HOW TO BUILD AI CAPABILITIES WITHIN YOUR ORGANISATION

A lack of technical expertise and a shortage of staff – these are among the main reasons businesses back from adopting Generative Artificial Intelligence (GenAI) [1]. However, GenAI has the potential to revolutionise the way companies across all sectors and of all sizes operate. Drawing on our own experience, in this article we aim to provide specific recommendations for building AI capabilities within organisations.

We outline the steps organisations should take to prepare their staff to work with AI solutions whilst effectively advancing their own skills framework.

Step 1: Every team member understands the basics of artificial intelligence

Step 2: Establish development pathways for technicians and AI experts

Step 3: Strategy and innovation: the right skills for decision-makers 

Step 1: Every team member understands the basics of artificial intelligence 

Anyone wishing to strengthen a company’s capacity for innovation must ensure that all staff have a solid grounding in working with AI. 

1. Provide training in basic knowledge 

Offer training courses that provide a basic understanding of AI and its potential applications. An overview of the possible applications and a general introduction to the existing AI services offered by the major providers is particularly helpful. These services can be tried out in interactive training sessions to directly engage staff. Providers usually offer ‘playgrounds’ or simple examples for this purpose [2]. 

2. Prompting workshops 

Like most tools, AI tools must be used correctly to create real added value and inspire your staff. You should therefore organise workshops in which staff in all roles can learn how to interact effectively with AI tools such as ChatGPT. These workshops should teach participants how to formulate precise prompts and apply specific techniques such as the ‘chain-of-thought’ method [3].  

3. Data protection and security 

Train staff in the secure use of AI tools, particularly with regard to data protection and the processing of sensitive data. Establish a basic understanding of the challenges faced by today’s models – such as hallucinations and bias – and what this means for their use. However, also highlight solutions to enable correct usage.  

Step 2: Establish career paths for technicians and AI experts

In addition to the general fundamentals, role-specific specialisations are important in order to offer technicians and AI experts tailor-made development pathways. This involves not only imparting technical knowledge and skills for integrating AI services, but also fostering creativity and innovation through practice-oriented approaches. 

Step 3: Strategy and Innovation: The right skills for decision-makers  

Technological innovation can only emerge if the right strategic decisions are made. Decision-makers need AI skills to be able to tackle current challenges and identify future growth opportunities. Here’s how these skills can be acquired: 

To ensure successful implementation, we would like to offer you a few more tips.

Tip 1: Develop AI skills through practical approaches 

Training courses are a key component in developing AI skills, but should always be complemented by practical projects. This enables participants to gain a deeper understanding and to embed these skills within the company’s culture. 

1. Interdisciplinary teams: Form teams to work on cross-functional projects (e.g. a team comprising department heads, software developers, UI/UX experts and AI experts). 
2. Practical learning: Testing services from major cloud providers as well as specialised, smaller providers to gain hands-on experience with various AI services.  
3. Community engagement: Actively participating in an AI community to share experiences and learn from the latest developments.  
4. Measuring success: Use metrics to assess progress in developing AI skills, e.g. based on the requirements of AI certifications (e.g. the Azure AI-102 exam). Alternatively, you can set your own targets, e.g. the number of specific implementations on various cloud platforms as proof-of-concepts (POCs). 
5. Feedback loops: Regularly reviewing and adapting training programmes based on feedback and AI trends.

Tip 2: Achieving impact through scaling – introducing AI in small steps

Radical changes often meet with resistance from staff. Start making changes in small steps to build acceptance. It is important to have a clear vision for the use of AI and to work towards it. 

1. Optimise individual activities through the use of AI: these could be routine tasks within a process that are automated using AI. 
2. Adapt roles within the organisation: The aim is to develop an understanding of how individual tasks can be managed more effectively through targeted improvements, thereby enhancing the quality of work.
3. Fundamentally redesign business and work processes: The greatest impact is achieved when entire processes are transformed using AI, e.g. redesigning a service desk to process enquiries more quickly, or even mapping the entire value stream using AI, as is the case in software development: requirements analysis, code generation and log analysis during operation with the aid of AI. 

Conclusion 

Current developments in the field of AI have the potential to transform businesses in the long term. To achieve this, the necessary skills must be developed, depending on the role. As different groups benefit from learning from one another, we recommend developing new products in cross-functional teams to build a shared understanding of AI deployment. It is important to make the new technologies easily accessible in order to achieve broad acceptance amongst staff at an early stage.  

Do you have any questions or need assistance?

You can find out more about the possibilities of artificial intelligence for your business on our website.