New Era of Transformation Brings a New Way of Thinking About Work

By Donald Thompson, LinkedIn

We're at a defining moment with AI: Its capabilities are advancing fast, with generative AI and multi-agent systems executing more complex tasks with elevated levels of efficiency and effectiveness. As organizations deploy increasingly sophisticated AI, it's reshaping the future of business and the future of work — from the skills employees need to the structure of teams and the way decisions are made. Insights from LinkedIn's Economic Graph Research Institute suggest that, today, 55% of LinkedIn members' jobs globally stand to be augmented or disrupted by generative AI.

These advancements raise new challenges and questions for businesses about how to adapt to this rapidly evolving environment. How do tech stacks need to change? What kind of support and tools do teams need to move at a faster, competitive pace? What skills, training, and new processes will people need to support the growth of the business?

A new chapter of enterprise transformation has begun: the cognitive era.

What Is the Cognitive Transformation Era?

Cognitive transformation signals a change in how businesses use technology to optimize outcomes. We're moving from the digital transformation era, which largely focused on digitizing processes, to the cognitive transformation era, which will focus on truly transforming how those processes work.

Related:AI Quiz 2024: Test Your AI Knowledge

Cloud computing was a driving force for digital transformation, shifting businesses from the world of paper to the world of computing. In varying and limited ways, businesses achieved degrees of digitization, but many stopped short of rethinking and enacting change in their processes for global optimization. Digitization mostly delivered incremental improvements, such as improving data mining and reporting.

Now, with more advanced technologies, new levels of optimization are possible. Rather than enhancing processes, we can use AI to reinvent them, transforming the way we all work. Instead of leveraging digitization to improve efficiency, AI-based systems can learn, adapt, and — with calculated checkpoints and oversight — independently execute tasks with greater efficiency and productivity.

A Changing Dynamic Between Employees and Tech

As AI incrementally takes on more tasks that previously only humans could perform, employees' relationship with technology is changing. Right now, we primarily use AI as a tool to support the decisions we make and the tasks we execute. This dynamic will shift as AI is given greater leeway in making more decisions. With comparatively low effort to the previous digital transformation era, AI not only automates but self-organizes to optimize business processes and outcomes — and that changes the role people play in the process. Human judgment will still be extremely critical: Employees need to teach and guide AI to make the right decisions, providing feedback to help it learn and adapt. Ultimately, it's up to us to decide what AI is allowed to do — or not to do.

Related:AI in 2024: Top Stories (So Far)

Across many job roles, employees and machine intelligence will likely form a symbiotic relationship, collaborating to help businesses achieve groundbreaking efficiency, productivity, and innovation. Research shows that business leaders are looking to empower people with AI rather than replace them — they're 2x more interested in using AI to increase productivity than to cut headcount. AI is changing the future of work and the nature of jobs — for many of us, learning to work with AI will be essential. It's time to start preparing for change on a mass scale.

Preparing for a Skills Evolution

To successfully navigate this transition, companies need a comprehensive strategy that prioritizes the upskilling of their workforce and managing change.

A critical first step is examining how jobs are evolving. What skills and competencies do people need? Most of us will need a basic understanding of how to effectively work with AI, even if we're not on the tech team. It will soon become a basic expectation. However, as AI starts to take on more tasks, we're also seeing a heightened emphasis on soft skills across the board. To understand how this really plays out, let's look at a specific job.

Consider the job of a software engineer, for example. Our analysis found that 96% of a software engineer's current skills — mainly proficiency in programming languages — can eventually be replicated and augmented by AI. That doesn't mean engineers aren't necessary; instead, it means coding won't take as much time, leaving more space for engineers to innovate, collaborate, and communicate with others. Even as more sophisticated multi-agent AI systems become common, we'll still need employees to implement, train, and oversee the technology — their judgment and experiences can't be replicated. While it will always be important for developers to have fundamental technical skills, those who think creatively and have a passion for learning will be in high demand.

As professionals outside of tech — from finance to marketing to sales — are asked to monitor and evaluate AI output more often, critical thinking and analytical skills will become more important. To use generative AI effectively requires strong prompting skills, which sounds technical, but looks very similar to the skills you need to communicate and reason effectively with other people. 

Regardless of the job, continuous learning and agility must be a priority for businesses. People need support in learning skills that are tied to where the business is going — not where it has been — and that will require bringing as much rigor to training people around soft skills as technical skills.

New Possibilities for the Future

We have a unique opportunity right now to shape this new era of transformation: AI isn't just about enabling improved productivity and efficiency; it can unlock better ways of working and new opportunities.

While disruption inevitably creates discomfort, there is optimism about how AI can change work for the better — such as being able to produce high-quality work in half the time and never having to mentally absorb unnecessary or irrelevant information again. New types of jobs are emerging. Over the past five years, the number of U.S. companies with a Head of AI position increased 2.6X.

AI can also help us realize a more equitable future of work. The labor market has long struggled to pair individuals' talents with opportunities. With the help of AI, recruiters can zero in on finding candidates based on skills — instead of pedigree. Online learning programs can empower employees of all backgrounds to learn new skills — including AI skills — opening the door to new career pathways. This creates a better footing for talented individuals of varied experiences and driven curiosity to find their stride.

Collaboration and communication are key to our collective success. A concerted industry-wide conversation — one that includes businesses, governments, regulators, educators, and many others — is necessary to navigate the societal and workforce implications of AI systems taking a more central role in enterprise operations. This involves sharing best practices, addressing ethical concerns, and collectively defining the new modus operandi for industries.

By coming together, we can create a future workforce that is complementary to AI, rather than displaced by it. And we can finally give people space to spend more time on the parts of their job that are most engaging. We want to hear your ideas.