Copyright Fast Company
For years, organizations looking to optimize operations and reduce costs have faced a binary choice. Either retain business functions within their own four walls or shift them to other geographic locations with more cost-effective labor and resources. Not anymore. Rather than decide simply between onshore and offshore, leaders now have a third option. They can reallocate tasks, business functions, and job roles to artificial intelligence (AI). In the age of automation, the most successful workforces will employ a three-pronged approach, built on the collaboration of humans and machines. New workforce, new workforce strategy But what does this look like in practice? First and foremost, leaders must evolve their workforce planning. Rather than veer immediately toward outsourcing to overseas global capability centers (GCCs), U.S. organizations should ask: “What if we transfer this to a machine agent?” This redefines the workforce strategy not in terms of location, but automation readiness. Subscribe to the Daily newsletter.Fast Company's trending stories delivered to you every day Privacy Policy | Fast Company Newsletters Of course, leaders must still be judicious. In many cases, human expertise remains essential. People best perform the roles relying heavily on emotional, behavioral, and creative thinking, along with those involving sensitive ethical, reputational, or relationship-based considerations. Even the administrative tasks often discussed in the context of automation shouldn’t be viewed as a given. Are we at a point where an AI agent could handle a procurement negotiation or contract agreement with another AI agent? Yes, probably. But would you want to give up these processes to technology? That depends on your firm’s partner ecosystem, risk tolerance, and overall level of AI maturity. When to build, when to buy The next critical consideration is timing. As major software vendors embed new capabilities into their platforms, some functions may soon come pre-equipped with AI. Companies must determine whether to invest in developing their own AI tools today or wait and assume they’ll be built tomorrow. The challenge for leaders, then, is to identify where business opportunities justify immediate investment in creating digital agents—and where it makes more sense to wait for out-of-the-box capabilities. A cross-functional team can deconstruct all the immediate AI transformation opportunities and place strategic bets based on your specific operating environment. For example, companies can now integrate AI agents into their financial processes. Or they might wait until their enterprise resource planning (ERP) platforms offer plug-and-play agent capabilities in a few years. In the latter case, an offshore GCC is a smarter short-term option. On the other side, how long will you need to wait for capabilities, and how customizable will they be for your operations? The answer differs for every firm and capability area—keep asking the questions. The rise of physical AI Beyond software, another frontier is emerging: physical AI. From humanoids and quadrupeds to drones and autonomous vehicles, once-futuristic prototypes are rapidly becoming viable business tools. This, in turn, opens up fresh opportunities for automation, particularly in sectors such as manufacturing, energy, and life sciences. But physical AI brings challenges too. Few companies possess the necessary skills to harness it in-house. Demand is growing for embedded systems engineers, robotics engineers, and computer vision professionals. These are not capabilities that can be simply upskilled. They represent entirely new disciplines requiring specialized training and expertise. Organizations must therefore decide whether to build those capabilities through recruitment and retention programs or rent them by engaging boutique firms or professional services vendors. Either way, a future-proofed talent strategy should include physical AI readiness as a factor in workforce planning. Don’t wait—upskill now A more pressing skills mandate applies to the current workforce. While necessary employee knowledge and capability types will undoubtedly shift in the long term, the most effective workers in the short term won’t necessarily be new hires. advertisement Instead, they will be existing team members who already know your culture, systems and clients—and can learn how to deploy AI to augment their performance. Companies must therefore empower employees to integrate AI into their workflows today, boosting productivity and competitiveness immediately. How they do so is up to the employees, and a divide is emerging between the carrot and the stick. Some organizations incentivize workers to embrace and innovate with AI through rewards, recognition, and career advancement. Others are more hard-line. Some leaders are already reducing headcount across areas like financial operations, with remaining staff required to use AI to plug the gap. Other organizations made headlines by mandating that no new hires will be approved without demonstrating that AI can’t perform the tasks in question. Both approaches offer pros and cons—and again, it’s up to leaders to decide what best suits their business strategy and culture. Regardless of the path taken, however, integrating AI into everyday work requires a broader rethinking of performance management. Whether now or in the future, it’s key to build AI usage into KPIs and promotion criteria for career growth. Tracking who’s using AI—and how effectively—will become standard practice. Divide and conquer Put simply, the makeup of the modern workforce has changed and will continue to change dramatically in the next few years. For businesses looking to get ahead, now is the time to transition from static job roles to dynamic, AI-augmented functions. Understand where AI can create real value today and table stakes tomorrow. Begin upskilling, hiring, and restructuring the talent pool. AI isn’t just a tool—it’s a catalyst for rethinking what work and job roles should look like. Onshore. Offshore. Agent. Organizations embracing this new three-pronged workforce will be well-positioned to lead in operational efficiency, innovation, resilience, and long-term growth. Tracy Gusher is EY Americas data AI and automation leader.
