Whether you’ve jumped on the bandwagon, or spent the last couple of years trying to avoid getting run over by it, there’s no denying that artificial intelligence has firmly made its mark.

With the quest for AI dating back as far as the 1940’s, we’ve all had plenty of time to immerse ourselves in the ideology that machines will one day be able to think and act just as humans do.

However, while the ambitious amongst us still believe we’re on the very brink of such a technological revolution, the truth is we don’t have too much to show from the last few decades.

In fact, recent data from Gartner suggests that even after years of propaganda and excitement, still only one in seven CIOs are actually deploying AI technologies in production.

Demonstrating just how immature the marketplace is, the initial, flashy promise of AI is still out of reach, with the reality being a more practical roll-out.

However, it’s not all doom and gloom as despite there not being the big-bang implementation the industry has been waiting for, a more accurate representation of how we can expect to see organisations using these technologies is within reaching distance.

We might not see HR teams making way for HAL 9000 in the next six months, but we can expect to see AI making people smarter, more effective and more productive – there are just a few things to consider along the way.

De-stressing staff

When it comes to conversations about AI, a notion still exists of people getting replaced and organisations ended up with a completely robotic workforce. However, what many businesses don’t consider is that by taking away the repetitive, manual tasks, employees are under less strain and have more time to spend on other value-driving areas.

If organisations can reduce the amount of stress their employees face in their day-to-day roles, the payback is much greater than any amount of money spent on technology.

Take the financial services industry for example, where staff can spend up to 70% of their time speaking to customers that are reporting lost debit cards, or asking for their pin number to be reset; pretty simple tasks that customers can theoretically self-serve through chatbots.

The other 30% of their time is focused on speaking to someone who has lost their partner and needs to deal with their financial affairs; trickier processes that require a human touch.

What organisations need to work out is where the balance lies, finding the right proportion of time for employees to carry out challenging work, while also considering their productivity levels and not setting them up for failure.

People need something to allow them to decompress, meaning businesses need to think about the way that they operate, how they are measured and what support they are being given.

Augmented, not artificial

Thanks to a mass of negative connotations, as well as concerns of a terminator-style takeover, instead of playing up the AI hype, organisations have now done a complete 360 and are starting to de-emphasise the role of AI in their operations.

In many other cases, businesses are deploying what they believe to be artificial intelligence, without realising that what they are actually channelling is augmented intelligence.

Similar to artificial intelligence, augmented intelligence does what it says on the tin – it augments the intelligence of the people using it, tapping into tools and capabilities that allow humans to make better decisions.

Whether this helps them use their time better, or do their job in ways that the technology can enable, you’re just looking at artificial intelligence in isolation.

Even large tech giants such as Microsoft have referenced the use of augmented intelligence, positioning it as the combination of deep learning technologies and modern era computing.

As organisations consider the idea of the ‘new AI’ and finding the right level of technology-led activity, they should apply one basic rule – if you can make a decision on a task in less than thirty seconds, that task can easily be automated.

If businesses apply intelligence to supporting those decisions that can’t be made in less than thirty seconds, they need to be backed by insight and analytics that help to find the right solution.

Setting expectations

The only realistic AI development for businesses in the next six to twelve months, however, is for them to understand the outcomes that they are looking to achieve. A lot of common myths are starting to get busted – AI will teach itself and solve a wealth of problems.

The hype and mythology is evaporating as businesses realise that the typical AI programme is taking four times as long as they originally intended.

Instead of being able to take place in a year – or even four years – vendors are claiming that this self-developing technologies are pre-populated with knowledge; but that’s not the case.

Instead of focusing on what may or may not happen, organisations should work on adjusting their mindset. The technology is not maturing or developing anywhere near the rate that the market noise would suggest.

There are small and organic increases coming in, but there is still a need for businesses to wake up to the fact that it is no longer good enough to talk about AI when they aren’t doing it.

A few years ago, robotics was something organisations just ‘had’ to do, without knowing how or why. More recently, AI has fallen into a similar space, with the perception that businesses will be seen as inadequate and fall behind competition if they do not engage with the AI uproar.

However, artificial intelligence is not something that organisations can just go out and do, but something that businesses will experiment with in multiple, smaller initiatives such as augmented intelligence.

Whether start-up companies or million-dollar corporations, those that have the greatest success with AI will be those that operate in a more agile mindset.

You can deliver realistic and meaningful ROI as long as you are bound by clarity of what you're looking to achieve, and realistic as to what the impact of the technology may or may not be.

Neil Kinson, chief of staff, Redwood Software.