Think of your business as a bicycle: The front wheel is the strategy, it gives the company direction. Artificial intelligence (AI) acts as the pedals to accelerate that strategy. Pedaling like crazy without a working wheel will ultimately get you nowhere. And though it’s possible to reach your destination without using the pedals, anyone who is using them will certainly beat you there.

Figuratively speaking, companies need both wheels and pedals to stay competitive: a clear business strategy that’s accelerated by AI. Similar to the internet and the cloud, AI has the power to transform the way we do business — but these game-changing technologies aren’t strategies in and of themselves. Throwing money at AI without thinking through a long-term plan won’t reap the intended results. Instead, maximizing your investment relies on developing a strategy that’s customized to the unique needs, pain points and goals of your business.

Throughout my career, I’ve seen plenty of companies go about this the wrong way — making knee-jerk investments with inadequate preparation on unrealistic timelines. The unfortunate reality is the road to a successful AI deployment is littered with potholes. That being said, companies can find their way around them with three key tactics.

Exploring AI? Start Slow

If you’ve never biked before, kicking things off with a 50-mile ride would be unwise. The same holds true for deploying AI. With all the hype, it’s tempting to dive in headfirst and try to solve all your problems at once — but doing everything at one time often means nothing gets done at all. For a steady ride, start slow. By starting with a limited scope, you can closely monitor your deployment’s performance and address any complications before you scale.

Before searching for AI solutions, take a close look at your business, its overarching goals and where it sits in the tech adoption curve. For example, if you’ve never introduced so much as a chatbot to your business, implementing AI across every department would likely overwhelm your team, cause internal confusion and decrease the deployment’s overall effectiveness. AI has a wide (and rapidly growing) range of capabilities — including tracking and managing assets, security, analytics, personalization and customer service to name a few. Rather than boil the ocean, identify your company’s greatest pain points and inefficiencies, and start there.

A focused initial deployment is particularly crucial for building confidence in the technology from the get-go. A successful implementation, however small, with tangible results allows your employees and company leadership to see the power of the technology, and drive faster buy-in and increased budget for the next initiative.

Related Article: We're Just Starting to Tap AI's Potential in the Workplace

Prepare People for AI, Through Training and Clear Communications

A bike without a cyclist isn’t going anywhere, and neither is AI without people. Contrary to popular belief, AI is expected to create jobs rather than eliminate them — meaning there’s a lot of human and AI collaboration in our future. To build a competitive edge, the right talent and training programs will be critical.

Learning Opportunities

With 31% of executives uncertain about their ability to hire for the AI skills they need, searching for outside talent on its own is insufficient. Businesses should also focus on upskilling the workers they have. We saw this with Amazon earlier this year: the company plans to retrain a third of its workforce to adapt to the rise of workplace automation, and I wouldn’t be surprised to see other leading companies soon follow in Amazon's footsteps.

Fostering effective collaboration requires appropriate and well-communicated expectations. To maintain morale and maximize output, it’s crucial that humans can leverage their unique strengths without becoming competitive with their AI counterparts.

Related Article: Why You Need to Know the Difference Between AI and Automation

Establish Your ETA

As with any strategic initiative, getting to your destination takes time. Just as you’d account for travel time when calculating your ETA, you need to set realistic expectations for your deployment timeline.

AI is lauded as the most transformative technology of our time, but seeing results won’t happen overnight. More often than not, companies won’t see an impact for several months, a year or even longer. With this in mind, it’s critical to establish reasonable expectations. Failure to set and widely communicate a realistic timeline will lead to underwhelming outcomes and foster doubt throughout your company about the technology’s capabilities. AI is a strategic long-term investment, not a fast-acting band-aid to slap on operational inefficiencies.

As we look toward 2020, the role of AI across business functions will only grow. But despite the race to beat competitors to the finish line, pedaling furiously in the wrong direction won’t help. Maximizing your company’s AI investment relies on a thoughtful strategy supported by the right people and rational expectations for success.

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