The next wave of AI is already on its way – and it promises supply chain reinvention

AI has come a long way from its first wave, when the technology gave a voice to Siri, turned Google Maps into the world’s navigator, and bested grandmasters at chess and Go.

But even the most impressive generative AI-enabled tools of the current second wave – from software that generates car designs to a platform that speeds up the development of new drugs – are just laying the groundwork for far greater innovations to come, both in terms of the tech itself and the benefits it unlocks.

For supply chain leaders, the coming third wave of AI won’t just turn heads, it’ll make jaws drop.

 

From AI interns to advanced assistants

If today’s virtual bots are passive interns, tomorrow’s AI assistants will be enterprising go-getters capable of carrying out complex tasks, real-time data analysis, and proactive inventory management.

These advanced assistants could transform sourcing, where employees are often overloaded with small tasks and struggle to see the wood for the trees. Handing over these routine assignments to advanced AI assistants will increase productivity and avoid wasted time and talent, allowing existing team members to take on higher-order work and drive greater value throughout the supply chain.

Companies like Walmart are already piloting AI systems that analyse historical purchasing data and predict stockouts. The system then automatically generates purchase orders, streamlining inventory management and preventing potential delays.

It could take up to ten years for advanced AI assistants to go mainstream, but early adopters that successfully harness the technology for specific supply chain functions could start reaping the benefits as early as next year.

 

The transformation of urban logistics

There are clear limits to how far we can scale the human doorstep delivery workforce and to what dense metropolitan areas can take in terms of additional congestion and pollution.

Fortunately, the rise of AI and reinforcement learning, where software learns and improves through trial-and-error, will jump-start the field of robotics and automation, and drive the wholesale transformation of our urban logistics infrastructure.

Rather than continuing to hire more drivers, companies will be able to train, deploy and scale autonomous delivery fleets at unprecedented speed. These fully electric, limited-range fleets will operate 24/7, zipping down the pavement using AI-optimised routes to achieve precise delivery windows and reduce the risk of serious accidents and collisions along the way.

Companies like Ford are already developing self-driving delivery vehicles designed specifically for navigating dense urban environments. Third-wave AI is the key to unlocking faster, more affordable and sustainable deliveries and a revolution in last-mile fulfilment.

 

A window into the future

The best companies have done good work in recent years to identify sources of supply chain risk, decide where they need alternatives, and use technology to support ongoing assessment and monitoring across their global networks.

However, supply chain issues and disruptions can arise suddenly from any direction at any given moment. What these existing systems cannot do is cut across all the data and intel to accurately predict where trouble may be brewing, let alone tell supply chain leaders what they should do about it or automatically execute a mitigation strategy.

Third-wave AI has the potential to change this, by allowing supply chain leaders to digitally replicate the entire supply chain and run simulations across it based on real-time external data.

It’s already possible to achieve a high degree of foresight on a small scale. Companies like Siemens are developing digital twins of entire factories, allowing them to optimise production processes and predict potential equipment failures before they occur.

When applied to the supply chain at large, AI-powered digital twins will unlock remarkable risk mitigation capabilities, running simulations based on everything from structured performance data to social media chatter, to calculate the cost of action versus inaction.

It’ll be another 5-10 years before the technology fully delivers on its promise, but AI-powered digital twins hold the key to building more resilient supply chains and furthering the shift away from reactive risk management towards proactive risk mitigation.

 

‘In the moment’ no-code software for all

Generative AI’s ability to translate natural language into computer code is one of the most significant second-wave breakthroughs we’ve seen. Yet the biggest breakthrough is still to come: allowing non-technical staff to reap the benefits.

With third-wave AI, every supply chain analyst on the planet will be able to have a natural language conversation with a coding agent and get a personalised application in return.

The ability to create an app that chases orders or solves sourcing problems without typing a single line of code will free employees from the IT bottlenecks that so often stymie supply chain transformation. We’ll see a no-code revolution that drives the development of supply chain technology that is fully bespoke, in the moment and ‘organic’ to every worker’s needs.

 

Organisations need the blueprint for tomorrow’s AI tech today

With the entire business world still grappling to translate AI’s promise into tangible long-term gain, supply chain leaders have a unique opportunity to own AI strategy and ready their organisations for the coming third wave of AI.

To do this, they must create an AI blueprint that accurately maps their existing AI capabilities, highlighting where the biggest future opportunities lie and where gaps may need addressing.

Supply chain leaders can use this blueprint to establish where bleeding-edge AI tech could deliver a unique competitive advantage, versus where a ‘leapfrog’ strategy makes more sense, learning from the mistakes and adopting the winning techniques of other AI leaders.

Successfully harnessing the third wave of AI doesn’t mean leading across every AI category and sub-category. It means tracking the rapidly evolving AI landscape, understanding your own business, and knowing where and when to go big.