Cloud May See More AI, Face Increased Geopolitical Friction

Hyperscalers and cloud data centers in the future might operate in a changed landscape where robots and AI fill gaps in the tech workforce and regional government entities seek more oversight of the space.

Gartner and Forrester issued separate predictions recently on what may lie ahead in the cloud. Gartner asserts that by 2025, some 50% of cloud data centers may deploy robots equipped with AI and machine learning capabilities. Meanwhile, Forrester points to the likelihood in 2022 of major hyperscalers preparing for antitrust reforms and geopolitical issues that may arise from government bodies across various regions.

Such regional regulatory pressure and reforms have been in the works for some time, says Lee Sustar, principal analyst with Forrester. “The growth of GDPR [General Data Protection Regulation] and the question of data sovereignty in Europe were some of the first indicators of differences in approach between the US on one side and the European Union the other,” he says.

Not all cloud services from providers are available in all regions, says Sustar, because of the effort it takes to roll out such services but there can be perceived obstacles to operating in different environments. For enterprise end users, this can mean asymmetrical cloud offerings being available in each region.

Geopolitical rivalries between the United States and China, he says, have laid the basis for certain tensions in the cloud landscape. “US-based hyperscalers have a truly global reach. That’s true of some but not all of the Asian hyperscalers,” Sustar says. “The question of who runs what data where becomes important from a basic data security standpoint.”

There may be internal debates within each country regarding such divides, he says, with the government of China instituting a number of interventions with big tech. “The government did mandate that state-owned enterprises move to state-owned cloud -- away from some of the market leaders,” Sustar says. “There’ve been interventions around financial and other considerations also.”

That could be interpreted as the government of China disciplining some Chinese operators, he says, to advance interests of the country. In the United States, there is an internal debate about deregulation of big tech, Sustar says, from social media to cloud infrastructure. “That’s less pronounced except that people who are more antitrust-oriented are populating key positions in the Biden administration taking a look at big tech,” he says.

Joint Warfighter Cloud Capability Initiative

Cloud providers have been linked to the national security program in the United States, Sustar says, seen in the JWCC (Joint Warfighter Cloud Capability) initiative, which is the successor to the cancelled JEDI (Joint Enterprise Defense Infrastructure) project. JEDI was meant to work with a single cloud provider, he says, but the process that led to the selection of Microsoft triggered legal challenges from rival providers. Under JWCC, there is an expectation that all major domestic cloud providers will play some role in the initiative, Sustar says. “Multicloud, US-based cloud tech companies being involved is a key component of how the US believes it needs to marshal its strength in geopolitical terms.”

The trend of government actors getting involved in this space is likely to continue, he says, based on broader geopolitical rivalries. “The question of cybersecurity becoming a key national security issue is also tied up inevitably with how cloud nationalism will take shape,” Sustar says. “One would expect the various national and regional operating environments will constrain how cloud operators work within them.” For example, Microsoft is segmenting data for its European cloud customers and installed a new leadership team in China. Meanwhile, France’s OVH is offering a disconnected version of Google Anthos software, he says, which allows them to meet data sovereignty requirements and other considerations.

Personnel demands to keep cloud data centers running smoothly may continue to pose a challenge, but according to Gartner, automation through AI and machine learning can alleviate some of the work. Gartner issued a projection that by 2025, about 50% of cloud data centers will deploy advanced robot resources that use AI, which could lead to an expected 30% increase in operating efficiency.

Tasks for Robots

Sid Nag, analyst and vice president in the technology and service provider group at Gartner, says while robots might not be new, they have not been fully exploited and leveraged in the automation of cloud data centers, where scale is a major issue. “It seems to me that provisioning, orchestration management, upgrades, monitoring activities that are very tedious, complex, and repetitive are still being done by humans,” he says. Those tasks are also error prone. “These repetitive tasks are perfect for a technology like robot.”

Nag says it is time to move discussions forward on AI, machine learning, pattern recognition, and natural language processing to drive IT efficiency in cloud data centers. “By talking to hyperscale cloud providers, I think they realize that’s the direction everybody needs to go,” he says. This could include tasks such as server upgrades, monitoring cloud data center security, and rolling out software at scale across cloud data centers.

This movement to robots that use AI and machine learning in cloud data centers might not just be for hyperscalers, Nag says. “Any cloud provider who has their own cloud data centers, or exchange providers, that are part of that hosted, colocation provider community can benefit from this.”

As seen in other aspects of IT, increased automation can lead to changes among desired skills for professionals in the field. There might be cases when robots summon humans to help them with a task, and there will also be plenty of high value work for people once performed repetitive jobs.

“They are going to be somewhat subservient to the robots in this model but conversely humans will also have to up their skills in programming these robots and updating the AI models that will be embedded,” Nag says.

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