In years to come, it’s possible that we’ll look back on 2018 as the year that Artificial Intelligence (AI) really arrived. When potential became possible, and hype gave way to enterprise adoption. But how much influence are CIO’s having in its adoption, and how well understood is the term?
AI and innovation
We recently launched the sixth edition of the annual Logicalis Global CIO Survey, which gathered the views of more than 840 CIOs in a number of areas. Innovation was a dominant theme, with this year’s survey demonstrating real progress in the role of the CIO in this area. CIOs are finding that they are very much at the heart of the action – with 83% either leading (32%) or enabling (51%) innovation. It’s an area they’re being increasingly judged on too, with half (50%) now being measured according to their ability to deliver service innovation.
Given that technology now pervades innovation – either delivering it or enabling it – we were keen to understand how CIO’s view the rate of adoption, utility and impact of emerging technologies – particularly Internet of Things (IoT) and Artificial Intelligence (AI). Whilst IoT shows signs of becoming more mature in its use, AI and Machine Learning, appear to be in an earlier phase of the hype cycle – possibly where IoT was 12 months ago. Nearly a fifth (19%) of CIOs claim that their organisations are already using AI. That adoption seems likely to continue at pace, with 66% saying AI will be in use in their organisations within three years.
Understanding who is responsible for AI
Before we get too excited about AI changing the face of business, it’s important that we stop and question just how the term is understood. Like IoT, AI is really complex, and many of the use cases we’ve seen up until now are just scraping the surface. The technology industry is still collectively scratching its head to work out what it really means, as the hype continues and threatens to dilute the concept. Do CIOs perceive AI simply as autonomous automated services and interfaces essentially guided by complex manually created rules? Or do they see it in its purest form, as technology that is not just autonomous and automated, but also able to learn and adapt independently based on context? In truth, it’s probably a bit of both.
The big issue facing CIOs when it comes to AI is less about the technology itself, and more about the people, process and culture which support its adoption. Whilst there’s clearly a value in products being ‘AI-ready’, the hangover from the rise of Shadow IT – which saw departments and individuals investing in their own hardware, software, apps and services – is organisations that have huge swathes of data residing in a wide range of places, some out of sight of the CIO.
When asked about where AI and machine learning were in use within their organisations, it was no surprise to see the CIOs we surveyed point to the IT department as the leading area. That’s likely because this is the department they’ve got the most sight of. The siloed nature of organisations, and the distributed data residing within, causes a headache in terms of ownership. Most business have a variety of people who own the data in each department, but few who want to be responsible. That’s where the CIO comes in, as issues such as data security and compliance sit squarely within their remit.
The opportunity for AI
So where can the CIO start, in order to truly realise the potential of AI? The first step is to get people together to understand and agree their processes around data. People and processes can change really quickly, so taking the time to agree a clear approach is important. Those silos aren’t going to be broken down overnight, so the CIO also needs to be realistic. Only then can you think about how to leverage what you’ve got in place, but even then this needs to be done in the right way, with issues such as security, performance and cost-effectiveness at front of mind.
From the survey findings, it was encouraging to see CIOs so bullish about their ability to engage with AI. This, more than anything, will be vital if organisations are to derive true value from AI. At present, rates of use across various business departments are low – with the exception of IT and customer service – which suggests operational, fringe and test cases. However, this also seems to be an opportunity for CIOs to build a culture of experimentation and small-scale deployments driven by clear customer or market needs.
AI should not be seen as a silver bullet. It isn’t the answer to everything. It needs more data, more resources and you need the right foundations and infrastructure in place and ready to go. Otherwise there is going to be a huge amount of inefficiency. Especially as the speed of change in technology terms is unbelievable, with new vendors and solutions springing up on a regular basis. To understand whether these new options are to deliver against your objectives it’s imperative that you look at the entire ecosystem, with people, culture and process playing a pivotal role.