Numerous reports and studies are consistently emphasizing the profound impact of generative artificial intelligence (AI) across various industries, urging sectors to recognize the significance of this technology. This wave of AI innovation not only symbolizes technological advancement but also signifies a fundamental transformation in business operations and strategic thinking.
In 2024, businesses will confront the challenge of effectively leveraging generative AI, assessing the benefits of its implementation, ensuring appropriate strategic integration, and enhancing advantages in decision support, innovation promotion, and efficiency improvement.
Table of Contents
List of FiguresFigure 1: Difference Between Analytical AI and Generative AI
Methodology
Primary research with a holistic, cross-domain approach
The exhaustive primary research methods are central to the value that the analyst delivers. A combination of questionnaires and on-site visits to the major manufacturers provides a first view of the latest data and trends. Information is subsequently validated by interviews with the manufacturers' suppliers and customers, covering a holistic industry value chain. This process is backed up by a cross-domain team-based approach, creating an interlaced network across numerous interrelated components and system-level devices to ensure statistical integrity and provide in-depth insight.
Complementing primary research is a running database and secondary research of industry and market information. Dedicated research into the macro-environmental trends shaping the ICT industry also allows the analyst to forecast future development trends and generate foresight perspectives. With more than 20 years of experience and endeavors in research, the methods and methodologies include:
Method
- Component supplier interviews
- System supplier interviews
- User interviews
- Channel interviews
- IPO interviews
- Focus groups
- Consumer surveys
- Production databases
- Financial data
- Custom databases
Methodology
- Technology forecasting and assessment
- Product assessment and selection
- Product life cycles
- Added value analysis
- Market trends
- Scenario analysis
- Competitor analysis
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