Transforming Case Management and Rostering Through AI
Evolve.i supported an aged care provider to redesign case management and rostering through a connected technology strategy, foundation CRM and layered AI capabilities. The transformation focused on reducing administrative pressure, improving workforce coordination, strengthening client responsiveness and creating greater visibility over service delivery and financial performance.
Sector
Healthcare & Aged Care
Service Pathways
AI Integration & Implementation, Business Process Redesign, Workforce Transformation
The Challenge
Case management and rostering sit at the centre of aged care service delivery. However, the organisation’s teams were working across disconnected systems, spreadsheets, emails and manual processes that made it difficult to coordinate clients, services and workforce capacity efficiently.
Case managers were spending significant time locating information, preparing routine documentation, tracking actions and coordinating services across multiple channels. Rostering teams relied heavily on manual knowledge and repeated communication to match client requirements with workforce availability.
This created several interconnected challenges:
client, workforce and service information was fragmented across different systems
case managers were required to enter, retrieve and reconcile information manually
routine documentation and follow-up activities consumed valuable professional time
communication histories and outstanding actions were not consistently visible
rostering decisions relied heavily on individual knowledge and manual coordination
workforce availability, capability and client requirements were difficult to view together
changes to client needs or staff availability required repeated intervention
case management and rostering processes were not sufficiently connected
limited system integration affected operational and financial reporting
leadership had insufficient visibility over productivity, utilisation and service performance
technology decisions had developed incrementally without an overarching strategy
AI opportunities were emerging without the systems, data and governance foundations required to introduce them safely
The organisation did not simply require another technology product. It needed to redesign how case management and rostering worked in the new Support at Home funding model.
Evolve.i Approach
Evolve.i approached the engagement as an end-to-end operational transformation rather than a standalone CRM or AI implementation.
The work connected service design, workforce practices, processes, systems, data, governance and financial performance. The objective was to create a practical operating environment in which technology and AI could reduce administration, support better decisions and return more time to clients.
Diagnose
Evolve.i reviewed the organisation’s existing technology environment and mapped how information moved across the client and workforce journey.
The diagnosis identified that the central issue was not one underperforming system. It was the absence of an integrated operating and technology architecture connecting clients, case managers, rostering teams, frontline employees and financial information.
Design
Evolve.i developed a technology strategy and future-state operating model centred on improving case management and rostering.
A foundation CRM was designed as the central environment for managing client relationships, communications, actions, service information and workflow visibility. It was positioned as an enabling platform rather than the final solution.
AI was intentionally positioned as a layered capability supported by reliable data, connected workflows and clear human accountability.
Deliver
Evolve.i supported the practical implementation of the foundation CRM and the redesign of priority case management and rostering processes.
Initial AI opportunities for case management included:
summarising approved client and case information
assisting with the preparation of draft case notes and correspondence
retrieving relevant information across authorised records
identifying incomplete information and outstanding actions
organising information for case manager review
supporting task and workload prioritisation
preparing routine service summaries and internal updates
reducing repeated administrative preparation
AI opportunities for rostering included:
bringing together client requirements and workforce availability
identifying potential scheduling gaps or conflicts
supporting the matching of skills and service requirements
highlighting changes that may affect service continuity
assisting with workforce demand and capacity analysis
identifying patterns in cancellations, vacancies and unfilled services
supporting more informed allocation and scheduling decisions
improving visibility of utilisation and rostering performance
AI-generated outputs were designed to support employees rather than make autonomous care or workforce decisions. Final decisions and accountability remained with authorised staff.
Evolve
The project established a scalable foundation through which the organisation could progressively expand its digital, automation and AI capabilities.
The longer-term pathway included opportunities to develop:
AI-assisted case management administration
proactive workflow and follow-up prompts
more responsive client and family communication
automated preparation of routine documentation
improved service coordination across teams
intelligent rostering recommendations
workforce demand forecasting
better visibility of service capacity and coverage
client-to-worker matching support
integrated operational and financial dashboards
improved analysis of utilisation and service margins
early identification of operational risks and service gaps
continuous measurement of productivity and client outcomes
This positioned the organisation to move from fragmented administration and reactive coordination towards a more connected, proactive and AI-ready service model.
Impact
The redesigned case management and rostering model was structured to deliver measurable improvements across productivity, workforce utilisation, client responsiveness and financial performance.
Reduction in Case Management Administration
AI-assisted documentation, information retrieval, workflow prompts and case summarisation could reduce the time case managers spend on routine administration by approximately 20–30%.
For every 10 case managers, this could release capacity equivalent to 2-3 full-time positions, allowing more time for client engagement, service coordination and professional decision-making.
Reduction in Manual Rostering Effort
Connected workforce information, automated workflow support and AI-assisted scheduling could reduce manual rostering and coordination effort by approximately 30–40%.
This includes time spent managing availability, identifying suitable workers, resolving scheduling conflicts and communicating changes.
Improvement in Workforce Utilisation
Better visibility of service demand, workforce availability, capability and location could improve productive workforce utilisation by approximately 5–10%.
This can support stronger service coverage while reducing avoidable gaps, travel inefficiencies and underutilised capacity.
Additional Operational Capacity
Together, the redesigned workflows, CRM foundation and AI capabilities could enable the organisation to manage approximately 15–25% more service activity without requiring an equivalent increase in administrative headcount.
Illustrative Annual Value
For an operating model comprising 20 case managers and four rostering employees, the productivity improvements could release capacity equivalent to approximately:
4-6 case management positions
1.2-1.6 rostering positions
approximately $500,000-$850,000 in annual workforce capacity value
This value may be realised through increased service capacity, avoided recruitment, reduced overtime, lower administrative costs or improved revenue capture. It should not automatically be interpreted as a direct cash saving.
Why It Matters in the AI Era
Case management and rostering sit at the intersection of client needs, workforce capacity, compliance and financial performance.
AI can reduce administration, improve information access and support workforce coordination, but only when it is built on connected systems, reliable data, clear governance and human oversight.
AI should return time to care, not remove people from care.
Strategic Overview
This project demonstrates Evolve.i’s business-first approach to AI transformation.
Case management and rostering workflows were redesigned before technology was applied. A foundation CRM created the connected data and workflow environment, while layered AI capabilities supported administration, workforce coordination and decision-making.
The result is a more productive, responsive and scalable aged care operating model.
Client Disclaimer:
This project has been anonymised to protect client confidentiality.
All identifying, operational, financial and technology information has been removed or generalised. Numerical outcomes represent indicative improvement potential based on the redesigned operating model and should not be interpreted as independently verified client results, financial guarantees or a client endorsement.