Artificial intelligence (AI) is no longer a futuristic possibility; it is a mainstream force reshaping how companies recruit, develop and retain talent. A 2025 state-of-AI survey from McKinsey found that more than three-quarters of organizations use AI in at least one business function, and organizations redesigning workflows around AI see the biggest impact on earnings. Yet adoption brings new questions about ethics, culture and the role of human judgment.
Few thinkers articulate these questions as provocatively as Laith Saud, founder of HumanAfter and respected board advisor. Saud argues that AI should not be treated merely as a productivity tool; instead, it constitutes a new kind of relationship that mediates every interaction in the workplace. HR teams, he notes, will become interpreters of algorithmic decisions and guardians of organizational culture. In this article we synthesise Saud’s philosophy with research-backed guidance to answer a pressing question: Is your HR team ready for AI?
We will explore how AI is transforming human resources (HR), examine board-level perspectives on AI adoption, provide a readiness checklist inspired by Saud’s thought leadership, present a real-world case study and offer an outlook on the future of AI-driven work. The goal is to equip HR leaders and board advisors with a comprehensive framework for adopting AI ethically and strategically.
AI’s Impact on HR and Laith Saud’s Perspective
Saud’s writings on HumanAfter challenge conventional narratives that view AI primarily as a tool for efficiency. In his essay “AI as Relationship, Not Tool” he warns that framing AI as a productivity instrument diminishes HR’s strategic influence. Rather than automating relationships, he believes AI will mediate every relationship in the workplace, from recruiting and performance management to employee well-being. This mediation changes power dynamics—algorithmic outputs influence hiring decisions, performance evaluations and even workplace culture.
Saud contends that HR must move beyond compliance functions and become stewards of this new relational landscape. He writes that HR leaders who treat AI as just another tool risk reducing HR to a compliance office, while those who see AI as a relational mediator will shape the future of work. In another article, he emphasises that AI integration is a civilizational shift that reorganizes labour relations. He argues that HR must claim ownership of AI implementation; otherwise, departments such as legal or operations might define AI parameters narrowly. The consequence is a risk that HR becomes reactive rather than strategic.
Saud’s perspective resonates with the growing sentiment among boards and executives. The 2025 McKinsey survey shows that organizations reporting the largest earnings impact from AI have redesigned at least one function’s workflows. When AI reconfigures work, someone must interpret how algorithmic systems interact with people. Saud argues that HR executives—especially those with board advisory responsibilities—are ideally positioned to translate the human implications of AI into boardroom language.
The Strategic Role of HR in AI Adoption
The integration of AI into HR is not just about adopting new software; it is about changing culture, governance, technology, competencies and goals. An extensive AIHR (Academy to Innovate HR) article summarises best practices for AI readiness. It notes that 71 % of organizations using AI in at least one business function report increased revenue and predicts that half of today’s work activities could be automated. AI is a game-changer, yet its deployment requires careful planning. AIHR outlines a five-pillar framework:
Culture – Encourage employees to view AI as a supportive partner. A culture of learning and experimentation helps employees trust AI systems and contributes to fair, data-driven decisions.
Governance – Establish clear policies, accountability structures and risk reviews. This means aligning AI strategy with ethical principles and legal standards while maintaining transparency.
Technology – Choose AI tools that solve real HR problems and integrate smoothly with existing systems. The technology should enhance the HR function rather than replace human judgment.
Competencies – Develop new skills within the HR team, such as data literacy, prompt design for generative AI and the ability to interpret algorithmic outputs.
Goals – Set clear, measurable targets aligned with business objectives and human-centric outcomes.
AIHR also identifies emerging technologies that will reshape HR. Agentic AI—autonomous agents that can manage entire HR workflows—already helps companies reduce staff attrition by 10 %. Conversational AI chatbots, such as the one used by Walmart, answer millions of worker queries and cut shift-planning time from 90 minutes to 30. AI voice technology analyses candidate tone and speech patterns to enhance interviews. These examples illustrate how AI can improve efficiency while still requiring human oversight.
HR’s role is to ensure that these technologies enhance human judgment rather than replace it. A Grant Thornton report cautions that AI can lead to job displacement, bias and ethical concerns if mismanaged. It urges HR leaders to embed fairness, inclusion and human-centricity throughout AI transformations. The EU’s AI Act, for instance, requires human oversight of high-risk AI systems, transparency about automated decisions and accountability for data practices. Grant Thornton suggests that HR should redefine entry-level roles, upskill employees for AI collaboration, conduct AI-readiness audits and lead with empathy.
Board-Level Perspectives and Why HR Matters
Board oversight of AI is becoming a critical governance issue. PwC’s 2025 guidance emphasizes that boards must take an active role in AI strategy. It stresses that the full board should oversee the company’s AI transformation because of its strategic and risk implications. Boards should align with management on a formal AI adoption plan, ensure the strategy drives value creation and require responsible AI practices. PwC lists six areas where boards can provide effective oversight, including developing a clear oversight approach, aligning on strategy and ensuring talent and culture considerations are prioritized. The guidance notes that 32 % of global CEOs report generative AI has increased revenue and 34 % report increased profits.
KPMG’s 2025 Board Leadership Center survey echoes these priorities. In interviews with nearly 100 US directors, KPMG found that boards see productivity and cost savings as the top benefits of generative AI, yet many companies are still scaling their AI initiatives. Directors identify talent and culture, data quality, security and compliance as major hurdles. They also note that adoption of recognized AI governance frameworks is lagging and that boards need stronger tech and AI expertise. These findings reinforce Saud’s argument: HR leaders who can interpret AI’s human implications will be invaluable in boardrooms.
Laith Saud’s AI Readiness Checklist for HR Leaders
Drawing on Saud’s philosophy and research from AIHR, PwC, Grant Thornton and KPMG, the following checklist helps HR leaders and board advisors evaluate their AI readiness.
- Embrace AI as a Relationship
Shift the mindset: Recognize AI as a mediator of relationships rather than a mere tool. Encourage teams to understand how algorithms influence hiring, performance reviews and employee engagement.
Guard culture: HR remains the guardian of organizational culture. When algorithms make recommendations, HR must interpret them in a way that aligns with core values.
- Claim Ownership and Define Purpose
Lead, don’t follow: AI integration is a civilizational shift. HR must claim ownership of AI strategies to prevent other departments from narrowly defining AI’s role.
Purpose over compliance: Frame AI adoption around human-centric goals—improving fairness, inclusion and well-being—not just compliance and efficiency. Link AI initiatives to the company’s mission and values.
- Cultivate a Learning Culture
Promote AI literacy: Provide training on data literacy, algorithmic bias and the basics of machine learning so HR professionals can engage effectively with AI tools.
Encourage experimentation: Foster a culture that views AI as a supportive partner and rewards experimentation.
- Build Robust Governance and Ethics
Establish a governance framework: Set up clear policies for data privacy, transparency, accountability and risk management. Ensure these policies reflect regulatory requirements like the EU’s AI Act.
Ensure human oversight: Maintain human “catchers” in the loop, especially in high-impact decisions such as hiring, promotions and terminations.
Audit regularly: Conduct AI-readiness audits to identify biases, check data quality and evaluate model performance.
- Integrate Technology Strategically
Solve specific HR problems: Adopt AI tools only when they address clear pain points—e.g., reducing attrition, improving candidate experience or enhancing training.
Leverage emerging tech: Explore agentic AI for workflow automation and conversational AI chatbots to handle employee queries. Understand limitations and ensure these tools complement human capabilities.
- Develop New Competencies
Data and analytical skills: HR professionals need to interpret algorithmic outputs and make data-driven decisions.
Prompt engineering: As generative AI becomes mainstream, HR teams must learn how to design effective prompts and assess AI-generated content.
Emotional intelligence: Even with AI, HR will remain the human heartbeat of the organization. Empathy, ethical judgment and communication skills will differentiate leaders.
- Align with Business and Board
Set measurable goals: Define metrics that capture both business outcomes (e.g., time-to-hire, turnover rates) and human outcomes (e.g., employee satisfaction, diversity).
Engage with the board: Provide boards with insights about AI adoption and cultural impacts. HR leaders should be prepared to answer these questions.
Monitor and report: Establish regular reporting on AI initiatives. Boards need metrics to evaluate success and prevent AI projects from becoming “black holes.”
Case Study: Unilever’s AI-Driven Recruitment
An example of successful AI adoption in HR comes from consumer-goods giant Unilever. The company implemented an AI system that analyses video interviews using facial expression, body language and word choice to predict job success. According to an industry case study, the system generated over £1 million in annual savings, saved more than 100,000 hours of recruiter time, processed 2 million applications and improved diversity by enabling objective, data-driven assessments. These gains underscore AI’s potential to transform recruitment, but they also highlight the need for careful oversight.
Unilever’s success reflects several checklist elements: the company used technology to solve a specific pain point (screening a large number of candidates), trained its recruiters to interpret AI results and monitored outcomes to ensure diversity improvements. The case also demonstrates the importance of human-AI collaboration—recruiters still made final decisions, and HR monitored how the system impacted fairness and culture.
Ethical Considerations and Human-Centric HR
AI systems can inadvertently replicate or amplify biases present in historical data. Grant Thornton warns that early-career roles may be most at risk of replacement and that HR must balance productivity gains with ethical concerns. Among its recommendations, Grant Thornton emphasises:
- Human oversight: Ensure that humans remain involved in decision-making processes, especially where algorithms impact people’s livelihoods.
- Transparency and inclusion: Communicate clearly with employees about AI use, obtain consent where necessary and involve diverse teams in AI design to reduce bias.
- Upskilling and empathy: Redefine entry-level roles to focus on uniquely human skills like creativity and emotional intelligence. Provide training to help employees adapt to AI collaboration.
The Pew Research Center’s Digital Life 2035 report highlights that experts anticipate AI improving sectors like healthcare and education but also warn about risks such as misinformation, surveillance, unemployment and mental health issues. These broader societal concerns reinforce the need for HR and boards to adopt responsible AI practices that protect employee well-being and data privacy.
Future Outlook: AI and HR Integration Trends
Looking ahead to 2030 and beyond, several trends are evident:
- Mainstream adoption across all HR functions – AIHR predicts that 80 % of organizations will use AI for workforce planning by 2025. Tools will extend beyond recruitment and training to performance management, compensation and benefits.
- Rise of agentic AI – Autonomous agents capable of completing entire workflows will reduce repetitive tasks and enable HR professionals to focus on strategic initiatives.
- Conversational interfaces as the norm – Chatbots and voice assistants will handle routine queries and provide personalized employee support.
- Growing board engagement – Surveys indicate a shift from experimentation to scaling. Boards will demand clear metrics on AI’s impact and will expect HR leaders to interpret the human side of AI adoption.
- Human-AI symbiosis – As repetitive tasks are automated, demand for adaptability, creativity and emotional intelligence will increase. HR will play a crucial role in developing these capabilities and ensuring a supportive culture.
Ultimately, AI will not replace HR—it will augment it. Saud’s vision of AI as a relational mediator means that the future of work will be negotiated between humans and intelligent systems. HR leaders who are fluent in both human dynamics and algorithmic systems will be indispensable.
Conclusion
AI’s rapid march into HR presents both extraordinary opportunities and profound challenges. Laith Saud urges us to view AI as a relationship that mediates every workplace interaction, not merely a tool. He warns that HR departments risk becoming compliance offices unless they claim ownership of AI integration. Research confirms that organizations reap the greatest benefits when AI is deployed strategically, with redesigned workflows and strong governance.
HR leaders and board advisors should use Saud’s checklist to gauge their readiness: embrace AI as relational, claim ownership, cultivate learning, build ethical governance, integrate technology strategically, develop new competencies and align with business and board objectives. Case studies like Unilever illustrate how AI can deliver remarkable efficiency and diversity improvements when implemented thoughtfully.
The journey toward AI-driven HR is just beginning. As agentic AI, conversational interfaces and other emerging technologies mature, HR will increasingly serve as the bridge between algorithms and the people they affect. Those who heed Saud’s call—to become interpreters of tomorrow’s workforce and stewards of culture—will help their organizations thrive in an AI-augmented world.