We’re inching ever closer to the annual Gartner Symposium/ITxpo happening in Cape Town, which means the research firm has been upping the ante as far as finding from its myriad surveys and reports go.

The latest one looks at artificial intelligence and machine learning, both of which will likely be spoken about at length at the Symposium, especially as it pertains to delivering value for CIOs and the organisations they run.

To that end a recent survey conducted in December last year found that organisations have, on average, four artificial intelligence (AI) or machine learning (ML) projects in development, with a further 59 percent of respondents noting that they have a solution which has been fully deployed, today.

Doubling down

That average number is predicted to more than double in 2020, with it accelerating to as many as 35 in 2022, with Gartner highlighting two key drivers in particular for this growth – improved customer experience and task automation.

“The rising number of AI projects means that organisations may need to reorganise internally to make sure that AI projects are properly staffed and funded. It is a best practice to establish an AI Centre of Excellence to distribute skills, obtain funding, set priorities and share best practices in the best possible way,” points out Gartner research VP, Jim Hare.

When it comes to customer experience, as many as 56 percent of organisations currently use AI as a means to support decision-making or offer up recommendations. “It is less about replacing human workers and more about augmenting and enabling them to make better decisions faster,” adds Hare. 

As for automation, it ranks second highest among respondents in terms of their key motivators for adopting AI at 20 percent. In particular these organisations are employing automation to handle tasks such as invoicing and contract validation in finance or automated screening and robotic interviews in HR.

Mind the gap

Should Gartner’s AI and ML project prediction come to fruition, one of the biggest challenges any business will face is skills, or the lack thereof.

In fact ineffective skills is the top concern for businesses looking to adopt AI, sitting at 56 percent. “Finding the right staff skills is a major concern whenever advanced technologies are involved,” confirms Hare.

“Skill gaps can be addressed using service providers, partnering with universities, and establishing training programs for existing employees. However, establishing a solid data management foundation is not something that you can improvise. Reliable data quality is critical for delivering accurate insights, building trust and reducing bias. Data readiness must be a top concern for all AI projects,” he concludes.

With AI and ML not only here to stay, but become engrained in many organisations’ way of business in the coming years, addressing the skills gap and finding an effective area for implementation will be top of mind for many CIOs.

Hopefully these will be topics of discussion at the Symposium later this year.

[Image – Photo by Alina Grubnyak on Unsplash]