Just as the internet, mobile devices, and cloud computing changed our perspective on the world of work, generative artificial intelligence is opening a new era with immense potential to alter the nature of work itself. However, this technological revolution is already placing new and unprecedented demands on the infrastructure that supports our business, prompting companies to radically rethink their networks and computing capabilities.
Article contents:
- Massive pressure on network infrastructure
- Humans are still essential: The automation paradox
- Human-AI collaboration
- The network as the nervous system for AI
- Building infrastructure for a new era
- The future: Connected intelligence and human-machine symbiosis
- Frequently asked questions
Massive pressure on network infrastructure
Artificial intelligence workloads require immense computing power and rapid data transfer. According to new research from Cisco, nine out of ten companies (91%) are boosting their investments in computer networks to handle AI demands. Nearly two-thirds of companies (71%) indicate that AI requirements exceed the capacity of their current data centers.
This is why 88% of companies are increasing their computing capacity wherever possible, whether on-premises or in the cloud. Traditional infrastructure is no longer sufficient to keep pace with the rapid evolution of artificial intelligence and its applications.
Humans are still essential: The automation paradox
Despite concerns that AI will replace humans at work, the current reality appears different. Recent studies indicate that the impact of generative AI on working hours or earnings remains limited so far. Rather than replacement, the AI era appears to be about finding ways to enhance human capabilities with artificial intelligence.
Anurag Dhingra, senior vice president at Cisco, says: “AI can do a lot of human-like work at machine speeds, but it cannot replicate the unique traits that define us.” Here lies the paradox: the more automation there is in the workplace, the more important human interactions become.
“Solving complex problems and sparking innovation happens when people discuss and collaborate in real-time,” Dhingra adds. “The sheer volume of information generated by AI actually amplifies the need for human oversight and communication.”
Human-AI collaboration
We are already beginning to see the potential for real-time human-AI collaboration. Logistics teams can use AI agents to autonomously gather data from demand forecasting, procurement, and tracking systems to fix supply chain bottlenecks before they happen. Product marketing teams can use AI to reduce product campaign launch times. This type of collaboration requires infrastructure capable of handling these complex tasks.
The network as the nervous system for AI
To achieve the full potential of human-AI collaboration, workplaces need a strong digital foundation. At the heart of this foundation is the network, which Dhingra describes as «the essential nervous system for AI».
Traditional networks were not designed to meet the demands of AI workloads in terms of bandwidth and reliability. As AI applications increase network traffic, organizations face growing complexity in managing traffic and devices.
«If your network is not up to par—if it has low capacity or high latency—frustrating delays, connection drops, and a fragmented experience await you», Dhingra says. «Without this foundation, human potential amplified by AI will be severely hindered».
Building infrastructure for a new era
Building an infrastructure that can handle both human collaboration and AI workloads requires specific capabilities. For human interactions, networks need ubiquitous, high-quality, low-latency connectivity to ensure clear video and audio calls and fast access to cloud applications.
For AI, the requirements are even higher. «AI agents do a lot of work and communicate at machine speeds», Dhingra says. «Ultra-low latency is critical for autonomous operation and real-time decision-making».
Advanced artificial intelligence is needed within the networks themselves to monitor, diagnose, and even correct issues before they become widespread outages. This is already possible thanks to new network components and IT management platforms that use real-time data and automation to drive intelligent action.
The future: Connected intelligence and human-machine symbiosis
Dhingra believes the working world is heading toward a true symbiotic relationship between humans and AI, supported by intelligent infrastructure. «As AI evolves from assistants to autonomous digital workers, the workforce is expanding to include digital workers (software agents) and even embodied AI, all communicating and collaborating at machine speed and scale».
Dhingra calls this symbiotic relationship «connected intelligence»—the close collaboration between humans and AI agents, and even among AI agents themselves. Networks will dynamically adapt to the demands of digital workers, optimize traffic, and predict and prevent issues to ensure robust, high-speed connectivity. The infrastructure supporting this transformation is the critical component to making it happen.
Frequently asked questions
Q: How does artificial intelligence affect corporate infrastructure?
A: AI places immense pressure on networks and data centers due to its high requirements for computing power and data transfer speed, prompting the majority of companies (91%) to increase investments in upgrading their infrastructure.
Q: Will AI replace humans at work?
A: So far, evidence suggests that AI enhances human capabilities rather than replacing them. In fact, the more automation increases, the more important human interactions and oversight become for solving complex problems and driving innovation.
Q: What network requirements are needed to support artificial intelligence?
A: Networks supporting AI require high bandwidth, superior reliability, and ultra-low latency to enable autonomous operation and real-time decision-making.
Q: What is «connected intelligence»?
A: It is a term describing the symbiotic relationship and close collaboration between humans and AI agents (digital workers), and even between AI agents themselves, in a work environment supported by intelligent and adaptive infrastructure.
