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AI Is Here: The 5 Steps You Need to Take Now

Yesterday, I used an app to find out how long my commute would be if I left later than usual. Today, my garage door opened when it sensed my phone, as I turned onto my street in my car. Tomorrow, I might download an app to find a bike near me, ride across town, and drop the bike off on the sidewalk for the next person to use it, without having to trudge to a docking station.

Are these examples of artificial intelligence (AI)? Absolutely, but the technology has become such a part of our lives that we don’t even notice it. As John McCarthy, who coined the term ‘Artificial Intelligence’ once said, “As soon as it works, no one calls it AI anymore.”

AI is here, but I have yet to meet a CIO whose long-term AI strategy is fully fleshed out; there is no such thing as an ‘overall AI plan.’ You don’t want to overspend on AI technologies that might not be relevant in a few years, but you don’t want to be left high and dry and miss the ‘transformation train,’ either. In the face of all of this uncertainty, though, there are a few things you can do to get started with AI now:

  • Put People First

The promise of AI is unprecedented, but it’s not a silver bullet. AI is only as good as the processes that are put in place, and the people who execute them.

While the big data that fuels AI technology will free us up to innovate and collaborate, it’s human intuition that will connect the data and reveal insights. Machines are great at matching learned patterns, but interpreting patterns for results is what we’ve learned to do over thousands of years. That’s why the people and culture of an organization will continue to trump technology every time.

Adopting a culture-first approach means that IT leadership needs to become a change agent for the enterprise and commit to the time and energy required to lead by example. They will need to clearly communicate the new framework and collaborate and engage with their teams.

On the talent side, start upskilling the organization to understand the basic capabilities of machine learning and buildtalent for deep learning, natural language processing (NLP) and computer vision.AI requires technical knowledge in specific AI technologies, data science and data maintenance. You will also need the skills to monitor, maintain and govern the environment.

  • Ask the questions you’re afraid to ask.

AI is a solution in search of a problem. Start asking questions to solve problems that you might not realize AI and ML can address. Blue-sky thinking will be the new norm. For example, ask your AI vendor how to bridge the gap between sales and product development by using customer feedback to innovate better products. Find out how you can increase booking growth and reduce cost of sales based on pattern analysis across a broad spectrum of sales reps. Finally, with consumers generating approximately 50,000 gigabytes of data per second, explore how you can understand your customers better and tailor product offerings.AI likes a challenge, and it’s up to us to build the AI ecosystem for this challenge.

  • Reimagine work by integrating AI into existing business processes.

Even best-in-class standard business processes are no longer enough. They must be reinvented and made much more flexible and responsive to real-time conditions. In other words, work must be reimagined. AI applications have the potential to integrate into existing processes with little disruption. Look for ways that AI can improve these processes beyond merely automating specific tasks in a job or workflow.

  • Align AI investment directly with your business objectives.

What matters the most is how AI can help you meet critical business objectives such as understanding customers better, gaining efficiency or identifying competitive advantages. CIOs are in the perfect position right now to educate their company’s CEO and board on how AI might influence business strategy at the outset, rather than simply implementing projects that follow up on the executive team’s decisions. Right now, image processing, NLP and voice recognition, via SaaS applications have the most potential to advance your objectives right now.

  • Just get started.

The very nature of AI is elusive, so start by solving for one problem at a time with one or two business functions. Develop your AI strategy by building on these small successes and learning from failures. Learn what works best for your unique set of conditions.

Every journey begins with the first step. Take that AI step now.

 

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