Für diese Tätigkeit liegen 5 Quellenbelege vor. Keiner untersucht diese Tätigkeit unmittelbar; die Aussagen stammen aus breiterem Kontext.
Das Aufsetzen von Budgets und Finanzplänen verschiebt sich zur KI hin, das Einordnen und Verantworten der Zahlen bleibt gefragt.
Das Planen und Kontrollieren von Budgets zählt zu den Finanztätigkeiten, deren KI-Nähe zuletzt gestiegen ist — die strukturierte, datengetriebene Rechenarbeit lässt sich mit KI-Werkzeugen zu einem guten Teil erledigen, von Budgetvorlagen bis zum Durchspielen verschiedener Szenarien. In stark KI-nahen Betrieben geht die Nachfrage nach reinen Budgetierungs- und Rechnungswesen-Kompetenzen etwas zurück. Zugleich bleibt Budgetierung gerade in den hoch betroffenen Berufen eine der meistgeforderten Fähigkeiten — das Rechnen verschiebt sich also eher zur KI, das Einordnen und Verantworten der Zahlen bleibt beim Menschen.
Diese allgemeine Einordnung ist keine Messung in jedem einzelnen Beruf.
Eine fehlende Bewertung bedeutet nicht, dass die Tätigkeit nicht betroffen ist.
Performing financial estimates to develop a household budget 0.37 0.64 0.64 The task of performing financial estimates to develop a household budget can be significantly automated with generative AI tools like ChatGPT due to the structured and data-driven nature of budget calculations. GenAI can generate budget templates, provide financial advice based on data inputs, and simulate different financial scenarios, which aligns closely with the theoretical group's higher score of 0.64, indicating strong po tential for automation with AI's current capabilities. [norm.] / Conversely, for tasks like ‚maintaining documentation of classes with children' or ‚performing finan cial estimates for household budgets', the experts recognized the structured and analytical nature of these tasks, which generative AI can assist with to a substantial degree. [norm.]
Generative AI and Jobs: A Refined Global Index of Occupational Exposure (ILO Working Paper 140) · 2025 · ILO WP 140, Table 4 (Sample of adjustments and justifications between the survey and expert scores), PDF-S. 35, gedruckt S. 32 [norm.]; ergänzend Abschnitt zur Score-Adjustierung, PDF-S. 34, gedruckt S. 31 [norm.]
Additionally, some occupations – such as financial analysts, and web and multimedia developers (gradient 4), as well as bank tellers, translators, applications programmers, investment advisers (gradient 3) – have increased their levels of exposure, highlighting the expanding abilities of GenAI technology to potentially automate more specialized tasks in professional and technical roles.
Generative AI and Jobs: A Refined Global Index of Occupational Exposure (ILO Working Paper 140) · 2025 · ILO WP 140, Zusammenfassung der revidierten Klassifikation, PDF-S. 49/50, gedruckt S. 46/47
Establishment-level AI exposure is associated with decreased demand for management skills. On average across countries in the sample demand for management skills declined by under 4 percentage points for a one standard deviation increase in AI exposure (Figure 4.2, Panel A). All countries in the sample are associated with a decline in management skills, and all are statistically significant from zero. Resource management includes human resource management, financial management, among others. Some of the most frequently demanded skills in financial management include budgeting and accounting.
Artificial Intelligence and the Changing Demand for Skills in the Labour Market (OECD AI Papers No. 14) · 2024 · OECD AI Papers No. 14, Abschnitt 4.2.1, PDF-S. 34/35, gedruckt S. 34
The most demanded skills in occupations with high AI exposure are management, business processes and social skills. Management and business processes contain skills such as project management, budgeting and accounting, administration, clerical tasks and customer support. On average across the 10 OECD countries in the sample, 72% of vacancies in high AI exposure occupations demand at least one management skill and 67% demand at least one business processes skill. [norm.]
Artificial Intelligence and the Changing Demand for Skills in the Labour Market (OECD AI Papers No. 14) · 2024 · OECD AI Papers No. 14, Executive Summary, PDF-S. ~9, Zeilenbereich 219 der Textfassung [norm.]
For JPMC, applications in fraud detection, predictive modeling, and financial forecasting map most closely to tasks performed by Other Financial Specialists and by Accountants and Auditors. / we find that higher mean exposure of an occupation's tasks to employer-adopted AI applications reduces subsequent employment growth in that occupation–firm pair, while greater concentration of exposure raises it. […] a one–standard deviation increase in mean task exposure reduces the occupation's within-firm employment share by about 14.5 percent over five years, while a similar increase in concentration raises it by about 7.5 percent.
Artificial Intelligence and the Labor Market (NBER Working Paper 33509) · 2025 · Hampole et al., NBER WP 33509, PDF-S. 15; ergänzend PDF-S. 6 (Netto-Effekt)
Diese Lösungen unterstützen die Tätigkeit in einem passenden fachlichen Kontext. Das ist keine Aussage über ihre Eignung oder gemessene Wirkung in jedem zugeordneten Beruf.
Zitierhinweis: SapientShift, Tätigkeit T-037 „Budgets und Finanzen planen und kontrollieren“, https://sapientshift.com/taetigkeiten/budgets-und-finanzen-planen-und-kontrollieren. Methodik und Grenzen.