How Digital Workers Could Force TA Leaders to Rethink Workforce Planning, Talent Operating Models, and Recruiting Processes
Your CEO is going to ask you about hiring AI agents. It might be next month, or next quarter, but it’s coming. Perhaps they’ll frame it as a cost-cutting mandate: “We need to reduce operating expenses by 30%—what roles can we automate?” Or maybe they’ll be more direct: “I keep hearing about these AI agents. We need a strategy for integrating them into our workforce.”
OpenAI CEO Sam Altman recently predicted that 2025 will be the year AI agents “join the workforce” and materially change company outputs. The numbers tell a compelling story: the AI agents market is projected to grow from $5.1B in 2024 to $47.1B by 2030. Unlike traditional productivity tools, these are autonomous digital workers that can handle entire workflows independently. They’re already transforming industries—conducting patient outreach in healthcare, qualifying sales leads in marketing, and managing complex regulatory compliance in banking. And they’re doing it all with minimal human oversight.
For TA leaders, the stakes are clear: wait until your CEO comes calling, and you risk becoming a tactical executor of someone else’s strategy. Prepare now, and you have an opportunity to shape your organization’s approach and position yourself as a strategic advisor in what could be the biggest workforce shift in decades.
So what exactly are AI agents, and what should TA leaders be thinking about to prepare for their arrival?
What are AI Agents?
Unlike the general-purpose AI chatbots most of us are familiar with—ChatGPT, Claude, Gemini, LLaMa—AI agents are digital workers designed for specific jobs. They are systems or programs capable of autonomously planning and executing tasks on behalf of users. And this descriptor—autonomously—is key.
Whereas ChatGPT or Microsoft Copilot can assist you with tasks, they require users to enter prompts or interact within their specific platforms to get help. AI agents, by contrast, can operate independently of user input and interact with the outside world. They may call patients flagged as high-risk for cancer to schedule a doctor’s appointment, set up LinkedIn campaigns to target a company’s ideal customer persona, or plan and book a vacation for a family of five—all without constant user intervention.
Key Differences Between Chatbots, Copilots, and AI Agents
Why This Time is Different
If you’ve ever had frustrating experiences with automated phone systems or chatbots, you might be skeptical of AI agents. But today’s AI agents represent a fundamental shift in capability, and they’re already transforming work across a wide range of industries:
- Healthcare: Hippocratic AI offers virtual nurses for hire who can help patients manage chronic diseases, prepare patients for upcoming appointments, and provide post-discharge instructions for complex conditions like congestive heart failure or kidney disease.
- Finance: Norm Ai provides Regulatory AI Agents that automate compliance analyses, ensuring financial institutions adhere to tens of thousands of federal banking rules and regulations.
- Sales: 11x developed AI Sales Development Reps Alice and Mike to track and qualify leads, do account-based marketing at scale, and automate inbound and outbound calls in 28 different languages.
- Hospitality: HotelPlanner’s AI hotel booking assistant takes calls, books rooms according to customer specifications, and finds the best deals in countries around the world.
- Logistics: HappyRobot’s AI voice agents act as freight brokers by autonomously managing communication tasks like load updates, capacity requests, check calls, and appointment scheduling.
Importantly, unlike previous AI advances that promised transformation but delivered only incremental improvements, these AI agents are already demonstrating measurable impact across industries—from digital nurses rated 36% higher on bedside manner than human counterparts, to digital freight brokers that reduce call times in half while reducing operational costs by one-third.
Why AI Agents are Rising in Popularity Now
These examples aren’t just isolated success stories—they represent a broader trend in how organizations are approaching their workforce needs. Specifically, AI agents are gaining traction for two key reasons:
- Addressing Staffing Shortages: Several industries face workforce challenges currently or will within the next few years. Consider healthcare, where the U.S. is projected to face a shortfall of 120,000 physicians by 2027, or accounting, where the number of accounting graduates steadily declined from 2016 to 2022. AI agents can bridge these gaps by helping companies maintain operations while they work to fill open positions.
- Streamlining Workflows: AI agents can also simply improve efficiency. By automating repetitive or deterministic processes, exhibiting judgment, and making decisions, they enable businesses to operate faster and at lower cost, while allowing human workers to focus on emerging priorities.
What AI Agents Mean for TA: 6 Key Areas of Impact
With AI agents already proving their value across industries as workforce shortages become increasingly acute, their adoption will fundamentally impact how organizations approach talent acquisition. There are 6 key areas TA leaders should start considering now:
1. Ownership of AI Agent Acquisition
A foundational question is whether AI agent acquisition belongs in TA. If you’re an organization whose contingent hiring lives with Procurement, perhaps AI agent acquisition follows the same path. But if AI agent acquisition sits with TA, the team may need to build relationships with AI agent providers across all business verticals, treating them almost like a new category of search firm or talent partner.
2. Workforce Planning
With some business units now able to augment or outsource workstreams to AI agents, workforce planning—a process few TA leaders view as “optimized” to begin with—may become even more complex. When a department needs five additional employees, will that mean five humans? Three humans plus AI agent augmentation? Two humans plus multiple AI agents? The traditional calculus of headcount planning may need a complete reimagining.
AI agents also introduce ripple effects for internal mobility and succession planning. While they excel at specific tasks or workflows, AI agents—unlike humans—cannot be retrained or redeployed to other roles should the need arise. Further, AI agents that backfill positions cannot grow into new positions, making traditional succession planning strategies less applicable. This shift will require TA leaders—in partnership with others in Workforce Planning—to rethink how they balance human talent with AI-driven support.
3. Global Talent Strategy
Organizations have spent decades building global talent networks, often capitalizing on labor arbitrage through offshoring. AI agents may disrupt this entirely. With AI agents able to handle tasks traditionally sent to low-cost locations outside the U.S.—call center operations being the quintessential example—without time zone constraints, extensive training, or onboarding, TA leaders will need to reassess their global talent strategies and workforce distribution. The geographic arbitrage that has shaped talent strategy for decades may become less relevant, and within TA, the way global talent networks are built.
4. TA Operating Model
The fluidity with which TA flexes up and down as hiring volume changes often dictates how effective the function can be. The option to leverage AI agents makes that flex much more tractable, but simultaneously introduces a paradox of choice. TA leaders will soon have to weigh the costs and benefits of AI agents against traditional options like RPOs, contingent workers, and FTEs.
For instance, AI recruiter Holly can autonomously source, screen, and engage candidates. While Holly is easily deployable and needs no onboarding, can it adapt to regional nuances and cultural contexts as well as an on-the-ground local recruiter? Alternatively, could a hybrid approach combining AI agents, copilots, and regional recruiters provide a more balanced solution?
The introduction of AI recruiting agents will inevitably create countless new variations in how global TA teams are structured, offering increased flexibility, albeit with no precedent to guide these decisions.
5. TA Metrics and KPIs
Metrics and KPIs are a top priority for TA leaders in 2025, but the potential integration of AI agents—both as recruiters and as hires—raises questions about how recruiter performance should be measured.
For example, how will recruiters be evaluated on quality of hire when the “hire” is an AI agent rather than a human? Conversely, how will AI recruiter agents themselves be assessed, and will their metrics count toward KPIs reported to leadership? Further, how will human recruiters be judged in contrast to these AI agents?
TA leaders will need to carefully assess which traditional metrics remain relevant in this context (e.g., time-to-fill, cost-per-hire), while developing new frameworks for measuring both human and AI contributions. Equally important, they must find ways of effectively communicating this impact to stakeholders to ensure their continued investment in TA.
6. Diversity, Equity, and Inclusion
The rise of AI agents in the workforce could have significant implications for organizational diversity, equity, and inclusion (DEI). Notably, AI-driven automation is expected to disproportionately affect roles predominantly held by underrepresented groups. For example, Black and Hispanic workers are overrepresented in the 30 occupations with the highest exposure to automation, and underrepresented in the 30 occupations with the lowest exposure. Similarly, women are more than twice as likely to be affected by automation as men, across both middle and high income countries.
This raises questions about how organizations maintain access to opportunities for traditionally underrepresented groups. For example, could companies implement policies requiring roles to be offered to human workers first—not unlike the common practice of posting jobs internally before posting externally?
From an equity perspective, the integration of AI agents also highlights issues around pay transparency. Will organizations disclose what AI agents “earn” for their work, particularly in comparison to human workers? If AI agents can deliver equivalent work at significantly lower costs, what does this mean for wage equity, and what are the implications for human workers’ perceived value and job security? Addressing these challenges proactively will be essential to ensuring that DEI initiatives evolve alongside advancements in AI integration.
3 Steps for TA Leaders to Take Today
These six areas of impact aren’t theoretical considerations—they represent real challenges that TA leaders will face as AI agents enter the workforce. Perhaps most critically, TA leaders need to consider how they prepare their functions, partners, and leaders for this transition. Hiring managers will need guidance on when to consider AI agents over human talent. Recruiters will need new skills to evaluate and “hire” AI agents effectively. And leadership will need frameworks for thinking about workforce composition in entirely new ways.
If Lattice’s foray into hiring AI agents—and the subsequent backlash against it—revealed anything, it was that organizations need to approach this shift with heightened sensitivity and thoughtful planning.
TA leaders looking to get ahead of this shift can take three immediate steps:
- First, start mapping which roles in your organization could be augmented or replaced by AI agents. This isn’t about immediately implementing changes, but about understanding your exposure and opportunities.
- Second, begin discussions with key stakeholders about AI agent ownership and governance. Whether AI agent acquisition ultimately sits with TA or elsewhere, your function needs a voice in how these decisions are made.
- Finally, use the six areas outlined above to create your own AI agent readiness assessment. Understanding where your organization stands on each dimension will help you identify priorities and guide strategic planning.
The organizations that thrive in this transition won’t necessarily be the ones that adopt AI agents first, but rather those whose TA functions recognized early that AI agents represent more than just another technology trend—they’re a fundamental shift in how work gets done and how talent needs are met.
