The Imperative of Work Design in the Age of AI: The Organisational Muscle needed for Continuous Adaptation

In 2025 and beyond, organisations will face unprecedented waves of AI-driven transformation. To navigate this shifting landscape successfully, businesses and leaders must develop robust work design and task intelligence capabilities. These will be crucial for effective AI adoption, workforce strategy, and skills-based talent management in a rapidly evolving world.

The Evolving Relationship Between AI and Work

AI is quickly moving from theory to practice in the workplace. Organisations are exploring various ways for humans and AI to collaborate, with different workforce combinations and division of labour between humans and technology. Research shows that some combinations lead to greater trust and role clarity when AI acts as a colleague. However, human distrust in AI often stems from how the work is structured and designed rather than from AI itself.

This reality calls for a strategic approach to work design. Many organisations are overlooking the impact of AI on human workers’ needs, skills, and job identity during change and implementation. Yet, focusing on these human factors can unlock performance and better outcomes for both individuals and organisations.

Reimagining Work as a Product: A Superior Approach

A transformative approach to work (re)design is emerging—one that views work as a product and employees as customers. Dart Lindsley, a leading advocate of work experience design, argues that work exists in a multi-sided market where employees are a second set of customers whose needs must be addressed through intentional design of meaningful work experiences.

This approach asks, “What do employees hire their jobs to do for them?” Dart’s research reveals that employee needs go beyond income, purpose, and belonging. Some seek interesting puzzles, tools to build with, or opportunities to make an impact. Others look for structure, social connections, or ways to escape challenging personal circumstances.

Dart recently shared a useful metaphor with me: companies need to be like double-sided tape—sticky on both sides, appealing to both traditional customers as well as employees. This human-centric approach will provide a crucial complement to data-driven work analysis and task/skills intelligence.

Many progressive companies are already applying product design principles to work:

• At Asana, managers discuss the “leadership product” they deliver to employees
• At Eli Lilly, teams map employee journeys using customer experience tools
• At Shopify, the Flex Comp program lets employees choose their preferred compensation mix

Balancing Data-Driven and Human-Centric Approaches

While data-driven work analysis is crucial, it’s equally important to balance this with a human-centric approach. Organisations need to consider both quantitative metrics and qualitative human experiences as they redesign future work and work structures.

Data-driven approaches offer valuable insights into capacity, productivity, efficiency, and skill requirements. They can help identify areas where AI can augment (or replace) human capabilities and streamline processes. However, relying solely on data risks overlooking the nuanced human experience of work.

Human-centric approaches, like Dart Lindsley’s work experience design, focus on understanding employees’ motivations, needs, and preferences. This perspective will ensure that job and work redesigns not only meet organisational goals but also create meaningful and engaging experiences for workers.

By combining these approaches, organisations can:

• Optimise processes and workforce while maintaining employee satisfaction
• Identify opportunities for AI integration that enhance rather than just replace human roles
• Create work design that balances efficiency with human meaning and purpose
• Develop more holistic skills intelligence that considers both technical and human-centric skills

This balanced approach is essential for creating work environments where both humans and AI can thrive, leading to better outcomes for the organisation and its employees.

The Continuous Cycle of Adaptation

Organisations face a continuous cycle of:

1. New technology emergence
2. Work analysis to understand impacts
3. Work redesign to optimise human-AI collaboration
4. Skills intelligence development based on human tasks and activities
5. Workforce strategy adjustment

This cycle will accelerate over the next five years as AI capabilities evolve. Assessment of human-AI systems must provide convincing evidence that the new work processes are easy to understand and adopt, and that AI technology is both user-friendly and effective in improving work outcomes.

Building Work Design Capabilities: Where to Start

To develop robust work design capabilities, organisations should:

1. Establish a Work Analysis Framework o Implement a consistent methodology for analysing work across the organisation o Use tools to measure work characteristics, job identity, and perception of AI technologies o Regularly assess tasks suitable for automation or augmentation o Create processes for redesigning roles based on work analysis
2. Empower Middle Management
   • Provide training in AI capabilities and work design principles
   • Give managers autonomy to adapt AI implementation to their team’s needs o Encourage managers to act as coaches, connectors, and strategists in the context of technological change
   • Create feedback loops between middle management and C-suite for insights on AI adoption
3. Create Human-AI Collaboration Prototypes o Develop various models of human-AI collaboration within your organisation o Test different divisions of labour between humans and AI
   • Assess the impact of each model on trust, role clarity, and workforce productivity
   • Iterate and refine based on feedback and performance metrics
4. Apply Product Design Principles to Work o Conduct qualitative research to uncover employee motivations and preferences o Use customer experience tools to map employee journeys o Implement regular feedback mechanisms to assess job satisfaction
   • Design work experiences that balance organisational needs with employee preferences

Implications for Talent Management

The continuous redesign of work has profound implications for talent management practices.

Organisations must:

• Develop robust skills intelligence capabilities o Implement AI-powered skills assessment tools
  • Create a dynamic skills taxonomy that evolves with technological changes o Use predictive analytics to forecast future skill needs
• Create flexible career pathways based on skills o Design role-agnostic career pathing models
  • Implement internal talent marketplaces to match skills with opportunities o Encourage cross-functional moves to build diverse skill sets
• Implement continuous learning systems o Develop personalised learning recommendations based on skills gaps and aspirations o Create micro-learning opportunities integrated into daily work o Foster a culture of continuous upskilling and reskilling
• Adopt agile workforce planning methodologies o Use scenario planning to prepare for multiple possible futures
  • Implement regular workforce strategy reviews aligned with technology adoption o Develop flexible workforce models that combine full-time employees, gig workers, and AI
• Design work experiences that unlock human potential o Apply the “jobs to be done” theory to understand employee needs o Create opportunities for meaningful work that leverages uniquely human skills
  • Balance efficiency gains from AI with opportunities for human creativity and problem-solving

Conclusion: The Path Forward

The waves of AI advancement demand a proactive approach to work design and analysis. Organisations that build this muscle will be positioned to:

• Make strategic decisions about AI adoption
• Continuously redesign work to optimise human-AI collaboration
• Develop skills intelligence that informs talent strategy
• Create competitive advantage through superior work design and enhanced talent attraction
• Deliver meaningful work experiences that engage employees as valued customers

Leaders must champion the development of work design capabilities now to navigate the transformative impact of AI successfully. By focusing on the human element of technological change and systematically redesigning work, organisations can harness AI’s potential while creating more fulfilling, productive roles for their workforce.

The future belongs to organisations that not only adopt advanced technologies but also systematically analyse and redesign work to leverage both human talent and artificial intelligence effectively. By treating employees as customers and understanding their needs and preferences, companies can create a “double-sided tape” effect, sticking both traditional customers and employees to the organisation through meaningful experiences and superior products.

By Gareth Flynn, Chief Executive Officer at TQ Solutions