A new role emerges for software leaders: Overseeing generative AI

While it is impossible to trace individual moves, many people left their previous roles and landed better-paying jobs in other occupations. The potential of technological capabilities in a lab does not necessarily mean they can be immediately integrated into a solution that automates a specific work activity—developing genrative ai such solutions takes time. Even when such a solution is developed, it might not be economically feasible to use if its costs exceed those of human labor. Additionally, even if economic incentives for deployment exist, it takes time for adoption to spread across the global economy.

With it, that share has now jumped to 29.5 percent (Exhibit 3).4Note that this is the midpoint, representing the average of a very wide range, from 3.7 to 55.3 percent. Automation, from industrial robots to automated document processing systems, continues to be the biggest factor in changing the demand for various occupations. Generative AI is both accelerating automation and extending it to an entirely new set of occupations.

The road to human-level performance just got shorter

Our previous research had anticipated these types of changes over a longer time frame, but the pandemic suddenly accelerated matters. The past few years have been a preview of trends we expect to continue through the end of the decade. The World Economic Forum Future of Jobs 2023 report confirms that technology will be a critical driver of business transformation in the next five years. More than 85% of the participating organizations said increased adoption of new technologies and broadened digital access are trends they expect to drive change at their companies. If you’re just entering the workforce, you’re in a unique position to choose a field expected to grow. Meanwhile, the way the workforce interacts with applications will change as applications become conversational, proactive and interactive, requiring a redesigned user experience.

A generative AI bot trained on proprietary knowledge such as policies, research, and customer interaction could provide always-on, deep technical support. Today, frontline spending is dedicated mostly to validating offers and interacting with clients, but giving frontline workers access to data as well could improve the customer experience. The technology could also monitor industries and clients and send alerts on semantic queries from public sources. The model combines search and content creation so wealth managers can find and tailor information for any client at any moment. Retailers can create applications that give shoppers a next-generation experience, creating a significant competitive advantage in an era when customers expect to have a single natural-language interface help them select products.

Our Generative AI Collaborations

If you are somebody in a creative field and you leverage generative AI to get your output up from six articles a week to 12, you’re spending less time per article. You may need to do that to get to publication in time, but that also means you’re not spending as much time in the shower, on a run, or in the car thinking about the articles. Your productivity will go up, but you may not necessarily genrative ai have as much time for creative thinking. We know that the most creative thoughts come from downtime—when you’re doing something else and letting your mind wander. But what if I, as the employee, can query, “Who are five success models with my strengths and weaknesses, and what have they gone on to do? In that way, when we check in a year later, I’ve really improved and increased my aspirations.

A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

“AI-native business models and experiences will allow small businesses to appear big and large businesses to move faster.” Generative AI technology has percolated genrative ai across multiple domains over the last few years. Much of this progress is due to advances in new large language models made possible by transformers.

Nearly all industries will see the most significant gains from deployment of the technology in their marketing and sales functions. But high tech and banking will see even more impact via gen AI’s potential to accelerate software development. Gen AI tools can already create most types of written, image, video, audio, and coded content.

The third generation (GPT-3), which predicts the most likely next word in a sentence based on its absorbed accumulated training, can write stories, songs and poetry, and even computer code — and enables ChatGPT to do your teenager’s homework in seconds. Greenstein predicted this will let firms reimagine their business processes to use the technology and scale what the workforce can do. “With that, entirely new business models will emerge, just as they do after any disruptive technology comes to the market,” Greenstein said.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem’s work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

• He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade.
• Applying generative AI to such activities could be a step toward integrating applications across a full enterprise.
• GitHub Copilot is a great example of AI being used by software developers in very specific contexts to solve problems.