How AI in Recruiting and Architecture Are Changing Everything in HR Technology

Artificial Intelligence (AI) is reshaping the landscape of business and technology faster than ever before. As someone deeply immersed in HR technology and talent management, I want to share some insights on where AI is headed as an architecture, why it’s fundamentally different from previous technological waves, and what this means for HR professionals, recruiting, and enterprise systems. This article aims to give you a clear perspective on how AI in recruiting and other HR functions is not just an incremental improvement but a quantum leap in how we build, interact with, and leverage technology.

Over the past few decades, the cloud revolutionized computing and business applications. But AI is poised to disrupt and transform those paradigms in ways that will redefine our enterprise systems, talent acquisition strategies, and learning and development methodologies. I will also introduce you to the next generation of AI-powered tools, including an exciting new release called GALILEO for managers, which integrates AI deeply into leadership support and HR workflows.

The Cloud Era: The Foundation of Modern Enterprise Systems

To understand AI’s revolutionary impact, we need to briefly revisit the cloud era, which shaped most of our careers and enterprise software today. Starting in the early 1990s and accelerating through the 2000s, companies moved their software applications and data systems from on-premise servers to centralized cloud data centers.

This shift enabled rapid deployment of corporate applications like SAP, Oracle, Workday, and Salesforce without the cumbersome process of licensing software on physical media like CD-ROMs and installing them locally. Cloud infrastructure empowered vendors and businesses to build scalable, multi-tenant applications accessible via the internet. Companies began stitching these applications together using collaboration tools like Microsoft Teams and building user-friendly interfaces such as websites and mobile apps.

The cloud became the fundamental platform of the last two decades. Cloud vendors grew rapidly, becoming the darlings of the tech world, attracting significant investment, and dominating enterprise IT.

Why AI Is Different: The Dawn of a New Architecture

AI emerged in a major way just two and a half to three years ago and has introduced three critical differences compared to the cloud paradigm:

1. Natural Language Interfaces: Unlike traditional applications that require carefully designed user interfaces, AI systems allow users to interact naturally through conversation. You can chat with AI, describe your needs, and it understands and interprets your requests, saving enormous effort in user experience and interface design. In many ways, AI personifies the computer, making it more intuitive and accessible.
2. Data-Rich, Multimodal Capabilities: AI systems are fed with massive datasets, enabling them to answer complex questions, integrate data from multiple sources, and generate outputs in various forms—text, code, graphics, audio, and video—capabilities we never had before.
3. Decentralized Processing with Specialized Chips: Unlike cloud systems that require centralized, massive data centers, AI is powered by highly specialized chips that can be deployed anywhere—on your phone, PC, smart glasses, or even clothing. This decentralization opens new possibilities for embedding AI directly into everyday devices and environments.

These architectural shifts mean that the traditional cloud-based software models face significant disruption. Enterprise vendors like SAP, Oracle, Workday, Salesforce, and Adobe recognized this early and began embedding AI models into their platforms to enhance their offerings. For example, Workday offers AI-powered tools that can generate job descriptions or assist with performance reviews, and LinkedIn has its recruiter assistant to streamline hiring processes.

AI Agents Versus Traditional Applications: A Paradigm Shift

While incumbents rushed to add AI features to their existing cloud applications, entrepreneurs and innovators saw a different opportunity: to think of AI not as just an application but as an agent. Unlike traditional software applications with fixed workflows and interfaces, AI agents can:

• Respond dynamically to user inputs.
• Manipulate other systems and data sources autonomously.
• Act as orchestrators or "masters" that command legacy cloud systems as "slaves."

This agent-based architecture is powered by new protocols like the Model of Context Protocol (MCC), which allows AI agents to send messages and transactions to other systems seamlessly. Imagine telling an AI agent, “Book me a flight to New York next week, leaving before 7 AM, arriving before 3:30 PM, aisle seat, and within my budget,” and the agent manages the entire booking process end-to-end without you having to click through multiple websites.

This approach is not limited to travel—it extends to customer service, product ordering, employee support, recruiting, and learning systems. Recruiting tools like Paradox, Mach E, Eightfold, and Phenom are already leveraging AI agents to compress complex multi-step recruiting workflows into single intelligent agents, something impossible to do efficiently with traditional cloud apps.

Implications for Legacy HR and CRM Systems

Many AI vendors now regard large HR and CRM platforms as essentially “dumb databases.” While these systems have embedded rich application logic and business processes, their architecture is seen as legacy and limiting in the new AI-driven world.

Stock valuations of traditional enterprise software companies have plateaued compared to the soaring growth of leading AI companies, often called the “Magnificent Seven.” There is a growing consensus that the next generation of enterprise software—whether a new Workday, SAP, Cornerstone, or Salesforce—will emerge from AI-native companies that embrace these new architectures.

However, history teaches us that predicting winners in technology disruption is difficult. Success depends not only on technology but also on market understanding, sales and marketing prowess, investor backing, and a bit of luck.

What This Means for HR and Tech Professionals

The rise of AI as an architectural force carries several critical takeaways for HR and technology professionals:

1. Don’t Rely Solely on Incumbent Vendors

Your current enterprise software providers will try to adapt and integrate AI, but don’t assume they will be the sole solution providers in the future. New entrants, especially Microsoft with its massive ecosystem and AI tools, are emerging as powerful players offering alternatives that can connect broadly across platforms and systems.

2. You Are Now an Application Builder

Perhaps the most exciting aspect of this revolution is that you, as an HR or tech professional, can build complex applications without traditional coding. By crafting detailed prompts in natural language, you can leverage large language models (LLMs) like GALILEO to create sophisticated workflows, learning experiences, and management tools.

For instance, in GALILEO Learn, you can upload content, build instructional templates, and generate courses or podcasts tailored to your needs. These prompts serve as reusable “code” that others can use, adapt, and share, unleashing a creator economy within your organization.

This shift means you no longer have to wait for vendors or IT departments to deliver solutions. Instead, you can rapidly prototype, iterate, and deploy applications that solve real business problems.

3. AI Will Become Ubiquitous Across All Roles

Within a year or two, every employee, from white-collar workers to retail staff, will have their own AI-powered assistant or LLM embedded in their devices—whether on computers, store kiosks, cash registers, or phones.

This ubiquity means AI systems will operate both locally and remotely, mixing corporate-wide data with localized context. For example, a manufacturing plant might receive a corporate safety policy but adapt it locally due to specific circumstances like a water shortage or emergency closure. Local managers will be empowered to tweak and customize AI-driven interfaces and workflows to fit their unique environment.

The Return of Client-Server Architecture, Reimagined

This interplay of centralized corporate data and decentralized local processing resembles a new form of the client-server architecture from the PC era, but far more flexible and programmable. It enables:

• Scalable systems that can be localized by region, department, or function.
• Personalized training, leadership development, and knowledge management.
• Real-time adaptation to changing conditions and regulations.

We are currently in the midst of extensive architectural research in this area, and I will be sharing a comprehensive survey soon. The implications for vendor disruption, reinvention, and innovation are huge.

GALILEO for Managers: AI-Powered Leadership Enablement

One of the most exciting developments I want to share is the upcoming release of GALILEO for Managers, coming out in the next few weeks. GALILEO is a widely adopted HR tool with hundreds of use cases and a vast repository of HR data and best practices.

The new manager-focused version embeds this data into an intelligent experience designed to support managers in real-time scenarios, such as:

• Having difficult conversations with employees
• Managing underperformance
• Conducting hiring and pay decisions
• Running effective team meetings
• Building development plans
• Understanding and growing their own skills

With over 500 case studies and leadership models from trusted organizations like SHL and Heidrick & Struggles integrated, this tool acts as a management coach and training system directly on managers’ desktops.

This tool can be paired with GALILEO Learn, an AI-powered native content platform, to create a two-tier architecture that delivers personalized learning and support at scale. Managers and employees can access tailored content, corporate policies, and hiring practices integrated with their existing applicant tracking systems (ATS).

What used to be a centralized, one-size-fits-all leadership development function can now be localized and personalized by region, store, or function, empowering employees with training and enablement exactly where and when they need it.

Broader Applications Across the Organization

This AI architecture is not limited to managers or HR. It extends to every role within a company:

• Salespeople can get AI-driven coaching and customer insights.
• Manufacturing workers can receive real-time safety and compliance guidance.
• Truck drivers and retail workers can have AI assistants embedded in their devices to improve efficiency and support.

Every company struggles with balancing central corporate controls and local adaptations—this new AI architecture provides a scalable, programmable way to solve that problem.

Getting Started with AI in Recruiting and HR: Practical Steps

For HR professionals and tech leaders eager to embrace this AI revolution, here are some practical recommendations:

1. Explore and Experiment with AI Tools: Get familiar with platforms like GALILEO and GALILEO Learn, which provide both consumption and creator environments for learning and HR workflows.
2. Build Your Own Prompts and Applications: Start developing repeatable prompts that automate complex HR processes like recruiting, performance management, and leadership development.
3. Encourage Collaboration and Sharing: Share your AI-driven solutions and prompts with colleagues to foster innovation and efficiency across your organization.
4. Stay Informed on Emerging Architectures: Keep an eye on new AI protocols like the Model of Context Protocol (MCC) and how AI agents are evolving.
5. Prepare for Localized AI Deployments: Work with your teams to identify where local adaptations are needed and empower local managers to customize AI tools responsibly.

By adopting this mindset, you can harness AI not just as a tool for answering questions but as a platform for creating powerful applications that transform your HR and recruiting functions.

Case Study: IATA’s Use of AI for Airline Industry Skills Modeling

A striking example of AI’s transformative power comes from the International Air Transport Association (IATA), which used GALILEO to analyze comprehensive data from Boeing, Airbus, and other sources to build a new skills model for the airline industry.

This model maps every role’s current and future skills requirements, growth rates, and geographic variations. IATA produced a detailed report and, more importantly, could share the underlying AI prompts with airline HR executives to localize and adapt the model to their own organizations.

Attempting to code such a model manually would take years and be nearly impossible to maintain or use effectively. AI enabled a rapid, flexible, and scalable solution that can evolve alongside the industry’s needs.

The Future of Learning and Development: From L&D to Enablement

AI is poised to redefine learning and development (L&D) into a broader concept I call enablement. Enablement goes beyond traditional training to encompass real-time support, coaching, knowledge management, and personalized development delivered through AI-powered platforms.

Our work with clients focuses on building these enablement applications, particularly in leadership and supervisory support. GALILEO and GALILEO Learn are at the forefront of this shift, providing AI-driven content creation and management tools that accelerate learning and application.

Conclusion: Embrace the AI Creator Economy in HR

The AI revolution is not just about new applications or automation; it’s about a fundamental architectural shift that empowers every HR professional and employee to become a creator, builder, and innovator. The cloud built the foundation for scalable enterprise applications, but AI is enabling decentralized, conversational, and highly adaptable systems that change how we work, learn, and lead.

For those involved in recruiting, AI in recruiting is already compressing complex workflows into intelligent agents, simplifying hiring processes, and improving candidate experiences. As AI technologies mature, these capabilities will expand across all HR functions and employee roles.

New platforms like GALILEO for Managers and GALILEO Learn demonstrate how AI can be embedded deeply into HR workflows, delivering personalized leadership support and learning experiences at scale. This two-tier architecture—combining centralized corporate data with localized AI-driven customization—is a game-changer for organizations navigating the balance between global consistency and local relevance.

As you explore AI’s potential, remember that you don’t need to be a coder or a data scientist to build powerful solutions. Learning to craft effective prompts and leveraging AI platforms can unleash your creativity and problem-solving capabilities, putting the power of AI directly into your hands.

The future of HR technology is bright, dynamic, and full of opportunity. Embrace the AI creator economy, experiment boldly, and prepare for a decade of transformation that will change everything we know about work, learning, and leadership.