As artificial intelligence and automation tools become more sophisticated, organisations need to consider not only which tasks can be automated, but also how this automation will affect the structure of entire departments. Restructuring based on automation potential allows companies to create leaner, more adaptable teams with clearer models for how humans and AI can work together effectively.
The narrative for the last couple of years has been “AI is not about replacing people, it is about augmenting people”. This sentiment avoids the indisputable fact that there are tasks that can be automated, or can be completed by agentic capabilities that are available today, and that there are roles where people do these tasks. Of course, AI won’t take jobs, but businesses will make decisions on the productive capability of AI for these tasks, and the redeployment or termination of roles that comprise solely of these tasks.
To aid the narrative, and provide a structure for thinking this disruptive situation through in a logical manner, we can take several steps towards understanding the scale of the problem.
Introduction: The New Organisational Imperative
As artificial intelligence and automation technologies continue to advance at an unprecedented pace, organisations face a critical strategic question: not just which tasks can be automated, but how this automation fundamentally transforms departmental structures. Forward-thinking companies recognise that automation is about reimagining how departments function and collaborate when equipped and accelerated by emerging technologies that can act as a force multiplier for competitive advantage.
Restructuring enables organisations to develop leaner, more responsive teams with well-defined frameworks that clarify how humans and AI systems can work together productively. Rather than viewing automation as merely a cost-cutting measure, this perspective treats it as a catalyst for organisational evolution.
Section 1: Assessing Automation Potential Systematically
Before implementing any restructuring plans, organisations must first develop a methodical approach to evaluating which aspects of their operations are suitable for automation. This assessment involves more than simply identifying repetitive tasks; it requires a comprehensive analysis of workflows, skill requirements, and operational interdependencies.
To conduct this assessment effectively, organisations should implement a systematic task inventory and scoring framework that addresses three key dimensions:
- Task Automation Feasibility Analysis: This involves cataloguing all departmental tasks and evaluating which percentage can be fully automated (requiring no human intervention), partially automated (requiring some human oversight), or must remain manually executed. This analysis should consider technological capabilities, cost-effectiveness, and regulatory requirements.
- Time Allocation Assessment: Beyond identifying which tasks can be automated, organisations must quantify the proportion of working hours currently devoted to these potentially automatable activities. This time-based perspective provides crucial context for understanding the scale of potential transformation.
- Role Dependency Mapping: This involves analysing how central automatable tasks are to specific job roles and functions. Some positions might be entirely comprised of automatable tasks, whilst others might include only a small percentage of activities suitable for technological handling.
To illustrate this assessment framework in practical terms, consider a data entry department where task analysis reveals that 60% of their current responsibilities could be automated through technologies such as optical character recognition and natural language processing. Time allocation assessment shows these automatable tasks consume approximately 80% of the team’s working hours. This significant proportion indicates that fundamental restructuring would be both justified and necessary, rather than merely making incremental adjustments to existing roles.
This quantitative approach provides organisations with an objective foundation for making restructuring decisions, helping to prioritise automation initiatives based on their potential organisational impact rather than simply technological feasibility.
Section 2: Core Principles for Effective Restructuring
Once automation potential has been thoroughly assessed, organisations can apply several fundamental principles to guide their restructuring efforts. These principles help ensure that the new organisational design maximises the benefits of automation whilst creating meaningful and fulfilling roles for human team members.
- Transitioning from Task Execution to Strategic Oversight: A core principle involves redirecting human capabilities away from performing routine, repetitive tasks towards activities that leverage uniquely human strengths. This means establishing roles focused on reviewing automated outputs, supervising system performance, making complex judgments in ambiguous situations, and handling exceptions that fall outside algorithmic parameters. For example, financial analysts might shift from manually compiling reports to interpreting automatically generated insights and making strategic recommendations based on those findings.
- Establishing Specialised Orchestration and Maintenance Functions: Automation creates the need for entirely new positions focused on designing, implementing, and maintaining technological systems. These might include AI workflow designers who map and optimise processes for automation, prompt engineers who specialise in effectively communicating with AI systems, and automation monitors who ensure technologies operate correctly and ethically. These roles bridge the gap between technical capabilities and business requirements, ensuring automation systems deliver their intended value.
- Implementing Outcome-Oriented Cross-Functional Integration: Traditional departmental boundaries often create inefficiencies and communication challenges. Restructuring presents an opportunity to organise teams around business outcomes rather than functional specialisations. This approach naturally reduces duplication of effort and creates more cohesive workflows. For instance, rather than maintaining separate customer service and technical support departments with overlapping responsibilities, organisations might create integrated customer experience teams empowered by automation tools that handle routine enquiries whilst facilitating seamless escalation for complex issues.
These principles should not be applied uniformly across all departments but rather adapted based on each unit’s specific automation potential, strategic importance, and customer impact. The goal is to create structures that enhance both operational efficiency and human contribution, recognising that automation should augment rather than simply replace human capabilities.
Section 3: Organisational Models for the Automation Era
Based on automation assessments and restructuring principles, organisations typically develop structures that fall into three primary archetypes, each representing a different balance between human and technological contributions.
- Human-Led with AI Support Model: In this arrangement, human professionals maintain primary control over processes and decision-making, whilst leveraging AI tools to enhance their productivity, insight generation, and service delivery. This model is particularly appropriate for departments where relationship management, creative problem-solving, and strategic thinking predominate. For example, a business development team might use AI tools to analyse market trends and identify potential opportunities, but rely on human judgment for relationship building and negotiating partnerships. This structure emphasises augmentation rather than replacement, with technology serving as a powerful enabler for human professionals.
- AI-Led with Human Oversight Model: This structure inverts the previous relationship, with automated systems handling the majority of operational activities, particularly those involving high-volume, routine transactions. Human involvement focuses on exception handling, quality assurance, and system improvement. This model works well for departments with standardised processes and clear decision parameters, such as claims processing or transaction monitoring. For instance, an insurance claims department might implement an AI system that automatically processes and approves straightforward claims, with human agents focusing exclusively on complex cases requiring judgment or those flagged for potential fraud. This structure maximises efficiency whilst maintaining appropriate safeguards.
- Split-Function Team Model: This hybrid approach divides responsibilities along natural boundaries between routine operational tasks and strategic or relationship-oriented activities. Automated systems manage the former, whilst human professionals focus exclusively on the latter. This model is particularly valuable in customer service contexts, where automated systems might handle common enquiries and transactions, whilst human agents manage complex problem resolution and relationship development. Similarly, in marketing departments, AI systems might execute and optimise campaign performance, whilst human marketers focus on strategy development and creative direction. This model creates clear delineation of responsibilities based on comparative advantages.
Selecting the appropriate archetype depends on several factors, including the nature of work performed, the sophistication of available automation technologies, regulatory requirements, and customer expectations. Many organisations implement different models across various departments based on their specific characteristics and requirements.
Section 4: Broader Organisational Implications
Restructuring based on automation potential carries significant implications that extend beyond departmental boundaries, affecting workforce planning, skill development, and performance measurement.
- Workforce Composition Transformation: As automation assumes responsibility for routine tasks, organisations typically require fewer total staff members. However, those remaining positions demand higher skill levels, particularly in areas such as critical thinking, complex problem-solving, technological fluency, and interpersonal communication. This shift necessitates thoughtful approaches to workforce transition, potentially including retraining programmes, early retirement options, or phased implementation plans that allow for natural attrition.
- Labour Redistribution Towards Higher-Value Activities: Automation creates opportunities to redirect human talent towards activities that generate greater business value. This typically involves expanding capabilities in design thinking, strategic planning, and ethical oversight. For example, as basic accounting functions become automated, financial professionals can focus more on forward-looking analysis, scenario planning, and strategic advising. This redistribution creates more intellectually stimulating work environments whilst enhancing organisational capabilities in areas resistant to automation.
- Enhanced Focus on Outcome Measurement and Governance: As processes become increasingly automated, organisations must develop more sophisticated approaches to measuring performance and governing workflows. This includes establishing clear metrics for both technological and human contributions, implementing robust quality assurance mechanisms, and creating transparent governance frameworks that ensure automated systems operate within appropriate ethical and operational boundaries. Without these accountability structures, automation can potentially introduce new risks or unintended consequences.
Conclusion: Creating Sustainable Automated Organisations
This structured approach to departmental restructuring ensures that organisations align their operational models with their level of automation maturity. Rather than implementing automation in a piecemeal fashion or treating it as merely a cost-reduction tool, this comprehensive framework helps companies develop truly integrated human-machine systems.
As technologies continue to evolve, this alignment enables organisations to scale operations efficiently, adapt to changing market conditions, and create environments where both technological systems and human professionals can contribute their unique strengths. The most successful organisations will be those that view restructuring not as a one-time event but as an ongoing process of adaptation and refinement in response to technological advancements and shifting business requirements.
By approaching automation-driven restructuring with both analytical rigour and human sensitivity, organisations can create more resilient, adaptable, and fulfilling work environments that harness the full potential of both technological and human capabilities.