Cloud is King, But McKinsey Warns of a Looming Edge Battle

Consulting firm McKinsey Digital has released its Technology Trends Outlook 2024 report, with critical next-generation connectivity technologies among the top 15 trends.

The report is partly based on self-reporting by around 1,000 technology leaders across 50 countries. It identifies cloud and edge computing, advanced connecting, generative and applied AI, and industrialization of machine learning and robots as the leading trends.

Of these, cloud and edge computing is the most mature technology, with 22% of respondents judging that they had fully scaled in this area and another 26% in the process of scaling.

25% said they were not investing in the cloud, with the other responses spread across the two other categories, experimenting (14%) and piloting (13%).

Advanced connectivity was next, with 17% scaled and 20% scaling, with 33% not investing.

AI is split into Generative AI and Applied AI, with 10% and 11% fully scaled, respectively.

Regarding machine learning, 8% were fully scaled, 19% were scaling, but 37% were not investing.

Robotic technologies have comparatively less traction, with only 5% of respondents saying they were fully scaled, with another 13% in the process of scaling. 41% said they were not investing in robotics.

Uncertainties and challenges

The report comments on each technology, with sections on uncertainties and future challenges.

For example, the report ranks security, privacy, and ethics as uncertainties in Generative AI. It suggests technology leaders consider issues such as the cost of model creation, how open sourced solutions are, and whether consumers will adopt the technology as rapidly as enterprises.

For advanced connectivity, McKinsey notes the telecoms industry’s ongoing struggle to invest in 5G “despite seeing incremental revenues from the technology.”

“Telco profitability is being strained as a result of competitive pricing, the commoditization of connectivity, challenges in monetizing better network quality, and the increasing traffic and deployment costs, all of which have led to challenging ROI,” the report said.

“While advanced connectivity undoubtedly creates value, the connectivity layer does not currently capture enough to sustain investment.”

A big question for the future was “what will 6G look like?” and the extent to which private network adoption would take off. There was also a question on whether there might be an oversupply of satellites in low orbiting (LEO) space.

“Edge will help enterprises maintain their edge.”

On the cloud, which was judged as the most mature technology, the rise of AI had driven a “massive increase” in cloud and edge usage in 2023, and the cloud market could expect compound growth of 30% through 2030.

“With the increasing growth of data volumes, particularly with the widespread deployment of AI and generative AI use cases, edge and cloud will continue to work in tandem,” said Bhargs Srivathsan, a McKinsey partner from the Bay Area in the US.

“Edge infrastructure will play a crucial role in enabling real-time inference much closer to the source of data generation. Edge will help enterprises maintain their edge.”

The report says that scaling could become uncertain “as the number of edge nodes and devices grows because edge computing does not benefit from the same economies of scale as traditional cloud computing.”

The was also a “limited availability of talent and management buy-in.”

A key question for the future of cloud and edge was whether “flexibility and positioning in a business and regulatory sweet spot make the edge more disruptive than cloud.”

“Or will inhibitors such as lack of interoperability and commonality of standards in networking prevent the edge from reaching its fully potential?” the report asks.

Long term endeavor

In 2023, McKinsey said that technology equity investments fell by 30 to 40% to approximately USD570 billion due to rising financing costs and a cautious near-term growth outlook, prompting investors to favor technologies with solid revenue and margin potential.

“This approach aligns with the strategic perspective leading companies are adopting, in which they recognize that fully adopting and scaling cutting-edge technologies is a long-term endeavor,” the report said.

McKinsey points out that scaling technology adoption also requires a conducive external ecosystem where user trust and readiness, business model economics, regulatory environments, and talent availability play crucial roles.

Geographical differences are also influencing different adoption scenarios.

“For instance, while the leading banks in Latin America are on par with their North American counterparts in deploying gen AI use cases, the adoption of robotics in manufacturing sectors varies significantly due to differing labor costs affecting the business case for automation,” the report said.

“Executives should monitor ecosystem conditions that can affect their prioritized use cases to make decisions about the appropriate investment levels while navigating uncertainties and budgetary constraints on the way to full adoption,” it added.

“Across the board, leaders who take a long-term view — building up their talent, testing and learning where impact can be found, and reimagining the businesses for the future — can potentially break out ahead of the pack.”

Image credit: iStockphoto/OSTILL