Sir Jero's Digital Hub: Marketing, Finance & Technology

Introduction

Artificial Intelligence (AI) is bringing significant changes to how business is done with information systems (IS). AI is automating many tasks, enabling new ways of collecting and analyzing vast amounts of data and providing valuable insights, so this is not just a fad but a powerful force of change in the way business is done. How does AI fit into our concept of an IS, drive digital transformation and make business better by becoming more efficient, responsive and inventive?

AI and Information Systems

All business systems depend on information, and today’s businesses run on them. This includes everything from operations and management, to crucial decisions. The typical system manages data by processing it according to predesigned rules and spitting out reports based on predefined parameters. What AI brings to the equation is a rampant, insatiable intelligence to all of the above, by making sense of large amounts of data and surfacing patterns while also making decisions, often faster than humans but with higher accuracy.

For example, enhanced Customer Relationship Management (CRM) systems can predict what your customers are likely to buy next, recommend specific digital marketing strategies, and even handle basic customer enquiries through AI-powered chatbots. No doubt, data-driven decision-making helps companies gain a competitive advantage not only by streamlining operations, but also by enhancing the quality of customer interactions.

AI in Digital Transformation

 Digital transformation is fundamentally about using digital technologies to redesign business models and operations to provide improved value to customers – and as such, AI is its critical enabling technology, providing enterprises with means to transform business processes into ones that can automate away mundane tasks, optimize workflows and provide innovation speeds that would otherwise be unimaginable.

 One forerunner application in digital transformation is ‘predictive analytics’, which uses AI to help process large sets of data in order to predict trends and outcomes, including customer behavior and potential risks. Predictive analytics can be deployed in highly effective ways, for instance in the field of manufacturing, where AI-enabled predictive maintenance can monitor equipment and machinery in real time to predict failing parts and breakdowns, thus preventing inconvenient downtimes and expensive repairs.

 Smart assistants and chatbots, too, are changing the way companies provide customer service, all by itself. An AI-automated service agent is able to answer consumer questions and troubleshoot problems as well as complete purchases. The agent can do so on its own and nearly around the clock, leaving human employees time for more challenging tasks.

Automating Business Processes with AI

 Robotic Process Automation (RPA), one of the sub-fields of AI, is disrupting the workplace as we know it. By automating repetitive, rule-based tasks from human colleagues, AI-powered robots dramatically boost efficiency, reduce errors, and speed up workflows. Employees can then devote more time to higher valued-added activities.

 For example, it supports finance by automating invoice processing, payroll management and producing compliance reports in retail where resource-intensive work such as, fulfilling customer orders, return management and forecasting can be automated to provide a seamless customer experience. By easing repetitive tasks with automation, work operations reduce both costs and mistakes, and compliance significantly increases.

 Go a step further than RPA and you find AI working its way into much more complex processes. For example, in supply-chain management, firms can use an AI algorithm to anticipate demand more effectively and manage stock levels more optimally. In any business looking to compete effectively in a climate of constant digital change, this type of automation is going to be essential.

Challenges and the Future of AI

 There are challenges to overcome, though. AI systems involve security and privacy issues – these intelligent systems need access to mountains of sensitive data in order to function, and businesses must invest in adequate security or comply with regulations.

 Moreover, AI technologies demand significant investment of time, money and expertise. Initially, companies must train their staff to use AI-controlled tools and to adapt to new, AI-enhanced workflows. But for those willing to invest the effort, they’ll reap huge rewards in productivity and innovation.

 Looking to the future, we will see AI continue to advance, with new capabilities, allowing us to build ever-more capable autonomous systems that can make decisions and learn from their own outputs. As these technologies develop, those companies that embrace AI will be far better placed to adapt to the future challenges of the digital world and be better positioned for sustained future success.

Conclusion

 Artificial intelligence used to be a buzz phrase, but it’s fast becoming a true game-changer. AI is revolutionizing information systems, and driving digital transformation across business sectors. It’s making businesses faster, smarter and more responsive by automating tasks, optimising decision making, and creating better experiences for customers. With no signs of slowing down, AI is about to become another critical tool for business in an increasingly digital world.

Furthermore, Al-Mekhal et al (2023) argued that AI would have a positive effect on customer relationships within Customer Relationship Management. However, some studies suggest otherwise.

References

Al-Mekhlal, M., Al-Buraik, M., & Al-Lubli, M. (2023). Digital transformation: AI-powered bot solutions and automation for customer services. International Conference on Digital Applications, Transformation & Economy, 1-7. doi:10.1109/ICDATE58146.2023.10248458.

Brown T. (2022). Robotic Process Automation in Finance: Game Changer. Financial Technology Today, 8 (1), 34-47.

N. Kumari, D. C. (2023). Artificial Intelligence in Supply Chain Optimization. 2023 International Conference on IoT, Communication and Automation Technology (ICICAT), 1-6. doi:10.1109/ICICAT57735.202

Jay Lee, J. S. (2020). Industrial AI and predictive analytics for smart manufacturing systems. In J. S. Jay Lee, & M. B. Masoud Soroush (Ed.), Smart Manufacturing (pp. 213-244). Elsevier. doi:10.1016/B978-0-12-820027-8.00008-3

Kamble, S. S., Mor, R. S., & Belhadi, A. (2023). Customer Relationship Management in the Digital Era of Artificial Intelligence. In S. S. Kamble, R. S. Mor, & A. Belhadi, Digital Transformation and Industry 4.0 for Sustainable Supply Chain Performance (pp. 175-190).

Kimla, N. (2024). How AI Can Maximize Your CRM: The Future Of Customer Relationship Management. Retrieved from Forbes: https://www.forbes.com/councils/forbesbusinesscouncil/2024/07/11/how-ai-can-maximize-your-crm-the-future-of-customer-relationship-management/

Ledro, C., Vinelli, A., & Nosella, A. (2022). Artificial Intelligence in customer relationship management: Literature review and future research directions. Journal of Business & Industrial Marketing. https://www.emerald.com/insight/content/doi/10.1108/JBIM-07-2021-0332/full/html#sec009

The University of Texas at Austin. (2024). Enhancing Customer Experience with AI Chatbots. Retrieved August 8, 2024, from The University of Texas at Austin: https://sites.utexas.edu/discovery/2024/06/24/enhancing-customer-experience-with-ai-chatbots/