Artificial intelligence will widen the gap between organizations. Those that have structured their processes and service relationships will fully benefit from it. Others will see their inefficiencies amplified. At Althéa, we position this observation as the starting point for a new offering, launched in 2026: Employee Relationship Management. Not an additional tool. A service relationship management model designed for the era ahead, applicable to all support functions—HR, Finance, Procurement, IT. Interview with Fatima-Azzahra Lemzaoui, Director and ERM Offering Leader at Althéa.
Why are current support function models showing their limits—precisely now?
In recent years, companies have invested heavily in their information systems. Core HR, payroll, Finance ERP, Procurement tools, ITSM… major programs, often costly, with a strong promise: simplify, industrialize, and improve the service experience.
In practice, the limitations are now clearly apparent, and AI makes them critical.
These systems were designed to manage processes, but not to absorb a massive volume of interactions or to deliver consistent service at scale. Support teams remain under pressure. Journeys are fragmented, and data degrades from the moment it is created.
With AI, this limitation changes in nature. AI relies directly on data quality, which itself depends on how processes are executed on a daily basis. Without upstream structuring, technologies do not hold up over time.
The issue is therefore no longer just about digitalization. It is about structuring operational execution (HR, Procurement, Finance, IT, etc.).
What does ERM concretely provide that tools do not?
Organizations today have numerous building blocks: ERP, HRIS, Procurement tools, Finance tools… These blocks are essential, but they remain focused on processing. What is missing is the ability to orchestrate the whole.
ERM introduces a cross-functional orchestration layer that connects employees, managers, support teams, and existing tools. It structures the relationship, organizes flows, and makes the service readable and manageable.
Where tools execute processes, ERM organizes interactions.
This model does not stop at the HR function. The same mechanisms apply to Finance (managing supplier requests, expense reports, accounting close), Procurement (qualifying requests, contract tracking, compliance), or IT (incident management, access management, user support). Wherever a support function receives requests, processes flows, and produces data, ERM creates value.
This change is decisive; it transforms a stack of building blocks into a coherent, cross-functional, managed, and scalable service model.
What are the concrete signals indicating that an organization should initiate an ERM approach?
In the field, the observations are immediate.
This translates into operational overload, poorly directed or incomplete requests, variable processing times, and frequent back-and-forth—whether in HR shared service centers, Finance teams, or Procurement departments.
This situation has a direct impact on employee and partner experience. An employee who does not know whom to contact, a supplier who follows up without response, a manager who does not see their request progressing—all immediately degrade the perception of the company. Service relationship thus becomes a strategic issue in its own right.
But the most structural impact concerns data. Every poorly framed interaction generates errors, re-entries, and inconsistencies, which weaken data from its origin and subsequently limit any capacity for management or exploitation.
Certain processes make these limitations even more visible:
→ In HR: onboarding, preboarding, offboarding, internal mobility—critical journeys that concentrate volume, delays, and errors
→ In Finance: unqualified supplier requests, poorly documented expense reports, closings delayed by incomplete data
→ In Procurement: purchase requests without framing, dispersed contract tracking, compliance difficult to audit
The result is twofold: significant operational burden and degraded performance, with unreliable data from the start.
At a large enterprise client facing several thousand onboardings per year, implementing an ERM system produced measurable results:
→ -20% to -40% HR requests related to onboarding
→ +1h to +2h saved per employee on the entry journey
→ -30 to -60 minutes of manager intervention time
→ Data quality and completeness significantly improved
These dynamics are identical in Finance and Procurement: fewer poorly qualified requests, fewer follow-ups, fewer data entry errors, and reliable data from the source.
How do you concretely intervene with your clients?
Our approach is based on a simple principle: start from field pain points, before choosing tools.
It unfolds in five stages:
→ 01: Opportunity Study: map pain points, assess eligible use cases, simulate impacts
→ 02: Process & Data Design: structure processes and data toward scaling
→ 03: Business Case & Selection Support: build the ROI and identify tools capable of supporting the trajectory (such as ServiceNow, Neocase, UKG…)
→ 04: Project Management & Post-Project Support: deployment, adoption, skills development
→ 05: Run & Continuous Improvement: manage performance, adjust, and secure over time
Throughout this approach, change management is integrated as a guiding thread, not as a final phase. Teams progressively adopt the model, and benefits are visible in their daily work.
We favor a Use Case Factory approach to prioritize high-value use cases, quickly generate concrete results, then progressively industrialize.
What is the impact on change management?
This is one of the most underestimated benefits of ERM: it structurally reduces the cost of change management.
Why? Because ERM acts on the orchestration layer, not on the tools themselves. When a system evolves or is replaced, only operational teams are impacted. Users continue to interact with the same entry point, the same journeys, the same experience. This decoupling is a major competitive advantage that allows the IS to evolve without imposing visible transformation, thus reducing resistance, training costs, and adoption risks.
Each stakeholder benefits differently:
→ CHRO: regain control of timelines, manage HR service performance, and reduce change management needs with measurable ROI
→ Shared Service Center Manager: absorb volumes through industrialization, without additional hiring
→ CFO / Procurement Director: control supplier payment timelines and improve working capital, reduce disputes and hidden costs related to follow-ups, ensure reliable accounting closings through data structured at the source, and gain visibility on commitments for more precise budget management
→ CIO / HRIS: ensure data reliability from actionable processes and create the conditions for truly useful AI
→ Business Functions: gain operational efficiency, with smooth journeys and predictable timelines
How is ERM a pillar of Althéa’s HR Transformation model?
All Althéa offerings are interconnected, and ERM plays a particular role in this ecosystem.
ERM is the point of contact between the user and all support processes. As such, it determines the quality of data that feeds Core HR, HR Data, Talent, Time & Attendance, as well as Finance and Procurement systems. Without well-framed interactions, the data entering these systems is unreliable, and the entire value chain suffers.
This is why Althéa chose to structure this offering in 2026: not as an additional building block, but as the operational binder that allows other offerings to fully express their value.
How does AI concretely transform execution—and what conditions must be met?
AI, and particularly GenAI, profoundly transforms the execution of support functions. But it builds on automation initiatives already underway. It does not replace them; it accelerates them.
What AI makes concretely possible is a new layer of intelligence on interactions: understanding a request formulated in natural language, qualifying it, routing it to the right contact, or processing it directly. It can guide a user throughout a journey (ask the right questions, detect missing information, follow up at the right time) without systematic human intervention.
In HR, it structures data collection and streamlines administrative steps. In Finance, it controls request compliance and accelerates closings. In Procurement, it qualifies needs and secures contract tracking.
But AI has an advantage that is still underestimated: it has no boundaries. Where a team is limited by its human resources, AI absorbs volumes at scale, consistently, without depending on geography or time zone. This is what profoundly changes the service equation in international organizations.
However, the challenge is not to deploy AI for its own sake. It requires non-negotiable prerequisites: structured processes, reliable data, clear governance.
No good AI without good data. No good data without good processes.
This transformation also changes the role of teams, who progressively shift from processing to supervision, analysis, and management.
Service relationship: the lever organizations have not yet activated
Organizations have digitalized their tools. They have industrialized their processes. But many have not yet structured the way they engage with their users (employees, managers, suppliers, partners)—and it is precisely this gap that weakens everything else.
ERM is not another response to a known problem. It is a shift in posture, enabling the transition from a processing logic to a service logic, from a tool vision to an experience vision, from passive data to managed data.
This is what we are building at Althéa in 2026. And this is what will determine, tomorrow, the ability of organizations to fully leverage artificial intelligence.
