Artificial intelligence (AI) is a key factor in the ongoing workforce transformation that is both creating and displacing jobs. For business leaders to benefit from this transformation and achieve returns on investment for AI implementation, it will be essential for them to prioritize workers and earn their trust.
The job landscape is expected to change significantly. According to the 2025 WEF Future of Jobs report, there will be a net increase in jobs by 2030, with 170 million jobs created, while 92 million will be displaced. While this job growth is forecast to take place in the logistics, software/technology, and healthcare industries, a host of jobs that are largely routine function-based are at risk of fading away. For business leaders thinking about their organizations’ sustainability, this workforce transformation should be an important consideration. Job security, dignity, and career growth are foremost in most workers’ minds. As business leaders work toward the kinds of tech innovation driving the AI workforce transformation, they should consider these concerns of workers to ensure that they are bought in on AI implementation.
AI investment moves from ambition to execution
One of the practical factors that prevents business leaders from moving forward in this workforce transformation, apart from talent gaps or regulation that lags innovation, is that they have not yet seen returns on AI investment. There has been an enormous amount of investment in AI, but most organizations remain at the pilot stage of AI implementation. Less than 40 percent of companies that invest in AI have seen profits from it.
Investment decisions are largely made at two parts of the AI stack. The AI stack is made up of infrastructure at the foundation (which is the compute, storage, networking, etc.); followed by the data layer (where the data is processed, including the various cloud services required); model development layer (where the models change from development to practical use); and the application layer (which is where the AI functionality is wrapped with interfaces that make the model actionable for users). Historically, major investments are made toward the bottom and top of the AI stack, meaning AI infrastructure and AI applications, respectively.
The stack-based approach lacks a holistic view that considers efforts to get workers’ buy-in, how effectively employees adopt AI tools, and how workflows adapt. For a better chance at meaningful returns on investment, business leaders should make long-term investments in AI that take into account how organizations will change over time and ensure that AI is embedded in organizations’ core operations.
Focusing on the workforce
A main reason companies are not seeing the expected productivity gains from AI implementation is that workers have not found it useful. This could be because workers don’t feel actively involved in the transformation process and have concerns that AI will lead to the loss of their jobs. Given the scale of the impact of AI, ensuring workers have a voice in this transition is critical.
The focus should therefore be on how to get buy-in from workers. Business leaders can try to accomplish this by:
- Developing frameworks for shared productivity gains: With the bulk of productivity gains from AI implementation expected to arrive within the next three to five years, the development of frameworks for shared productivity gains can provide workers with reassurance that their contribution toward productivity gains for the organization will be recognized. At present, organizations are reinvesting AI-driven productivity gains into innovation, data infrastructure, and workforce upskilling, which bodes well for increasing the impact of AI across multiple workflows rather than employing it to boost efficiency for a single workflow.
- Transparently communicating to the workforce about the impact of AI on potential job losses: If job losses are expected, then clear communication about new skill requirements and head count changes will be valuable. In instances where the focus is on augmenting rather than replacing human workers, clear messaging to this effect will also be helpful.
- Including the workforce in the transformation process from the start: Business leaders should bring domain experts or users of the technology into the lab to offer perspectives and test the technology at various stages. Currently, almost 50 percent of C-suite leaders would not involve nontechnical employees in the early development stages of AI tools, i.e. requirement gathering and ideation. Involving domain experts/nontechnical users at the outset can help make AI systems more inclusive.
The task for business leaders is to make the most of their employees’ readiness to adapt to an AI-augmented workplace. This can help increase the pace of AI implementation while ensuring trust, safety, and transparency. The prioritization of human capital strategies will determine the success of businesses in leading the workforce through rapid technological changes.
Reevana Balmahoon is a nonresident senior fellow at the Atlantic Council’s GeoTech Center. She has experience leading the development of new technologies, shaping strategic partnerships, and securing technology investments.
The GeoTech Center champions positive paths forward that societies can pursue to ensure new technologies and data empower people, prosperity, and peace.
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