Unlocking the power of data with artificial intelligence

The faculty’s new AI Centre for Decision Analytics is transforming the way we use data to make better decisions

Data is at our fingertips like never before.

Thanks to advances in artificial intelligence (AI), information technology, engineering and online scrolling habits, the availability of data today has skyrocketed. Yet a recent study reveals fewer than one in four companies consider themselves data-driven

With all this data at our disposal, how can we distinguish what’s most valuable? How can it be used to make informed decisions? What are all the possibilities? 

The Alberta School of Business’ new AI Centre for Decision Analytics (AI4DA) is well on its way to answering these questions through innovative research, industry partnerships and educational opportunities. 

Harnessing the power of AI, the centre aims to transform how data is analyzed and used to make informed decisions and provide solutions to the most pressing challenges facing organizations today. 

“We have the potential to revolutionize decision-making processes,” says AI4DA’s director, Borzou Rostami. “The outcomes span beyond efficiency and productivity gains — they have the power to improve the quality of life of our communities.”

The centre focuses on research and analytical tool development in areas touching most impacts of daily life: healthcare operations, city planning, transportation, the environment and retail operations.

Undergrad and graduate students can also register for several AI and analytics courses and participate in research studies to gain experience outside of the classroom. 

Maximizing data potential through integration

According to Rostami, harnessing the full potential of data starts with bridging two crucial AI functions: machine learning (ML) and optimization algorithms. 

ML techniques analyze vast amounts of data, identify patterns and make predictions.

“They help us extract the most important data and provide insights into complex data sets,” he explains. “In the healthcare setting, this can translate into analyzing patient data to assist doctors in diagnosing diseases, predicting treatment outcomes and personalizing treatment plans.” 

On the other hand, optimization algorithms are essential for finding the best possible solution among a set of alternatives.

“In business operations, this can look like optimizing supply chain management, inventory planning and resource allocation to minimize costs and maximize efficiency,” says Rostami. “For instance, in logistics, optimization algorithms can find the best routes for delivery vehicles, reducing fuel consumption and emissions while ensuring timely deliveries.”

He adds that while each function can operate independently, system integrations are essential to achieving breakthroughs. 

“While ML could help predict the medical outcome of a chosen combination of treatments and drugs in specific dosages for a patient over a set time frame, there could be an exponential number of combinations and constraints to factor in, like side effects or resource scarcity,” says Rostami. “It’s impractical to enumerate the set of such high-dimensional combinations — we need support from algorithms to search efficiently and return an optimal choice.” 

AI in the real world  

Research and partnerships at AI4DA are already underway, tackling critical healthcare and environmental challenges and adapting to the needs of modern retail businesses. 

Consider some of the obstacles facing Alberta’s healthcare system: rising expenditures, long wait times, staffing and drug shortages. 

The AI4DA team is developing AI solutions to support healthcare professionals, managers and policymakers, by enabling them to make well-informed decisions that contribute to improved outcomes for patients. 

“Data-driven decision-making is the cornerstone of modern organizational strategy,” says Rostami. “We want to empower decision-makers with strategies backed by real evidence.”

Using ML and algorithm optimization, the team’s work has provided recommendations to improve hospital resource allocations, bed management and supply chain processes. 

On the mobility front, AI4DA is tapping into the TELUS Data for Good initiative to analyze mobility patterns in Edmonton and assist delivery companies in creating effective sharing economies, such as crowd shipping. 

“This project addresses the challenges of last-mile delivery, the last step in the delivery process when a parcel moves from a transportation hub to its final destination, which is crucial to supply chains,” says Rostami. “In Canada, last-mile delivery is valued at over 17.8 billion U.S. dollars and significantly contributes to greenhouse gas emissions. Transitioning to innovative delivery models is essential for meeting customer demands while reducing environmental impacts.”

The centre is also collaborating with a local Edmonton company to assess urban fire risks in cities across North America. Predictive models and risk assessment tools are under development to help mitigate the impact of urban fires and enhance disaster preparedness. 

“The future of AI4DA holds immense promise,” he shares. “I’m thrilled to have the opportunity to continue pushing the boundaries of AI and decision analytics to drive innovation in both theoretical research and practical applications.”

To learn more about AI4DA, visit www.uab.ca/ai4da

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