5 Trends that Shaped Wealth in 2024 | #4 The AI Inclusion

In 2024, the integration of Artificial Intelligence (AI) into business operations reached a tipping point. AI is no longer a buzzword: Thanks to the strides it made in 2024, AI has become a ubiquitous force driving productivity, efficiency, and wealth creation. From automating routine tasks to reshaping customer experiences, AI is now central to business strategy, investment trends, and competitive advantage.

The adoption of AI extended beyond Fortune 500 companies. Indian startups, SMEs, and global conglomerates embraced AI to create new revenue streams and redefine operational efficiency. Here’s a closer look at how AI inclusion shaped wealth in 2024.

The First AI-Generated Advertisements

2024 saw the debut of fully AI-generated advertisements, revolutionizing brand storytelling and marking a paradigm shift in marketing strategy. Businesses scaled their creative efforts, tested ad variants instantly, and produced regionally relevant content at a fraction of the cost. Additionally, businesses adopting AI-driven marketing gained a competitive edge by enhancing customer engagement and boosting revenue.

Case in Point:

• Cadbury India’s AI Ad Campaign: Cadbury’s AI-based celebrity endorsement technology allowed for regional actors and sports stars to be digitally embedded into local brand campaigns. Personalized Diwali festival ads were created, allowing customers to generate custom greetings featuring Bollywood superstar Shah Rukh Khan.
  

• Nike’s Hyper-Personalized AI Ad Campaigns: By analyzing purchase behavior, app activity, and browsing history, Nike’s ads delivered hyper-personalized video content on platforms like Instagram and X (formerly Twitter).
  

Big Tech’s Role in AI Revolution

In 2024, Big Tech played a pivotal role in democratizing AI, making sophisticated AI tools accessible to businesses of all sizes. By embedding AI-driven capabilities into everyday business software, they enabled companies to automate workflows, enhance productivity, and reduce operational inefficiencies. Key innovations included AI-powered productivity tools that automated document generation, financial modeling, and real-time meeting summaries. Advanced generative AI assistants were introduced, capable of handling complex, multi-step tasks such as drafting business proposals, managing schedules, and generating personalized recommendations. This democratization of AI reduced the reliance on human intervention for repetitive tasks, driving efficiency gains for startups, SMEs, and large enterprises alike.

Key Announcements:

• Google - Duet AI for Workspace: Google’s Duet AI for Google Docs, Sheets, and Gmail automated workflows, provided instant meeting summaries, and generated content suggestions, which helped Indian startups and SMEs reduce administrative overhead.
• Microsoft - Copilot for Office 365: Microsoft’s Copilot transformed tools like Excel, Word, and Teams by offering features like automated proposal writing, financial model generation, and instant meeting note summaries. Corporates and MSMEs embraced Copilot to reduce dependency on manual labor, cutting costs significantly.
  

• Apple - Siri’s AI Upgrade: Apple’s Generative AI upgrade for Siri enabled it to handle multi-step commands, such as creating travel itineraries or generating expense reports. This enhanced productivity for users and introduced new use cases for AI in personal finance and business support.
  

AI in Healthcare

AI's role in healthcare extended far beyond simple automation — it became a catalyst for medical breakthroughs. By leveraging machine learning, predictive analytics, and large language models (LLMs), healthcare providers were able to offer faster diagnoses, personalized treatment plans, and more efficient drug development. India, with its vast healthcare ecosystem, witnessed the rapid adoption of AI, especially in early disease detection, medical imaging, and digital health platforms.

Case in Point:

• Apollo Hospitals (India) - AI for Early Disease Detection: Apollo Hospitals partnered with Microsoft Azure to develop an AI-powered early-detection system for cardiac diseases. This tool analyzes health records, blood reports, and lifestyle data to predict heart-related conditions, enabling preventive care.
  

• Narayana Health - AI-Based Imaging Analysis: Narayana Health leveraged AI diagnostic imaging to analyze X-rays, MRIs, and CT scans. AI reduced diagnostic time from 2 days to 2 hours, significantly accelerating cancer detection and treatment initiation.
• Dr. Reddy’s Laboratories - AI-Driven Drug Discovery: Dr. Reddy’s used AI-powered drug discovery platforms to shorten time-to-market for new drugs. AI models identified promising drug compounds and simulated their efficacy, expediting clinical trials.
  

AI in Manufacturing

• Tata Steel (India) - AI for Predictive Maintenance: Tata Steel’s Jamshedpur plant integrated predictive AI maintenance systems. Sensors embedded in heavy machinery detected potential malfunctions, reducing equipment downtime by 30% and saving operational costs.
  

• Mahindra & Mahindra - AI for Supply Chain Optimization: AI-driven demand forecasting models enabled Mahindra to optimize supply chains, reduce overstocking, and minimize material wastage. This resulted in a 20% reduction in excess inventory, improving working capital efficiency.
  

• Boeing - AI-Driven Quality Control: Boeing’s AI-enabled vision systems inspected aircraft components for manufacturing defects. AI’s visual recognition accuracy of 98% reduced production errors and rework costs.
  

• Foxconn (India) - Smart Robotics with AI: Foxconn’s Indian assembly units introduced AI-powered collaborative robots (cobots), enabling human-robot teamwork. This hybrid workforce increased assembly-line productivity by 25%.
  

AI Inclusion in Financial Services

The financial sector has consistently been at the forefront of AI adoption, with 2024 witnessing a deeper integration of AI into banking, investment advisory, and wealth management services. Financial institutions embraced AI to streamline client onboarding, accelerate loan approvals, and strengthen fraud detection. AI-powered robo-advisors, predictive analytics, and machine learning models were on the rise, offering personalised investment strategies, better forecasting of market trends and enabling data-driven insights.

Noteworthy Examples:

• Wealth Management - Robo-Advisory Boom: Indian platforms like Groww, Zerodha, and Kuvera launched AI-driven robo-advisors that created tailored investment portfolios based on user risk profiles. Waterfield Advisors introduced AI-powered insights for Discretionary Portfolio Management Services (DPMS), streamlining asset allocation strategies.
  

• HDFC Bank - AI-Powered Loan Approvals: HDFC’s AI-driven system reduced loan approval times from 48 hours to just 30 minutes, using real-time credit eligibility assessments.
  

• RBI - AI for Fraud Detection: The Reserve Bank of India (RBI) adopted AI models to detect fraudulent transactions in real time. This initiative reduced online payment frauds by 25%, enhancing trust in India’s digital payment ecosystem.
  

• JP Morgan’s AI Investment Research: JP Morgan’s AI-driven research assistant analyzed historical data, predicted stock price movements, and provided actionable insights to traders, which was subsequently adopted by Indian wealth advisory firms.
  

AI in Retail and E-commerce

AI-driven personalization reshaped the retail and e-commerce landscape in 2024, transforming consumer behaviours. Retailers leveraged AI to provide hyper-personalized shopping experiences, dynamic pricing models, and visual search technology. This shift led to increased conversion rates and higher customer retention. AI's role extended to inventory management, where predictive analytics models forecasted demand with higher accuracy, reducing overstocking and improving supply chain efficiency. The convergence of AI and e-commerce has not only boosted operational efficiency but also provided new investment avenues for wealth managers looking to capitalize on the growth of AI-enabled retail platforms.

• Myntra - AI-Driven Fashion Recommendations: Myntra’s AI-powered recommendation engine analyzed user clicks, preferences, and purchase history to offer personalized suggestions. This approach increased conversion rates by 40%.
  

• Amazon - Smart Pricing Algorithms: Amazon’s dynamic AI pricing models adjusted prices in real time based on demand, stock, and competitor prices. Consumers experienced frequent price changes on electronics and groceries.
  

In 2024, Artificial Intelligence truly went beyond the inflection point. AI applications are now a must-have for all businesses to survive and compete in this highly efficient world. As AI continues to evolve, it is important to be equipped with data-driven actionable insights to navigate the AI-coded world. In 2025, as wealth becomes more tech-enabled, the future of investment lies in agility, efficiency, and personalized AI-powered recommendations.