1. Automation of routine activities
- Work processes: AI automates repetitive tasks, such as screening CVs, scheduling appointments for job interviews and managing application processes.
- Work content: HR specialists can concentrate more on strategic activities, such as talent management, employee retention and strategic personnel planning.
- Changes in the workplace: The automation of routine tasks can lead to a reorganisation of HR positions. The focus is shifted to more demanding tasks.73
71 See Kirste 2019, pp. 58-71.
72 See Weibel 2016, pp. 437-462.
73 See Fink, V. 2021, p. 17f.
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2. Better recruitment and selection of talent:
- Work processes: Support from AI in analysing large amounts of applicant data to identify qualified candidates and improve hiring decisions.
- Job content: HR professionals can focus on developing more effective recruitment strategies and assessing soft skills.
- Changes in the workplace: As AI helps to identify candidates with the exact skills required, the role of the HR department in talent acquisition is becoming more strategic.74
3. Improved familiarisation and further training:
- Work processes: AI can create personalised onboarding programmes and develop training plans. These are based on individual skills and needs.
- Work content: HR can focus more on organising training measures to promote the continuous professional development of employees.
- Changes in the workplace: HR takes on a more active role in developing training programmes and promoting a learning-friendly corporate culture.75
4. Efficient performance management:
- Work processes: AI can help support the continuous monitoring of performance data and identify areas for development.
- Job content: HR specialists focus on interpreting performance data and supporting employees in their professional development.
- Changes in the workplace: Traditional annual appraisals can be replaced by continuous feedback and a detailed analysis of performance. 76
5. Personalised employee experience:
- Work processes: AI is able to create personalised employee experience models to better understand individual needs and preferences.
- Work content: HR focuses on developing personalised measures to retain employees and improve the employee experience.
74 See Fraunhofer IAO 2020, p. 48f.
75 See Capelli et al. 2018, p. 4-23.
76 See Petry 2023, p. 9ff.
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- Changes in the workplace: Employee programmes and benefits are designed on the basis of precise analyses of employee data.77
6. Predictive analyses for talent management:
- Work processes: AI can use predictive analyses to identify talent with the greatest potential for future management positions.
- Job content: HR plays a crucial role in developing talent strategies and identifying key people for organisational development.
- Job changes: The planning of succession programmes and the development of managers are supported by the precise analysis of data.78
The intensive use of AI in HR work is significantly changing the traditional role of HR
work. New opportunities are opening up for strategic alignment, for improving the recruitment and development of talent and for personalised employee support. In order to fully utilise the potential of AI, this also requires HR professionals to adapt their skills and undergo continuous training.
3.4 Effects of the use of AI in marketing:
The intensive use of artificial intelligence (AI) is changing marketing in many ways, leading to new approaches, increased efficiency and a stronger focus on personalised strategies. Some of the most important changes are79
1) Addressing target groups more precisely:
- AI analyses large amounts of customer data. This allows precise target group profiles to be created. Marketing campaigns can be tailored more precisely to the needs and preferences of the target group.
2) Personalised marketing content:
- Based on the individual behaviour, interests and previous engagement of customers, AI enables the creation of personalised content. This enables marketers to create content that is more relevant and engaging. 80
77 See Petry 2023, p. 10f.
78 See Fink, V. 2021, p. 57f.
79 Cf. Volkmar et al. 2021, pp. 359-375/Cf. Fraunhofer IAO 2020, pp. 14-21/Cf. SRH 2021, pp. 2-78.
80 See Gentsch 2019, p. 55f.
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3. automation of marketing tasks:
- AI automates recurring tasks such as target group segmentation, email distribution, A/B testing of ads and campaign optimisation. The result is an increase in efficiency and the opportunity for marketing managers to focus on strategic aspects.81
4) Predictive analytics for better decisions:
- By using AI, marketing managers can utilise predictive analytics. This allows future trends, customer behaviour and the success of marketing strategies to be predicted. This allows well-founded decisions to be made. Campaigns can be adapted in real time. 82
5. Chatbots in customer service:
- AI-controlled chatbots are an efficient means of interacting with customers. They are available around the clock and can answer enquiries, provide product information and improve customer service.83
6. Optimisation of advertising campaigns:
- Advertising campaigns can be automatically optimised in real time with the help of AI. In order to achieve the best possible performance, this includes the adjustment of bids, the placement of adverts and the display of content.
7) Analysing the customer journey:
- With the help of AI, marketing managers have a better understanding of the entire customer journey. This includes identifying touchpoints, tracking and analysing customer interactions with the aim of optimising the purchasing process. 84
8) Proactively recognising market trends:
- To identify market trends at an early stage, AI continuously analyses large amounts of data. This enables marketing managers to proactively adapt their strategies and utilise trends instead of just reacting to them.
9. risk management and compliance:
- AI can help to identify potential risks in connection with marketing campaigns, particularly with regard to compliance and data protection. In this way, compliance with regulations can be supported and the risk of legal problems minimised.85
81 See Davenport et al. 2020, pp. 24-42.
82 See Torra et al. 2019, pp. 9-26.
83 See Huang 2018, pp. 155-172.
84 See Kietzmann et al. 2018, pp. 263-267.
85 See Colson 2019.
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10) Development of new marketing technologies:86
- The development of new marketing technologies and platforms is promoted by the intensive use of AI. These could offer advanced automation, personalisation and analysis functions and tools. 87
The intensive use of AI in marketing is leading to an industry transformation characterised by data-driven decisions, personalised interactions and more efficient workflows. Marketers are increasingly becoming strategists who utilise AI as a powerful tool to develop meaningful and effective marketing strategies.
3.5 Impact of the use of AI in sales
The intensive use of artificial intelligence (AI) is fundamentally changing sales and enables new approaches, increased efficiency and improved customer interactions.
Some of the most important changes are88
1) More efficient lead generation:
- By analysing data, potential customers can be identified more precisely with the help of AI. Automated scanning of large amounts of data enables faster identification and prioritisation of qualified leads.
2) Personalised customer approach:
- By using AI, sales employees can create personalised messages based on individual customer profiles, interests and early interactions. This contributes to greater customer loyalty.
3. automated communication:
- AI-based chatbots and automated communication systems make it possible to answer customer enquiries in real time and automate simple interactions. The result is an increase in efficiency and an acceleration of customer service.
4) Predicting customer needs:
- With the help of predictive analytics, AI is able to predict the needs and preferences of customers. These findings support sales employees in creating personalised offers and responding to individual customer needs.
86 See Wolan 2020, pp. 25-50.
87 Cf. Volkmar et al. 2021, pp. 359-375/Cf. Fraunhofer IAO 2020, pp. 14-21/Cf. SRH 2021, pp. 2-78.
88 Cf. Fraunhofer 2020, pp. 22-25/Cf. Stummeyer 2021, pp. 20-24/Cf. Krackl 2023, pp. 6-42/Cf.
Rainsberger 2021, pp. 17-34/Cf. Mühlenhöver 2023, pp. 2-6.
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5) Optimisation of sales processes:
- With the...
