Skip to main content

Generative AI and the Future of Work

Preparing your organization for the boundless potential of AI in the workplace and its impact on jobs

Did Generative AI create that advertising image you’re looking at? What about the 3D model of a protein’s structure that a scientist is examining?

What is Generative AI? How is it being used? Better yet, how can you and your organization prepare people to use it safely and efficiently? Generative AI is a rapidly evolving branch of artificial intelligence designed to generate new content ranging from text, code, and voice, to images, videos, processes, and other digital artifacts, including intricate protein structures.

Generative AI's capabilities are far reaching and truly transformative. It can and should:
 
  • Accelerate human innovation
  • Deliver valuable outcomes
  • Require thoughtful, purposeful adoption
  • Be implemented with only the highest levels of ethics and trust

How is Generative AI disrupting work?
 

AI took a major leap with Generative AI and its ability to disrupt the way we work because of its ability to create content that profoundly supports human expertise and skills—writing memos and reports, designing website graphics, creating personalized marketing strategies, and curating employee learning programs, for example. The examples of Generative AI use cases by industry are boundless and illustrate the breadth of work that can be augmented using Generative AI. Ideally, Generative AI can bolster innovation, productivity, and outcomes while making work easier for people.

For business leaders, globally, the challenge is two-fold: understanding the possibilities and risks Generative AI brings and preparing for the inevitable organizational change that is headed their way. The future success of Generative AI will hinge on a renewed focus on humans.

What is Generative AI’s impact on humans?
 

By nurturing a workforce equipped to adapt, learn, and evolve with Generative AI, we can help ensure that we are shaping a future in which technology serves as a tool for human empowerment.

Despite all the hype, it’s not meant to replace humans, but to better unlock human potential—just as technology was always meant to do. The need for humans didn’t diminish with the invention of the personal computer. They got better and faster at accomplishing work. If done well, Generative AI can aspire to the same promise: Making humans better at work and work better for humans™. That said, executives should begin to consider “futureproofing” the Generative AI-enabled workforce because work is apt to shift quickly, and workers will need new skills.

Changing the structure of "work"
 

Before you can change workflows or adjust employee roles, it’s important to take a deeper dive into what exactly is changing in the work.

Here’s the premise: if humans can use Generative AI to complete tasks faster, easier, or better than they could before because the technology has certain skills, then we can start to assign tasks differently. This is a key to success—technology is not directly replacing jobs; rather it’s changing the tasks and skills we use to get the work done.

Work

Work is defined as the outcome created (e.g., achieving sales targets, enhancing user experience, increasing customer satisfaction) by leveraging human capabilities and the tools they have invented to help accomplish the goal.

Jobs

Jobs are the traditional construct to describe the work humans do to achieve the outcomes. There’s significant concern about jobs disappearing due to Generative AI’s ability to automate tasks, but that’s not the complete picture. First, tasks aren’t jobs. Second, we need to look at skills to understand how jobs will be redefined given the adoption of Generative AI.

Tasks

Tasks are specific activities performed to achieve work outcomes. Historically, we have thought of tasks as part of the work people perform in jobs, and that’s still the case. Tasks require skills and tools to achieve a certain outcome. Generative AI may automate those tasksaltogether, freeing up a worker’s ability to focus on new tasks, or they make those tasks easier for people and create time for the individuals. Some tasks humans do better. Some tasks machines do better. Some tasks are better done with a combination of the two.

Skills enable us to carry out the tasks necessary to achieve work outcomes. Both humans and Generative AI have skills that can perform tasks to create work outcomes. Understanding the skill sets within your organization and the various job roles that use them can shape the future of work with Generative AI. Doing so will help determine what kind of upskilling curricula will be necessary for workers down the road—readying their workforce for automation, strategizing for augmentation, appreciating human-centric skills, and even pioneering new roles. We have long said it’s “humans with machines” and not humans or machines that will transcend leading organizations.

Preparing for Generative AI in the workplace
 

When we talk about the Generative AI impact on jobs and skills, we can’t overlook the significance of human skills. Emotional intelligence, critical thinking, leadership, and complex problem-solving are innately human attributes—all are challenging for machines to emulate.

Skills-based organizations see results.

Leading in a Generative AI era
 

By adopting a researcher’s mindset, digging into the technology to deeply understand and experiment with Generative AI, and then harnessing its collective human and AI potential in a way that is efficient and humane, the onus is on leaders to steer their organizations with vision, adaptability, and a deep commitment to human-centric progress. It isn’t necessary for executives to be Generative AI experts—what is important is to create and manage by a framework that focuses on and supports leadership’s vital role in guiding Generative AI-induced changes.

There’s quite a bit of work to do.

Did you find this useful?

Thanks for your feedback

If you would like to help improve Deloitte.com further, please complete a 3-minute survey