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    When businesses assess "how to implement AI," in addition to using "enterprise design thinking" or "traditional design thinking" to determine AI use cases within the organization, they also face the critical question of "how to choose AI technologies and solutions."

    Since AI technologies and solutions are often integrated into various business applications to enable data analysis, provide strategic recommendations, predict performance, and support critical decision-making, it is crucial for businesses to ensure that these AI systems adhere to "Responsible AI" principles. Verifying their reliability and trustworthiness is essential when selecting AI technologies and solutions.

    However, many businesses face challenges such as limited capabilities in strategy development and evaluation, an inability to define data quality standards, and a lack of industry guidelines. These gaps indirectly increase operational risks when planning to adopt AI.
Key Factors in Choosing AI Technologies and Solutions
Before deciding to invest in AI technologies and solutions, businesses should consider the following five points. This not only helps reduce implementation risks but also enables effective assessment of the suitability of AI technologies and solutions for the organization.

Business Strategy
  • Evaluate how AI can enhance business decision-making, create a competitive advantage in the market, and positively impact business performance.
  • This includes defining the scope, timeline, and potential impacts of AI applications set by the internal AI or data teams, the implementability and adaptability of AI technologies and solutions, and the development vision of AI technology and solution vendors.

Commercial Strategy
  • Evaluate how AI technologies and solutions align with broader business strategies.
  • This includes assessing the business value of the investment, performance measurement standards (KPIs), total cost of ownership (TCO), ongoing adjustment and management costs, and management approaches for addressing uncertainties regarding outcomes.

Data Strategy
  • Evaluate the effectiveness of AI technologies and solutions based on the premise of achieving business goals through the analysis of valuable data.
  • This includes preparing the necessary datasets, understanding data interrelationships, and ensuring compatibility between AI applications and future data strategies.

Ethics and Sustainability
  • Assess whether AI technologies and solutions have a positive impact solely on ethics and sustainability.
  • This includes ensuring accountability within the organization for AI implementation, evaluating AI for bias, adherence to ethical standards, alignment with diversity and inclusion, and compatibility with sustainable resource usage.

Governance, Risk, and Regulation
  • Establish and integrate risk management strategies into AI technologies and solutions to enhance operational resilience against potential digital risks posed by AI applications.
  • This includes managing data sources, addressing cybersecurity threats and personal data risks, and overseeing AI governance practices.

Electrum Cloud Offers Professional Strategy Consulting Services to Help Businesses Find the Most Suitable AI Technology Solutions
When selecting and implementing AI technologies and solutions, a comprehensive evaluation helps reduce implementation risks, ensures the applicability of the AI technologies and solutions, and maximizes business value.

Electrum Cloud has a professional strategy consulting team and offers "Corporate AI Design Thinking Workshops," which includes five key components: objectives, data and policies, understanding, reasoning, and knowledge. These workshops guide businesses in clarifying the reasons for adopting AI, identifying the problems they wish to solve with AI, and defining expected outcomes.
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