Can AI really solve supply chain issues?

The world has plenty of supply chain problems and varying ideas about how to solve them. Some advocate moving supply chains closer to customers, reducing opportunities for things to go wrong.

Following a worldwide microchip shortage, for instance, the US responded with a slew of home-grown semiconductor production plant initiatives, encouraged by the Biden Administration’s Chip Bill.

Others are trying on-site replenishment options, such as using 3D printers to print spare parts.

One standout technology to smooth out issues may be artificial intelligence. AI in the supply chain can predict problems before they start and allow people to respond more proactively – but how feasible is it and is the technology enough to solve such complex issues?

Let’s look at some of the factors at play here.

Barriers to adoption

Some decision-makers initially overlook the time required to choose an AI solution, training time and applications of the technology that it takes to achieve meaningful outcomes. They can’t expect to find a product, then start enjoying the results within days or weeks.

A 2022 survey of global supply chain executives found more than three-quarters of respondents thought it would take 1-2 years to implement an AI-based solution for managing their materials. Additionally, 76% of those polled blamed data silos and a lack of knowledge for preventing their adoption of AI and other digitally transformative technologies.

Long implementation timelines alone are not reason enough to stop exploring AI solutions. However, people must have long-term viewpoints and realise it might take years to see the expected results.

C-suite executives must recognise this reality, too. If they don’t see positive outcomes quickly, they may feel they’ve wasted money and time. However, that’s not necessarily the case. AI can solve some supply chain problems but it is not a quick fix.

Pandemic wake up call

Many executives hesitate to make changes in their organisations, even if they have strong evidence of the benefits of a tech adoption. Eventually, an external event – like the Covid-19 pandemic and lockdowns which ensued – act as a much-needed wake-up call.

A 2023 Ernst & Young survey of senior supply chain executives revealed 72% of respondents felt the pandemic had negatively impacted their organisations.

However, many began using AI and machine learning to become more resilient. The results showed 37% currently use those technologies, while another 36% plan to start soon.

Elsewhere, 2022 research from Anglia Ruskin University found AI protected many small and medium-sized businesses from supply chain problems during Covid-19. More specifically, those using AI apps reported a 3.1% reduction in business risks during the pandemic.

A breakdown of the application types showed those relying on AI to provide people with personalised shopping recommendations reduced supply chain upset risks by 2%. So, firms that targeted audiences with AI lowered their risk by 1.2%.

Lead author Professor Nick Drydakis said, “The outcomes proved true regardless of enterprise size, turnover, and years of operation, indicating that AI applications have helped SMEs to adapt to unprecedented conditions during the Covid-19 pandemic.

“It seems investment in AI apps could be a smart move for the three-quarters of small businesses that do not currently utilise them.”

Drydakis’s final sentence is telling, although this study did not explore barriers to AI adoption within this group.

AI in the supply chain is now common, but that doesn’t mean all decision-makers have equal access to solutions and enough open-mindedness, financial resources and other necessities to succeed.

Implementation requires planning

Adopting an AI solution is not always the first step many companies take. Most venture into technology gradually. A great starting point is to use integrations to streamline tech usage and processes. They combine separate applications into a condensed system, increasing your technological capabilities.

Using an AI integration to improve the supply chain could entail adding a chatbot that lets people track shipments or a demand-forecasting tool that prevents unexpected stockouts.

Some leaders also use integrations to track shipping price fluctuations associated with third-party transportation companies. Once people have good results with their integrations, they’ll feel more confident about scaling up their tech usage in other ways.

Getting started might mean using AI in a targeted way first before branching out if the initial efforts succeed.

For instance, many companies rely on AI to solve supply chain problems related to urban congestion. When an AI tool plans a route, it accounts for factors such as road construction, traffic accidents and peak traffic hours.

Although humans can analyse those things too, AI often detects things people overlook or don’t have time to study.

Using AI in the supply chain can also enable companies to pursue automation – although that too, takes time, even when using highly advanced solutions.

Consider how 89% of respondents to a 2022 survey thought process automation in the supply chain was important or very important to their digital supply chain objectives. However, 72% said their supply chains were less than 50% automated. Then one-third of those polled said they’d only automated a quarter of their supply chains so far.

These takeaways illustrate that the knowledge of the need to make change is not enough on its own. People also need to use the appropriate planning measures to reach milestones and reach their ultimate goals.

AI no magic bullet

Many of the findings show how AI can address supply chain problems and improve overall outcomes. However, as people investigate how to use AI in the supply chain, they must maintain realistic expectations of what’s possible.

That answer differs for every organisation and depends on things like executive buy-in for AI, the budget and the training time allocated for people to learn the new solution.

People are most likely to get positive outcomes and remain motivated if they have thorough plans and targeted intentions from the outset. Then, they’ll stay focused on what matters.