Bridging the AI Strategy Gap in the C-Suite

An IBM executive talks with InformationWeek about a study finding a disconnect between executives over AI implementation.

Shane Snider , Senior Writer, InformationWeek

August 15, 2023

4 Min Read
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Feodora Chiosea via Alamy Stock

A new IBM study shows CEOs are bullish on AI’s potential and want to implement competitive solutions -- but just 29% of their executive counterparts believe they have the in-house expertise to adopt generative AI.

The company polled more than 3,000 CEOs in over 30 countries on business priorities, challenges, and opportunities. Poll results showed CEOs are in a race to adopt emerging technologies like generative AI -- 69% said their organizations were prepared. But the disconnect between the CEOs’ vision and other executives' confidence in AI implementation could hamper digital transformation efforts.

Salima Lin, IBM’s senior partner and vice president of strategy, transformation, and thought leadership, says the study shows a need to close that gap. “It's not surprising to have CEOs that are visionaries and future-focused and want to move with speed when it comes to transformative technologies,” Lin tells InformationWeek in an interview. “While executive teams are really focused on, ‘How am I going to execute this right and make this a reality for my people.’ Nevertheless, there is a divide, there is a gap. And it's important to close that gap and bring the technology and the business together to move forward here.”

Going Beyond AI Hype to Form a Plan

The study does offer some suggestions about how to handle the apparent executive AI disconnect. Part of the issue, Lin says, is the hype surrounding generative AI can cloud an organization’s implementation plan.

“Every day you pick up the paper or listen to the news, there are all these use cases being thrown out there around using generative AI,” Lin says. “No doubt, generative AI will impact every organization in every industry, every function, and every role. No one’s immune to it. But as a company, it’s important to go beyond all that hype and figure out what are the specific opportunities and use cases that we are going to prioritize for our organization where it’s going to have the biggest impact -- and making that specific to your organization.”

Lin also said listening to CTOs and CIOs will be crucial to any generative AI implementation strategy.

“It’s important to create a clear shared vision of this as part of your enterprise strategy and not as a one-off -- and to assess how your business is going to navigate the disruption and the skills that you’re going to need to drive adoption. The CTO and the CIO have a more nuanced view of where the gaps are in technical skills and infrastructure. They’ll be very instrumental in aligning priorities to manage any potential operation risk of integrating generative AI prematurely.”

Barriers Will ‘Moderate’ Speed of AI Adoption

Talk of AI regulation has been swirling since ChatGPT’s meteoric rise highlighted warnings about the technology’s potential to disrupt many facets of human life. In May, OpenAI CEO Sam Altman appeared before US Congress to plead for new guardrails. And last month, the Federal Trade Commission launched an investigation into generative AI company over data privacy concerns. Lin believes regulation will be a top concern for organizations as they begin implementing these AI strategies.

“Time will tell, but I think there’s going to be some form of moderation as time goes on,” she says. “There’s incredible excitement around adopting generative AI. The study says that 75% of CEOs believe that competitive differentiation will depend on how extensive the adoption of generative AI is in an organization. At the same time, they are identifying barriers. And one of the big barriers is regulation. There are other barriers -- around security of data, around data accuracy and around bias. These barriers will moderate the pace. That’s why it’s so important to set the guardrails to understand what the impact is and to figure out the rate and pace that you want to drive your organization forward.”

Three Big Use Cases

Lin thinks generative AI implementation will continue to be driven by three use cases: Those are customer service interactions, talent acquisition and human resources, and application modernization and automated coding. “I think it’s really important not to just gravitate around what’s coming out -- it depends on your industry, where, as a company, you are in your competitive evolution,” Lin says. “While I would put those three up there foremost, I would stress to look across and figure out what’s most important for your specific company.”

Narrowing the Gap

Many might find the sizable gap in executive thinking surprising, but Lin said the issue is not insurmountable. “I absolutely believe that gap will start to narrow,” she says. “Every organization will be at a different pace.”

She does think there are some key areas to address immediately. She said companies need to “do a better job of ensuring all their employees have a basic understanding of AI and the capabilities and can become critical thinkers and users of the technology so that it’s bottom-up. Companies that can do that better can bring the technology and business together and can drive that shared vision.”

What to Read Next:

Podcast: What Makes AI Different from Other Tech Hype?

AI and Cultivating an Automation Mindset within Organizations

Risks and Strategies to Use Generative AI in Software Development

About the Author(s)

Shane Snider

Senior Writer, InformationWeek, InformationWeek

Shane Snider is a veteran journalist with more than 20 years of industry experience. He started his career as a general assignment reporter and has covered government, business, education, technology and much more. He was a reporter for the Triangle Business Journal, Raleigh News and Observer and most recently a tech reporter for CRN. He was also a top wedding photographer for many years, traveling across the country and around the world. He lives in Raleigh with his wife and two children.

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