First, global AI investment continues to surge, with spending projected to reach $2.52 trillion in 2026, according to Gartner. However, many organizations still struggle to convert AI experimentation into measurable business value. In fact, analysts estimate that 90–95% of generative AI projects 失敗する deliver meaningful returns. Consequently, Gartner notes that many initiatives have entered the “Trough of Disillusionment,” where hype fades and ROI questions intensify. Nevertheless, analysts argue this phase offers companies a chance to reassess strategies and refocus AI efforts on practical outcomes.
One key priority is capacity building. The rapid growth of AI systems necessitates a significant expansion of infrastructure, including AI-optimized servers, data centers, and computing capacity, to train and run models. Gartner expects spending on AI infrastructure to increase sharply as hyperscalers and technology providers build the platforms required to support next-generation AI systems.
The second strategy is developing strong technology partnerships. Rather than building complex AI systems independently, most organizations will rely on established vendors across cloud, software, and data platforms. Analysts suggest companies should evaluate which AI capabilities they need to own internally and which can be delivered through trusted partners.
The third recommendation is to avoid random AI exploration. Many organizations launched ambitious “moonshot” AI projects without clearly defined business outcomes. Successful initiatives focus on specific business problems, supported by strong data foundations and operational processes.
Another important factor is aligning incentives with technology providers. Outcome-based or co-development partnerships, where vendors share responsibility for results, can help ensure that AI projects deliver measurable value rather than experimental prototypes.
Ultimately, organizations that combine infrastructure investment, strategic partnerships, and disciplined project selection will be better positioned to turn AI experimentation into real operational impact.
ソース：
https://www.zdnet.com/article/how-to-target-your-ai-investments-gartner/
