Tech giant IBM held a virtual forum on Tuesday, Aug. 25, to discuss the current challenges that enterprises are facing in their digital transformation during the pandemic. The online sessions highlighted IBM’s use-cases from its clients where artificial intelligence (AI) has been the main enabler of their digital strategies.
The “Data and AI Forum” also shed some light on the barriers between organizations and AI, as well as how to scale properly. Aside from AI, there were also breakout sessions that discussed cloud modernization, data modernization, data ops, and data science.
“Data is what fuels digital transformation and AI is the defining technology of our time which can unlock the value of that data, and yet, successful adoptions remain challenging for many organizations. We have been exploring this for a while and we have identified three main challenges facing the broad adoption of AI,” said Patricia Yim, general manager for Asean at IBM.
Yim identified scarcity in talent, complexity of data, and the clients’ lack of trust in data and the outcomes of AI systems that govern them as the main hindrances for a comprehensive AI adoption. Even at the 2020 World Economic Forum Annual Meeting, it was predicted that a reskilling emergency on a global scale is imminent.
By 2022, based on how pre-existing jobs have been transformed with the technology brought by the fourth Industrial Revolution, 42% of the core skills required in current job roles will be changed. Aside from technology-based skills, there will be an increased demand on new skills in the industry of sales, human resources, and care and education.
In terms of data complexity, since organizations need to have readily accessible products and services all the time, it will require them to put up scalable servers and databases on top of their pre-existing architecture. And since some services will require the capabilities of AI and machine learning, these organizations will need more accessible content and the technology to back them up.
Finally, since customers are always prioritize the privacy and security of their data, they will need tools that let them control content while preventing unauthorized access. Since the privacy regulatory and legislative landscape is continuously evolving, these customers will depend on tools that will help them meet their compliance needs.
Rob Thomas, IBM senior vice president for IBM Cloud and Data Platform, explained that consumer AI focuses on smart devices and social media while business AI deals with how to make better predictions and optimizing or automating tasks. He also added that the three most critical areas needed by businesses to properly leverage AI included – natural language processing, trust, and automation.
“Your AI is often only as good as your data. There’s no AI without IA – information architecture. Your data is going to drive the quality of your AI, and the quality of your AI drives the ability of the organization to make better predictions and better decisions,” Thomas said.