Sexiest profession of the 21st century: Is the quick engineer supplanting the data scientist?

Estimated read time 5 min read

Sexiest profession of the 21st century: Is the quick engineer supplanting the data scientist?

More than ten years ago, in an article in the Harvard Business Review, Thomas Davenport declared that the data scientist was the “sexiest profession of the twenty-first century”. Today, in the age of generative artificial intelligence (AI), is the “prompt engineer” about to assume this title?

What is already certain is that this is one of the most fashionable professions. PROMPT engineering consists in obtaining the best and most relevant answers from generative AI tools. This is both a conversational activity, but also a programmatic one, with built-in prompts in the code.

And with the global buzz around generative AI, prompt engineers are in great demand. And good profiles are rare. The recruitment of prompt engineers is therefore not within everyone’s reach. “I think most people who recruit in this field steal skills from competitors,” notes Greg Beltzer, head of technology at RBC Wealth Management.

“Today, a good prompt engineer costs more than a data scientist”

I had the opportunity to speak with Mr. Beltzer at the recent Salesforce conference in New York, where he spoke about the challenges related to training in the age of AI. “Today, a good prompt engineer costs more than a data scientist,” he observes. “It is extremely difficult to find someone who has experience. You will not find someone who has more than five years of experience. At most, you can get two or three years, but it’s hard to find”.

Beltzer continues: “There is a dire need to train people in the engineering of the prompt. But is it a science? Is it an art? Are we going to build more tools? The good news is that once the tools are in place, it may be easier to train artificial intelligence models using prompt in a systematic and programmatic way,” he adds.

However, until robust and useful tools are available, the engineering of the prompt will remain a challenge. Even with tools, Beltzer believes it’s important to note that this skill set goes beyond technical acumen. In addition, it is still too early to determine exactly which experience and know-how is best suited for a prompt engineer.

“We are looking for people who are on the business side and who have a penchant for technology”

For example, Mr. Beltzer does not think it makes sense to train a data scientist or other IT professional to adopt engineering skills from prompt: “A large part of these skills must be adapted to the context of the company. You have to think like the user to help do prompt engineering – it’s not just code, it’s not just development. It is a set of commercial technical skills that are also creative”.

He points out that some of the people who arrive in this field are not necessarily technicians: “They are copywriters,” he observes. “They just know how to write. And this is one aspect of the question”.

RBC keeps an eye on its internal talents, emphasizing the combination of business acumen and technical acumen, says Beltzer, “We are really looking for people who are most often on the business side and who have a penchant for technology. And I don’t want to go any further than that until the tooling is a little more advanced”.

Let’s wait for the tools

The level of investment in AI and generative AI companies over the past year “is also going to shape the type of talent that we will have,” says Beltzer. “Until then, the talent market will be very small. If you look at the turnover rate within these booming companies, you will see that they can set their price”.

At RBC, which was once a very conservative company, change has become the rule, starting with the increasing adoption of cloud-based capabilities and services. “Once we moved to the cloud, we did 25 updates a year,” says Beltzer. “Which, in the financial services sector, is madness: the industry average is one update per year. We have a great team, composed of business professionals and IT specialists, and we can evolve the platform very, very quickly”.

At the same time, Mr. Beltzer does not think that his organization will get into AI 100% anytime soon. While AI can help developers and sales reps complete 80% of their tasks, the remaining 20% require human intervention, he says: “I think AI is real. But I think we still have work to do for commercial viability in my sector.”

AI capabilities are useful for employees who speak directly to customers

For example, RBC is using generative AI to help contact centers. “We have some good use cases, but it’s about reducing costs rather than generating revenue,” says Beltzer. “But it’s a good start”.

On a more general level, AI may never completely replace humans in the wealth management sector, he adds. What we have found is that people do not want to talk to a machine that tells them: “Everything is going to be fine”.

The capabilities of AI, however, are useful for helping employees who speak directly to customers. “More and more people are resorting to wealth management, because we have more assets,” explains Mr. Beltzer. “So they will be able to serve their customers with more technology – by making sure that a certain box is ticked or that a certain formality is done for them. This is where we need to develop. Thus, advisors will be able to focus on the relationship with the client and make sure that what they have invested in will meet their long-term goals.”

As IT manager, “our challenge is to make systems more scalable and more efficient,” explains Beltzer. “I have to make it so that employees can do more of what they love and remove activities that don’t add value”.

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