In 2018, Gartner reported that 40{aa282f308afcc222aaa21b0478c79e01a8fedd01972e2180867097bd93930f22} of the CIOs from top-performing companies ranked Artificial Intelligence technologies as the number one game-changer in their organization, followed by, data analytics and cloud.
This year, Gartner released a study that only 7{aa282f308afcc222aaa21b0478c79e01a8fedd01972e2180867097bd93930f22} of CIOs in the Asia-Pacific Region have no interest in Artificial Intelligence technologies.
Both data sets confirm that despite the unique obstacles and bottlenecks in the deployment of the technology, more and more CIOs are embracing AI’s application in their organization’s critical business points.
In this age of digital transformation, CIOs are expected to adopt, engage and lead the company in its business strategies by building a solid digital enterprise.
In the recent round table discussion held at SAP Asia-Pacific, CIOs of SAP and MyRepublic shared how they leverage AI capabilities in their organizations and how they manage the roadblocks of their AI initiatives.
SAP’s AI Efforts
For many years now, SAP has been at the forefront of digital innovation driving and expanding its business globally, now taking full advantage of SAP Cloud Platform and the AI capabilities from its SAP Leonardo portfolio.
Manik Narayan Saha, CIO of SAP Asia-Pacific, has stated that today’s business problems are underpinned by AI thinking. In fact, the company’s center of excellence already had the initiative of building AI models not just for analytics, but also to automate transactions, effectively moving rule-based to pattern-based automation.
In SAP’s APAC headquarter in Singapore, an AI team of experienced data scientists are now put to work. Saha said,
“We’re starting to reach the hockey stick moment where we’ve built enough organizational competencies that can be used across the board… The next step would be to use external data to provide our sales teams with news and other information about their customers.”
One of the company’s AI projects is to develop a digital assistant that would use natural language processing to help its sales team manage accounts and opportunities in their sales pipelines.
MyRepublic’s AI for better CX
Eugene Yeo, group CIO and CEO of MyRepublic, a multinational telecommunications company delivering fiber broadband, voice and digital services to homes and businesses across APAC, recognizes the contribution of AI in helping the company understand its customers better.
“We’ve focused a lot on gathering customer data, as well as external data, to understand our customer segments, including their values, interests, and connections with other people over time,” he said. “This will enable us to create better product bundles catered to their needs.”
The company also recently formed a data science team to support its AI initiatives.
Clearing the bottlenecks
The two CIOs explained how they have managed the key challenges they encountered in rolling out their AI initiatives. Below are the ones mentioned:
Lack of computing power
According to Saha, this is the bigger bottleneck than data issues, particularly when running highly specialized algorithms and models that could take days to generate an outcome.
As with MyRepublic, Yeo said that the company is now using cloud-based serverless computing services to ease the computing crunch needed in driving sales and marketing initiatives.
Utilizing Chatbots
Yeo said that instead of powering chat bots with a knowledge base, his team is working with Google to build a chat bot powered by user stories helping their customers step-by-step through digital interaction.
Saha stated that at SAP, chat bots handle 10-15{aa282f308afcc222aaa21b0478c79e01a8fedd01972e2180867097bd93930f22} of the million IT support requests from employees they receive yearly, which emphasizes the importance of achieving scale in AI deployments.
ROI on AI
“To get full value from AI, you need to deploy it at scale, simply because the upfront investment is significant,” Saha said. “If you are only doing it in one subsidiary or country, it is unlikely that you will get a good return on investment.”
In the same context, Saha warned that AI projects do not always deliver guaranteed results based on a certain metric and within a specific period of time.
“But one thing that’s different between AI and other projects is that the returns from AI will get better as the machine gets smarter and more optimized over time… Just look at Amazon’s Alexa, which can now handle exponentially more scenarios than when it was first released.”
Saha said SAP has embarked on explainable AI projects to look into the factors that influence AI decisions.
Read the Gartner report here.
