In a 2016 research reportWhy Artificial Intelligence is the Future of Growth, Accenture found that adoption of artificial intelligence tech across all industries may double economic growth rates by 2035. AI investment is expected to increase labor productivity by 40 percent. In fact, 70 percent of executives say they plan to “significantly increase” AI investment.

In the realm of inventory and supply-chain management, AI adoption, specifically the use of optimization algorithms, is revolutionizing inventory agility – reducing stock depletions and maximizing stock levels.

“The use of AI in supply chains is helping businesses innovate rapidly by reducing the time to market and evolve by establishing an agile supply chain capable of foreseeing and dealing with uncertainties,” says Accenture Managing Director Manish Chandra. “AI armed with predictive analytics can analyze massive amounts of data generated by the supply chains and help organizations move to a more proactive form of supply chain management.”

Supply chain processes generate giga-tons of data, and AI can deploy predictive analytics to make sense of it all. Freshly updated and analyzed data then builds a solid foundation when it comes to real-time vision and information flow. Every key player across the supply chain is empowered with the best data and maximizes it accordingly.

AI is no longer an “ain’t-it-cool” innovation in the industry but rather a necessity. With the erosion of the brick-and-mortar model and rise of real-time consumer expectations, supply chain/inventory management practices must embrace machine learning that far outpaces the speed of human thought and action. Consider these stats from the 2017 MHI Industry report concerning the speed of supply-chain transactions from just one e-tailer on Black Friday:

“A reported 426 orders per second were generated from the website throughout the day. That equates to over 36 million order transactions, an estimated 250 million picking lines at the distribution centers (DC), 40 million DC package loading scans, 40 million inbound sortation hub scans, 40 million outbound sortation hub scans, 40 million inbound regional sortation facility scans and 40 million outbound delivery truck scans.”

How should industry leaders respond? The answer, according to the report, is clear. Supply-chain companies must embed “analysis, data, and reasoning into the decision-making process. Position analytics as a core capability across the entire organization, from strategic planners through line workers, providing insight at the point of action.”

As Accenture economic research director Mark Purdy concludes, companies that survive will fully invest in the potential power of AI going forward: “To fulfill the promise of AI, relevant stakeholders must be thoroughly prepared – intellectually, technologically, politically, ethically and socially – to address the benefits and challenges that can arise as artificial intelligence becomes more integrated in our daily lives.”