Strategy

The head of IBM’s Watson outlines how tech leaders can avoid the pitfalls that doom AI projects to failure

Rob Thomas
Rob Thomas is the general manager of data and Watson artificial intelligence. IBM
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Technology leaders are increasingly spearheading efforts at top companies to push a new digital-first agenda. But often, they can't do it alone and need counterparts within specific business units to help advance the strategy.

Despite efforts to adopt artificial intelligence, machine learning, and other data-heavy initiatives, many projects still fail. One key reason is the difficulty in changing the company culture. Often, sectors like the IT department and sales are not used to coordinating with each other. But breaking down those silos is key to advancing applications that actually serve the customer or the organization and lead to cost-cutting or new revenue generation.

One way to ensure projects advance is to appoint leaders within each respective business unit to help support the chief technology, data, or innovation officers, argues IBM's Rob Thomas, a system he refers to as the "hub-and-spoke" model because the structure resembles one in which a central point is connected to several secondary points.

"You need somebody that has a seat at the table at the top that's saying it's important to the company," he told Business Insider. Organizations also "need somebody in those business units that owns this day-to-day, but is accountable back to the company strategy."

It's the model Thomas uses at IBM, where he is the general manager of data and Watson artificial intelligence — a role that gives him authority over investments, sales and marketing, and product development relating to the company's signature AI product. 

Direction at the top, execution at the bottom

Under Thomas' model, the leader at the top — which could be a chief technology, data, or innovation officer — works with the CEO to figure out what areas of the business are best suited for a tech overhaul, whether that be supply chain, talent acquisition, or another sector.

Once the strategy is established, the tech leads within each unit are responsible for experimenting with applications based upon the data they have available to meet that goal. It's a way to solve the problem of top-down mandates.

Such a system doesn't work, argues Thomas, since often the C-suite is unfamiliar with exactly what information the sectors have stored. Data is needed to power the AI-based applications, and without intimate knowledge of what is available, it is difficult to determine what ideas can actually be executed on. 

Technology chiefs have to empower unit heads to "go figure out which use cases you want to target under the umbrella of the strategy and the standards that were set," he said.

Changing the culture for AI: Without support it's 'just a science project'

While investments in tech upgrades sometimes total in the tens of billions of dollars, many projects still fail as a result of resistance within the workforce. That's why it's so imperative for executives to take steps to change the internal culture.

One way to get staff more engaged is to host an "AI challenge," or a contest where employees can submit their best ideas and judges choose a winner. It's a tactic Thomas employs and one he argues every CEO should pursue.

"The fact that I reviewed submissions, the fact that I was a judge as people were presenting, all those things indicate a level of importance," he said. "It shows you care."

Read more: Large CPG companies are under tremendous pressure to keep up with the pace of innovation. M&M's and Snickers maker Mars is investing in 2 accelerator programs to stay ahead.

Another is to pair chief data officers or other tech leaders within business units with other AI advocates on the operational-side of the organization. In a manufacturing firm, for example, that could be the supply chain lead. At a financial services firm, it could be the retail banking manager. That champion can help push projects with coworkers who may not have the technical chops to build the product, but have a vested interest in the outcome — like reducing costs or driving profits.

"AI projects happen when the business team comes together with the technology team," said Thomas. I've never seen "a pure technical project that's led to a meaningful business outcome because there's no context to it. It's just a science project."

Organizations should also celebrate the small victories to empower employees to try ideas out themselves. Many companies, argues Thomas, don't even realize the successes they have. "Success begets more risk-taking," he said. "It starts to snowball in a positive way."

Given the large investments behind many digital transformation efforts, it's imperative companies take into consideration the internal reporting structures and the roles that will lead the initiative. Doing so can help mitigate potential problems like cultural resistance. 

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I'm a senior reporter on the enterprise technology desk at Business Insider, covering emerging tech like artificial intelligence, quantum computing, and virtual reality. I'm interested in innovative startups, industry leaders with a strong point of view on the future of the technologies, lawmakers carving out the path forward on policy frameworks, and everything in between.  I also run our Innovation Inc. series, which gives readers an in-depth look at how legacy companies like Walmart, JPMorgan Chase, and FedEx are undergoing their own digital transformations and adopting AI, VR, and other tech. You can sign up for updates on that newsroom-wide project here.  Got a tip? Contact me via email at jwilliams@bjinnox.com, on Signal/WhatsApp at 309-265-6120, or direct message on Twitter @JoePWilliams31.