With the valuation of the global artificial intelligence (AI) market set to jump from 2.42 billion US dollars in 2016 to an immense 59.75 billion US dollars by 2025, it’s clear that enterprises are racing to reap the revenue rewards that machine learning and AI technologies can deliver.

In 2018, AI is still a point of differentiation across the IT industry. The tech giants are the frontrunners with cloud service providers like Amazon Web Services and Microsoft Azure in a bidding war to become the developer’s preferred cloud computing choice. The key here? Both are investing heavily to provide frictionless AI adoption by offering it (and its concomitant sub-systems) as a built-in service on their platform. And the competition only gets fiercer as Google continues to nip at their heels.

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The rest of the IT world is not far behind. In fact, a recent survey by SolarWinds shows that one in four IT managers across the UK in small, midsize and enterprise companies cite AI as their biggest priority right now. It won’t happen tomorrow (let’s be realistic, the on-the-ground initiatives in most companies today involve ongoing cloud migrations, containerisation of essential systems, and the miniaturisation of essential motions into functions-as-a-service), but sooner than we may be willing to believe (or admit), AI will stop being a weapon to be brandished against the competition by bleeding-edge frontrunners and will fast become a real capability necessary for survival.

The benefits of the analytics and predictive capabilities enabled by machine learning (ML) and AI are far-reaching, automating many manual, labour-intensive tasks that often require little human input. As organisations push to leverage business data in new ways, it’s the IT professional’s job to implement and manage that data responsibly.

So, what are the main priorities for IT professionals in the year ahead?

1. Conceptualising in code

The battle cry to learn coding, which has echoed throughout the technology community and onto the national curriculum for the past several years, is getting increasingly louder. This is as much about understanding how programming languages work and the way that different inputs generate different results as it is learning to actually code.

Developing even a theoretical knowledge of this will be vital for understanding the role of AI in a business, whether it will be applied as part of internal operations, used to streamline the delivery or quality of a product, or be packaged and offered as a product itself.

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Hands-on training through vendor initiatives or beginning to investigate API client programming requirements will empower admins to suggest where and how IT can harness AI to deliver added value to their organisations in the year ahead. This training will also prepare admins for the integration of new machine-based technologies, such as bots and, eventually, AI capabilities.

2. Breaking the hype cycle

The hype around AI is huge. However, players are throwing around bold claims of ‘smart algorithms,’ ‘machine learning capabilities,’ and ‘predictive technologies’ without truly understanding the buzzwords. Many supposed AI or ML powered initiatives actually boil down to little more than the automated crunching of extremely large data sets. Some of these solutions pull in hundreds of different strands of data which are analysed and then used to draw conclusions which inform high-level business decisions. This is no mean feat. It’s just not AI.

In a world where enterprises across every industry are racing to unlock the power of AI for their organisations, only a true understanding of the nuances will help businesses wring every drop of value from these technologies.

3. Converting AI into GBP

Perhaps the most important priority for an IT manager to have in his or her view is the ability to explain the value of these emerging technologies in a way that shows the c-suite the impact it can have on the bottom line.

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For example, according to Gartner, AI is expected to create 2.3 million jobs by 2020, and eliminate 1.8 million jobs. Potential job losses and gains should be considered when investing in AI, as well as how the technology will change worker collaboration and decision making. It’s the IT professional’s responsibility to provide counsel to the executives and leaders making decisions around IT investments.

Getting ahead

There are myriad challenges facing businesses looking to leverage AI and ML. With endless hype shrouding a technology which has huge business potential, it’s hard to know which moving part to focus on first. The most important thing for IT professionals is getting ahead of these emerging technologies before they completely permeate the tech landscape.

Only by laying the right groundwork, from company education to making a compelling business case, will they have a chance of capitalising on the impact that AI can have on their organisations.

Sourced by Leon Adato, Head Geek, SolarWinds