50 AI usecases / applications in 2018: In-depth guide

50 AI usecases / applications in 2018: In-depth guide

AI is changing every industry and business function. We are tracking the most impactful AI use cases here. This is meant to be a list that grows over time so feel free to contribute with your comments, this list is definitely not comprehensive now.


Optimize Pricing & Placement

Pricing optimization: Optimize markdowns to minimize cannibalization while maximizing revenues.

Merchandising optimization:  Leverage machine learning and big data to optimize your online or offline merchandising.

Shelf audit/analytics: Use video, images or robots on the retail area to audit and analyze your use of shelf space.

Visual Search Capability: Leverage machine vision to enable your customers to search your products by image or video to immediately reach their desired products.

Image tagging to improve product discovery: Leverage machine vision to tag your images taking into account your users’ preferences and relevant context for your products.

Optimize marketing spend

Neuromarketing: Leverage neuroscience and biometric sensors to understand how your content impacts your audience’s emotions and memory.

Marketing personalization: Reach the right customers, at the right time, through the right device and channel with the right message.

Context aware advertising: Leverage machine vision and Natural Language Processing to understand the context where your ads will be served to protect your brand

Personalize Recommendations:

Recommendation personalization: Leverage customer data to reach customers with personalized recommendations via email, site search or other channels.

Connect & Leverage Customer Feedback

Social media monitoring: Leverage machine learning to optimize the channel, target audience, message and timing of your social media posts.

Social media optimization: Leverage machine learning to optimize the channel, target audience, message and timing of your social media posts.


Analytics: Connect all your marketing data and KPIs automatically. Act on your data to manage campaigns, trigger alerts and improve your marketing efficiency

Social analytics & automation: Leverage Natural Language Processing and machine vision to analyze and act upon all content generated by your actual or potential customers on social media, surveys and reviews.

PR analytics:Learn from, analyze, and measure your PR efforts.

You can check out our complete guide on the topic as well.


Forecast sales

AI allows automatic and accurate sales forecast based on all customer contacts and previous sales outcomes.

Empower sales reps

Lead generation: Use a comprehensive data profile of your visitors to identify which companies your sales reps need to connect to.

Predictive sales/lead scoring: Predict customers’ likelihood to convert based on 3rd party and company data, allowing your sales reps to prioritize effectively.

Sales content personalization and analytics: Preferences and browsing behavior of high priority leads are analyzed to match them with the right content, aimed to answer their most important questions.

Automate sales activities

Sales data input automation: Sata from various sources will be effortlessly and intelligently copied into your CRM

Sales rep response suggestions: AI will suggest responses during live conversations or written messages with leads

Meeting setup automation (digital assistant): Leave a digital assistant to set up meetings freeing your sales reps time.

Sales rep chat/email bot: Chatbots are ideal to answer first customer questions. if the chatbot decides that it can not effectively serve the customer, it can pass those customers to human agents.

Sales analytics & performance management

Sales attribution: Leverage big data to attribute sales to marketing and sales efforts accurately

Customer sales contact analytics: Analyze all customer contacts including phone calls or emails to understand what behaviors and actions drive sales.

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

Customer service

Identify customer issues with social listening and ticketing solutions powered by Natural Language Processing capabilities.

Authenticate customers with biometrics

Assign agents to customers

Call classification systems leverage Natural Language Processing to understand what customer is trying to achieve enabling your agents to focus on higher value added activities.

Intelligent call routing systems route calls to most capable agent available. Customer’s preferences from previous calls and agents’ expertise and communication styles are analyzed to optimize customer’s experience.

Automate agent activity

Call intent discovery Leverage Natural Langugage Processing and machine learning to estimate and manage customer’s intent (e.g. churn) to improve customer satisfaction and business metrics

Customer service response suggestions Bots will listen in on agents’ calls suggesting best practice answers to improve customer satisfaction and standardize customer experience.

Customer service chat bots: Let 24/7 functioning, intelligent, self improving chat bots to handle most queries and transfer customers to live agents when needed.

Chat bot testing: Automated bot testing frameworks allow your bot to be thoroughly tested.

Customer service analytics

Chat bot analytics: Chatbots are much more free-text heavy than other digital products. Intelligent analytics tools enable teams to extract insights from bot usage.

Call analytics: Advanced analytics on call data to uncover insights to improve customer satisfaction and increase efficiency

11- Survey&review analytics:Leverage Natural Langugage Processing to analyze text fields in surveys and reviews to uncover insights to improve customer satisfaction and increase efficiency

We have a more extensive article on this topic as well.


Robotics: Factory floors are changing with programmable collaborative bots that can work next to employees to take over more repetitive tasks.

Intelligent or cognitive automation: The white collar equivalent of robots is Robotic Process Automation. Programmable bots can complete repetitive copy/paste & simple data processing tasks since 2000s. However with the advance of AI, these bots are now acquiring more decision making skills and automating more challenging tasks.


Hiring: Hiring is a prediction game: Which candidate, starting at a specific position, will contribute more to the company? Machine’s better data processing capabilities augment HR employees in different 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.


Patient Care

Assisted or automated diagnosis & prescription: AI audit systems minimize prescription errors and give a chance to find accurate disease.

Pregnancy Management: Monitor mother and fetus to reduce mother’s worries and enable early diagnosis

Real-time prioritization and triage: Prescriptive analytics on patient data to enable accurate real-time case prioritization and triage.

Personalized medications and care: Find the best treatment plans according to patient data reducing cost and increasing effectiveness of care

Patient Data Analytics: Analyze patient and/or 3rd party data to discover insights and suggest actions.

Medical Imaging and Diagnostic

Early diagnosis: Analyze chronic conditions leveraging lab data and other medical data to enable early diagnosis

Medical imaging insight: Advanced medical imaging to analyze and transform images and model possible situations.


Drug discovery: Find new drugs based on previous data and medical intelligence.

Gene analysis and editing: Understand gene and its component. Predict the impact of gene edits.

Device and drug comparative effectiveness

Healthcare Management

Brand management and marketing: Create an optimal marketing strategy for the brand based on market perception and target segment.

Pricing and risk: Determine the optimal price for treatment and other service according to competition and other market conditions.

Market research: Prepare hospital competitive intelligence.

We have only scratched the surface here. To see all AI use cases, feel free to:

Explore our library of AI use cases

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

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