AI Staff Augmentation

As AI becomes increasingly integrated into the workplace, it is up to talent development, organization design, and L&D leaders to partner closely with the business and each other to identify the specialist roles and skills necessary for success.

As we contemplate AI and the future of work, what might these specialist AI roles and skills look like?

I asked John Cleave to share his insights with us. As SweetRush’s Senior Learning Engineer, John has been working with AI in L&D for decades, beginning with his graduate work in symbolic AI at the Northwestern’s Institute for the Learning Sciences. Here’s his take on the roles and skills leaders should consider as they partner with the business to develop an enterprise-wide strategy.

Bonus content!
As a bonus, John also shares the roles and skills that L&D teams should consider developing or adding to enable, enhance, and accelerate the implementation of the AI strategy.

What are the Specialist AI Roles and Skills Leaders Should Consider?

AI Strategy and Governance Roles

AI initiatives require careful oversight and a strong ethical framework. The following roles are crucial for any organization implementing AI, regardless of specific applications:

Governance and Regulation Specialist: Formulates and revises AI policies and practices, devises management protocols, develops and institutes controls, and advises on potential risks. This role ensures responsible AI usage across the organization.
Security and Policies Specialist: Creates security protocols (e.g., approval process), identifies potential risks, handles breaches and violations, and provides leadership with knowledge of consequences, safeguarding both data and ethical practices.
AI Generalist with HR Focus: Identifies applications of AI in HR (talent acquisition, employee development, etc.), works to integrate AI into HR practice, and stays abreast of emerging trends, ensuring alignment between AI and HR goals.

AI Data Analysis

Data analysis and model training are fundamental to any successful AI implementation. The following roles are essential for extracting meaningful insights and driving data-informed decisions:

Business (Statistical and Data Visualization) Analyst: Applies AI methodologies to evaluate data in order to gain insight into the business, visualizes data, identifies data sources, and generates data via AI. This role makes the connection between data and actionable business intelligence.
Data Analytics Expert (backend collection, reporting): Creates data handling and analysis protocols, constructs data lakes, and applies statistical analysis to operations, ensuring data integrity and efficient data management.
Machine Learning and Big Data Manager: Devises machine learning models, collects/cleanses data, evaluates results (statistically, against business norms, etc.), detects patterns, and spots new opportunities to apply AI, driving innovation through data-driven insights.

AI Construction

Building and implementing AI solutions requires specialized technical expertise. The following roles are crucial for developing and deploying AI tools and systems:

Machine Learning Engineer: Constructs machine learning models, trains and evaluates models, selects algorithms appropriate for solving business problems, and works with data analysts to refine and distill data, enabling the creation of powerful AI applications.
Natural Language Processing (NLP) Specialist: Uses NLP engines (e.g., Siri) to process NLP inputs, connects inputs to actions, and creates inputs and outputs, facilitating human-computer interaction and automating language-based tasks.
Large Language Model (LLM) Expert: Sets up an LLM for a purpose(s), creates retrieval-augmented generations (RAGs), tests outputs, manages costs, and creates application programming interfaces (APIs) and overlays, harnessing the power of LLMs for advanced language-based applications.
AI Tools Implementor: Advises an organization on tools (ChatGPT, Exemplary AI, Dall-E, Claude, Paragraph Generator, Midjourney, Writesonic, Canva, Grammarly, Podcastle, Synthesia) useful for solving business problems, conducts experiments and R&D, evaluates options, addresses challenges, and trains on tools, facilitating the effective adoption of AI tools across the organization.

AI & L&D: Specialist Skills and Roles for AI-Powered Learning Creation

This section focuses specifically on roles that leverage AI to enhance learning experiences and drive L&D innovation.

Instructional Design/Learning Experience Creator: Uses AI to support and enhance learning, incorporates AI into LX, provides guidance on best practices and techniques, and uses AI to generate content for training, creating more engaging and effective learning experiences.
HR/L&D Strategy and Change-Management Consultant: Provides guidance in the use of AI to bring about organizational improvement and transformation, explores use of AI to automate processes and create efficiencies, and guides the organization through the changes associated with AI adoption.
RAG Creator: Applies symbolic AI to guide and focus LLMs and deep learning (e.g., skills definition) and pairs symbolic AI and deep learning to improve AI efficacy, enabling more accurate and contextually relevant learning experiences.
Reinforcement Learning/Advanced AI Developer: Creates, evaluates, and trains AI-infused devices, constructs and shapes environments, shapes and manipulates AI models, and experiments with advanced AI techniques to create adaptive and personalized learning environments.
Expert AI Tool User: Steps in and uses AI tools (ChatGPT, Dall-E, Claude, etc.) in order to bring about organization improvement (e.g., generates content), provides guidance on best tools (evaluates alternatives), and maximizes the value of AI tools for L&D.
Asset Creators: Creates videos, audio, and/or animations using AI-based tools, streamlining the production of multimedia learning assets.

As AI continues to reshape the workplace, talent, OD, and L&D teams must work together to identify the skills and expertise needed to help organizations meet their goals for the future. Understanding the roles outlined here is a crucial first step!

Need Help Building YOUR Workplace of the Future?

As an award-winning custom learning solution provider with more than two decades of experience in digital and immersive learning technologies and over a decade of experience sourcing temporary talent for L&D, SweetRush is uniquely positioned to help you navigate this new landscape. We provide comprehensive support in the following ways:

AI Strategy and Implementation: SweetRush’s AI strategy and consulting services empower your organization to navigate the complexities of AI adoption, offering not only cutting-edge learning experiences and programs, but also holistic roadmapping, foundational assets, and ongoing support to ensure your AI initiatives are human-centered, future-proofed, and drive lasting value.

AI Training: We create custom training programs to upskill your workforce quickly and comprehensively.

AI Talent Sourcing: We can source and place the ideal candidates for the AI roles you need, whether for temporary staffing or permanent positions. We have access to a deep bench of AI experts across diverse fields who can support your needs.

AI has reshaped how we approach recruitment. But to use this technology wisely, we must pair its capabilities with the uniquely human qualities that make recruitment personal and impactful.

In this article, I share my experience and advice for leveraging AI in a way that helps to maintain and elevate the human experience.

AI: A New Chapter in Talent Acquisition

AI is revolutionizing recruitment. From automating job postings to pre-screening résumés, AI is eliminating time-consuming tasks, freeing up recruiters to focus on building relationships.

However, as powerful as AI is, it should not overshadow the human aspects of hiring. Instead, it should complement them, serving as a tool to streamline processes while amplifying empathy and connection and validating intuition.

Hung Lee captures this balance perfectly in his talent acquisition forecasts for 2025: “Our attention will be reserved for a) known callers and b) conspicuously human. Recruiters who have network, community standing and profile—and are obviously human—will win in a world dominated by AI composed information.”

This insight highlights a critical truth: In a landscape increasingly influenced by AI, human authenticity remains a competitive advantage.

Human-Centered Recruitment in the Age of AI

While AI can analyze vast amounts of data and match skills to job requirements with remarkable precision, it cannot replicate the nuanced judgment and relational expertise of a skilled recruiter. People connect with people. As Lee suggests, the recruiters who thrive in an AI-dominated world will be those who bring visible humanity, trusted networks, and community influence to the table. Recruiters must now do more than just fill roles; they need to cultivate meaningful relationships and establish themselves as trusted advisors within their industries.

Candidates are more likely to respond to someone who is “conspicuously human” than to an automated outreach, no matter how well-tailored it might be.

AI and Recruitment Strategy: Prioritizing Skills and Potential

One of AI’s most transformative impacts on recruitment is the shift away from traditional credentials. The résumé, long the gold standard of hiring, is losing relevance in an era where AI can assess candidates based on skills, experiences, and even potential. By focusing on capabilities rather than titles, AI helps recruiters identify talent that might have otherwise been overlooked.

This evolution encourages a more inclusive hiring approach, opening the door to candidates from diverse backgrounds and non-linear career paths. With the support of AI, we can prioritize potential over pedigree, building teams that are innovative and adaptable.

Recruiting with AI: An Ally for Human Recruiters

The integration of AI into recruitment is not about replacing humans but empowering them. This requires intentionality. Organizations must continuously evaluate AI tools to ensure they promote fairness, eliminate bias, and respect candidates’ individuality. Similarly, recruiters must be trained to interpret AI-generated insights critically and thoughtfully.

To succeed, recruiters must embrace a dual role: leveraging AI to manage the technical aspects of talent acquisition while doubling down on the human elements—relationship building, empathy, and authenticity—that no machine can replicate (at least not yet).

The Future of Staff Augmentation: AI and Human Collaboration

By combining AI’s efficiency with human creativity and connection, we can move beyond the outdated mindset of a “war for talent.” The recruiters who excel in this new era will be those who embody Lee’s vision—professionals with genuine networks, a strong sense of community, and the unmistakable presence of humanity.

AI has the potential to enhance recruitment in profound ways, but its success depends on how we wield it. Together, we can use AI not as a weapon of war, but as a tool for collaboration, creating a hiring process that is more inclusive, efficient, and human-centric. The war for talent is over. Now, let’s build the future.

Rodrigo Salazar-Kawer is the Director of Talent Solutions at SweetRush, where he and his team work with clients to help them find high-performing talent and augment their teams in L&D, a people-centric field that impacts all lines of business within the enterprise. Connect with Rodrigo.

Tag: AI Staff Augmentation

AI and the Future of Work: A Leader’s Guide to Roles and Skills