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Artificial Intelligence, the Next Star at IBM, But Highlights Role of Adoption

In the recently concluded virtual forum, tech giant IBM discussed how its business adapts and changes in the age of digital transformation and the pandemic.

Entitled the “Data and AI Forum,” the online sessions capped IBM’s best practices employing artificial intelligence (AI).

One of the main topics covered was the barriers between organizations and Ai, including learning how to scale this properly.

Adding more depth, the virtual event also breaks out sessions that tackle cloud modernization, data modernization, data ops, and data science.

According to Patricia Yim, General Manager for the ASEAN of IBM, “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,” she added.

Among the identified points was Yim scarcity in talent, the complexity of data, and the clients’ lack of trust in data and the results of AI systems that govern them as the main hindrances for a comprehensive AI adoption.

The track that IBM is taking through this discussion is aligned with the 2020 World Economic Forum Annual Meeting, forecasting reskilling emergency on a global scale is imminent.

It is also predicted that by 2022, contingent on the pre-existing jobs has been changed with the technology because of the fourth Industrial Revolution, 42% of the core skills required in current job roles will be changed.

An increase in the demand for news skills in human resources, care, education, and sales. This is on top of the technology-based skills which are existing side from technology-based skills; there will be an increased demand for new skills in the industry of sales, human resources, and care and education.

Scalable services and databases on top of existing architecture will need to be installed for enterprises to cope with the difficult times, and the requirement for data complexity. More accessible content and technology capability are required to back up AI and Machine learning functions.

Lastly, these organizations are also asked tools to enhance content and mitigate unauthorized access to address the need of the people for online security and safety.

Because the privacy regulatory and legislative landscape is continuously growing, these customers will depend on tools to help them meet their compliance needs.

According to the IBM senior vice president for IBM Cloud and Data Platform, Rob Thomas, “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.”

Furthermore, he stated that “[Y]our 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 organization’s ability to make better predictions and better decisions.

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