Generative AI will reshape - not replace - the workforce

Generative AI isn’t coming for our jobs, but those who learn to use generative AI are, as we enter a new era of work defined by human-AI collaboration. Leaders should therefore act quickly and carefully to define their organizations’ stances toward generative AI in order to harness its potential for the work it’s best suited to, and to integrate it into their workforce in order to make the work that humans do more human.

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Part of an ongoing cycle of change

Generative AI is the latest in a long line of technological innovations that have reshaped and redefined work and the workplace over the past 250 years. Over time, a familiar pattern has emerged: recognition of a technology’s potential, resistance to change, and then eventual adaptation and acceptance as old roles and tasks give way to new opportunities. However, unlike previous technological shifts, such as upon the advent of PCs, the internet, mobile phones, and the cloud, the emergence of generative AI is a seismic shift—a point of discontinuity with what came before. Why? Because generative AI technology is available to anyone with an internet connection, and it has the potential to help people search for the information they need and to absorb new knowledge more effectively than ever.

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Generative AI is poised to change the office in the way robots have changed factories and warehouses. Administrative duties, data analysis, programming, communication, and content creation will all be affected by this innovation. For example, generative AI could be used to analyze a company’s sales data in order to predict the products that are likely to be popular in future, informing both business strategy and decision-making. Some generative AI solutions can already write code based on natural-language instructions, and these solutions could be used to reduce developers’ workloads and accelerate the development process overall. Generative AI could, too, analyze communications sentiment to proactively identify potential issues, draft responses to emails and other messages, and automate report generation, thus freeing up staff for other, more strategic tasks.

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But the generative AI revolution is different from those we’ve seen, due to its exponential pace of development, the accessibility of the technology, and a growing gap in the global workforce’s readiness to embrace the change it offers. A Goldman Sachs study estimates that two-thirds of all US jobs will be at least partly affected by generative AI, with 25% to 50% of tasks within this subset automated as a result. Guiding an organization through such a period of intensive change and instability will require strong, visionary leadership and a critical look at how an organization may have fallen behind in its embrace of generative AI innovations.

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Deloitte’s human capital trends research over the years has shown that executives’ understanding of the impact of AI on the workforce is lagging. For example, in 2015, roughly 60% of executives reported that they felt the implications of using computers for cognitive tasks were important—but less than 5% understood the workforce impact. As AI adoption increased in the ensuing years, this gap remained largely unchanged. Today, more than 90% of leaders understand the importance of AI, but only 22% believe their organization is ready to harness it. That gap is concerning, especially at a time when workers may already be experimenting with generative AI tools.

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The shape of work to come

Historically, companies have looked at work through a job-centric lens. Work involved defining tasks, managing resources, and implementing specific practices to align with a specific job description. For years, Deloitte has encouraged businesses to move beyond this outdated way of thinking and instead structure work around outcomes, not jobs and processes.

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In this new way of thinking about work, humans will still need to achieve desired outcomes. But the skills and tasks required to do so can increasingly be performed by humans augmented by technologies such as generative AI. Workers can then focus on what they do best—creativity, strategy, empathy and engagement, and critical thinking—while generative AI can execute tasks that don’t rely on innate human capabilities. This includes the mundane, repetitive tasks that can consume large parts of workers’ days—the drudgery that can lead to fatigue, boredom, or burnout. Still, humans will be needed to review generative AI outputs, given the tools’ inherent limitations and inaccuracies. For example, using generative AI to review contracts and other legal documents may prove faster, but the technology may miss nuances and interpretations that would be noticed by a human who has studied law for years and understands how other humans would respond to those subtleties. Ultimately, companies that simply try to replace workers with generative AI capabilities will likely find the benefits short-lived—both in the near and long terms.

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In our view, companies would benefit from considering generative AI as a new team member of its human workers, with each member bringing unique skills to the table, and everyone able to review the other’s work. This form of human-machine collaboration would see workers interact with generative AI tools throughout the day, as they would with any other team member, leading to faster brainstorming, iteration, and results. For example, generative AI could be used to help human workers overcome the so-called blank-page problem when faced with writing an analysis or report: the AI tool would create the first draft, and then its human teammate could review it, ask for clarifications, and suggest revisions based on his or her own knowledge, experience, and perspective. In time, this kind of human-AI collaboration would yield a symbiotic relationship, with humans and machines helping each other be the best versions of themselves. Human workers could train the machines, explain their output, and ensure their responsible use; machines, in turn, could enhance humans’ cognitive skills and creativity. Workplaces characterized by human-AI symbiosis would then quickly be positioned to offer new job opportunities that make use of completely new skills, such as prompt engineering, which is already in demand for training large language models (LLMs).

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Bringing your workforce and generative AI together

Organizations and leaders need to act now to close the widening readiness gap. To do so, they must understand and embrace the generative AI opportunity, but all the while recognizing and addressing any potential negative impacts. Integrating generative AI into the workforce will require leaders to champion experimentation, encourage a willingness to change, become relentless about upskilling and reskilling their workers, and put new focus on nurturing and refining irreplaceable human capabilities.

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Here are five steps to take that can help you begin your organization’s generative AI journey:

1.?????Learn how generative AI can affect your workforce. Identify tasks that could be automated effectively and areas where generative AI could augment human capabilities. Experiment—and let your employees experiment, too. Monitor the skills gaps that exist in your organization and identify how workforce needs will change upon the introduction of generative AI—ensuring that workers are ready to evolve to meet future needs and are able to take on more complex, strategic roles that capitalize on what humans do best.

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2.?????Shift the focus from jobs to outcomes. The future of work isn’t defined by job descriptions. It’s defined by the outcomes delivered and the unique human skills that employees offer—and which can be enhanced by their generative AI counterparts. Take a critical look at how your organization’s work can be restructured to embrace a future that is already here.

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3.?????Develop a balanced training and reskilling plan. Prepare your workforce for the introduction of generative AI. Be transparent and offer training to ease uncertainty about the unknown of generative AI’s capabilities. Soft skills such as leadership, emotional intelligence, and problem-solving are inherently human, business-critical, and irreplaceable. Therefore, organizations that nurture a balance between technical expertise and these vital human capabilities should be well-positioned to thrive in the age of generative AI.

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4.?????Embrace risk and ethical consequences, and foster a culture of encouragement. Explore, align on, and help workers understand the risks and ethical implications associated with generative AI implementation. Establish guidelines to help ensure the responsible use of AI, and foster a workplace culture that encourages creativity, experimentation, and smart risk-taking—without compromising concerns about privacy, transparency, and bias.

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5.?????Recognize that change is constant—and fast. Accept and embrace the fact that technology will continue to change rapidly—and disrupt industries as it does so. Work to anticipate future technology developments, the disruptions they may bring, and the opportunities those disruptions may create. By accepting technology’s swift pace of change and disruption, organizations can stay ahead of the curve and capitalize on emerging capabilities as they arise.

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While generative AI is accelerating an already profound transformation of how we work and do business, it’s not a threat. It’s not just a tool, either. Generative AI is an opportunity to make work better for humans—and to make humans better at work.?