We conducted a survey about a week ago with a hundred CIOs and CTOs who said that AI is going to be crucial during the next two years. But, they also said in the same survey that they don’t think their teams will be able to drive that change. What’s your perspective on how IT Executives can better prepare for it?

At Royal we started by fomenting the AI-Data Analytics knowledge across the entire enterprise. Everyone in the company should be involved and understand the capabilities at a macro level. That way you will have more people with ideas on how to translate data to create business value. We also created a channel where people can come up with such ideas. We are building our Data Analytics team and changing our business models to be more data driven. As for talent, it is a real challenge indeed but instead of looking only outside our organization we are looking inside and finding potential data scientists, data engineers and data translators that just need training and exposure. It is imperative that the CEO embarks in the journey and supports the culture. Also, count with experience vendors and have a great leader in that arena.

CIO’s need to begin to prototype and pilot AI and ML projects. When possible, they need to look at partnerships.

When it comes to internal skills and team building, they need to anchor around a dedicated leader who has experience.

AI and RPA AUTO can help the business drive positive business outcomes with various business processes and other tasks, both strategic and tactical, but first the business have a clearly mapped out problem to solve for. Otherwise it may result in developing solutions for problems/situations the business may not have just yet. 

Find a real need rather than inflating the hype of adding AI unnecessarily into the environment, as it just simply creates a bubble of unstable frameworks that will not lead to a proper development of its true benefits.

 AI is the end result of well implemented BI and ML programs. however, the technology change from BI to ML to AI are step changes from one another and require different levels of investment in talent, skill set, technology, infrastructure and operations. AI and ML will also drive changes to core business operations at the company based on the application of AI. Legacy IT teams will most probably be hesitant to implement AI as most leadership teams treat AI as a buzz word and view it as the /"next shiny toy/" to show off rather than view it as a serious restructuring tool. Implementation of AI requires transformation thinking and necessitate some business model changes. Once leaders realize how difficult, expensive and time consuming it is to put an enterprise grade AI program in place, some structure tends to fall in place and use cases will be rolled out slowly.  IT executives can prepare for the change by taking a long, hard look at their company's business model and identifying key focus areas where AI may delivery reasonable results with existing resources. They may then expand their data programs to augment implementation of a sustainable AI program.