HR is under enormous pressure – and AI is gaining more and more momentum in everyday work. Sandra Preiser, Head of SAP HXM at Nagarro, explains why AI requires a new approach in business organization: consistently thinking about processes before technologies and never losing sight of people.
Executive Summary
AI in business organization: processes before technologies
- The challenge: AI is fundamentally changing workflows, roles and forms of collaboration. Many companies are already investing in new applications, but clear strategies, governance structures and consistent alignment with business processes are often missing. This makes the successful use of AI more difficult and poses new challenges for HR in particular.
- The solution: AI should be understood as an organizational task. Successful companies realign processes, responsibilities and competencies, create resilient data and governance structures and accompany change with change management and targeted qualification. HR takes on a key role here – as a user and enabler of the transformation.
- Your benefit: Anyone who strategically anchors AI in the company organization increases efficiency, uses resources more specifically and creates the conditions for value-adding and scalable AI use.
- Focus: AI in business organization, organizational development, change management, HR as a business partner, governance, process design, competence development, AI strategy.
Whether in recruiting, personnel management, personnel development or personnel planning: three quarters of HR departments in Germany use AI. Typical applications include optimized job advertisements, onboarding chatbots, individualized learning content and forecasted personnel requirements.
Generative artificial intelligence has barely become established when intelligent, autonomous AI agents are already in the starting blocks. In the future, AI will not only make processes more efficient, relieve the burden of routines, enable data-based decisions and create a consistently positive experience for employees and applicants – but also support the work of HR managers across the entire employee life cycle.
But the clearer it becomes that technology needs to be firmly integrated into everyday working life, the more uncertain companies become about where and how exactly they could use tools to support it. Although budgets are specifically released for AI, many people don’t know whether projects should be initiated by IT or the department. There are also open questions about quality, standards, data, compliance and user enablement. In many places this leads to excessive demands, disappointment and frustration.
Three insights that determine success or failure
Three insights are fundamentally important when it comes to HR and AI in order to overcome typical thinking traps, implement projects more easily and meet expectations.
Firstly, it is a task for the entire companynot just human resources, to make AI practically ready for use. Technology is fundamentally changing work processes, tasks, requirements, roles and responsibilities. What was previously done by humans can now be done by agents.
In this context, we also talk about redesigning work: redesigning the division of labor between humans and machines. Consequently, the entire company must transform and with it organizational structures, processes, working methods and competencies must be adapted.
This is exactly what is often underestimated: budgets are planned without being clear about a sensible distribution. Software is introduced without developing detailed strategies and considering processes. Tools are implemented without having any idea of resources released. And they are used without governance structures in place.
A second insight is that AI requires more than raw datain order to be able to act independently within processes and rules – it needs networked data and a business context. An example from human resources planning shows why this is the case: Only when data on qualifications, further training, performance and company goals are brought together can AI provide reliable recommendations; provided the data quality is correct.
Third, AI should not be viewed as a panacea: it doesn’t always make sense everywhere and excessive use of three or more tools in parallel has been proven to even lead to reduced productivity and mental exhaustion, known in specialist circles as “AI Brain Fry”.
Successful AI starts before the technology: three important dimensions
How can it be better? When starting out, it is advisable to approach the use of AI not “ad hoc” as a “one-time project”, but rather strategically, structured and holistically. Together with all departments. An honest look at the status quo shows the level of maturity, need and potential in the dimensions of strategy, people and technology.
Important questions in this context are: Are the organization and IT ready for AI? Are there the necessary structures, processes, roles and forms of collaboration? Are employees able to work with new tools, keyword upskilling? How can technologies be chosen so that they are suitable and seamlessly integrated? Is there a governance model, especially for AI in human resources? Can data protection requirements be met?
The more budget is invested in all three dimensions, the more value-added an AI project becomes and the easier it is to scale. Anyone who establishes agile working methods and proceeds iteratively can continuously control changes and react quickly to innovations.
HR as an enabler of transformation
When introducing AI, HR comes into focus in two ways: firstly as a user and secondly as an enabler. HR managers should therefore deal particularly intensively with the various instruments and tools and the associated opportunities and risks.
And they, in turn, should learn new skills, especially the core competence of actively accompanying and supporting the organization in its transformation. This includes aspects such as change management including communication, specific training to use AI extensively, professionally and responsibly in the respective role, and guidelines that protect employees from digital overload when using AI.
Experience shows that the biggest hurdle with AI is not infrastructure or data – although there is still a lot of catching up to do here – but the people in the company. Many are tired of change, worried about their jobs, and are resisting. The good news is: the higher the value of AI is perceived and the better the AI knowledge is, the more likely people are to be encouraged to completely change: towards a way of working in which they orchestrate more, evaluate results and take responsibility for AI-supported processes.
The changes brought about by AI in particular illustrate the central role of HR: accompanying people through change, building new skills and actively developing the organization. This shows once again that companies need HR as a business partner – not as an administrator.
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