Top business use cases for AI

AI is already embedded in our daily lives. Every time we get recommendations on Netflix, directions from Google Maps, or suggestions in email from Gmail – that‘s AI algorithms at work. The same technologies are revolutionising businesses. AI refers collectively to information systems that can learn, reason, and interact with the world autonomously through data analysis and pattern matching rather than explicit programming. It encompasses innovations like: Machine learning, Neural networks and deep learning, Natural language processing (NLP), Robotic process automation (RPA), Computer vision

When combined creatively, AI systems enable breakthrough efficiency, insights, accuracy, and automation across business functions. Adoption is accelerating, with global AI investment growing at a 50% CAGR since 2015 to over $136 billion annually. Read Article

1. Finance

AI in finance is primarily used to enhance operational efficiency, reduce risks, and improve customer service. Financial institutions leverage AI to automate tasks.

Such as Fraud detection and prevention,Algorithmic trading, Risk management, Automated customer support (chatbots)

Tools:

• IBM Watson: Used for risk management and fraud detection. It uses AI to detect anomalies in financial transactions.
• H2O.ai: A platform used for creating predictive models for financial forecasting, credit scoring, and fraud prevention.
• TensorFlow & Keras: Open-source machine learning libraries that help in building financial models for stock market predictions and risk analysis.
• Splunk: Analyses real-time data to help detect fraudulent activities by identifying unusual patterns in transactions.

2. Healthcare

AI is revolutionising healthcare by improving diagnostics, personalising treatments, and predicting patient outcomes. AI models are trained on large datasets from medical records and research, helping doctors make more informed decisions. Medical imaging diagnostics (AI-driven radiology),Personalised treatment plan ,Drug discovery and development,Predictive analytics for patient outcomes

Tools:

• Google DeepMind: Used for medical imaging analysis. It helps doctors identify conditions such as cancer more accurately by analysing scans.
• IBM Watson Health: Provides AI-driven insights into patient data to assist in clinical decision-making and personalised care.
• NVIDIA Clara: A healthcare AI platform used for medical imaging, genomics, and drug discovery.
• BioPython: A tool for handling bioinformatics data, aiding in genomic research and drug development.

3. Retail & Ecommerce

AI helps e-commerce platforms and retail companies by personalising customer experiences, optimising inventory, and improving supply chain management. AI-powered recommendation systems drive more sales by showing relevant products to customers.

Tools:

• Amazon Web Services (AWS): Offers AI-driven tools for personalised product recommendations and demand forecasting.
• Salesforce Einstein: Provides predictive insights into customer behaviour, helping marketers optimise campaigns.
• Google Cloud AI: Optimizes supply chains using AI to predict demand and manage inventory level.

4. Manufacturing

AI is enabling manufacturers to optimise production processes, improve quality control, and predict equipment failures. With predictive maintenance powered by AI, manufacturers can save costs by addressing machine breakdowns before they happen. Predictive maintenance Quality control and inspection, Process optimization and automation

Tools:

• Siemens Mindsphere: A cloud-based industrial IoT platform that leverages AI to improve manufacturing efficiency and machine maintenance.
• Uptake: Predictive maintenance tool that uses AI to monitor machinery health and predict failures before they occur.
• SparkCognition: Uses AI for optimising industrial operations and improving asset performance through data-driven insights.
• Sight Machine: Provides real-time data visualisation and insights into manufacturing processes to enhance efficiency and quality.

5. Human Resources

AI in HR automates recruitment, enhances employee engagement, and predicts workforce needs. AI tools help screen resumes, match candidates to roles, and analyse employee sentiment, improving HR efficiency, Resume screening and candidate matching, Employee engagement analysis, Workforce planning and turnover prediction

Tools:

• HireVue: An AI-powered interview analysis tool that assesses candidates through video interviews and behavioural assessments.
• Pymetrics: Uses neuroscience-based games and AI to match candidates to roles based on personality traits and cognitive abilities.
• Hiretual: A talent sourcing tool that uses AI to find, engage, and recruit candidates across various platforms.
• Ultimate Software: Uses AI to analyse employee engagement and predict workforce trends, including turnover and productivity.

6. Marketing & Advertising

AI helps marketers automate and optimise campaigns, personalise content, and predict customer churn. It can analyse large datasets to create targeted ads, segment audiences, and improve customer engagement.

Use Cases:

• Targeted advertising
• Sentiment analysis for brand management
• Customer churn prediction

Tools:

• Adobe Sensei: Adobe’s AI-powered tool for automating and optimising marketing campaigns, including personalised content creation.
• HubSpot CRM: Uses AI to analyse customer data and provide insights for sales and marketing teams, helping them prioritise leads and improve conversions.
• Sprinklr: AI-powered tool for social media listening, sentiment analysis, and customer engagement.
• Tableau: A data visualisation tool often used in marketing analytics to create dashboards that provide insights into customer behaviour and campaign performance.

7. Logistics & Supply Chain

AI is transforming logistics by optimising routes, predicting demand, and automating inventory management. AI-driven solutions help companies save time and reduce costs by improving operational efficiency.Route optimization, demand forecasting, Inventory management automation. Read article

Tools:

• SAP Leonardo: A digital innovation platform that uses AI and IoT to optimise logistics and supply chains.
• ClearMetal: Uses machine learning to predict supply chain disruptions and optimise inventory levels.
• FourKites: A real-time supply chain visibility platform that leverages AI to track shipments and optimise logistics operations.
• Amazon Forecast: An AI service that helps with demand forecasting to ensure the right amount of stock is available at the right time.

Summary

AI is driving innovation across multiple domains. From finance and healthcare to retail and logistics, AI tools are enabling businesses to automate processes, derive insights, and improve decision-making. The integration of AI in these fields enhances efficiency, reduces costs, and helps in building customer-centric products and services. With tools like IBM Watson, Google DeepMind, and Salesforce Einstein, businesses can implement cutting-edge AI solutions tailored to their needs. Read More use cases

ADOPTION OF AI FOR BUSINESSES:

Across the breadth of industries, AI’s tendrils have wound their way into various facets, from conversational interfaces to operational refinement, data sifting, and content orchestration. Yet, this piece remains a testament to human authorship. With projections foretelling a global AI market valuation of US$407 billion by 2027, it’s no surprise that enterprises are voraciously vying for their portion of the AI windfall.

• 77% of companies are either using or exploring the use of AI in their businesses. 83% of companies claim that AI is a top priority in their business plan.
• AI could increase labour productivity growth by 1.5 percentage points over the next ten years. Globally, AI-driven growth could be nearly 25% higher than automation without AI.
• 56% of businesses are using AI to improve and perfect business operations.
• 51% are turning to AI to help with cybersecurity and fraud management.
• 47% harness AI tools in the form of digital personal assistants.
• 46% are using AI for customer relationship management.
• 40% are turning to AI for inventory management. Read More