Combining AI, automation & cloud is key to improving workplace productivity

Source – computerweekly.com

If you take productivity at its most basic – as a measure of how much output you get for how much you put in – then it follows that to increase it you must remove as much unnecessary strain as possible from the input cycle.

Over the past decade, cloud computing has established itself as a key tool for helping companies streamline workflows. And, by allowing multiple users to work remotely on the same data at once, boost productivity.

But, just as productivity is effectively a measure of cause and effect, there’s been a negative – or at least stultifying – impact as a result of this enthusiastic uptake of cloud technology too.

Managing the process of digitisation through the cloud, particularly when done at increasingly large scale, has become unsustainably complex. Processes become jumbled, admin-heavy, and offset by unavoidable human error.

The somewhat ironic result is of course a slowdown in productivity. There’s a growing sense, however, that more can be done with this technology – and that we’re currently looking at just the tip of the cloud computing iceberg.

AI, automation and cloud?

Automation, artificial intelligence and machine learning have dominated both dominated the tech press over the past year, whether for beating humans at board games or stirring up fears of job replacement.

They’re actually already helping to streamline people’s daily lives in more ways than they might realise – whether at a one-click online checkout or in sending auto-generated email responses. When automation is applied well, the user won’t notice its presence at all.

And there’s no reason why the same logic shouldn’t apply to how organisations are managing their resources. In fact, it stands to reason that they absolutely should be looking at where automation can be applied.

Automation, bolstered by AI and machine learning, presents an opportunity to minimise the menial, repetitive, administrative tasks that can so often eat up an employee’s day. The result is more free time that can be put to use tackling more complex, thoughtful tasks that require actual intelligence.

Manual tasks have been automated since the industrial revolution, as humans find new roles and ways of working that are built on automation. While automation isn’t new, its scale and intelligence is.

What might you achieve with your day if you didn’t need to mindlessly wade through sales order data, capacity planning outlines, or cumbersome financial operations? The opportunity is immense, and it all comes back to productivity as people get more done during their work hours – and at a smaller overall cost to the business.

Combining the cloud

Beyond the mitigation of the immediate productivity issue, though, there are further benefits to be reaped from the integration of AI and cloud-based services.

Real-time insights, and the ability of computers to learn from them over time, open up the possibility of AI-informed service improvements.

Analysing enormous amounts of data generated on a daily basis, noticing patterns, and responding to them with suggestions or automatic adjustments is bread and butter for the AI and machine learning programs of today.

And they’re ripe for integration with the flexible, agile business approaches that have become commonplace through widespread cloud adoption. In fact, you might go as far as to argue that the two make ideal – if not essential – bedfellows for this exact reason.

In a hyper-connected world, it’s beyond the realms of acceptability for organisations to fall back on established, static practices.

Conventional wisdom indicates that failing to keep up with the pace of technological change will lead to both irrelevance and a decline to the point of non-existence. In fact, mere irrelevance may soon be considered getting off lightly.

It’s a Catch-22 situation: meeting increased, perhaps more ambitious, productivity targets will be key to survival. But to do that, employees need to be able to make the most of the time they spend at work.