Bottom line: Enterprises are attaining double-digit improvements in forecast error rates, demand planning productivity, cost reductions and on-time shipments using machine learning today, revolutionising supply chain management in the process. Machine learning algorithms and the models they're based on excel at finding anomalies, patterns and predictive insights in large data sets. Many supply chain challenges are time, cost and resource constraint-based, making machine learning an ideal technology to solve them. From Amazon's Kiva robotics relying on machine learning to improve accuracy, speed and scale to DHL relying on AI and machine learning to power their Predictive Network Management system that analyses 58 different parameters of internal data to identify the top factors influencing shipment delays, machine learning is defining the next generation of supply chain management. Gartner predicts that by 2020, 95% of Supply Chain Planning (SCP) vendors will be relying on supervised and unsupervised machine learning in their solutions.

As thousands descended upon the South by Southwest (SXSW) 2018 Conference this year to catch a glimpse of the interactive industry's biggest leaders, Digital McKinsey was pleased to take part in some of the most engaging conversations in data science (Ines Marusic), design (Mahin Samadani), and artificial intelligence (Mehdi Miremadi). As in past years, Artificial intelligence (AI) continues to emerge as a key issue as businesses and consumers wrestle with its perceived value and underlying threats. The conversation at SXSW focused on how we need to rethink our processes, examine underserved groups, and be realistic about expectations of AI. We contributed to discussions in three areas of particular importance: 1) providing inclusive ways to solve complex problems; 2) expanding the skill set of empathy and design with data; and 3) understanding the nuance of AI's impact. Data scientist Ines Marusic of QuantumBlack joined a women in AI panel to discuss the impact of today's algorithms on inclusion and fairness.

The massive snowfall in Davos this year certainly made getting around a little more challenging compared to years past, but that did nothing to dampen the conversation. We were fortunate to be at this year's World Economic Forum, and after dozens of conversations with executives from around the world, we wanted to share a number of things that struck us about what we heard. AI is top of mind for many executives, but the application of AI--and, more broadly, advanced analytics--is generating more thoughtful and nuanced conversations. While there are serious concerns about the social implications of AI, the reality is that it's hard to see how machines can really be effective on their own, just as it's hard to see how humans can work as well without machines. The most thoughtful organizations are looking to understand how AI can most effectively augment humans.