predictive analytics (Elnur/


How AI, private-sector innovations secure supply chains

In February, President Donald Trump showed his administration’s commitment to keeping America at the forefront of technological advancements by signing an executive order directing federal agencies to allocate resources to expand the use of artificial intelligence as part of a new “American AI Initiative.”

With a renewed focus on innovation, the U.S. has a unique opportunity to invest in the technologies that can unlock the full potential of data. Information is generated at a rate that far surpasses our ability to process and measure it. To bridge that gap, we must develop technologies that help identify and mitigate risks within datasets. This process, however, is complicated. Instead of finding a needle in a haystack, we need to find the right needle in a stack of needles.

Supply chain risks represent one of the many “needles” we can identify and mitigate. With the help of AI data analytics, we can digest each tier of a government supply chain to reveal a project’s suppliers, from the final delivered products down to the manufacturers of the smallest nuts, bolts and other components. But how does this work?

Consider a niche, medium-sized company that specializes in making aircraft heat shields for the Defense Department. In a phishing attack, a fraudster sends an email to the entire billing department, urging “YOU HAVE OUTSTANDING INVOICES.” Two employees click the link in the email, and one inputs billing information to pay the fake invoice. Next, the company’s computer systems go down, thousands of dollars go missing. The contractor is now vulnerable to having its trade secrets stolen, and counterfeit parts can be made and placed into the military supply chain.

What just happened? An extensive government supply chain tasked to produce military aircraft is now highly susceptible to fraud due to something as common as a phishing email.

Effectively managing risks like these requires processing a breadth of information, right down to data on who enters an agency or contractor building. Managing risk also includes training personnel to help prevent access to systems via phishing and other attacks, as well as using technology to ensure the  supply chain  partners, whether local or abroad, are trustworthy. While many agencies know their Tier 2 suppliers, the subsequent levels of supply chains often provide the greatest amount of risk.

AI programs like predictive analytics help surface risks so that agencies and contractors can efficiently prioritize the myriad moving parts of mitigation plans.  AI-driven predictive analytics can give agencies a more effective snapshot of a business and its supply chains before it moves forward on a program with potential supply chain vulnerabilities. The private sector already uses these tools and techniques, and the government should as well. With relevant data at hand, agencies could make informed decisions to choose less risky suppliers or fortify a supply line so disruptions are minimized.

To begin tackling supply chain risks, the House in September 2018 passed the Securing the Homeland Security Supply Chain Act of 2018 (H.R. 6430) -- bipartisan legislation that would ensure the Department of Homeland Security has the ability to limit exposure to risky or fraudulent suppliers.

But, there is still more and important work to be done. Due diligence must be performed across the entire chain, down to even the smallest supplier and across all agencies. In leveraging AI and private-sector innovation, the federal government can benefit from the extraordinary capabilities of machine learning while simultaneously fine-tuning these systems to meet its specific information needs.

While supply chain risks cannot be completely eliminated, employing predictive analytics will give agencies and contractors a much better understanding of supplier risks over time so they can make more informed decisions.

By working smarter with AI, the government can proactively identify potential fraud and bad actors at all levels -- helping ensure there are not any breaks in an increasingly important supply chain.

About the Author

Brian Alster is global head of supply and compliance with Dun & Bradstreet.

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