Implementation of Artificial Intelligence within a Large Enterprise: the Case for Mastercard
Introduction — The decade long promise of Artificial Intelligence within Enterprises
Even though there has been a massive amount of hype surrounding Artificial Intelligence over the last 12–18 months, a lot of the underlying technology and promise has been in the making for decades. Moreover, tech-forward enterprises across many different industries have already been adopting Artificial Intelligence in one way or another due to their recognition of how game-changing the technology can be across several areas of an Enterprise.
As businesses across industries absorb extensive data volumes and aim to fuse and scrutinize it for valuable insights, they are increasingly relying on artificial intelligence to unveil trends and patterns indicative of opportunities for enhanced decision-making and subsequent actions. AI is swiftly expediting tasks and enhancing human expertise with remarkable speed and precision. Progress in AI and its affiliated domains, encompassing machine learning and deep learning, holds the key to unlocking the complete potential of data.
AI significantly amplifies the exploration of data, facilitating improved decision-making and assisting organizations in uncovering answers to queries they may not have even considered. Through AI technologies, machines undergo training to discern patterns within data, contributing to streamlined processes across diverse business functions. AI is streamlining workflows and business operations, aiding organizations in managing operational expenses while concurrently enhancing performance and expediting the introduction of superior products to the market. AI plays a pivotal role in fueling today’s most captivating customer experiences, fostering awareness, and cultivating loyalty.
One specific example I would like to further explore is MasterCard. Its CEO has been extremely vocal in describing MasterCard as an AI pioneer and wanting to pave the way for the next wave of innovation across all functions of the company. For over a decade the company has deployed AI across both its solutions as well as various internal functions. However, this has raised the broader question: What is the most effective way to deploy and integrate Artificial Intelligence across such a large and established organization?
The Case for Master Card — An early adopter of AI
Master Card has been pioneering AI applications within its solutions for almost a decade with its robust AI application for fraud prevention. Since 2014, MC has been partnering with the likes of Apple to incorporate mobile wallet features with iPhones which removed the need to submit their credit card and potentially expose expiration dates and security code. With the rise of e-commerce over the recent years, innovating in this pillar has become increasingly important, and Master Card should continue to deploy resources toward their AI fraud prevention technologies.
Current AI Strategic Focus — Internal Integration Across Departments
Looking toward the future, Master Card has importantly recognized that in order to be the AI Powerhouse they hope to be, they need to deploy the use of artificial intelligence across all internal functions of the company. This includes: audits, compliance, finance and HR. The main problem I believe that will be faced, however, is the actual reluctance for all business segments to adopt these new AI powered tools and processes. There are very few examples of successful full-scale integration of AI functions across all company business units currently in existence. In addition, the staffing shortages of high-quality talent is a real limiting factor to consider.
For these reasons, I believe the creation of a smaller, more prestigious division that offer attractive career development and promotion opportunities would likely attract higher quality data scientists that specialize in Artificial Intelligence. Finally, two more important factors that Mastercard should be heavily factoring are: 1) ethical issues and need to centralize authority and 2) Effective account integration across divisions.
Integration of new specialized AI Division
Integrating this division into Mastercard’s org structure in a way that allows both the focused benefits of centralization while also touching all business segments will be critical to its success. From a cultural standpoint, I think this new Division needs to assign various group segment leads, that are in-charge of i) education of the business unit specific AI use cases and applications ii) appropriately quantify that segments priorities and relevance of AI use case which in return will feed budgetary decisions toward new product innovation for the various business segments. It will be impossible for a perfectly symmetrical rollout to happen across all business units, with the same priority and budget allocation given the differences in the application of AI. The budgetary priority will and should be different as the value proposition and instant impact will be greater in some divisions, however this all needs to be very carefully rolled out in order to create a collaborative culture where business units are willing to work with the centralized AI team toward the future.
