As disruptive technologies reshape the fabric of the modern enterprise, technology teams must evolve. In a world where AI and GenAI are increasingly integrated into business processes, the focus of tech teams is shifting from merely implementing and managing IT to driving tangible outcomes and executing business strategy. To fulfill this new role, tech teams require new skills, diverse perspectives, new structures and external partners who can provide essential services at scale.

While the new shape of these teams is still coming into focus, there is nothing ambiguous about the impact AI is having on businesses. According to Foundry’s inaugural AI Priorities Study, 89% of IT decision-makers are either researching or using AI, with 61% expecting their spending toward AI projects to increase this year. And while hiring for new roles to support GenAI is still gradual, 38% of enterprise organizations have already added data scientists, 31% have added AI researchers and 39% have either added or are seeking a chief AI officer.

“What you’re looking at is an overall reinvention of the IT organization,” says John Gallant, Enterprise Consulting Director at Foundry, a media and martech company. “In the past, the complaint was that IT wasn’t having enough measurable impact on the business. The focus now is on driving innovation, driving growth, driving new revenue and improving customer and employee experience. And they’re going to need new skills and a new organizational structure to support that.”

A new set of skills

The transformative potential of GenAI was clear to Comcast CIO Mike Crisafulli as it started to become widely available in 2022. He saw it as an opportunity to fundamentally evolve his team’s role within the company. “Instead of starting with the technology and looking for problems, we thought, ‘What if we looked for business problems that this technology could solve?’” During sessions facilitated by Comcast technology leaders, heads of every business unit shared their long-term objectives in order to compile a list of goals where GenAI could make an impact. The next step was building the right team to achieve those goals, including upskilling and reskilling employees working with GenAI.

In the short term, Crisafulli anticipates needing to expand his pool of data scientists who can structure and manipulate the company’s data to address the company’s business objectives. In the longer term, Crisafulli believes he will need to add new roles like prompt engineers, filled by people who may not have traditional tech skills but who do possess deep domain knowledge and the language skills to craft questions that elicit useful responses from GenAI. “Computer science skills will always be required,” says Crisafulli, “but as things get more abstracted, there may eventually be a bigger shift beyond the typical technology and computer science skills toward people who can bring the creative thinking needed to leverage GenAI.”

According to the Foundry report, 57% of tech leaders say they have either hired or are seeking new data scientists, and 51% have hired or are seeking machine learning engineers. Only 37% have either hired or are seeking prompt engineers, and 31% are hiring AI writers, but Gallant expects those numbers to increase considerably by the next survey. “Right now, CIOs are being deluged with requests around generative AI,” says Gallant. And unlike, say, an accounting application, it is still unclear whether GenAI applications will deliver the expected outcomes. “As companies go through the process of figuring that out, their hiring needs will become clearer.”

Amit Verma, CTO for Comcast Business, says every CIO he speaks with is looking for ways to leverage AI, and as they do so there is a need for collaboration between software development teams, data engineers and business unit experts. “It’s the business unit experts who know the processes and the outcomes they’re looking for,” says Verma.

Diversity is mission critical

What is clear now is the critical need to build GenAI teams that include a diversity of perspectives. While diversity is a priority for enterprises at large, the risks associated with AI and GenAI are immediate and consequential because large language models trained to detect and follow patterns are uniquely vulnerable to inherent bias when exposed to only a narrow point of view.

“Anything customer facing that involves things like health data, financial data or making decisions on loans needs to be free from inherent bias or other ethical issues,” says Gallant. “Having a diverse team to work on those applications is going to help you train them better and make sure you avoid those problems.”

Given the current shortage of qualified talent, building such teams isn’t easy—and is only likely to get harder as competition for talent heats up. While there’s no easy solution, Crisafulli says Comcast has found success by instilling metrics around diversity objectives and investing in an inclusive culture. Creating an ecosystem that helps diverse talent feel included can help ensure you aren’t squandering the effort required to find and recruit that talent, he explains.

Finding balance with external partners

Given the nature of GenAI, external partners such as a managed services provider (MSP) will be essential to tomorrow’s enterprise tech teams. AI’s ability to detect patterns and anomalies within massive troves of data makes it well-suited to jobs like cybersecurity and threat detection, but building such a system internally will likely remain impractical for most individual companies. “That kind of investment makes more sense for someone who’s doing security as a service,” says Gallant.

And working with an MSP gives CIOs the time and flexibility to figure out which roles they need permanently, and which may turn out to be transitional. By outsourcing non-core services, tech leaders can focus on building out their core competency instead of ancillary functions. “You can leverage managed service providers to, for example, design low latency networks to get your data to where the AI computing is occurring,” says Verma. “Then leaders can be more focused on building their specific business requirements and expertise.”

While AI is forcing shifts among tech teams, it is also freeing them to focus on key organizational priorities and have a greater impact on business outcomes. The full impact of GenAI likely won’t be felt for years, but the teams that find success quickly—and in the long run—will be those that find the balance between human and computer intelligence so that each is working to its full potential.

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