Rise Of Generative AI And Demand For Talent To Leverage It
Prompt engineering is the new gold rush. Anthropic, an AI startup founded by former OpenAI team members and backed by Google, recently advertised for a Prompt Engineer and Librarian with a salary range of USD 280,000-USD 375,000 a year.
One of the key requirements of the position is a creative hacker spirit, a love for solving puzzles with basic programming skills, and comfort with writing small Python programs. Let’s put that in perspective. In the short space of two years that generative AI has taken to capture business imagination, the demand for prompt engineers has shot through the roof.
This is because of the high impact the proper use of generative AI can have on exploring and creating new products, managing customer experience, understanding markets, delivering efficiencies, and expanding labour productivity. Organisations would give an arm and a leg to address these challenges—and they are.
Anthropic was not the only one ready to pay a king’s ransom for the right AI talent. By the end of April, a diverse lot of organisations were seeking prompt engineers—basically, a tribe of people who can talk to AI.
These organisations included the Boston Children’s Hospital, vidIQ, Sourcegraph, and Skyward, all paying between USD 93,000 and USD 243,000 a year. Even actor Donald Glover was looking for AI prompt animators for his creative studio, Gilga. For a quick look at where the needle in prompt engineering careers is pointing, data from the US Bureau of Labor Statistics: The median annual wage for computer and information technology occupations was USD 97,430 in May 2021.
The market for prompt engineers is quickly opening. Tools such as Beatoven, ChatGPT, Dall-E, Eleven Labs, GitHub Copilot, Google Bard, Microsoft Bing Chat, NotionAI, Stable Diffusion, and hundreds of others mushrooming each day are creating the boom.
The results of a Salesforce survey released in March showed that 67 per cent of senior IT leaders would be prioritising Generative AI over the next 18 months, and 33 per cent said they would make it their top priority.
In the next 12 months, every Fortune 1000 company can be expected to seek out prompt engineers. One survey by Accenture found that 40 per cent of all working hours can be impacted by large language models (LLM) such as ChatGPT.
The floodgates to a new career opportunity are about to open. At a time when layoffs in the tech industry are becoming rampant, prompt engineering will become a lifeline for many. Expect a brutal talent war to erupt soon.
But let’s not be misled by requirements such as “creative hacker spirit” and a “love for solving puzzles.” Sam Altman, the CEO of OpenAI observed recently in a Tweet that, “Writing a really great prompt for a chatbot persona is an amazingly high-leverage skill and an early example of programming in a little bit of natural language.”
Where is this sophisticated talent going to come from—one that has an understanding of AI models and data structures, the nuances of natural language processing, tools training, prompt assembly, guiding the model to the type of output required, ethical considerations, and industry domain expertise?
There are no easy answers to these questions. Before we get to the kind of training initiatives required, it is vital to begin right now by ensuring HR leaders know what motivates this category of AI talent and how organisational leaders, data engineers, and scientists within organisations can play a role in attracting this talent and keeping it engaged.
A simple but not-so-quick strategy for talent management teams across top enterprises will be re-skilling existing talent. This talent will come with pre-existing knowledge of the business and will be familiar with organisational goals. However, this talent will need to be freed for long durations from their day jobs before they can qualify as prompt engineers.
Meanwhile, we can expect a host of organisations—in the guise of academies—offering courses in prompt engineering, hoping to cash in on the boom. These will be joined by boot camps for prompt engineers, hackathons and challenges, industry-specific ready-to-use prompt guides, toolkit tutorials, prompt boosting and attention mechanism masterclasses, creative prompt debiasing tips and tricks, and so on. Advanced courses will be gamified, immersive, and personalised. Certifications will appear, some reliable, some dubious.
The long-term approach to building the required talent at scale is to include prompt engineering in academic courses as an adjunct to specialisations in computer sciences as well as in industry-specific areas. Industry and sectoral bodies—associations, guilds, and promotion groups—should guide such initiatives, working to ensure that the technology provides the highest returns to their area of operations.
Colleges and universities that begin to include prompt engineering in their syllabus will automatically find a rush for campus recruitments. At the moment, we are riding the ‘OMG curve’ of Generative AI—where we are surprised, fascinated, and entertained by the capabilities of the new technology. Soon, when large businesses decide to put money behind the technology, they will want more than self-taught experts.
