more, feel free to check our article on AI in underwriting.

Claims processing

Claims processing includes multiple tasks, including review, investigation, adjustment, remittance, or denial. While performing these tasks, numerous issues might occur:

Manual/inconsistent processing: Many claims processing tasks require human interaction that is prone to errors.

Varying data formats: Customers send data in different formats to make claims.

Changing regulation: Businesses need to accord in changing regulations promptly. Thus, constant staff training and process updates are required for these companies.

2. Claims document processing

Claims processing includes multiple tasks, including review, investigation, adjustment, remittance, or denial. While performing these tasks, numerous issues might occur:

Manual/inconsistent processing: Many claims processing tasks require human interaction that is prone to errors.

Varying data formats: Customers send data in different formats to make claims.

Changing regulation: Businesses need to apply new regulations to their processes as soon as they are introduced. Thus, insurance companies must train their staff and update their processes constantly. 

Insurers can use NLP-driven technologies and document capture to  handle large volumes of documents. This can help companies process documents rapidly, save time and costs, detect fraudulent claims, and check if claims fit regulations.

You can also check our lists of AI tools and services:

You can read our article on the Top 3 Insurance Claims Processing Automation Technologies to learn more about claims processing automation.

3. Automated repair cost estimation

Insurtech companies can deploy AI models to perform repair cost estimation:

AI systems can receive accident images,

Analyze them,

Compare them to previous images they’d received for other cases, 

And provide an estimated repair cost accordingly in real time.  

For instance, Bdeo, an insutech business, uses computer vision models to enhance the claim adjustment process. As a result, insurers increase the efficiency of their claims processing and the accuracy of their estimations. 

4. Insurance pricing

According to the Word Economic Forum, 42 billion IoT-connected devices such as cars, fitness trackers, home assistants, smartphones, and smartwatches are expected to be used by 2025 globally. 

As these devices become more popular, the amount of consumer data rapidly increases.

IoT devices allow insurance companies to use the wearers’ real-time vitals data to use alongside other data, such as: 

Lab testing data, 

Biometric data, 

Claims data, 

And health data. 

When evaluating their customers’ risk profile. 

Ideally, this will result in more accurate insurance pricing, meaning less risky customers enjoying lower premiums and vice versa. This increases equitability, insurers’ profitability, and their market outreach].

You can also learn more about business insurance pricing. 

5. Document creation

Insurance companies need to generate high volumes of documents, including specific information about the insurer. 

While creating these documents manually is time-consuming and error-prone, using AI and automation technologies such as RPA can generate policy statements based on rules-based criteria, which minimizes mistakes, increases compliance, and ensures accuracy.

Learn more about document automation. 

6. Responding to customer queries

Conversational AI technologies such as chatbots can play a critical role while interacting with customers. As responding to customer queries can be a tiresome task, simple queries can be handled by chatbots, which enables employees to focus on higher value-adding activities.


For instance, Zurich Insurance automated 84% of customer queries thanks to Zuri, their insurance chatbot, which was designed by conversational AI company Haptik. As seen in Figure 3, Zuri can:

Manage policies.

Schedule a call back from the insurance company.

Help customers to make a claim etc.

Figure 3: Capabilities of Zuri

Source: Haptik

7. Understanding customers better 

Insurance companies can benefit from affective computing, also known as emotion AI, to understand customers better and take action according to their mental states. 

For instance, affective computing can pick up on the callers’ voice tone, volume levels, and enunciations to assess their level of anger, hopelessness, agony, etc. to intelligently route their calls to more experienced call agents to ensure their satisfactions and to address their needs as best as possible.  

8. Insurance fraud detection

About 30% of insureds have admitted to lying to their car insurance company to gain coverage in the US. Text analysis and AI-powered predictive analytics might detect fraudulent claims based on comparing the data captured from the claimant’s story with the insurance’s business rules.  

Insurance companies can also benefit from voice analytics to understand if a customer is lying while submitting a claim.

Learn more about the technologies powering insurance fraud detection. 

9. Personalized services

According to an Accenture study, 80% of insurance customers want more personalized experiences and are willing to disclose their personal data in exchange. 

By using AI, insurance companies can better understand their customers and offer customized products that enable individuals to only pay for the coverage they need. For instance, insurance companies can offer a customized policy interpreting the applicants’  driving data, such as their speeding tickets, the number of times they’ve been pulled over, the number of accidents, and more.

Data-driven services can increase  the appeal of insurance to a wider range of customers, especially considering that in the US, 9.2% of people have no health insurance and may be purchasing a policy for the first time. 

10. Appeals processing

After the claims are processed, some can face  appeals, which is automatable via a combination of AI, OCR, and RPA.  

Thus, insurers can reduce their expenditures while offering a faster appealing process for their customers.

Future of insurance with AI

You can  check out other AI applications in marketing, sales, customer service, healthcare, or analytics. 

You can also read our other articles about AI and insurance:

If you have more questions, do not hesitate to contact us:

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.





Considering Tco For Mobile Devices With Dedicated Applications

Ask an IT manager about using mobile devices for dedicated applications, and the first thing that comes up is total cost of ownership (TCO). Whether it’s employees carrying around electronic catalogs to help customers, or wine lists on tablets making it easier for clients to see what’s available, every aspect of digital transformation comes down to cost.

Fortunately, there are lots of ways to change that equation and make mobile devices a cost-effective way to deliver dedicated applications to staff, whether it’s in the back office and warehouse, engaging customers on the retail floor, tablets locked into kiosks or anyone who needs accurate, timely information in your organization. Samsung Knox Configure, a cloud-based service from Samsung that supports all of their Android devices, is the first step to customizing your devices.

What Is Knox Configure?

Knox Configure is a tool that lets the IT manager create a predictable and secure configuration that will automatically be downloaded by a Samsung smartphone or tablet the very first time it is turned on — and redownloaded and applied even if the device is reset to factory defaults.

Get Your Ultimate Guide to Knox Configure

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Learn how to optimize tablets for your unique business needs using Samsung Knox Configure. Download Now

More Than Customization: The Knox TCO Advantage

Knox Configure also inherently acts as a mobile device management (MDM) and enterprise mobility management (EMM) tool, but comes with a tighter focus: building secure configurations to cut the time required to deploy a new device to the bare minimum.

A security benefit of Knox Configure — especially over standard MDM tools — is its capability to control hardware features of Samsung’s Android devices. A Knox Configure kiosk profile, for example, can specify which wireless network to use, enable or disable hardware controls (such as volume and brightness), personalize what types of alerts can pop up, control how and when screen savers will appear or how screen rotation is handled. Add that to traditional security controls, such as restricting what applications can run and what websites can be visited, or how security and software updates are applied, and Knox Configure makes devices secure enough to hand to customers without fear of introducing a data breach.

Unlike “golden master” deployment tools that IT managers might already be using for desktops and laptops, Knox Configure doesn’t require special servers or expertise. Once you’ve identified an application you want to deploy in a dedicated mode, you can create a profile, apply it to a device — and that’s all the work needed.

If this sounds interesting for a single application, consider the possibility of having a wide variety of dedicated application devices. Deciding what application runs on what device is just a matter of applying a profile in the Knox Configure portal — which means that you can easily scale up or down the number of devices as needed, and repurpose a device from one application to another whenever needed. The TCO of devices managed under Knox Configure makes dedicated applications easily affordable for businesses of any size.

Still wondering how smartphones and tablets can become dedicated application devices for your business? Download our free guide to all of Knox Configure’s capabilities, or watch a roundtable discussion about the benefits of customizing devices.

Using Chatgpt To Create Prompts For Ai Art

There are so many great resources available on the internet about creating prompts, some even try to sell you their prompts – don’t fall into that trap. You don’t need to buy prompts when there is so much freely available information out there.

I saw this amazing technique for Nick who documented his whole process in his twitter thread. He also plans to share more on his Youtube channel so make sure you follow and subscribe to him on his socials. This post would not be possible without his great work.

What do you need?

In order to be able to follow the below and create your own series of prompts you need to have access to:

Midjourney – AI Art creation tool run via Discord. You can subscribe to their service but if you are new you’ll get some free credits. If you need to know how to get started here check out this blog “Midjourney – start your journey”

Discord – you need a free account to be able to use Midjourney

ChatGPT – of course you need access to ChatGPT for this.

Note: By the time this post was published Midjourney released its v5 model for AI image creation. Below Images are all generated using v4 model but the prompts will work on v5 as well.

Nick’s Process

Firstly he uses ChatGPT and asks it to create:

Nick explains that Additive Prompting is dynamic & modular by design, so it works well in the table format. If you’re after something specific, let ChatGPT know at the end of your prompt. For example… …10 rows of data where: Composition = “Editorial Style Photo” Room Type = “Living Room”

You can simply copy the rows or ask ChatGPT will to go a step further, Nick explains: You can copy & paste any row into Midjourney and it’ll work great. Or, you can send a follow-up request and ask: “Please write each row as a comma-separated sentence. Append each sentence with –ar 16:9”

There you go, infinite images with a good Additive Prompt structure and ChatGPT hack. If you want new data, just ask for “10 more rows of data” Now that you have a strong foundation to build off, you can tweak and edit the outputs to whatever you’d like.

Follow @nickfloats on Twitter and also on YouTube he will releasing content there as well. Prompt credit goes to Nick for sharing this in his Twitter thread.

Prompt: Editorial Style photo, Eye Level, Traditional, Library/Study, Bookshelves, Wood, Leather, Desk Decor, Artwork, Dark Tones, Pottery Barn, Table Lamp, London Townhouse, Morning, Sophisticated –ar 16:9

Editorial Style Photo, Eye Level, Modern, Living Room, Fireplace, Leather and Wood, Built-in Shelves, Neutral with pops of blue, West Elm, Natural Light, New York City, Afternoon, Cozy, Art Deco:: Additive::0 –ar 16:9

Editorial Style Photo, Off-Center, Mid-Century Modern, Living Room, Eames Lounge Chair, Wood, Leather, Steel, Graphic Wall Art, Bold Colors, Geometric Shapes, Design Within Reach, Track Lighting, Condo, Morning, Playful, Mid-Century Modern, Iconic, 4k –ar 16:9

Editorial Style Photo, Eye Level, Modern, Living Room, Fireplace, Leather and Wood, Built-in Shelves, Neutral with pops of blue, West Elm, Natural Light, New York City, Afternoon, Cozy, Art Deco:: Additive::0 –ar 16:9

Editorial Style photo, Eye Level, Traditional, Library/Study, Bookshelves, Wood, Leather, Desk Decor, Artwork, Dark Tones, Pottery Barn, Table Lamp, London Townhouse, Morning, Sophisticated –ar 16:9

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