What factors are hindering enterprise adoption of artificial intelligence?

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Everybody wants to jump on the artificial intelligence (AI) bandwagon. It's cool, it's exciting, and it's the future. However, it's not a matter of plug-and-play. AI is complex, which is part of the beauty of it. For some organisations though, this can be a huge frustration in their quest to become more innovative.

That's not to say that AI adoption is impossible. It just requires some careful steps to ensure your organisation gets the most out of it. Here are just some considerations to bear in mind if you're thinking about embracing AI.

The power is in the people

The first thing you may be hit with is the fact that no one among your employees is that well-versed in AI. It'd be no surprise either; in fact, most organisations are suffering at the hands of the AI skills shortage.

A great first step is to upskill your current team. In particular, you should consider rolling out in-house training (for yourself too) for a hands-on approach on bridging the skills gap. Alternatively, you can switch it up a gear and (for lack of a better word) aggressively scout for machine learning talent. Of course, this does not mean aggressive poaching; rather, get ahead of the game by looking now, instead of when you desperately need it.

Make peace with not knowing the how or why

AI doesn't have the vocabulary that we do, which can be a source of frustration for users. In particular, it can't elaborate on its choices, which has formed the basis of 'explainable AI', a concept that is yet to come into fruition.

In light of this, it's important to think tactically about what you need AI for. Of course, it's tempting just to apply it to anything and everything, but you must be strict. More specifically, it's best to weigh up the pros and cons of each AI application: how bad will it be if it can't explain itself? What is our contingency or remediation plan in the event of this? More importantly, how critical is it for you to understand the basis of AI's choices?

You know you should, but why should you?

Another point to note is that it seems there is pressure for enterprises to adopt AI. Everybody knows that they should, but not everybody knows what its specific use case is for them. For example, if customer service is your realm, how can AI boost their experience? If banking is your playing field, what does AI have to offer?

Of course, it's a bit frightening to delve into the unknown. Much of this is down to lack of concrete figures. On that note, Gartner does predict that in the next 10 years, "50% of AI investments will be quantified and linked to specific key performance indicators to measure return on investment." Thus, if the fear is holding you back, you've not long before we can make use of real results. Either way, it takes careful consideration; don't adopt AI for the sake of it. Think about shortfalls in your current processes and explore how AI can be their relief.

If you'd like to learn more about attitudes towards AI, check out our Tech Chat episode with Brendan Dykes at Genesys.