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Businesses are investing huge amounts in artificial intelligence technology, with vendors pushing it to customers and integrating it into nearly every software platform or application. But how many are actually ready for AI? According to an Omnia Strategy Group (OSG) analysis, only 28 percent of data centers are prepared to accept AI workloads and provide AI services that offer high performance levels.
For the rest, some of the biggest challenges include the following:
- Lack of graphics processing units (GPUs) and high performance CPUs
- Insufficient power from the grid
- Limiting internal power distribution infrastructures
- Cooling infrastructures can’t keep AI racks from overheating
- Not enough space to introduce liquid cooling
- Lack of internal AI expertise
“The economic implications of this readiness gap are profound,” said Omnia CEO Jessica Marie. “This lack of preparedness signals an urgent need for investment in digital infrastructure and highlights the critical role of APIs in supporting AI integrations.”
Despite these challenges, OSG’s AI report shows that 86 percent of businesses believe that AI will reshape global digital infrastructure, with most rushing to adopt AI any way they can. The findings make it clear that organizations must prioritize readiness, invest in infrastructure, and take a more strategic approach to implementation. Those who address these challenges head-on will be better positioned to leverage the full potential of emerging technologies in the years to come.
API and Infrastructure Constraints
Application programming interfaces (APIs) let different software applications communicate with each other and make it easy for platforms such as Amazon Web Services (AWS) and Microsoft Azure to integrate with vast numbers of other applications. APIs act as the go-between, providing a standardized method of interaction and integration. These APIs are already being used widely to combine AI with existing data analytics applications.
According to the Omnia report, 46 percent of businesses believe that integrating AI and machine learning workloads into existing operations will be difficult. APIs should ease the addition of AI into the enterprise and facilitate AI readiness, but confidence is relatively low that the current state of the technology will be sufficient. Only 27 percent of respondents think that current API management platforms will be able to support the complexities of AI integration over the next decade. Nearly half of potential AI users are also worried about the problems AI might cause in areas such as security, privacy, compliance, and automation. Many have realized that legacy infrastructure and IT complexity are likely to inhibit their AI ambitions.
The Geopolitical Implications of Artificial Intelligence
Some consider AI will herald a new era of happiness and productivity for mankind. Others see AI leading to a stark dystopian tomorrow. Certainly, geopolitical disruption is likely. Omnia numbers in the AI readiness report show that 79 percent see AI as having a significant geopolitical impact and as a major disruptor in the competitive landscape across the planet.
Any nation that lags behind in AI adoption and integration could find itself at a disadvantage politically, economically, and militarily. According to Omnia, 74 percent believe Artificial Intelligence will play a pivotal role in addressing climate change, future pandemics, and other global challenges. Most accept that disparities in AI capabilities between nations are likely to lead to conflict and heighten competitive dynamics.
“84 percent of respondents think that control over digital infrastructure will be very or extremely important in determining geopolitical influence in the coming decade,” said Marie. “This underscores how technological capabilities are increasingly shaping global power dynamics.”