Using ‘Artificial Intelligence’ (AI) in companies in seven steps

The following list is a general guideline on how – especially profit-oriented, medium-sized – companies could address the topic of Artificial Intelligence or, more generally, the challenges of digitization (simply replace <AI> with <Digitalization>).

Needs Assessment

Identify the current challenges and needs of your company. Consider which processes could or should be automated or optimized, and how AI/ML (Machine Learning) could contribute to this at all. Keep in mind your primary business objectives (vision and mission), real and realistic stakeholder needs (external and internal), and your competition. Examine existing processes and workflows closely: Identify any potential bottlenecks, “pain points”, inefficiencies, or issues within the company that require optimization. Then prioritize all identified needs according to your business objectives.

Feasibility Study

Investigate the organizational, technical, and financial feasibility of AI solutions in your company. This includes assessing the required infrastructure, resources, and costs. The most relevant resource are the people involved and affected (time budget, effort, enablement, willingness/curiosity/openness). Technological, possibly regulatory, and purely monetary considerations follow afterward.

Identify Business Cases

Identify and develop as specific as possible real use cases for AI in your company. These can include process automation, data analysis, customer communication, or content creation. The more specific and accurate these cases are developed and described, the more promising the outcome! Close collaboration and open, content-related conversations between company-/business-specific and AI/IT expertise is crucial for a potential success. (Questions like (“I didn’t understand that yet, please explain it again to me” are always welcome) Always consider where and by whom value added occurs within the company.

Pilot Projects

Launch pilot projects to test AI solutions in selected areas of your company. This allows you to assess the effectiveness and benefits of the technology before implementing it on a larger scale. Also take into account the current technological developments and innovations relevant to your business. These may offer additional opportunities for improvements or growth. (Competitive advantage) Pay attention to a serious but ambitious schedule.

Performance Measurement

Define Key Performance Indicators (KPIs) and monitor and analyze these KPIs to assess the impact on value added in your company. Conduct a Cost-Benefit Analysis (CBA) – including the zero-option and based on the KPIs – to measure the success or failure of AI solutions in your company.

Scaling and Integration

If the pilot project(s) is/are successful and deliver the desired results, try to scale the AI solutions and integrate them into your existing systems and processes. (“Lessons learned” / economically multiple use)

Training and Change Management

Create an environment where your employees can embrace and effectively use new technologies. Invest in training and change management to promote the acceptance of AI solutions within the company.

Services offered

Expertise and advice on possible use cases of AI technologies in your company Specific, usage-based recommendations and implementation of real applications. Unlocking the power of AI and ML for your business.

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