The changes caused by AI and machine learning might not be obvious for a while. Currently, less than 5% of occupations are completely automated, according to McKinsey. The research firm reported that the jobs most susceptible to automation “are physical ones in highly structured and predictable environments, as well as data collection and processing.” These jobs account for a staggering 51% of activities in the economy and $2.7 trillion in wages.
Factors that will best determine the speed of automation include:
- the ongoing development of technological capabilities,
- the cost of technology,
- competition with labor, including skills and supply and demand dynamics,
- performance benefits including and beyond labor cost savings,
- and social and regulatory acceptance.
All systems Go
Still, machine learning is progressing faster than previously thought possible. Just look at AlphaGo, Google’s DeepMind program that was the first to defeat a Go world champion. (Go is a 3,000-year-old Chinese board game with simple rules, yet the complexity of the game has made it much more difficult for computers to win versus other classic games such as chess.) Traditional AI methods like heuristic search do not work with Go, so AlphaGo combines less novel approaches – an advanced tree search with deep neural networks – to master the game.
While Go could be brushed off as just a “game”, the program’s ability to work through 10 to the power of 170 possible board configurations shows how machines are able to handle infinitely more data points than humans can. Possessing the ability to constantly assess and learn from data enables computers to access insights that may have never been uncovered by humans.
What does AI mean for supply chain?
AI and machine learning are becoming widely-accepted and crucial technologies in the aging supply chain industry. In an industry where many organizations are still operating with systems built for past eras, companies are using these technologies will possess an undeniable competitive advantage. Here are just a few of the benefits AI is bringing to supply chain:
- Complements and leverages existing systems and investments.
- Correlates and interprets data from across systems and sources.
- Empowers organizations to analyze supply chain data and intelligence in real-time.
- Significantly reduces the time needed to retrieve information and manage disruptions.
- Drives automation using instant analysis and trusted recommendations.
How will AI transform B2B networks?
You’d be hard-pressed to find any truthful reasoning in deciding not to incorporate AI into your supply chain operations. Making the jump to these technologies is not as scary as it seems. You don’t have to say goodbye to your trusted legacy systems. Think of AI as an “add-on” that exists to leverage your current operations – making them faster, smarter, and easier to manage. A great place to start is with your data aggregators and analyzers. Your data aggregating system should be able to integrate seamlessly with any number of sources, so that you can retrieve, correlate, and transmit your data quickly, and ensure compliance with your trading partners – all in one system.
Your data analyzing system should be able to connect and analyze data from across your supply chain to provide predictive insights and recommendations based on continuous learning. Real-time analytics and accurate predictions are no longer a pipedream.