Are you blinded by the promise of AI?

While many businesses are fueled by their ambition to implement AI initiatives, few understand how it can work for their businesses. How do we keep our AI ambitions in line with the business needs of our organization?

The business world is sharply focused on AI and ready to spend generously on what it might offer. In a recent PwC survey of 1,000 business executives, 20% of respondents said that “their organizations plan to implement AI enterprise-wide in 2019.” That’s one in five businesses planning enterprise-wide AI initiatives. According to the 2019 Harvey Nash/KPMG CIO Survey, AI/automation use is up as a board priority by 17%.

On top of that, the survey also revealed that over one-third of IT leaders worldwide believe that 20% or more of their workforce will be automated in the next five years. The AI and automation march forward is a growing and global one driven by two powerful stimuli: fear and ambition.

Fear first

Today’s business leaders have a healthy fear of disruption, having seen once global powerhouse businesses like Blockbuster, Borders, Woolworth’s and Kodak brought to full extinction by new digital models. They also see tech industry leaders like Microsoft and Google making massive investments in AI. Most recently Microsoft announced a $1 billion exclusive computing partnership with OpenAI, an organization which defines its mission as ensuring that “artificial general intelligence (AGI) benefits all of humanity.”

Rather than wait on the wrong side of AI disruption, business leaders and corporate boards are asking their IT leaders to invest in and lead the AI evolution. If AI, like digital, is the new battleground for competition and growth, we can’t wait and see or risk falling behind.

Ambition without a plan

Many businesses are also fueled by the ambition to lead and innovate with tech but, in terms of AI, few understand how it can work for their businesses. It’s a common tech adoption story. In recent years, several technologies have had their moment in the sun as “the next big thing.” First cryptocurrency was the next big trend in tech. Journalist Cale Guthrie Weissman described cryptocurrency as having a “gravity-defying surge” for years before it crashed spectacularly in 2018.

And then there was blockchain, another emerging technology deemed certain to transform and disrupt industries of all kind and size. Instead, the adoption of block chain had a rather traditional technology emergence story in which early adopters created buzz and a gold-rush like mentality. That frenzy has since died down and we are starting to see the technology find use and promise in a few key industries. As that success grows, more industries and businesses will find uses for it.

Welcome to the AI hot seat

A simple Google search will tell you that AI has now moved into prime gold rush position. Where once Cloud, Big Data, Cryptocurrency and Block Chain held the position of top tech trend in business, AI is now everywhere and, for many reasons, it should be. AI offers advanced data processing and analytical capabilities that people simple cannot match. It means machines can help people and businesses rapidly comb vast amounts of data to identify trends and solutions. It’s a leap big lead forward in software development, which is exactly what businesses need to see it as—an advancement to consider thoughtfully and implement strategically.

How to wade into AI

Just as the Internet was another marketplace, AI can be seen in its simplest form as another new way of programming. To adopt AI strategically, businesses first need to understand how automated programming capabilities can be used to better serve customers, employees and the business. Here are three ways to get started.  

Step 1: Start with customers

Customer focus is an essential question that needs to be revisited with each technology emergence: how will this technology help me better know, and serve my customers? If companies like Blockbuster and Borders focused earlier on how the Internet was simplifying and improving shopping options for its customers, they might have changed their models more drastically and quickly in order to compete and survive.

Rather than focus on AI technology, businesses must start by looking to their own business models and their own customer base to see where the AI opportunities are. One of the primary areas we see AI at work today is in customer engagement, with chat bots taking over a growing amount of customer service work.  Anywhere that wait time is slowing down customer engagement is a place for businesses to consider an AI-powered solution. I have seen firsthand how companies can gain market share by introducing chat bots that engage more customers and potential customers at once, freeing up talent to manage more sophisticated service needs.  The medical industry is seeing the same benefits as AI-based remote monitoring and troubleshooting of medical devices and patients creates a new world of expeditious, proactive patient support and care.

Step 2: Look for data-based opportunities

Data is being collected by technologies across your business faster than any human can assess, analyze and leverage it. The big leap forward in data analytics has been the machine learning capabilities that result in algorithms that can forecast behavior and offer recommendations and/or potential pathways. From the recommendations that come from content streaming services to shopping options that pop up in online advertising, many of us see these algorithms at work every day.

Customer data—when collected with permission, security and high integrity—offers businesses potent customer personalization opportunities, from sending discounts or information around important life events (anniversaries, holidays, etc.) to creating personalized communications.  Because AI can collect and analyze large data sets at remarkably fast rates, businesses can use it to predict potential issues, favorable market opportunities or customer needs. To identify these opportunities, organizations need to work across all business groups to assess the numerous places data is collected, and how and when that data can be used (again with integrity and sensitivity to privacy and security concerns).

Step 3: Focus on skill needs rather than job loss

Some of the recent buzz around AI has focused on job losses that could come with automation. For example, in January the Brookings Institute published a report which found that “approximately 25% of U.S. employment will face high exposure to automation in the coming decades.” Jobs in the study were classified as “high exposure” to automation if 70% or more of its tasks could be performed by machines using current technology. 

As in the past with technology evolution, job loss is a recurring theme. When banks adopted ATMs—a radical move in banking at that time—the fear was tellers would lose jobs. Instead, more branch locations were built and more teller and service jobs were created. With AI, the kinds of new jobs created will require new, tech-centric skills. Amazon just committed $700 million to reskilling its workforce and other companies are following suit.  

All businesses should take a careful look at the skills of their workforce and consider how workers they have today can adapt to a workplace where AI has a greater role and where they need to recruit for key positions. Where will roles fade away and where will the skill gaps emerge? Building an AI-ready workforce now is key to AI success today and tomorrow.

The excitement and fear of transformation can be distracting. The best strategy for surviving the gold-rush phase of a new technology is to keep your strategic head about you and focus on what you should know best: your customers and what they want. If AI can help you better deliver on that, you have found the right place to start.

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Copyright © 2019 IDG Communications, Inc.

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