By Pascal Bornet, Associate Partner, McKinsey Singapore and Thomas Carlsen, Partner, McKinsey Brisbane
Successful AI is not a pure technology play, it is before all a business transformation
To solve this issue, companies need to not only build a multidisciplinary CoE but also transition to “enterprise AI,” where integrated project teams consider and combine the full breadth of technologies and concepts as they build solutions to business problems. One example is combining RPA to collect and reconcile millions of data from different systems with data analytics that use this information to create insights for decision making. This integrated approach enables a multiplier effect that unlocks more value from use cases and ensures a smoother integration of new technologies.
5. Place people at the center of the transformation
Finally, it’s crucial for the CIO and other top leaders to anticipate and address the impact of AI on workplace dynamics, culture, communication, labor relations, and structure as employee acceptance and buy-in is vital as organizations scale AI. To build a scalable workforce for the future, the C-suite should consider identifying:
• The best combination of people and machines. AI performs some tasks better than humans—but not all. Understanding what each does better is crucial to effectively augment employees—whether automating mundane tasks so staff can focus on value-added work or using advanced analytics to process millions of data points in seconds.
• How new AI technologies, such as deep learning, and flexible team structures and approaches, such as agile, can enable greater innovation.
• Ways to organize and train employees based on capabilities instead of skills so they can more easily adapt as AI evolves.