The Future of AI in America: What All Leaders Should Consider

Regardless of the spotlight President Trump put on AI, the technology was destined to make a big impact in 2019, and companies will need AI to compete successfully.

Guest Commentary, Guest Commentary

February 27, 2019

5 Min Read
Image: Sikov -

With President Trump’s recent executive order, he has put AI firmly on America’s radar. But to many of us in the technology industry, prioritizing AI development wasn’t a groundbreaking announcement — it was an essential strategy that will help advance America in the technology race.

Artificial intelligence offers countless opportunities for both the public and private sectors, but it also presents complex challenges. AI offers opportunities to improve operations, enhance the customer experience, develop new business models, and increase revenue. But there are challenges: defining an AI strategy, finding AI-literate workers, getting data AI-ready, and ensuring AI is trustworthy and responsible.

There’s a great deal at stake for both government and private sector organizations. Currently, 80% of U.S. CEOs believe that AI will change the way they do business in the next five years. The financial implications are just as significant: By our estimates, AI could potentially increase worldwide GDP by 14 percent by 2030, representing an infusion of $15.7 trillion into the global economy.

If AI is to truly fulfill its potential and have a greater impact on our world than the internet revolution, businesses in every sector must lay the foundation now. How can they get started? Regardless of whether you’re a government entity or a private company, there are a number of priorities that you need to adopt.

Infuse AI Throughout the Organization

To derive the most value from artificial intelligence, companies need to formalize their approach to AI and develop company-wide capabilities. By doing so, a business can create small projects that are easily replicable in other parts of the organization.

One way we’ve seen companies successfully formalize their AI efforts is by creating a center of excellence. That’s because AI oversight requires a diverse team of individuals that have business, IT and specialized skills. At PwC, we’ve found success through our own AI Center of Excellence and have found it to be an effective way to accelerate AI adoption throughout the organization.

Create an AI-Savvy Workforce

As companies have created AI workforce strategies, we’ve seen three levels of AI-savvy employees emerge:

Citizen Users: Many employees will learn how to use their company’s AI-enhanced applications, support good data governance, and get expert help as needed.

Citizen Developers: About 5 to 10 percent of the workforce will receive additional training to become citizen developers. These are typically power users who can identify business use cases and data sets, and work closely with AI specialists to develop new AI applications.

AI Specialists: This small but crucial group of data engineers and data scientists does the heavy lifting to create, deploy, and manage AI applications.

To create citizen users and developers, companies must educate employees on core data science concepts and data governance. Data scientists, in turn, may need coaching to enable them to partner effectively with business staff.

Make AI Trustworthy
While AI is having a transformative effect on business, we believe that one of the most important challenges businesses will face this year is making it trustworthy.

There are a number of questions that companies need to consider on this front: Are we minimizing bias in our data and AI models? Can we explain how an AI model makes decisions? Who is accountable for AI systems? Do we have the proper controls in place?

We’re beginning to see more companies answer these questions through ethics boards or chief ethics officers. As the year progresses, we expect a number of enterprises to open up AI’s black box and make its decisions more transparent, interpretable, and provable. They’ll also need to anticipate when algorithms will require auditing. As time goes on, some governments will likely make some level of interpretability a regulatory requirement.

Convergence is Key
Managing the convergence of AI with other technologies will be another key priority for organizations this year. That’s in large part due to the explosion of the internet of things.

Large organizations may soon have millions of IoT sensors collecting data from business and consumer devices. AI and analytics will work together to identify patterns in this data, which supports everything from marketing insights to product strategy.

Your employees will also have to “converge.” Instead of data scientists completing an algorithm and handing it to an IT specialist to code it, and then sending it to a business user to apply it, these teams will have to work together from the start.

It Starts Today
Regardless of the spotlight President Trump put on AI, I believe this technology was destined to make a big impact in 2019. I also believe that companies will need AI to compete successfully in the future — and that the priorities I've outlined will be crucial to that success.


Scott Likens leads PwC’s New Services and Emerging Tech practice in the United States, Japan, and China. With more than 21 years of emerging technology experience, he has helped clients transform their customer experience and enhance their digital operations.

Scott has worked across industries with some of the biggest multinational companies to transform their business by applying a local lens to global digital and emerging tech trends. He has expertise using emerging technology and advanced analytics in many areas including e-commerce, digital architecture, mobile technologies and social customer engagement.

About the Author(s)

Guest Commentary

Guest Commentary

The InformationWeek community brings together IT practitioners and industry experts with IT advice, education, and opinions. We strive to highlight technology executives and subject matter experts and use their knowledge and experiences to help our audience of IT professionals in a meaningful way. We publish Guest Commentaries from IT practitioners, industry analysts, technology evangelists, and researchers in the field. We are focusing on four main topics: cloud computing; DevOps; data and analytics; and IT leadership and career development. We aim to offer objective, practical advice to our audience on those topics from people who have deep experience in these topics and know the ropes. Guest Commentaries must be vendor neutral. We don't publish articles that promote the writer's company or product.

Never Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.

You May Also Like

More Insights