While many users see generative artificial intelligence (genAI) technology as automation tools that will eliminate many of today’s jobs, most in the IT industry see it as a generator of knowledge jobs.
That’s because genAI tools such as ChatGPT and Midjourney can help eliminate mundane tasks, freeing up workers to take on more valuable creative roles and be more productive.
GenAI is also expected to “democratize jobs.” That is, the technology will enable employees without computer science degrees to create applications using AI-augmented coding. Already, many companies see that possibility as genAI’s “low-hanging fruit.”
In addition to changing the way employees work, genAI and AI in general will also create net-new jobs — more than half a billion of them by 2033, according to a new Gartner report.
Mark Kashef, an AI consultant and prompt engineer on Fiverr, an online freelance marketplace, believes genAI will create jobs that today can’t even be imagined. Areas such as AI development, data analysis, and AI ethics are all fields likely to see a boom because of genAI adoption.
“Plus, by automating all those repetitive tasks, AI can free up workers to focus on higher-value stuff that really requires that human touch,” Kashef said. “And as the performance of language models goes through the roof while the price keeps dropping, the possibilities are endless.”
One new role Kashef came across recently was that of “Agent Engineer,” whose responsibility is to create AI assistants for a company using chatbot and AI agent no-code tools. “This never existed, and we're going to see tons of new roles just like this pop up in the next five years,” Kashef said.
If the democratization of jobs currently envisioned proves to be true, those jobs will become accessible to non-specialists. In turn, that will reduce costs and improve the availability of existing or new AI-powered products and services, according to Gartner Vice President Analyst Pieter den Hamer.
Economic growth spurred by genAI adoption will likely occur in all industries worldwide, “assuming more or less stable other economic conditions,” den Hamer said.
A survey of 1,400 US business leaders commissioned by the freelance job platform Upwork also found that companies will hire more because of genAI. Forty-nine percent of business leaders surveyed — respondents included senior managers through C-suite level employees — indicated they’ll hire more more full-time employees, with the same percentage saying they’d hire more freelancers. And 64% of C-suite respondents indicated they would hire more professionals of all types due to generative AI, Upwork found.
A slow rollout over years
GenAI’s ascension will be a slow roll, though. Currently, only 15% of organizations have effectively adopted it, according to den Hamer, meaning it's not yet a significant threat to jobs.
Even so, companies need to consider how to train up their employees to use AI-based tools effectively, just as those same tools need to be trained or contextualized to reduce limitations and to mitigate risks.
“…It is much more realistic that jobs will get augmented, not replaced,” den Hamer said.
Because many jobs involve a diversity of tasks, even genAI tools that support just one task — say number crunching or analytics — can help employees allocate their time more efficiently.
AI will kill some jobs
Fiverr’s Kashef, has seen the headlines about genAI being a job-killing technology, but that doesn't seem to be happening in the “wide-scale” marketplace.
“Many folks that I work with on Fiverr work in the domains that everyone keeps saying are 'fully-automated.’ I can invariably see that AI is augmenting their roles, but for the better,” Kashef said.
The rare cases where genAI is good enough to fully automate activities is predominantly involves content creation such as text writing, image/video creation, software coding, translating, summarizing, and composing search results.
But, van Hamer said, “in most cases there is still a need for a human to be in the loop to validate and correct AI, which offsets the initial productivity gain.
“Nonetheless, in particular for those jobs in which content generation activities make up a significant part of the role, headcount reductions are likely to occur over time, assuming job descriptions stay the same and demand does not increase,” van Hamer noted. “This is much less likely for jobs in which content generation is only a minor part, let alone in other jobs with activities such as physical labor in which AI hardly can play a role, yet.”
In addition to helping with software creation, other early uses for genAI fall into two categories:
- Writing position descriptions, marketing copy, and employee reviews.
- Helping workers at large call centers answer high-value calls first, and providing them with better information about the customer who's calling.
Those use cases should enable employees to be faster and more customer focused, according to Martha Heller, CEO of IT job recruiting firm Heller Search.
“I do not believe the need for some human thought will ever go away, despite how sophisticated AI can get,” Heller said. “While AI might replace a few knowledge workers who have minimal competence in their jobs, it is far more likely that genAI will perform rote services that let knowledge workers innovate in and grow their businesses.”
In addition, she expects “an explosion” of AI solution providers, which will create opportunity for new executives in finance, technology, marketing, and sales.
GenAI is also likely to bolster an already growing demand for data scientists, she said, because AI without a high-value use case is a waste of time and money.
“Data scientists are those rare people who can read the data, develop business strategy, and then articulate it to the people who can fund it,” Heller said. “GenAI will also put a premium on people who are good with data integration. AI is only as valuable as the data it runs on.
"When CEOs ask, 'Where is my AI strategy,' tech leaders will turn their attention to integrating the data necessary for AI value.”
What AI skills should employees add to their resume?
One of the top issues for leaders implementing genAI tools has been the lack of skilled employees. AI skills and talent strategies is the top challenge facing enterprises today, according to IDC’s president, Crawford Del Prete, who spoke at IDC’s Directions conference last week.
Fiverr’s Kashef said the top skill employees need is being able to leverage AI tools “and knowing which tooling to use to expedite which task.” For that, employees can often turn to the usual chatbot assistants, such as OpenAI's ChatGPT and Anthropic's Claude.
ChatGPT, for example, has a myriad of functionalities employees can take advantage of, such as image-to-text prompting, querying the live Internet using Bing, or most notably creating powerful custom GPTs (LLMs) that can take in custom actions that connect to any type of API.
“Being 'ChatGPT-competent' is and will be an in-demand skill moving forward,” Kashef said. “It's not just about writing prompts, but building a workflow where you interchange between human input, plus AI output, plus human feedback loop with the AI.”
With AI tools ingesting all kinds of documents and data from PDFs and Excel spreadsheets, data literacy is also key, Kashef said. While workers don't necessarily need to read the documents and learn all the Excel formulas, they do need to understand how to quickly interpret them, he said.
“And understand what is worth inputting and what your final outcome should look like,” Kashef said.
Other top jobs Kashef sees in the future:
- Building AI Agents (Agentic AI): A cutting-edge skill that basically is about creating AI systems that can autonomously make decisions and take actions to achieve goals.
- Cybersecurity in AI: As AI becomes more powerful and widespread, securing systems will be critical.
- AI Product Management: The successful integration of AI into products and services requires a unique blend of technical understanding and business acumen. AI product managers who can bridge the gap between AI capabilities and market needs will be in high demand.
Training employees is key to success
Global services company Ernst & Young (EY) has been deploying general AI (machine learing, etc.) since 2012. Over the past decade, it has seen major improvements in employee efficiency and accuracy.
For example, the firm implemented automated document readers that could summarize reports; it also rolled out data classification engine and prediction algorithms — tools that helped employees with everyday tasks.
Jeff Wong, Ernst & Young’s Global Chief of Innovation, said automating tasks through AI resulted in a 10-fold improvement in time to completion and five-fold improvement on accuracy of results. And instead of replacing workers, it forced the firm to hire more technologists.
In 2018, for example, the company had 2,100 technologists; today it has more than 75,000. A lot of those workers were added to address new capabilities created by AI.
“Moving task time to thinking time was incredibly valuable for us,” Wong said. “I’m part of the crowd who believes over the 15- to 20-year time frame, AI will be more expansive to jobs and job creation. We will go through a shift in changing period between now and then.”
With the adoption of AI, Ernst & Young faced a problem common to all organizations seeking to roll out the technology: an ill-prepared workforce. So, Wong led an effort to upskill employees and is now rolling out AI training to all 400,000 workers. So far, 84,425 have completed the training.
Additionally, 15,000 EY employees have completed specialist "AI badges" and 22,000 more are in the process of getting them.
Six years ago, EY partnered with Stanford University to begin offering advanced technology “bootcamps.” The school also began offering MBAs in digital and data sciences that can be a foundation to AI skills.
Wong believes skills training can enable employees who don’t have a computer science degree to effectively understand concepts like computer coding — without actually having to be able to write code.
In fact, many of the jobs available at EY involve interacting with AI systems without needing to code, Wong said.
“Honestly, I think society is not doing enough to train people in AI,” Wong said. “Because of the acceleration in pace of change, significantly driven by AI, governments and society have an obligation to invest heavily in retraining.
“If people don’t change to adapt quickly enough, we’ll get the 21-year-old who’ll take on a greater responsibility faster and will leave behind the generation that couldn’t shift,” Wong added.
Originally published at Computerworld