With two thirds of data and analytics leaders investing in AI in the Middle East and Africa, we look at what businesses can do to ensure their initiatives succeed
AI is now well into its ‘early adoption’ phase, with businesses throughout the Middle East and Africa clamoring to launch new initiatives.
Almost three quarters of the data and analytics leaders who responded to our latest regional benchmarking survey say their organization has appointed someone to be responsible for AI deployment.
Two thirds say their organizations are exploring potential uses for AI, with 40.2% of them saying they’ve at least reached the ‘early implementation’ phase. Just 15% say they aren’t looking to develop AI capabilities, 18% want to learn more about them and 26% are doing feasibility studies.
The potential benefits AI may bring to a business have proven extremely enticing for business leaders in the region, as FNB South Africa CAO, Consumer Banking and Chief Risk Office Mark Nasila explains.
“We’ve designed algorithms to try to offer the right product to the right customer at the right time,” he says. “We enhance this with financial crime models to make sure we’re not offering products to criminals.”
Given the prevalence of financial crimes in the region, developing AI capabilities to combat fraud and money laundering is a priority for the banking industry’s data leaders.
FNB is acutely aware that combatting cybercrime is essential for developing good relationships with its customers, and machines can check for suspicious activity far more effectively than humans can.
“The bank is now using an in-house developed AI system to optimize the due diligence forensic review process,” Nasila explains. “This AI system automatically creates a single consolidated report with all the information required, which includes a single view for financial crime risk management.”
“It’s important that we understand the customer’s intentions on our platform going forward. They might be good today, but based on our algorithms and behavioral data, in the future they might turn out to be criminal” – Mark Nasila, CAO, Consumer Banking and Chief Risk Office, FNB
He concludes: “So, instead of the analyst doing all this work, we’re having the analyst just doing quality assurance and making the decision.”
Initiatives like these have the potential to revolutionize the ways businesses provide goods and services. But with Gartner predicting that 80% of AI projects “will remain alchemy, run by wizards whose talents will not scale” through 2020, it’s not clear that all organizations are ready to deliver these projects.
Data Leaders Must Walk Before They Run
The failure rates for AI and other advanced data projects are high. According to a 2019 study from the International Data Corporation, 25% of organizations report that half of their AI projects result in failure. Survey respondents cite “unrealistic expectations” and a lack of skilled staff as the top reasons for these failures.
“Once you’ve decided to have a data strategy, the first thing most people do is buy hardware and software,” says Hartnell Ndungi, CDO at Absa Bank of Kenya. “So, you go and start buying ‘best in class’ BI solutions before knowing exactly whether the tools are really going to solve your problems.”
Only 40.7% of respondents in our survey plan to invest in data governance or management in 2020, and just 29% expect to invest in data quality or enrichment improvements. Yet, these architectures underpin every successful AI program.
Given that data leaders in the Middle East and Africa are grappling with data silos and working to instill data culture in their organizations, the importance of these investments should not be overlooked.
The business world may be excited about the potential of AI and advanced analytics. But organizations must make sure they have the right foundations in place first in order to succeed with these ambitious new initiatives.