CIOs: Machine Learning A Must For Digital Transformation




The road through digital transformation is beginning to meander, with a myriad of ways for CIOs to accomplish goals and build on ever-present initiatives.

As 2017 winds down and 2018 ramps up, enterprise IT leaders are beginning to focus on machine learning and automation processes that will further efficiencies not only in workflows, but to handle security incidents in real-time – a true differentiator in how organizations can protect data and progress the business.

In a new report co-authored by Oxford Economics and ServiceNow that surveyed more than 500 Chief Information Officers in 25 different industries, 72% said they were personally leading digitization efforts in their enterprise, while more than half – 53% - said machine learning is now a major focus area moving forward.

The proof is in the pudding when it comes to those responses as well. According to research firm IDC, spending on AI and machine learning is going to grow from less than $8 billion in 2016 to about $47 billion in 2020 – less than half a decade’s time to realize unprecedented growth.

The drive toward that innovation has already begun, with nearly 90% of IT leaders claiming they already use some form of machine learning now. Conversely, 11% say they have no current plans to implement machine learning technology.

As previously reported by Enterprise Mobility Exchange, there’s a general consensus around the idea that Artificial Intelligence is the next frontier of enterprise mobility.

“These technologies are definitely beginning to gain a foothold,” said Jeff Wallace, Founder and President of Global Kinetics. “I see a combination of both the consumer and enterprise play. There’s a big data umbrella, but what are we doing with that data? That’s where machine learning comes in.”

See related: AI Is The Next Frontier Of Enterprise Mobility

Some industries are also growing much faster than others. Recent forecasts show the AI market for the financial services industry specifically is primed to grow at an absurd 40.4% CAGR in the next half decade, with a proposed $7.306 billion market value in 2022.

“A large amount of non-trivial data is generated in the financial sector, and due to the unstructured data with compliance issues, financial companies are struggling to manage data. These issues need to be analyzed and monitored in order to plan further actions,” a MarketsandMarkets report stated. “Data quality and data governance solutions enable organizations to extract a better picture of their compliance related issues as well as data management. Data discovery is expected to be crucial in the years to come.”

While many either lump together these new technologies as the same, or worse, treat them as opportunities within silos, they indeed need to work cohesively for best results.

“Machine learning is one of the main enablers of AI,” said Don Grust, CEO of Espria Digital, in a contributed column to Enterprise Mobility Exchange. “People often use the terms synonymously and loosely, hence the confusion. But ‘AI’ is a simple term that effectively captures the essence of the topic and works well when the distinctions are not important.”

See related: 7 Essential AI Terms: What Do They Mean?

One more important piece to the morphing puzzle: CIOs and decision makers will need to increasingly focus attention on the teams they build, now requiring skillsets that encompass coding, analytics, and even management.

The road ahead is paved in challenges, but CIOs have the opportunity to create enterprise success by forging ahead.