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Math and business development: Why the 2 divergents skills matter in an AI world

For roles heavily immersed in building AI applications, it's time to shore up basic math skills. And for more right-brained roles, business development skills are the top requirement.
Written by Joe McKendrick, Contributing Writer
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Dmitriy Sidor/Getty Images

Artificial intelligence (AI) keeps upending our ideas about future skill requisites in interesting ways. On one level, AI requires a deep understanding of underlying technology, data science, and statistics. 

At the same time, AI also calls for less immersion in underlying technicalities and an ability to keep an eye on business advantage

Also: 5 essential traits that tomorrow's AI leader must have

With the rise of AI, technology managers, and professionals face some critical decisions regarding which of these two seemingly divergent skill demands they ought to pursue.

Tools built on generative AI offer compelling productivity advantages for developers and other technology professionals -- but it also means rethinking their roles. For those seeking to get heavily immersed in building AI applications, this may be the time to shore up one's basic math skills. 

For others seeking more right-brained roles, business development skills are the top requirement.  

That's the word from Maxwell Wessel, chief learning officer at SAP and venture capitalist, who shares his observations on the impact of AI on the technology profession. It may be time to revisit math skills, he advocates. 

"Most technical pros are going to need to go back to the basics: math," he says. "Problems that were defined when I was coming up were defined in code. Limitations of coding languages, operating systems, and hardware were often the most foundational to understand. In a world of AI, those same systemic issues are going to be best defined in statistics. The more understanding people have of the math, the easier it will be to understand the usefulness of the models."

Also: 6 ways business leaders are exploring generative AI at work

Math may be at the forefront for a lot of AI work, but for those not directly building or architecting AI applications, "the skills that will come into question are less technical," Wessel continues. "They may not need to code as much, but they'll need even more product management, design, and user research capabilities to get the most out of their new tools."

Expect more changes to IT roles. "The function of IT talent will continue to evolve as technology does, and this means that the roles and expectations of IT professionals will change simultaneously," Wessel predicts. "We have seen time-consuming, repetitive tasks become more and more automated over the past 40 years, and that will certainly continue to progress as AI becomes smarter and more capable of integrating into the processes of app development and deployment."

Also: Generative AI's 'revolution in productivity' is retrenching software developer roles

Wessel is optimistic about the potential impact of this emerging technology. "Overall, gen AI is going to unleash a wave of workforce innovation, helping to address a lot of the skill shortages we face," he states.

"Generative AI offers an incredible tool to help developers accomplish tasks better," he continues. "It can help with debugging. It can provide short statements summarizing unknown code snippets. It can offer suggestions on how to tackle a problem. All of these help devs save time and shift into more strategic thinking."

IT professionals will continue to see their roles enriched as they move closer to the needs of the business. "By getting out of the monotonous day-to-day automations, there will be more opportunity to partner with business leaders to leverage creativity, an understanding of the technology, and newfound capacity to solve some big problems," says Wessel. 

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AI-based tools, in essence, "make the complexity of coding more accessible. In that sense, it is a low-code tool. There will be citizen developers doing ever more complex things -- which will free up the deeply technical computer and data scientists to focus more on issues that require an in-depth understanding of how the systems work."

Still, Wessel emphasizes, "AI is going to be magic. After all, as [science fiction author] Arthur Clarke said, any sufficiently advanced technology is indistinguishable from magic."

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