AI isn’t finally here – it’s been here for a while in everything from the autocorrect on your phone and the recommendations you get on Netflix – but it’s now in the mainstream. And thankfully, we’re having some of the hard conversations we failed to have when other technologies like social media were emerging. These will be long, complicated, and potentially inconclusive discussions, but at least they’re happening.

Clearly, a significant element of the discussion is around what AI means for work, and, as with most things, the answer is a variation of ‘it depends’ because every business and industry will be affected differently.

What Does AI Mean for Your Business?

So how can you think about AI with respect to your work?

I’ve put together some questions you can ask as a worker or manager, which might help, but let’s start with a simple definition of AI.

“First, a short description of what AI is: The application of mathematics and software code to teach computers how to understand, synthesize, and generate knowledge in ways similar to how people do it. “

From Marc Andresson’s essay, ‘Why AI Will Save The World.’

How we use this software is wide-ranging and opens up incredible opportunities to do great and terrible things but let’s not lose sight of the fact that, at its heart, it’s software, and we can get it to do what we ask it to.

So what questions should you ask to help you determine how you could or should be using this technology at work?

AI Questions for Everyone

Everyone should ask:

• How can I use AI to make me more effective and efficient?
• What’s something AI lets me do that I couldn’t do before?
• Unless you are a carpenter, stonemason, or something similarly artisanal, if you answer ‘nothing’ to either question, you are probably deluding yourself.

AI Questions for Managers

Managers should be asking:

• How can I make my team more efficient with AI?
• How can AI improve our quality?
• What are the downsides of using AI in our business?
• What happens if we don’t use AI in our company?
• How can AI be used by, assist, or replace staff?

The last part of the last question will be uncomfortable for some people, but the reality is that every manager will be looking for efficiencies and advantages wherever possible. At one stage, that was replacing the typing pool with desktop PCs. Then it meant offshoring services to call centers abroad. Today, it means replacing some of your low-skilled workers or contractors with software or robots.

AI Questions for Early-Career Professionals

Anyone early in their career should be asking:

• What does AI mean for my chosen career?
• How must I adapt what I’ve been taught to this new technology?
• Which of these tools do I need to learn to use most urgently*?

Their younger siblings will grow up as ‘AI natives’ in the same way that they’re digital natives, but for now, professionals under 30 should be best placed to adapt to these new technologies. That should make them the group most able to harness these tools and, consequently, the least affected.

AI Questions for Late-Career Professionals

Older workers might be tempted to ignore AI as the lure of the golf course or planning cruises (or whatever else people do when they retire) increasingly dominate their thoughts. After all, they’ll be free of the workplace by the time the disruption hits. However, even though the disruption won’t get those closest to retirement, they might want to think about two things.

• How can this technology help me capture what I know and share it with others?
• How can I help shape the narrative around AI adoption for my industry to help those who are coming along behind me?

AI Questions for Mid-Career Professionals

Finally, I think that mid-career professionals need to be moving with the greatest speed with respect to AI. In addition to everything else, the big question they need to be asking is:

• What parts of my job can be replaced by AI? (Really, how can I be replaced?)

After 15-20 years at work, these folks are set on a path and can see a relatively straight path toward retirement. Unfortunately, that’s still a decade or two away, and many mid-tier professional jobs will be threatened by AI in that time. Highly-competent experts will still be valued but mid- to low-competence workers – the folks who do most of the professional heavy lifting currently – are highly vulnerable to this disruption.

Professions that immediately come to mind are:

• Designers
• Developers
• Financial analysts
• Copywriters
• Video editors
• News reporters
• Risk and intelligence analysts(!)

Remember that changing careers mid-career is tough (citation: the resounding silence from the 100+ job applications I’ve sent in the last year). So, for many, this could be an ‘adapt or get replaced’ situation. If you think you’re in this group, you should be thinking about these issues long and hard. Actually, forget long: if you’re in this group, you have to think about these matters deeply, urgently, and take action quickly.

And FWIW, I am. Because I’m convinced that a lot of the work I do – writing contingency plans, building and running exercises, conducting risk assessments and analysis – will be done by software very soon. So I’m trying to get ahead of the curve by being the one to build these tools with things like crisisdojo. But the days of spending weeks consulting with a firm to conduct a risk assessment or develop a crisis management plan (CMP) are drawing to a close.

The Best of Both Worlds

However, it doesn’t need to be all doom and gloom: in fact, mid-career professionals might come out on top. Especially when they are able to work with their AI counterparts.

So you should be asking: how am I going to work alongside your robot counterpart?

They’ll be able to meld years of experience with this new technology to make them incredibly effective. Meanwhile, human judgment, experience, and expertise are still required to get the most out of these systems. This judgment and understanding is something that more tech-savvy junior colleagues will still be developing, so their experience will still be a competitive advantage. But only as long as it’s coupled with some technical ability.