Artificial intelligence (AI) may have a more significant impact on the lives of humans than the telephone or the internet. For the tech-inclined among us, AI integration in one form already powers our lives; within ten years, it will become pervasive in almost every aspect of society. The grease that facilitates every purchase, making every interaction a smooth and thought-out one. At least, that is the plan.

If time is our most valuable commodity, AI aims to save more by broadly improving efficiency and adapting to customer needs across an infinite spectrum of habits and lifestyles. AI integration is at hand, from how traffic flows to how we research, produce, and purchase everything.

From social media, a multi-trillion-dollar industry, to AI algorithms used for content moderation, sentiment analysis, and targeted advertising on social media platforms. AI-generated art and music are becoming more common in entertainment; as ‘smart cities’ pop up worldwide, AI-driven solutions for traffic management, energy optimization, and public safety are happening in real-time.

Finally, one must respect the sheer size of AI today, in 2024, but also the almost unimaginable growth forecast:

According to Fortune Business Insights,

“The global artificial intelligence market size was valued at $428.00 billion in 2022 & is projected to grow from $515.31 billion in 2023 to $2,025.12 billion by 2030, representing a CAGR of 21.6%…”

Few markets are expected to grow from half a trillion today to over $2 trillion in just 7 years. Investors can no longer afford to ignore AI, and because it permeates every sector, it can seem overwhelming. Here are the top 5 sectors AI integration will impact the most and, along with them, an actionable list of subsectors for investors to target.

Top 5 Artificial Intelligence (AI Integration) Sectors

Healthcare: AI is being used for medical image analysis, drug discovery, patient risk prediction, and improving healthcare operations. In 2021, artificial intelligence (AI) use in healthcare was worth around US11 billion worldwide.

Statista states,

“It was forecast that the global healthcare AI market would be worth almost 188 billion US dollars by 2030, increasing at a compound annual growth rate of 37 percent from 2022 to 2030.”

A compound growth rate of nearly 40% makes AI and healthcare one of the fastest-growing subsectors of this new paradigm. While everyone wants a personalized, unique experience regarding their health, optimizing tech while harnessing the power of AI is expected to improve patient outcomes.

Here is a real-world example of AI in healthcare that improves patient outcomes today. AI algorithms for medical image analysis, particularly in radiology, are being widely adopted. AI-powered image analysis can help radiologists detect and diagnose diseases more accurately and quickly, leading to better patient outcomes. Here’s how it works:

Medical Imaging Diagnosis: AI systems can precisely analyze medical images such as X-rays, MRIs, and CT scans. For instance, AI algorithms can identify abnormalities, tumors, fractures, or other conditions in these images.

Faster Diagnoses: AI can process images much faster than a human radiologist. This speed is critical in emergencies or when rapid diagnosis is essential for effective treatment.

Reduction in Human Errors: Even the most experienced radiologists can make mistakes due to fatigue or distractions. AI doesn’t suffer from these issues and can provide consistently accurate results.

10 Subsectors where AI is expected to significantly impact Healthcare:

  • Disease Detection and Diagnosis: AI-powered diagnostic tools can assist healthcare professionals in identifying diseases and medical conditions more accurately and quickly. For example, AI can analyze medical images like X-rays and MRIs to detect anomalies.
  • Personalized Medicine: AI can analyze genetic data and patient histories to develop customized treatment plans. This can lead to more effective treatments with fewer side effects.
  • Drug Discovery: AI accelerates drug discovery by analyzing massive datasets to identify potential drug candidates and predict their efficacy.
  • Predictive Analytics: AI can analyze patient data to predict disease outbreaks, patient readmissions, and patient deterioration, allowing healthcare providers to intervene earlier.
  • Telemedicine and Remote Monitoring: AI-powered telemedicine platforms and wearable devices can monitor patients remotely, enabling more accessible healthcare and early detection of health issues.
  • Natural Language Processing (NLP): NLP algorithms enable healthcare providers to extract valuable information from unstructured clinical notes, improving decision-making and patient care.
  • Medical Records Management: AI can help streamline and organize electronic health records (EHRs), making them more accessible and reducing administrative burden.
  • Robot-Assisted Surgery: AI-powered surgical robots enhance precision and reduce the invasiveness of surgeries, leading to faster recovery times for patients.
  • Drug Adherence and Compliance: AI-driven applications can remind patients to take medications, improving adherence to treatment plans.
  • Healthcare Chatbots: AI-driven chatbots can provide patients with information, schedule appointments, and answer basic medical questions, improving patient engagement and reducing administrative workload.

AI integration in healthcare comes with challenges related to data privacy, regulatory compliance, and ethical considerations. However, the potential benefits, including improved patient outcomes and more efficient healthcare delivery, make AI an area of continued growth and investment in the healthcare sector in North America. The overall trend is towards greater integration of AI technologies. While all large healthcare providers are implementing some form of AI, reviewing the R&D division and the amount allocated to AI is a great way to determine the potential healthcare leaders of tomorrow.

Finance and Fintech: AI integration for fraud detection, algorithmic trading, customer service chatbots, and credit risk assessment in the financial sector.

Future Market Insights believes AI in fintech was valued at $10.1 billion in 2021 but will see compound annual growth of 16.5% through 2032, reaching $54 billion.

One of the key sectors is cyber and banking fraud.

This is not surprising, as cyber criminals make about $1.5 trillion in profits annually, according to research from 2018.

Virtualization-based security firm Bromium released a study that portends some cyber criminals are making up to $2 million per year. The study found that even mid-level cyber criminals were making $900,000 per year.

Bromium CIO Gregory Webb stated,

“Cybercrime is a lucrative business, with relatively low risks compared to other forms of crime.”

Click here to read the entire article, published on in 2018 by Warwick Ashford.

As the digitization of everything accelerates, the need to stop cybercrime on its track and provide customers with secure services is greater than ever.

Artificial intelligence (AI) already significantly impacts North America’s finance and fintech industries.

Here are the top five subsectors and ways AI is transforming fintech:

  1. Algorithmic Trading: AI-powered algorithms analyze vast amounts of financial data and execute trades at high speeds, making markets more efficient and enabling quantitative trading strategies. AI can more effectively identify market trends, anomalies, and arbitrage opportunities than human traders.
  2. Fraud Detection and Prevention: AI is crucial in detecting and preventing fraud in financial transactions. Machine learning models can analyze historical data to identify unusual patterns or transactions indicating fraudulent activity, protecting businesses and consumers.
  3. Risk Assessment and Credit Scoring: AI-driven credit scoring models analyze a broader range of data sources, including non-traditional data like social media behavior and transaction history, to assess creditworthiness more accurately. This helps expand access to credit for underserved populations.
  4. Customer Service and Chatbots: AI-powered chatbots and virtual assistants are used extensively in customer service within fintech and financial institutions. They provide 24/7 support, answer customer queries, and assist with account management, improving customer experience and reducing operational costs.
  5. Robo-Advisors: Robo-advisors use AI algorithms to create and manage investment portfolios tailored to individual investor goals and risk tolerance. They offer lower fees than traditional financial advisors and provide automated, data-driven investment advice.

AI’s use in cybercrime and fraud detection may become worth trillions. Its algorithmic trading and customer service in the fintech industry may also be transformative to these industries. It enhances regulatory compliance by automating tasks such as transaction monitoring and reporting. But, like all new technologies, criminals will likely find a way to harness the power of AI as well. But, if AI can make even the smallest irregular activities known in real time, detection speed will improve, shutting down criminals before they start.

AI is Transforming the Face of Retail in North America

Retail: One of the largest sectors of any advanced economy, making up nearly 75% of the US economy in consumer spending, retail will be a massive playing field for AI.

According to Fortune Business Insights,

“The global artificial intelligence in retail market size was valued at $5.50 billion in 2022 & is projected to grow from $7.14 billion in 2023 to $55.53 billion by 2030, exhibiting a CAGR of 34.1% during the forecast period.”

AI-driven personalized recommendations, demand forecasting, inventory management, and cashierless stores are transforming retail.

Personalized Customer Experiences: AI-powered recommendation engines analyze customer data, including purchase history and browsing behavior, to provide personalized product recommendations. This enhances the shopping experience and increases the likelihood of conversion. Companies that don’t automate sales will be left behind.

Inventory Management and Supply Chain Optimization: AI can forecast demand accurately and optimize inventory levels. This reduces stockouts, minimizes overstocking, and improves overall supply chain efficiency, leading to cost savings.

Chatbots and Virtual Assistants: AI-driven chatbots and virtual assistants provide real-time customer support, answer product inquiries, and assist with order tracking. They offer 24/7 availability and help reduce customer service costs. While annoying, some people put up with it, saving the company time and money and increasing their bottom line.

Visual Search and Augmented Reality (AR): AI enables visual search capabilities, allowing customers to search for products by uploading images. AR applications enable customers to virtually try on clothing and accessories or visualize how products will look in their homes, enhancing the online shopping experience. A massive opportunity, instead of having to search on Amazon, consumers will snap a photo of something and automatically be brought to a page to purchase the item.

Loss Prevention and Security: AI-powered video analytics and surveillance systems can quickly identify suspicious behavior and potential theft. This enhances store security and reduces shrinkage.

Additionally, AI is used for pricing optimization, fraud detection in e-commerce transactions, and customer sentiment analysis from social media and reviews. AI also plays a crucial role in demand forecasting, which helps retailers plan promotions and inventory levels more effectively.

AI Integration in Manufacturing

AI-powered automation, predictive maintenance, quality control, and supply chain optimization are enhancing manufacturing processes. For countries like Germany and China, manufacturing is the economy’s lifeblood. Supercharging it with AI will be essential and may also give lesser-known manufacturing nations a chance for a leg up. AI will change the face of productivity forever.

5 SubSectors Powering the Manufacturing Sector

  1. Predictive Maintenance: AI-driven predictive maintenance models analyze sensor data and historical equipment performance to predict when machinery is likely to fail. This enables proactive maintenance, reduces downtime, and lowers maintenance costs.
  2. Quality Control: AI-powered computer vision systems can inspect and identify product defects on the production line with high accuracy and speed. This ensures higher product quality and reduces the likelihood of defective items reaching customers.
  3. Process Optimization: AI algorithms analyze production data in real-time to optimize manufacturing processes. This includes adjusting variables like temperature, pressure, and speed to maximize efficiency, minimize waste, and reduce energy consumption.
  4. Supply Chain Management: AI is used for supply chain optimization, helping manufacturers plan and manage inventory, logistics, and demand forecasting more effectively. This reduces delays, lowers costs, and enhances overall supply chain efficiency. Look for AI-powered blockchain applications to dominate this sector in the future.
  5. Robotic Automation: AI-powered robots and cobots (collaborative robots) are increasingly used in manufacturing for assembly, material handling, and even complex tasks like welding. These robots work alongside human workers, increasing productivity and efficiency.

Additionally, AI is used for demand forecasting, quality control, and root cause analysis of production issues. It can also enhance worker safety by monitoring and alerting them to potential hazards. Overall, AI in manufacturing helps increase production efficiency, reduce costs, improve product quality, and enhance competitiveness. All top manufacturing firms will soon be utilizing AI or be left behind.

Welcome to the Fast Lane & Sector #5: AI in Autonomous Vehicles

AI is a crucial component of self-driving cars, trucks, and drones, with applications in transportation and logistics.

AI is at the core of many advancements in autonomous vehicles (AVs), and it’s poised to impact this industry significantly. Here are the top five ways AI will influence autonomous vehicles:

  1. Enhanced Perception and Sensing: AI-powered sensors, cameras, Lidar, and radar systems are used in AVs to perceive and interpret their surroundings. AI algorithms process this data in real time to identify objects, pedestrians, road signs, and other vehicles. This enhances AVs’ ability to make safe driving decisions, even in complex and dynamic environments.
  2. Predictive Analysis and Decision-Making: AI enables AVs to predict the behavior of other road users, such as predicting the trajectory of pedestrians and anticipating the actions of nearby vehicles. These predictive capabilities are crucial for making proactive and safe driving decisions.
  3. Mapping and Localization: AI plays a crucial role in high-definition mapping and localization for AVs. Machine learning algorithms can process vast amounts of mapping data to create precise and up-to-date maps, which is essential for AVs to navigate accurately and safely.
  4. Autonomous Control Systems: AI algorithms control the vehicle’s acceleration, steering, and braking systems to navigate traffic, follow traffic rules, and avoid collisions. These control systems continuously adapt to changing road conditions and scenarios.
  5. Driver Monitoring and Safety: AI is used for driver monitoring, ensuring that when a human is present in the AV, they are attentive and ready to take control if needed. AI-based systems can detect drowsiness, distraction, or impairment in the human operator, issue alerts, or take corrective actions.

AI’s impact on AVs goes beyond these areas, as it also plays a role in connectivity, cybersecurity, and vehicle-to-vehicle communication. As AV technology advances, AI integration will continue to be at the forefront, enabling safer, more efficient, and more accessible autonomous transportation.

Additionally, autonomous vehicles (AVs) are significantly impacting manufacturing in various ways, revolutionizing processes and operations. We didn’t want to include this sector under the manufacturing section above because, with AVs, they would exist.

Here are the top five ways AVs are influencing the manufacturing industry:

  1. Material Handling and Logistics: AVs, including autonomous forklifts and transport robots, are being used in manufacturing facilities to move materials, components, and finished products efficiently. They can operate autonomously within predefined areas, reducing the need for human labor in logistics and warehousing tasks.
  2. Smart Factories: AVs are an integral part of smart manufacturing facilities. They can transport materials between workstations, deliver parts to assembly lines, and move finished products to storage or distribution areas. This improves production efficiency and reduces cycle times.
  3. Flexible Manufacturing: Autonomous mobile robots (AMRs) transport work-in-progress items to different workstations, enabling more flexible and agile manufacturing processes. Manufacturers can quickly adapt to changing production needs without significant reconfigurations.
  4. Safety and Quality Control: AVs with cameras and sensors can perform safety and quality control inspections within manufacturing environments. They can identify defects, monitor equipment health, and ensure compliance with safety protocols.
  5. Intralogistics and Just-in-Time Delivery: AVs are used for intralogistics within manufacturing facilities, ensuring the timely delivery of components and materials to production lines. This supports just-in-time (JIT) manufacturing principles, reducing inventory-carrying costs and waste.

Overall, autonomous vehicles enhance manufacturing efficiency, reduce operational costs, improve safety, and enable more agile and responsive production processes. As technology advances and AVs become more integrated into manufacturing operations, their impact on the industry is expected to grow.

5 More Sectors where AI will play a Massive Role

Customer Service: Chatbots and virtual assistants can improve customer support and engagement across various industries.

Marketing and Advertising: AI is used for targeted advertising, content recommendation, customer segmentation, and campaign optimization.

Education: AI transforms online learning with personalized content, automated grading, and intelligent tutoring systems.

Energy: AI is used for energy grid optimization, predictive maintenance of power plants, and renewable energy resource management.

Agriculture: AI is improving crop monitoring, precision agriculture, and livestock management for increased productivity and sustainability.

AI integration is happening in real time everywhere. It will become so pervasive that we will not even see it. It will be what curates almost every experience, purchase, and transit. From what we buy to what we eat. AI will touch every supply chain and virtually every industry in one form or another. Seeking specific leaders in each field should be at the top of every investor’s to-do list. Now that we know where AI’s expected growth and implementation will be, investors have a road map.