Point of no Return: Why Operational AI is Here to Stay
Best described as the use of artificial intelligence to improve business operations by integrating technology into everyday processes, operational AI is changing the game from a supply chain perspective.
Clear and well-documented advantages include the ability to automate routine tasks and make decisions in real time, resulting in enhanced efficiency and optimised performance across the board.
It is already an established tool being used in a variety of real-world situations such as predictive procurement maintenance, where AI forecasts potential disruptions in availability. This enables companies to strategically time purchases to avoid cost spikes and secure better pricing.
There are plenty of additional uses across the procurement and supply chain space, as Christoph Schenter, Principal of Data & Insights at INVERTO, the specialist supply chain management arm of Boston Consulting Group, explains.
“In supply chains, operational AI improves logistics and inventory management and is also a powerful tool to help procurement functions with negotiations, where it’s used to design strategies and enable game theory powered negotiations,” says Christoph.
“In customer service industries, AI chatbots are now widespread, with automated responses being used to enhance customer support.”
In truth, the numbers do most of the talking when it comes to assessing the extent to which companies have been willing to put their faith in operational AI.
PwC’s Digital Trends in Operations Survey for 2024 discovered almost 55% of firms had invested in AI, including machine learning, to digitise their operations.
That figure will undoubtedly have increased since the consulting giant published the results of its study back in March.
SAP: Flying the flag for AI
One organisation which has long flown the flag for the integration of AI into day-to-day operations is SAP.
Led by its SAP Digital Supply Chain business, the German technology giant harnesses the power of AI across its entire catalogue of supply chain solutions.
Darcy McClaren, Chief Revenue Officer of SAP Digital Supply Chain, has spoken frequently – including to Supply Chain Digital – about AI setting new standards and becoming the backbone of risk-resilient supply chains.
Assessing the fast-moving situation with which supply chain professionals are grappling, she says supply chain management software has entered the “adaptive era”, harnessing advanced analytics, AI and machine learning to analyse large volumes of data.
Darcy’s take is that AI’s more advanced offshoot, generative AI, now serves as the interface for practitioners to engage in extensive data analysis to enhance supply chain resiliency.
“The future promises an autonomous era, defined by software that can operate with minimal human intervention, powering more efficient and responsive supply chains,” she adds.
“This evolution paves the way for operational AI – the practical application of AI into day-to-day business operations and processes. Operational AI enables companies to connect digitally and optimise their operations across product and asset life cycles. It transforms supply chains with AI-driven insights, recommendations and integrated automation.”
The key, Darcy says, is ensuring AI is embedded across an organisation’s entire supply chain strategy so that anyone can tap into its benefits.
She continues: “By investing in operational AI, businesses can create a single, constant digital process across the supply chain and guide decisions with real-time operational and business data, enabling the autonomous supply chain.”
AI unlocks full value of data
As Darcy indicates, Gen AI and machine learning hold the potential to greatly enhance supply chain efficiency and resilience across countless industries.
By utilising natural language, supply chain leaders can quickly access information, navigate systems or implement changes without needing to be in a specific application.
The result? Manual and repetitive tasks are reduced, time is saved and errors are minimised.
With Gen AI tools at their disposal, leaders can unlock the full value of data, uncover new insights, identify efficiencies and, ultimately, drive stronger business results.
“These advanced AI tools help to automate complex tasks and improve the decision-making accuracy of operations,” Christoph emphasises.
“Gen AI can also be used in product design and to optimise operational processes, while machine learning is being used to analyse data to predict future outcomes including customer demand.”
Darcy also highlights Gen AI’s ability to elevate product quality by optimising manufacturing and asset performance.
She reveals SAP customers are particularly interested in automating the ordering of highly-configurable products.
“When a customer places an order where there are a lot of different options; there’s a process in place to help tailor the order,” Darcy explains. “Within that process, there’s opportunity for automation like predicting equipment failure based on IoT data to service assets proactively.
“By leveraging gen AI, organisations can generate prioritised maintenance plans to maximise uptime and optimise service schedules using advanced rules to dispatch the right technicians.”
Creating synergies
Christoph describes operational AI as “essential” to modern supply chains.
He is straightforward in his belief that, without investing in the technology, companies risk lagging behind competitors in terms of both innovation and operational effectiveness.
Darcy expresses the importance of AI in almost identical fashion, but highlights a crucial need for supply chain leaders to first educate their organisations on the power and benefits it can bring.
This, she adds, is the starting point for addressing adoption challenges and building foundational AI capabilities.
“For supply chain leaders looking to integrate gen AI with existing solutions, it’s vital to ensure AI is relevant, reliable and responsible, so business outcomes can be achieved in a secure, compliant way,” says Darcy.
“Supply chains equipped with new tech and tools will help reveal new business opportunities, improving lead times, offering more effective executive review cycles and managing inventory levels quicker. By connecting AI with rich data from across the enterprise, organisations can create synergies that enhance productivity, improve business agility and reduce costs.
“Altogether, these improvements can ripple throughout the entire organisation to optimise operations.”
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