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23 AI Strategies for Making Your Life in IT Suck Less - Part 2

In case you missed Part 1 of our "23 AI Strategies for Making Your Life in IT Suck Less" blog series, you can check it out here. Ready for the second half of the list? Continue on for the rest of our 23 tips, tactics and strategies for how you could bring artificial intelligence (AI) into your organization.

13. Data volume and complexity

The volume of data is only increasing, and much of it is unstructured or only semistructured. This makes it very hard to make sense of the volume. Artificial intelligence is one great way of making sense of the growing complexity. Use AI to help your teams and organization make sense of the growing complexity.

14. Data preparation and hygiene

Data scientists have estimated that they may spend as much as 80% of their time just preparing data through a variety of manual steps. Plan at least some time and resources for preparing your data, so you can get the most out of it when you apply AI and machine learning to it.

15. It’s (machine + humans) and not (machine – humans)

There’s a lot of talk about artificial intelligence taking our jobs, but the reality is far from it. Machines can never replace the people talent within your organization, and there are some perspectives and tasks that only human talent can address. Instead, things like artificial intelligence and predictive analytics can compliment your people talent, freeing them up from the monotonous and the routine and bringing their time and attention to the things that matter most.

16. Learn from others

Plenty of companies of every size in every industry are achieving incredible things with AI. Learn from some of the best, like TransUnion which is using AI to predict and prevent imminent outages in advance. Also, consider Viasat’s approach of protecting their customer experience with proactive and predictive monitoring.

17. Plan to fail, and then plan again

Rarely do organizations find their most successful AI strategies in their initial attempts. So plan time and resources for experimentation, play and education. Bring together different roles and people talent to help, and celebrate every failed or unsuccessful attempt because they bring you that much closer to the things that will bring you value.

18. Celebrate successes, big and small

When you do find something successful and something that works, celebrate it! Whether it’s the automation of a single task, or the improvement of customer satisfaction scores because you’re using AI to predict and prevent problems before they occur. All of these need to be evangelized to support growing your efforts with these emerging technologies.

19. Plan for a few break-ups

Legacy tools are great...for what they’re designed for. However, many organizations are finding that they can limit your scope and often silo your data. So as you explore emerging technologies on your path to things like predictive analytics, it’s okay to break up with a few legacy tools along the way. (It’s not you, it’s them...)

20. Make integration and scale a priority

When you find the combinations of platforms, technologies and tools that work for you and your AI strategy, you’ll most likely want them to play nicely with the rest of your stack. So consider making integration and scale important considerations for picking artificial intelligence tools and platforms. You may not need them at first, but you’ll probably need them soon!

21. Measure everything

We can talk a lot about what artificial intelligence can do with all of your data, but you’ll want to create some new data about your AI efforts, too. Whatever you do and whatever you explore, make sure you measure as much as you can. Not only are these great data points to help you report on what you’re learning, but they are also great data points to feed back into your AI efforts themselves.

22. Set and reset expectations

Once word gets out that you’re exploring AI, machine learning and predictive analytics, everyone is going to want a piece of the action and to know what to expect. Keep expectations moderate, but do set some up front. Then be willing to reset them as you explore, experiment and learn.

23. Watch the “The Terminator” movie

Okay, so this last tip has almost nothing to do with your AI strategy, but you’re going to find that everyone will start making the obvious “Skynet” and “T-1000” jokes once you start talking about machines doing cool stuff. Watch the movie, so at least you can play along. ;-)

Want to see a great AI strategy in action?

We hope you’ve enjoyed Part 2 of our series! If you haven’t had a chance to see how Accenture and Vodafone developed their own AI strategy, there’s still time to check out their "5 Steps to a Predictive IT Strategy" webinar.

You’ll learn:

  • 5 steps to an effective predictive IT strategy
  • How Vodafone with Accenture improved their customer experience with AI
  • Where AI can help, and where it can’t

Register for the webinar now!

Bryan Jennewein
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Bryan Jennewein

Vocational Technologist. Voracious Academic. Feminist Philosopher. Meditator & Mindfulness Cultivator. Irish Wolfhound Dog Dad. I strive to employ my vocation, knowledge, and hobbies to make the world a better place and laugh a lot with as many awesome people as I can.

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