How AI is Transforming the Workplace: Real-World Examples and Insights

Artificial intelligence (AI) is on a rocket-like trajectory. Globally, the AI market is expected to exceed more than $1.8 trillion by 2030 — more than 12 times the size it was in 2022.

The IMF says that nearly 40% of global employment could be affected by AI; in advanced economies that could rise to 60%. And in those sectors best positioned to take advantage of AI are seeing an almost fivefold increase in labor productivity growth.

In the UK, job listings requiring AI skills are growing 3.6 times faster than overall job postings. In Singapore, the number of positions requiring AI skills has grown 13.5 times faster than the overall job market. In the US, AI jobs pay up to 25% more.

It’s evident that, at the current pace of technological advancement, organizations must proactively prepare their workforce for the impact of AI.

In this blog post, we’ll survey some of the real-world applications of AI and explore how it’s reshaping industries and job roles. Understanding these changes is crucial for staying competitive and ensuring that your workforce is equipped with the skills needed to succeed in an increasingly AI-driven world.

AI’s Impact Across Industries

AI is intelligence demonstrated by machines, as opposed to natural intelligence displayed by animals including humans. This involves machine learning, natural language processing, computer vision, robotics and more.

This versatility creates many opportunities — enabling personalized experiences in retail, predictive maintenance in manufacturing, and advanced analytics in healthcare, among others.  

AI applications address several common employee challenges:

• Information overload: AI makes it possible to analyze massive datasets, producing valuable insights quickly.
• Poor resource allocation: AI can predict demand and identify inefficiencies, boosting productivity.

• Time spent on manual tasks: AI can automate repetitive tasks like data entry and scheduling, freeing employees to focus on more valuable activities. Pearson's research found that millions of work hours can be saved for more valuable tasks by using generative AI to help them on the job.

• Lack of real-time insights: AI delivers real-time data analysis, allowing organizations to respond to market changes and operational needs swiftly.
• Inefficient customer service: AI-driven chatbots and virtual assistants efficiently handle many routine customer interactions, improving quality and response times.
• Murky market predictions: AI forecasts trends by analyzing patterns in historical data, helping businesses stay ahead of the curve.
• Security threats: AI strengthens cybersecurity by detecting anomalies and responding faster.

AI in Action: Industry Use Cases You Need to Know

Consider these examples of how organizations are leveraging AI in various industries:

1. Manufacturing troubleshooting and maintenance
   
   AI is improving efficiency and reliability in manufacturing, according to the World Economic Forum: “[By] using AI to monitor and analyze data from machinery and shop floor processes, manufacturers can identify anomalous patterns to predict or even prevent breakdowns.”
   
   For example, Siemens’ Industrial Copilot is an AI tool that assists automation engineers with coding and troubleshooting in industrial settings. It can write new code and track down software bugs. In pilot projects, the tool has identified problems and suggested solutions.
   
   
2. Customer service chatbots and virtual assistants
   
   Companies like Delta Airlines use generative AI to create more natural and helpful customer service chatbots. The bots help customers check in, track bags, and find flights, and they have reduced call center volumes by 20%.
   
   Chatbots solve customer problems faster and more efficiently. According to AI chatbot software provider Tidio, an average conversation with a chatbot includes only 5.7 messages; 62% of customers say they would use a chatbot rather than a human agent if the AI is quicker.
   
   
3. 
   Healthcare diagnostics
   
   Hospitals and healthcare facilities are starting to use AI to analyze medical images and identify potential diseases, often with greater accuracy than human healthcare professionals. For example, SISH, a self-teaching deep-learning algorithm at the Mahmood Lab at Harvard Medical School, can diagnose rare diseases and identify patients likely to respond to similar treatments.
   
   In a global survey, 72% of healthcare leaders recognized the positive influence of predictive analytics on health outcomes in clinical settings. In Japan alone, the market for diagnostic and therapeutic AI healthcare tools is expected to be around $114 million by 2027.
   
   
4. Finance fraud detection and prevention
   
   In finance, AI algorithms are analyzing transaction patterns to identify anomalies and flag potential fraud. In London, Mastercard leverages AI to help banks identify and stop scams in real-time — before funds leave a victim’s account.
   
   
   
5. Multiplying the power of marketing with data analysis
   
   Companies are using AI to create more targeted and personalized ads, analyze performance and optimize marketing campaigns; almost a quarter — 24% — of businesses are using AI for audience segmentation. IBM is leveraging AI and machine learning to use predictive analytics based on customer data, providing insights into customer behavior, personalizing content and identifying patterns in large datasets.
   
   Pearson's author, Gary Armstrong, shared his view on how AI can be used in marketing analytics.
   
   

    

6. Recruitment and talent acquisition in human resources
   
   Talent acquisition professionals are already using AI-powered tools to help screen résumés, identify top candidates and even conduct initial interviews. According to Garter, 76% of HR leaders believe they must implement AI in the next 1-2 years or risk falling behind.
   
   Oracle is using its AI-powered human resource solutions to help customers improve candidate sourcing, streamline screening and interviewing, help managers make better hiring decisions and increase onboarding efficiency.
   

The Importance of Upskilling Employees

While AI automates routine tasks, enhances decision-making and fuels innovation across industries, it also requires new skills from employees. AI upskilling is crucial for several reasons:

• Adapting to technological change: AI is reshaping job roles. Employees must upskill to adapt as their jobs change. That includes understanding how to collaborate with AI systems and embrace new responsibilities.
• Enhancing decision-making: AI tools offer powerful insights through data analysis, but the ability to interpret and apply these insights belongs to humans. Upskilling employees to make smart decisions, optimize business processes and contribute to strategic initiatives can unlock value in the workforce.
• Fostering innovation: AI can support employee innovation. Upskilling in AI empowers them to help develop AI-driven solutions, ensuring their employer remains competitive.
• Ensuring ethical AI practices: As AI becomes more deeply integrated into business operations, understanding the ethical implications is vital. AI knowledge equips employees to recognize potential biases, ensure transparency and advocate for responsible AI practices.

Explore our blog to learn more about why identifying and addressing AI skills gaps is crucial and how to effectively tackle them.

How to Encourage Upskilling in the Age of AI

• Create personalized learning paths: Tailor upskilling programs to address the specific needs and career goals of employees within an AI-powered enterprise. This will ensure that the training is relevant to employees and, therefore, boost engagement.
• Leverage digital badges and certifications: Digital badges and certifications offer tangible recognition for learning achievements and can be showcased on professional profiles, validating employee efforts and boosting their career prospects. Digital credentials also make it easier for companies to assess and track AI upskilling and reskilling efforts.
• Encourage a growth mindset: Foster a culture where continuous learning is valued and celebrated. Encourage employees to view AI skills as opportunities for professional development. AI is a catalyst for profound change in the workplace. Organizations that upskill their employees in AI will be better positioned to leverage its transformative potential.

The future of work is not about replacing humans with machines. It’s about empowering humans with AI to make work better. Organizations can leverage digital credentials, verified through platforms like Credly, to ensure their workforce has the skills needed to succeed.

To learn more about the top 10 in-demand AI skills and discover how we can help you build a future-proof workforce, complete the form below to download our report: "The Top 10 In-demand AI Skills for 2024 and Beyond."