Scaling AI in Recruiting: Top 5 Fixes to Supercharge Your AI and Gen AI Initiatives

Artificial intelligence (AI) and generative AI (Gen AI) are revolutionizing industries worldwide, including the critical domain of recruiting. As organizations increasingly seek to harness AI in recruiting to improve hiring outcomes, streamline processes, and enhance candidate experiences, scaling these initiatives successfully across the organization remains a significant challenge. Drawing on insights from Gartner’s VP Analyst Gareth Herschel, this article explores five essential strategies to scale AI and Gen AI effectively, ensuring your recruiting efforts—and broader business functions—fully realize the transformative potential of these technologies.

Introduction: Why Scaling AI in Recruiting Matters

AI in recruiting is more than a buzzword; it’s a powerful tool that can reshape how organizations attract, assess, and select talent. Whether it’s automating resume screening, enhancing candidate matching, or generating personalized communication, AI technologies are delivering measurable benefits. However, many organizations struggle to move beyond pilot projects and isolated use cases to scale AI solutions across their recruiting functions and beyond.

Gareth Herschel’s expert guidance offers a clear path forward, emphasizing five key approaches that help organizations not only adopt AI but embed it into their operational DNA. These strategies highlight the importance of precision in language, continuous measurement, governance, data readiness, and audience segmentation by attitude. By applying these principles, recruiting leaders can accelerate AI adoption, optimize investments, and ensure ethical, impactful deployments.

1. Always Consider AI as an Option—But Choose the Right Tool

One of the foundational steps in scaling AI in recruiting is to consciously consider AI as an option for every data and analytics initiative related to talent acquisition. However, it’s critical to distinguish between AI and Gen AI, as they represent different technologies with different use cases.

Gen AI focuses on generating new content based on existing data—think of it as a creative engine capable of writing job descriptions, crafting candidate outreach emails, or even simulating interview scenarios. Traditional AI, on the other hand, encompasses a broader range of techniques, such as predictive analytics for candidate scoring, decision intelligence for hiring recommendations, or hybrid AI systems that combine multiple approaches.

When evaluating recruiting projects, ask:

• Is this use case better suited for traditional AI, Gen AI, or a combination?
• What would the process look like without AI—how did we do this five years ago?
• What incremental value does AI or Gen AI bring to this task?

This thoughtful approach prevents organizations from jumping on the AI bandwagon prematurely or applying AI where it’s not the best fit. For example, automating interview scheduling may not require AI, whereas candidate matching might benefit significantly. Choosing the right tool for the right project ensures resources are used effectively and enhances the likelihood of successful scaling.

2. Always Be Measuring—And Communicating the Impact

Measurement is the backbone of scaling AI initiatives. In recruiting, it’s tempting to focus only on pilot projects or proofs of concept, but the real value emerges when you continuously measure AI’s impact throughout deployment and beyond.

Why is ongoing measurement so important?

• Financial accountability: AI projects, especially those involving Gen AI, often involve ongoing costs such as software subscriptions or cloud compute expenses. You need to demonstrate that these investments deliver tangible returns.
• Continuous learning: AI solutions evolve, and ongoing measurement helps identify new benefits or unforeseen challenges, enabling iterative improvements.
• Risk management: Monitoring helps detect unintended consequences or inappropriate use of AI tools, allowing early intervention.

For recruiting teams, key metrics might include time-to-hire reduction, quality of hire improvements, candidate satisfaction scores, or cost savings from automated processes. However, measuring alone is not enough. Effective communication of these outcomes to stakeholders across the organization is equally vital. Tailor your message to resonate with different audiences—HR leaders, hiring managers, finance teams—highlighting the benefits that matter most to them.

It’s also important to recognize that AI’s impact on headcount and workflow may vary over time. While some organizations initially increase headcount to support AI adoption, medium-term effects often include process efficiencies that reduce workload. Being transparent about these dynamics fosters trust and helps manage expectations.

3. Establish Strong Governance to Enable Safe Innovation

Governance often gets a bad rap as a bureaucratic hurdle, but effective governance is actually a powerful enabler of AI in recruiting. Good governance provides clear guidelines on what AI and Gen AI can and cannot be used for, empowering teams to innovate confidently while managing risks related to ethics, privacy, and security.

Key governance principles include:

• Preapproved use cases: Define activities where AI adoption is encouraged and does not require additional permissions.
• Prohibited activities: Clearly state what is off-limits, such as using AI to make legally sensitive decisions without human oversight.
• Permission-based use cases: Identify scenarios where approval is needed, specifying who grants permission and the criteria involved.

In recruiting, governance might address concerns like bias mitigation in AI-driven candidate screening, data privacy compliance when processing applicant information, and transparency in automated decision-making. Engaging legal and compliance teams early in the AI adoption process is crucial. Interestingly, Gartner’s research shows that organizations most successful at scaling AI involve legal from day one, turning them into allies rather than obstacles.

By embedding governance into the AI lifecycle, recruiting teams can accelerate deployment while maintaining organizational trust and adhering to regulatory requirements.

4. Make Your Data and Content AI Ready

Data readiness is a well-known prerequisite for AI success, but when scaling AI in recruiting, it’s important to recognize the nuances involved. AI-ready data is not a one-size-fits-all concept. Instead, it varies by use case, technology type, and organizational context.

For traditional AI in recruiting, you might focus on structured and semi-structured data such as candidate resumes, assessment scores, interview feedback, and historical hiring data. Ensuring this data is clean, accessible, and appropriately governed is critical.

When it comes to Gen AI, the emphasis shifts to content readiness. Gen AI models learn from large corpora of text, images, video, and other forms of content. Recruiting teams need to collaborate closely with knowledge management, document management, and information governance functions to curate and prepare this content effectively.

Key considerations for AI-ready data and content in recruiting include:

• Data quality and completeness
• Data accessibility and integration across systems
• Privacy and ethical considerations in candidate data usage
• Content relevance and freshness for Gen AI training

Rather than waiting for a perfect state of AI readiness—which may never come—take a pragmatic approach by defining readiness criteria specific to each recruiting use case. This approach accelerates progress and helps avoid the common trap of endless data preparation that stalls AI initiatives.

5. Segment Your Audience by Attitude to Drive Adoption

Scaling AI in recruiting is not just a technical challenge; it’s also a human one. Different people within your organization will have vastly different attitudes toward AI, which influences their willingness to adopt and champion these technologies.

Instead of segmenting your audience solely by function or skill level—such as HR professionals versus hiring managers—consider segmenting by attitude and emotional response to AI. Gartner’s research highlights an evolution in perceptions over time:

• From fascination to complexity: Early adopters viewed AI as fascinating and impressive.
• To complexity and threat: More recent attitudes often include fear or skepticism, with concerns about job security or loss of control.

In recruiting, you may encounter:

• Champions who see AI as a career accelerator and efficiency enabler.
• Skeptics who fear AI will replace human judgment or threaten jobs.
• Neutral parties who are indifferent or unsure about AI’s value.

Understanding these attitudes allows you to tailor your communication and training efforts. For example, address fears directly by emphasizing AI as a tool that augments rather than replaces recruiters. Showcase success stories that highlight AI’s role in freeing up time for strategic activities. Provide hands-on experiences to build confidence and demystify the technology.

By segmenting your audience by attitude, you can foster broader acceptance and accelerate AI adoption across the recruiting function and beyond.

Conclusion: Transforming Recruiting with Scalable AI

Scaling AI in recruiting is a complex but rewarding endeavor. By always considering AI as a strategic option, rigorously measuring and communicating impact, establishing robust governance, preparing your data and content thoughtfully, and engaging your audience based on their attitudes, you can unlock the true power of AI and Gen AI.

These five fixes not only help avoid common pitfalls but also enable recruiting leaders to drive meaningful business outcomes—improving hiring efficiency, enhancing candidate experiences, and supporting innovation.

As AI technologies continue to evolve, staying informed and agile will be key. Embrace these principles to build a resilient, scalable AI strategy that transforms your recruiting operations and positions your organization for sustained success in the era of intelligent talent acquisition.

Remember, AI in recruiting is not just about technology; it’s about empowering people and processes to work smarter and more effectively. Start small, think strategically, and scale with confidence.