AI - The only thing to fear is inaction

Nate Buchanan Director, Pathfindr

As I write this, today is Friday the 13th, and while I’ve never seen one of the eponymous movies, every time the 13th falls on a Friday my thoughts are always drawn - however briefly - to bad fortune. If you’re like me, perhaps you’re extra careful when crossing the street and avoid black cats like the plague (though to be fair, I’m not much of a cat person on any other day either). Better to be safe than sorry, right?

BUT…what if on the other side of the street there’s a crisp $100 bill just lying on the ground? Or, what if the cat turns out to be incredibly cool and would make a great companion? In those scenarios, my irrational fear would have held me back from a positive outcome.

It’s the same with AI. Too often, organizations are worried about what could go wrong, or are too risk-averse to plow headlong into the world of AI. But even if your “taking the plunge” looks more like “dipping a toe”, there is plenty of benefit to be had with minimal risk. Here are some ideas to make your own luck with AI experimentation - maximizing value while minimizing risk.

1. Ask around the office

There is a 99% chance that there are at least three processes in your organization that are burning your team out, are incredibly annoying, or are otherwise distracting people from doing work that really matters. And of those three, I guarantee that one of them will involve a manual task that AI is really good at - creating a report by combining multiple inputs, summarizing results from a week’s worth of sales calls, or analyzing customer trends, for example. Pick one, invest a couple weeks of your team’s time into figuring out how to use AI to tackle it (you can start with ChatGPT and see if you need something else later) and before you know it you’ll have happier staff with more time to focus on the important stuff, without spending a lot or adding any risk.

2. Put anything external on the back burner

You’ve probably read a lot about all of the great things AI can do for your customers. Chatbots, personalisation engines, and virtual customer care reps are everywhere these days, yet many organizations are hesitant to fully embrace them.

And you know what? I don’t blame them one bit. Anyone who has used a website chatbot in the past several years will tell you that the experience is suboptimal at best, if not downright off-putting. It’s because of this concern about negative customer impacts and bad brand reputation that companies will agonize over when - or whether - to use AI for customer-facing processes.

The simple answer is - don’t waste time trying to get approval for something that’s not fully baked. Kick that can down the road. If you’re experimenting internally, you're already getting benefits from AI, and your team is getting familiar with the technology and how to harness it. There will be many more tools and improvements on existing solutions to come in the next few months and years, and they will improve AI to the point that teams will be a lot more comfortable putting it in touch with their customers.

3. Have a policy on AI

Policies by themselves don’t remove all risk, but it’s always a good idea to put in writing what your team can and can’t do with AI. It can help you set guidelines that you want people to follow as they experiment and can even outline your strategic direction for AI in your business. What do you want to achieve? Where do you see this going? Until it’s in writing, it’s all speculation. It’s much easier to act boldly when you’ve got a roadmap to get where you’re going, and an AI policy is a great starting point. If you don’t have one, you can use Pathfindr's AI Policy Generator to create one completely free.

I hope this post has given you some ideas of how to break out of AI inertia and get started with some great use cases that will make things easier for your team.