You might recognize Peter Drucker as the man who coined the term “knowledge worker,” and who penned The Effective Executive in 1957.

The book may be over 60 years old, but his five practices that help executives shift focus from efficiency to effectiveness can be revamped through AI to make an impact on the future of work today. AI is poised to make effectiveness attainable at a large scale, upgrading Drucker’s practices.

We’re entering an era where AI complements, supplements and automates the hard skills of leadership – think technical knowledge, corporate intelligence, monitoring performance and tracking results. With the right tools at our side, we can all be effective managers.

Here’s how, with Drucker’s recommendations in mind.

Know where your time goes

Time is the ultimate limited resource. Using it effectively - knowing where it goes and limiting excesses and distractions – starts with tracking everything from the big chunks of work to the five minutes we spend on Facebook 12 times a day.

Luckily, there’s AI solution for that. Several, actually, like Memory AI, which graphs schedules and software use, or Smarter Time that breaks down how those smaller distractions add up. Once you know have that data, you’re equipped to make better decisions about where your time has the most value.

Focus on outward contributions

It’s easy to lose sight of why you’re doing what you’re doing when you’re treading water against the daily tide of meetings, deadlines, and tasks. But effective managers focus on the contributions they make through their work, rather than the work they have on their plates.

Knowing where you stand on those central goals is an important part of the equation, one that’s backed up by dashboards that can track progress and intelligent virtual assistants that can do everything from managing your schedule to drafting personalized emails. They move those menial tasks off our plates, giving us time to do what we do best – create and innovate towards those contributions.

Build on strengths

That talented closer on your sales team might not love engaging new leads, and that rep who consistently hooks great prospects may not be a strong closer. That’s actually perfect – an effective manager looks for strengths that complement each other rather than weaknesses that cancel out.

It’s increasingly easy to pinpoint our performance strengths along with our softer skills, especially with all the data we can collect about how we do our tasks. AI is an increasingly useful tool to sift through that data and provide insights about what works (and who does it best). Chorus.ai does this particularly well, capturing the conversations sales reps have with clients, parsing out critical moments and analyzing what made them successful or unsuccessful so everyone can benefit from those strengths.

Double down on priorities

What goals will make the most difference? Set those areas as priorities and assign your strongest performers. What work isn’t really worth doing? Get rid of it so you can concentrate on what matters.

Those priorities will look very different depending on your organization and team, but AI tools that assist prioritization generally look at what’s currently successful and map that onto future opportunities to pinpoint where efforts are best spent. On a sales team, for example, that might mean predicting your highest value leads so you can assign your top reps to them. For marketers, it might mean nailing down your best buyer personas so you know which key behaviours to target.

Make effective decisions

Note this one says “effective,” decisions not “a lot” of decisions. A great executive should focus on making calls for a few key priorities at a time. And those decisions are most effective when they’re tested and rooted in fact.

Machines and computers are getting really good at making predictions and recommendations because they’re experts in digging through a whole lot of data from many sources and surfacing patterns we wouldn’t otherwise see. But when it comes to considering that data in a real-world context, we still need a human at the helm. And we’ll be better armed with the data we need to make a fact-based call at the end of the day.

Drucker said that, if there’s one thing we can be certain about in a world of automation, it’s that jobs will change radically – and often.

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In medicine, you’ll find AI diagnosing cancer, strokes, and broken wrists. Self-driving cars have clocked millions of miles on the odometer. Even the world’s top Go player was recently trounced by Google’s DeepMind.

Like with any new technology, change is coming. (But it doesn’t have to hurt). An AI-enabled world means technology will conform to the way we do things, not the other way around. It means we’ll enjoy more time focused on the things we love doing – and do well.

And it means we’ll be more effective – and more human.