AI and its impact on workforce transformation

Since ChatGPT exploded onto the scene, generative AI has quickly become embedded in the workplace. Knowledge workers feel the urgency to incorporate these tools into their daily work to stay ahead, but so far this change has largely been ad hoc.

For organizations to take full advantage of AI, they need an intentional workforce transformation program that keeps them abreast of new developments continuously.

Accenture expects that generative AI will transform 40% of all working hours within the next decade, while Gartner predicts that 40% of enterprise applications will have AI built in by 2024. Yet, while some jobs may be displaced, others will be created, and in others AI will augment or enhance work.

There’s no doubt the increasing pervasiveness of AI in business has its challenges, but it also brings immense opportunities to address the macro environment that organizations face.

Demographic changes, competition for talent, and changing skills needs all make it more difficult to for businesses to anticipate future skills demand and close skills gaps. If implemented well, AI could help solve these issues but it requires a deep understanding of work and skills, rather than people and jobs.

Challenges and opportunities of AI in the workforce

Analysts predict that generative AI will disrupt knowledge workers in the way that robotics has disrupted manual work in manufacturing. 38% of organizations using AI today expect more than 20% of their workforce will need to be reskilled.

Responding to these changes in a more systematic way will be important to prevent any adverse effects on productivity and to avoid unnecessary loss of talent.

Accenture believes that, over the next decade, “AI will be a megatrend that transforms industries, organizations, and the way we live and work”. But rather than cost reduction, AI supports business growth, as it frees up 60-70% of workers’ time, so they can concentrate on higher-value tasks.

Recent studies suggest that generative AI has the potential to make an annual contribution to the worldwide economy ranging from $2.6 trillion to $4.4 trillion. To put this into perspective, the entire gross domestic product of the United Kingdom in 2021 was $3.1 trillion.

In short, the positive impact AI can have on productivity and profitability is already abundantly evident: 12% more tasks are completed using AI, 25% are completed more quickly, while organizations see a 40% increase in the quality of work. The results speak for themselves.

Focus on work and skills, not people and jobs

Despite these impressive statistics, workforce transformation involving AI is in its infancy and introducing cognitive technologies into the organizational structure at scale and in a distributed way is challenging. But analyzing work and skills as the basis for organizational redesign, rather than people and positions, is a game changer for these transformation projects.

There are many questions to answer before businesses undertake an organization-wide workforce transformation. How can leaders anticipate how these technologies will displace work and where they will augment tasks that people do? How will introducing AI change the type of work done to achieve business goals? And what will the associated costs of these changes be?

Answering these questions is good context for understanding which roles are most likely to be affected first or most significantly. With this insight, you can compare findings against the industry benchmark and begin to see the implications. So, start with the work to see the impact on roles.

But before you can model your future workforce, you need a complete view of the current state of your organization. To do this requires data from many disparate sources to be brought together in a single source of truth. A solid data foundation enables an understanding of work composition across the organization, so you can then plan and model future states.

Understand the work your organization does and who does it

Understanding the work people do to support business goals begins with activity analysis. This links people data to activity data, so you can see the cost and effort of each activity, as well as who’s doing them, to reveal opportunities to bring AI into the workforce.

Building an activity taxonomy with Orgvue’s platform to highlight where AI can augment human work enables organizations to redesign roles around a redistribution of tasks.

Activity analysis also shows how productively work is being done, whether it’s fragmented or being duplicated, and whether it could be automated, consolidated, or centralized.

With a clearer view of the work being done, the cost of that work, and the roles involved in different tasks, you’ll be able to plan your investments in workforce transformation more effectively.

Model your future workforce and use AI to close skills gaps

With a fuller understanding of work, you can begin to assess your current skills demand and supply, then model opportunities to integrate AI and automation into your future workforce to close any skills gaps.

You can use Orgvue to model and assess scenarios that explore whether work is better done by humans, machines, or a combination of both. You’ll see where there’s scope for upskilling to prompt and validate the work being done by AI, ensuring accurate, appropriate outcomes, and improved productivity.

A skills and competency analysis will help you baseline what you have today, the skills you’ll need tomorrow, and how your talent needs may change as you bring in AI and other cognitive technologies.

By building insights like these into your workforce planning, you can explore how you might reassign people rather than lose them, redesign roles to redistribute tasks and activities, as well as create new roles to support new technologies in the workforce.

A continuous approach to AI and workforce transformation

Structuring your organization to be future ready using a different approach to organizational design means you’ll have a much clearer view of your workforce transformation requirements. A continuous, iterative approach is what’s needed to keep up as AI technology evolves.

Orgvue can you help identify skills gaps and track progress against closing them, making it easier to manage these gaps as you begin to build a workforce where people and machines work in partnership.

You can find out more about how Orgvue can help with workforce transformation through our website. Or ask us to show you how our approach can make bringing AI into your organization in a managed way easier and less risky.

In the next article in this series, we’ll look in more depth at activity analysis and how it can help you determine which tasks should be done by people and which can be done more efficiently with AI.