# Robots, RPA, AI & The Future of Work # Key Takeaways Key aspects to understand about Robotic process automation (RPA) and artificial intelligence (AI) and their importance to the Future of Work: **Changing Nature of Jobs:** Job Displacement: Some jobs will be replaced by automation and AI, especially those that involve repetitive tasks. Job Creation: New kinds of jobs will emerge, which didn't exist before. Job Evolution: Many jobs will be augmented by AI, where human workers will work alongside intelligent systems. **Skills in Demand:** Soft Skills: Empathy, creativity, problem-solving, critical thinking, and adaptability will be more valuable than ever. Technological Literacy: While not everyone needs to be a coder, understanding the basics of tech, AI, and RPA will be crucial. **Continuous Learning and Adaptability:** The rapid pace of technological advancements means that continuous learning will become a necessity. An "always be learning" mindset will be a critical advantage in the future workforce. **Ethical Implications:** AI and RPA bring about ethical dilemmas, such as biases in algorithms, job displacement, and privacy concerns. Leaders need to navigate these challenges responsibly. **Business Process Transformation:** RPA and AI will streamline many business processes, making organizations more efficient. This will redefine business models, customer experiences, and value propositions. **Decision Making:** AI can analyze vast amounts of data faster than humans, providing valuable insights. However, the ultimate decision, especially in critical areas, will still require human judgment. **Collaboration Between Humans and Machines:** Successful businesses will be those that best integrate human talents with the capabilities of AI and RPA. Understanding how to manage and collaborate with a "digital workforce" will be a key skill. **Global Impact:** AI and RPA are not limited to developed nations. Emerging economies will also see shifts in work due to these technologies. This can lead to global shifts in economic power and influence. **Regulatory and Policy Challenges:** As AI and RPA become more prevalent, there will be calls for regulations to ensure they're used ethically and responsibly. Business leaders need to stay updated with these regulations and contribute positively to policy discussions. **Strategic Integration:** It's not just about adopting AI and RPA; it's about integrating them strategically into the business. # Example: RPA in Invoice Processing **Background**: Large companies often receive thousands of invoices from suppliers every month. Processing these invoices manually is time-consuming and prone to errors. It involves verifying the details, checking for duplicates, matching invoices with purchase orders, seeking approvals, and then initiating payments. **How RPA is Applied**: 1. **Data Extraction**: - The RPA bot starts by scanning incoming invoices, whether they arrive via email or other channels. - It then extracts the relevant information from these invoices, such as supplier name, invoice number, date, total amount, line item details, etc. 6. **Validation and Matching**: - The bot checks the extracted data for completeness or errors. - It matches the invoice against corresponding purchase orders or delivery receipts in the system to ensure they align. 8. **Duplicate Check**: - The RPA bot searches the database to ensure the invoice hasn't been processed already, thereby avoiding duplicate payments. 10. **Approval Workflow**: - If everything matches, the bot can either: a. Automatically approve the invoice for payment if it's below a certain amount. b. Route it to the appropriate department or person for manual approval if it's above a threshold or if there are discrepancies. 12. **Initiation of Payment**: - Once approved, the bot can initiate the payment process by entering the necessary details into the company's payment system. 14. **Notifications and Reporting**: - The bot can send out notifications to relevant stakeholders about the status of the invoice processing. - It can also generate regular reports about the number of invoices processed, amounts paid, discrepancies noted, etc., and send them to the finance team. ** ** **Benefits**: 1. **Speed and Efficiency**: What used to take hours or even days can now be accomplished in a fraction of the time. 2. **Accuracy**: RPA bots drastically reduce human errors, ensuring more accurate invoice processing. 3. **Cost Savings**: Automated invoice processing can lead to significant cost savings in terms of manual labor and error rectification. 4. **Scalability**: As the volume of invoices increases, RPA bots can easily scale to handle the added workload without requiring a proportional increase in resources. 5. **Audit and Compliance**: RPA ensures a consistent process that can be audited, and it maintains a clear record of actions, assisting with compliance requirements. # Further Reading Agrawal, A., Gans, J., & Goldfarb, A. (Eds.). (2019). The economics of artificial intelligence: an agenda. University of Chicago Press. [https://www.nber.org/books-and-chapters/economics-artificial-intelligence-agenda](https://www.nber.org/books-and-chapters/economics-artificial-intelligence-agenda) Arntz, M., Gregory, T., & Zierahn, U. (2019). Digitization and the future of work: macroeconomic consequences. In *Handbook of labor, human resources and population economics* (pp. 1-29). Cham: Springer International Publishing. [https://docs.iza.org/dp12428.pdf](https://docs.iza.org/dp12428.pdf) Biclesanu, I., Savastano, M., Chinie, C., & Anagnoste, S. (2023). The Role of Business Students’ Entrepreneurial Intention and Technology Preparedness in the Digital Age. Administrative Sciences, 13(8), 177. [https://www.mdpi.com/2076-3387/13/8/177](https://www.mdpi.com/2076-3387/13/8/177) Syed, R., Suriadi, S., Adams, M., Bandara, W., Leemans, S. J., Ouyang, C., ... & Reijers, H. A. (2020). Robotic process automation: contemporary themes and challenges. *Computers in Industry*, 115, 103162. [https://www.sciencedirect.com/science/article/abs/pii/S0166361519304609](https://www.sciencedirect.com/science/article/abs/pii/S0166361519304609) Webb, M. (2019). The impact of artificial intelligence on the labor market. *Available at SSRN 3482150*. [https://www.michaelwebb.co/webb\_ai.pdf](https://www.michaelwebb.co/webb_ai.pdf)