AI with IT

The IT industry is at the forefront of technological innovation and is driving digitalisation worldwide. At a time when data is the new oil, artificial intelligence (AI) plays a central role in transforming business processes, improving customer experience and increasing operational efficiency. Despite the potential of AI, there are specific challenges in the IT industry that need to be considered when implementing AI.

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The five most important challenges when implementing AI in IT

Data quality and availability: Access to high-quality and comprehensive data is crucial for the success of AI projects. Data must be well-structured, up-to-date and relevant.
Scalability of AI solutions: The ability to scale AI solutions from small pilot projects to company-wide implementations is often a major challenge.
Integration into existing systems: Existing IT systems and infrastructures must be compatible with new AI technologies, which requires technical and organisational adjustments.
Shortage of skilled labour: The lack of qualified specialists with expertise in AI and machine learning can hinder the development and implementation of AI solutions.
Ethical and legal concerns: Compliance with data protection regulations and the consideration of ethical aspects when using AI are key challenges that need to be addressed.

Why a standardised AI strategy is important for all departments

A uniform AI strategy ensures that all departments within a company work in a synchronised manner and can benefit from the advantages of AI. By harmonising AI initiatives, redundancies are avoided and synergies are created that increase the efficiency and effectiveness of the entire organisation. In addition, a common strategy promotes the transfer of knowledge between departments, which leads to more innovative solutions and faster implementation of AI projects.

Why the KIROI strategy is so highly valued by over 400 companies

The KIROI masterplan offers a structured and holistic approach to implementing AI in companies. By taking into account all relevant aspects - from employee training to compliance with ethical standards - KIROI ensures that AI initiatives are implemented sustainably and successfully. The plan is flexible and customisable to the specific needs and challenges of the IT industry, making it the ideal solution for companies looking to drive their digital transformation.

KIROI master plan for IT

Step 1: Share knowledge

Share your knowledge about AI with managers and employees to create a common understanding and interest.
Identify key people in different departments who can act as AI ambassadors.
Organise regular workshops and seminars to raise awareness of AI and its potential applications.
Develop an internal knowledge portal that provides resources, case studies and training materials on AI.
Promote a culture of open dialogue about AI, where questions and concerns can be discussed openly.
Use internal communication channels such as newsletters or the intranet to share current developments and successes.
Implement a mentoring programme in which experienced AI experts pass on their knowledge to less experienced colleagues.
Organise cross-functional team meetings to promote the exchange of ideas and best practices.
Encourage employees to attend external conferences and training courses to expand their knowledge.
Develop a strategy for continuous training in the field of AI to stay at the cutting edge of technology.

Step 2: Explore tools

Analyse the current and potential AI tools and technologies that could be relevant for your company.
Create a list of the most important requirements and criteria for selecting the right AI tools.
Carry out pilot projects to test the effectiveness and suitability of various AI tools.
Consider both commercial and open source solutions to find the best options for your specific needs.
Plan training courses and workshops to train your employees in the use of new AI tools.
Develop a long-term roadmap for the introduction and scaling of AI tools across the organisation.
Encourage collaboration between IT and business departments to ensure that the tools selected meet the needs of all users.
Use feedback loops to continuously evaluate the effectiveness and user-friendliness of the tools used.
Ensure that the selected tools are compatible with existing systems and can be seamlessly integrated.
Invest in the necessary IT infrastructure to maximise the performance of the AI tools.

Step 3: Big data and smart data

Identify the most important data sources in your company and assess their quality and relevance.
Develop a data collection and storage strategy that ensures that data is available in high quality and in real time.
Use advanced analysis tools to gain valuable insights from large amounts of data.
Implement data cleansing and normalisation procedures to improve data quality.
Promote cross-departmental collaboration in data utilisation to create synergies.
Develop a data management system that facilitates access to and use of data throughout the organisation.
Use AI-supported algorithms to recognise valuable patterns and trends from your data.
Ensure that all data protection requirements are met to guarantee the integrity and security of your data.
Carry out training courses to teach your employees how to handle and analyse large volumes of data.
Develop a long-term data strategy that ensures the continuous use of big data and smart data in the company.

Step 4: Cultural issues

Promote a corporate culture that is open to technological change and innovation.
Develop programmes to raise awareness and train your employees in dealing with AI and its impact on the world of work.
Implement incentive systems that reward the use and promotion of AI in the company.
Promote cross-departmental collaboration and the exchange of ideas and experience in dealing with AI.
Develop communication strategies that emphasise the importance of AI and its benefits for the company.
Ensure that the introduction of AI is done ethically and responsibly to gain the trust of your employees.
Use change management methods to facilitate the transition to an AI-supported way of working.
Promote a culture of continuous learning and development to keep pace with rapid technological change.
Implement feedback loops to continuously assess and adapt the impact of AI on the corporate culture.
Actively involve your employees in the AI implementation process to increase their acceptance and commitment.

Step 5: Ethics and compliance

Develop a company-wide policy on the use of AI that takes ethical and legal aspects into account.
Ensure that all AI projects comply with applicable data protection laws and regulations.
Implement a compliance management system that monitors compliance with all relevant regulations.
Promote a culture of transparency and responsibility in dealing with AI.
Offer training courses and workshops on ethical issues and legal requirements in connection with AI.
Establish an ethics committee to monitor and advise on the development and implementation of AI projects.
Develop procedures to assess and minimise risks associated with the use of AI.
Ensure that all AI solutions are fair and unbiased to avoid discrimination and bias.
Promote dialogue on ethical issues and the social impact of AI in the company.
Continuously monitor compliance with ethical and legal guidelines and adjust them if necessary.

Step 6: Own department

Identify specific challenges and opportunities in your department that can be addressed through the use of AI.
Develop concrete use cases and pilot projects to demonstrate the benefits of AI in your department.
Encourage cooperation with other departments in order to utilise cross-departmental synergies.
Train your employees in the use of AI tools and technologies that are relevant to your department.
Develop KPIs and metrics to measure and evaluate the success of your AI projects.
Implement continuous improvement processes to increase the efficiency and effectiveness of your AI solutions.
Promote a culture of innovation and experimentation in your department.
Use feedback loops to continuously improve the implementation of AI.
Ensure that your department has the necessary IT infrastructure to successfully implement AI projects.
Communicate successes and best practices within the department to promote employee acceptance and commitment.

Step 7: Ideas for other departments

Work with other departments to identify specific challenges that can be addressed by AI.
Develop cross-functional pilot projects to demonstrate the benefits of AI.
Encourage the exchange of ideas and best practices between departments to create synergies.
Train employees in other departments in the use of relevant AI tools and technologies.
Implement a cross-departmental feedback system to support the continuous improvement of AI projects.
Develop KPIs and metrics to measure the success of cross-functional AI projects.
Encourage collaboration between IT and business departments to ensure that AI solutions meet the needs of all users.
Ensure that all departments have the necessary IT infrastructure to successfully implement AI projects.
Communicate successes and best practices across departments to promote employee acceptance and commitment.
Use cross-departmental workshops and meetings to promote the exchange of knowledge and develop innovative ideas.

Step 8: Expertise of employees

Develop a comprehensive training programme to strengthen the skills of your employees in the field of AI.
Offer regular further education and training courses to keep your employees' knowledge up to date.
Encourage participation in external conferences and seminars to support the transfer of knowledge.
Implement a mentoring programme in which experienced employees pass on their knowledge to younger colleagues.
Utilise e-learning platforms to provide flexible and accessible training opportunities.
Encourage cross-departmental collaboration to support the exchange of ideas and best practices.
Develop KPIs and metrics to measure the progress and effectiveness of the training programmes.
Ensure that all training programmes are practical and tailored to the specific needs of employees.
Encourage employees to actively participate in the development and implementation of AI projects.
Develop a long-term competence strategy that ensures the continuous development of expertise in the field of AI.

Step 9: Competence of managers

Develop special training programmes for managers to strengthen their understanding and competence in dealing with AI.
Offer regular training courses and workshops to keep managers' knowledge up to date.
Encourage participation in external conferences and seminars to support the transfer of knowledge.
Implement a mentoring programme in which experienced managers pass on their knowledge to younger colleagues.
Utilise e-learning platforms to provide flexible and accessible training opportunities for managers.
Encourage cross-departmental collaboration to support the exchange of ideas and best practices.
Develop KPIs and metrics to measure the progress and effectiveness of leadership training programmes.
Ensure that all training programmes are practice-oriented and tailored to the specific needs of managers.
Encourage managers to actively participate in the development and implementation of AI projects.
Develop a long-term competency strategy that ensures the continuous development of expertise and leadership skills in the field of AI.

The view from scientific research

The introduction of artificial intelligence (AI) in companies brings with it many challenges, especially for small and medium-sized enterprises (SMEs). Despite the major benefits that AI can offer, such as increased efficiency and cost-effectiveness, many SMEs are still hesitant to implement it. One reason for this is scepticism as to whether AI is even suitable for smaller companies, as resources are often limited and there is a lack of the necessary data infrastructure[1].

To overcome these hurdles, it is important to build trust in the technology and strengthen the skills of employees. Assessment tools and guidelines for AI applications can be helpful here[1]. A holistic implementation in the corporate strategy is also often neglected, but is crucial for the successful use of AI in marketing and other areas[3].

Ethical and legal aspects

In addition to the technical challenges, the use of AI also raises ethical and legal questions. For example, there is a risk that AI-supported decision-making processes could lead to discrimination. The legal system is not yet sufficiently prepared for this[5]. There are also fears of changes in the doctor-patient relationship as a result of AI in the healthcare system and increasing economisation[7].

Potentials and limits

Despite the challenges, AI offers enormous potential in many areas. In medicine, it promises better care and more efficient processes[7]. AI can also provide valuable support in product planning[9] and project management[16], for example by prioritising tasks and making work easier. However, it is important not to use the term "AI" in an inflationary way and to take a sober view of its actual capabilities[16].

The introduction of AI in companies requires careful consideration of opportunities and risks. In addition to technical aspects, ethical, legal and social issues must also be taken into account. However, with the right approach and support, SMEs can also benefit from the advantages of AI. A holistic strategy that creates trust and strengthens the skills of employees is crucial. In this way, AI can realise its potential and become a valuable tool in many areas.

This KIROI masterplan offers a comprehensive approach to implementing AI in IT. By applying the KIROI steps in a structured way, companies can ensure that all levels of the organisation are prepared for the use of AI and can use these technologies effectively.

Find out more on KIROI.ORG

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KIROI masterplan: Implementation of Artificial Intelligence in IT

The view from scientific research

Ethical and legal aspects

Potentials and limits

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