Artificial intelligence (AI) gets a headstart in the consumer business with organizations utilizing the technology for various use cases such as predictive actions and smart devices. Global technology company IBM highlighted AI’s strengths that enterprises can leverage at its “IBM Data and AI Virtual Forum ASEAN” held recently.

“Based on our past engagements, clients have to start with a focus on the quality of their data if they intend to adopt AI,” said Rob Thomas, SVP, IBM Software. “Because their data is going to drive the quality of their AI and the quality of their AI drives the ability of the organization to make better predictions and decisions.”

IBM’s AI for Business is focused on three areas: natural language processing, trust, and automation.

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Natural language processing is the idea of understanding all of your data. Trust is about how do organizations know that they are deploying AI that can trust decisions and complies with the regulator. Automation is about how do to start to really change the way that organizations are working.

“Think of this as the next phase of digitizing your business because digitizing your business is about automating tasks and giving your employees ‘superpowers’ by giving them the ability to use AI,” Thomas said.

Outperforming revenue growth

AI has pulled itself from the “emerging technologies” category as more and more companies are using it either for consumer or enterprise services. Thomas highlighted that companies that are using AI, the ones that are getting into production now, are starting to outperform their peers in terms of revenue growth and profitability.

“AI is starting to have the impact that we all thought it would years ago,” Thomas said. “We are starting to see an increase in AI adoption. Companies now are trying to deliver real-time answers to consumers.”

Quality of data

For organizations that are contemplating adopting AI for their business processes, Thomas said that based on what they learned over the years working with customers, “AI is often only as good as your data. There is no AI without IA or information architecture.”

“All our engagements have taught us that clients that are going to adopt AI, they often have to start with a focus on their data, because their data is going to drive the quality of their AI, and the quality of their AI drives the ability of the organization to make better predictions better decisions,” Thomas explained. “So it’s really fundamental to this journey.”

IBM has developed a concept called the AI Ladder, which is some sort of a methodology that allows organizations to think through the process of making data ready for AI to support the kind of outcome they wish to achieve.

“Ladders about how do you collect, organize, analyze data and ultimately how do you infuse it into your business processes,” he said.

Security

As with any cloud-based applications, security is always an issue. IBM built an architecture that supports the needs of organizations for security at all layers, from the operating system to the data to the application to any endpoints in order to help companies understand any potential risks and deal with them as they present themselves.

For CIOs (chief information officers), IBM previously introduced Watson AIOps, which is an AI-powered IT incident resolution fueled by the organization’s data. It synthesizes data no matter where it resides to provide you with real-time insights and recommendations. It helps organizations address complex IT issues quickly to minimize service disruptions and prevent outages.

Thomas calls IBM Watson AIOps the “CIO’s superpowers” because it helps them monitor the activities of the whole IT architecture.

“How systems are running and predicting where things could possibly go wrong,” he explained. “Helping you quickly triage or fix problems if they emerge. It really becomes the nervous system for your whole IT environment. So that you have AI watching over everything that’s happening in your organization.”

Watson AIOps

Watson AIOps has also sped things up in terms of the resolution to problems.

“What would have taken hours to resolve now gets resolved in minutes,” Thomas said. “This is all about using AI, to give your CIO superpowers.”

“Today we are finally starting to see some distance being created between companies that are leveraging AI and companies that are not,” he said. “What I would encourage you to think about is this whole concept of the AI Ladder. Think about how you are collecting, organizing, and analyzing data. Because what we found is that most companies need to make their data ready for AI.”