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“Businesses are evolving faster than ever, and to stay they need to focus on highimpact priorities,” Masood told his audience. “But that can be difficult with the backlogs of data, internal processes, and endless administrative tasks.

“Many companies seek products to solve this challenge, but a one-size-fits-all technology solution doesn’t account for the uniqueness of every business.”

AI ‘unlocks human ingenuity’

Masood adds that he and his UST colleagues combine strategic business expertise with knowledge management, automation, and AI “to unlock your company’s human ingenuity”.

“When it comes to your business there is no greater advantage than empowering the ingenuity of your workforce,” he says, adding:

“By reimagining your business operations, we empower your people to focus on those opportunities with the highest impact potential.”

He explains that AI-led technology works by ”learning processes and decisioning frameworks” and that it “maps how each piece of your business is connected”.

Typical of many AI platforms for supply chain and beyond, UST’s also mimics learned decision patterns “to execute processes at optimal speed and accuracy,” says Masood. “And also begins to suggest revenue-driving insights for your business.”

He says using AI-driven solutions, UST has delivered “measurable business outcomes within 90 days” and that it has also “reduced

Dr Adnan Masood

TITLE: CHIEF AI OFFICER & LEAD ARCHITECT

COMPANY: UST GLOBAL

INDUSTRY: IT SERVICES

LOCATION: US operational costs for global companies by 30% within the first year”.

Masood is an engineer, researcher, and thought leader. His expertise includes scalable enterprise architecture, machine learning, and cloud platforms –especially Microsoft Azure and AWS – and is a Microsoft Most Valuable Professional for Data Platforms.

Interestingly, Masood says that when properly embedded, AI doesn’t even feel like AI.

“When enterprise software companies build seamless AI into applications as part of your machine learning stack, it’s so organic you don’t even feel it’s AI anymore, even though these cognitive components are automating your workflow.”

ML experts in short supply

Masood also told his audience that demand for machine learning experts is far outpacing the supply, and that to address this gap, recent years have seen “the biggest strides in the development of user-friendly machine learning algorithms”.

He added: “With auto-ML capabilities, non-experts can apply automated machine learning “to ease the burden and the workload”. He says this is all part of “the democratisation of AI”, another strand of which he says is “reinforcement learning”.

“Reinforcement learning is a semisupervised learning model that allows agents to take action and interact with the environment,” he says.

He adds that use-cases for reinforcement learning include personalised recommendations and “anything in which you need an intelligent loop of understanding and learning”.

Masood’s final word on AI was “it is a team sport. It is the business units, technology groups, and research teams all working together to provide business outcomes.

“That’s the key message – that all the components of AI are targeted towards providing businesses with a cohesive business outcome.”

SAPInsider report points to importance of AI to supply chain

A recent report suggests process automation is key to creating a robust supply chain during times of economic uncertainty.

The benchmark report –Process Automation in Supply Chain was produced in collaboration with SAPinsider, the world’s largest SAP community.

It shows that 51% of respondents say resiliency is the top supply chain concern driving the need for process automation, with agility close behind (46%).

It also found that 89% believe process automation in supply chain is either ‘important’ or ‘very important’ to attain digital transformation objectives.

But it seems a major gap remains between where the industry needs to be and where it currently stands: nearly three-quarters (72%) indicated that less than half their supply chain processes are currently automated, with this dropping to just 25% for a further onethird of respondents.