With the rapid development of artificial intelligence technology, the demand for electricity is continuously increasing. According to a recent report by Gartner, newly installed servers consumed 195 terawatt-hours of electricity last year, equivalent to the annual electricity consumption of 18 million households. This figure is expected to soar to 500 terawatt-hours by 2027, roughly the annual electricity demand of 46 million households. Image source note: The image is generated by AI, and the image licensing service provider Midjourney. Furthermore, existing data centers consumed electricity in 2022.

According to a recent study released by Gartner, it is expected that 80% of software developers will need additional training related to generative artificial intelligence (AI) by 2027. This report reveals a significant trend: as AI technology evolves, companies will increasingly require specialized AI engineers to build AI-driven applications. Gartner's analysts believe that generative AI will undergo three distinct development phases in software development. In the short term, they anticipate a moderate increase in production.

According to the latest forecast from market research firm Gartner, by 2026, the market share of AI personal computers is expected to reach 43%. This means that in the future, large enterprises will almost exclusively choose computers equipped with AI technology. Doesn't that sound interesting? Gartner anticipates that the shipment volume of AI personal computers will reach 43 million units by 2024, a nearly 100% increase compared to 2023. Furthermore, by 2025, this figure is expected to surge to 114 million units, reflecting an impressive growth rate of 165%.

Artificial Intelligence (AI) is increasingly integrated into our lives and work, providing convenience while also posing risks. Gartner analyst Mesaglio points out that companies may encounter cost discrepancies of up to 500% to 1000% when applying AI, primarily due to rising vendor prices and companies' neglect of cloud resource usage. While AI processes unstructured data to obtain more information, the costs are high. Additionally, AI applications may lead to 'productivity leakage', where employees may use saved time for leisure rather than work.

At a recent Gartner IT symposium, analysts predicted that by 2027, 40% of generative artificial intelligence (GenAI) solutions will achieve multimodal integration, significantly up from 1% in 2023. The integration of multimodal GenAI can capture relationships between different data streams and expand benefits across various data and applications, supporting human multitasking in different environments. Gartner's report indicates that multimodal GenAI and open-source large language models will have a profound impact, benefiting enterprises in the next five years.

Generative AI is rapidly becoming a core tool across industries, with projections indicating it will attract over 100 million users by 2026. Industries such as healthcare, advertising, manufacturing, software development, financial services, and entertainment are extensively utilizing generative AI to significantly enhance work efficiency. In healthcare, AI enhances medical image analysis, designs new drugs, and personalizes treatment plans. The advertising industry efficiently generates content that aligns with brand tone using AI. In manufacturing, AI accelerates design processes and predicts equipment failures for intelligent maintenance. Software development leverages AI to generate and optimize code.

Gartner's latest research indicates that by the end of 2025, approximately 30% of generative AI businesses currently under testing will be abandoned by companies due to cost issues. The high deployment costs, ranging from $5 million to $20 million, along with an annual maintenance fee of $11,000, pose major challenges for AI projects. Gartner analyst Rita Sallam states that despite the long return on investment period for AI, 15.8% of companies have seen increases in revenue and 15.2% have experienced reductions in costs after adopting AI.

A recent report by the renowned market research firm Gartner reveals that, based on a survey conducted by Gartner in December 2023 among 5728 customers, a significant 64% of respondents expressed a preference against the use of AI in customer service. More notably, 53% of customers stated that if they found a company's customer service using AI, they would consider switching to a competitor. These figures undoubtedly serve as a wake-up call for customer service companies actively deploying AI se

By 2026, the number of traditional search engines is expected to decline by 25% as virtual agents capture their market share. With the emergence of generative AI solutions, the status of natural and paid search will be shaken. Search engine algorithms will increasingly prioritize content quality to balance the quantitative advantages of AI-generated content. The practicality and quality of content remain the keys to success for organic search results. Businesses need to focus on creating helpful, professional, and trustworthy unique content for their customers.

The democratization of generative artificial intelligence (GenAI) will accelerate enterprise adoption and enhance the connection between employees and knowledge. The rising demand for AI trust, risk, and security management can improve decision-making accuracy. Intelligent applications, serving as foundational capabilities, will be widely used to enhance and automate work, receiving high attention from CEOs. Sustainable technology plays a crucial role in achieving ecological balance and human rights, with CIO personal compensation linked to the impact of sustainable technology.

🚀 AI Trends: Since the release of ChatGPT, generative AI has been on the rise, with enterprises continuously developing or adopting AI models. 📊 Forecast Numbers: The Gartner report predicts that by 2026, 80% of enterprises will use generative AI APIs or models, a significant increase from less than 5% in 2023. 💡 Innovation Directions: The report highlights innovative areas that will have a profound impact on organizations over the next decade, including generative AI applications, foundational models, as well as AI trust, risk, and security management.

According to Gartner, the global semiconductor sales revenue for executing AI workloads is expected to grow by 20.9% year-over-year in 2023, reaching $53.4 billion. By 2027, AI chip revenue is expected to more than double compared to the market size in 2023, reaching $119.4 billion. Many industries and IT organizations will deploy systems containing AI chips as the use of AI workloads within enterprises matures.

The 2023 Gartner Hype Cycle for Emerging Technologies indicates that generative artificial intelligence is at the peak of 'inflated expectations'. Generative AI is influenced by overly high expectations, misleading vendor marketing, and market confusion. The next phase will enter the 'trough of disillusionment', but there is still debate about whether it can deliver long-term value to businesses and society.