It’s been more than a year since Artificial Intelligence (AI) became the dominant theme of the business world. 

In the past year, the business landscape has undergone significant transformations, compelling companies to rethink their operating models. One key driver has been the availability of generative AI, which has dominated the business world and found its way into strategy updates, earnings statements, and almost every stakeholder communication. At its current level of mass scale impact, AI may well surpass cloud and even the internet in its significance as a technology disruptor. This has profound impacts on how businesses navigate issues such as the ongoing skills gap, as well as their sustainability and security journeys.

AI continues to take center stage

It’s been more than a year since Artificial Intelligence (AI) became the dominant theme of the business world. The pressure to deploy it is relentless, with all companies surveyed in Cisco’s 2024 AI Readiness Index reporting a heightened urgency to implement AI solutions over the past year.

As companies embark on their AI adoption journeys, they are realizing that leveraging AI is not as straightforward as anticipated. Only 22% of companies in Vietnam are fully ready to capture AI’s potential, as reality sets in on what is needed to succeed. Despite AI being a priority investment, many companies are saying that returns on these investments are falling short of expectations.

The primary challenge remains infrastructure readiness, with gaps in compute, data centre network performance, and cybersecurity, amongst other areas. Only 38% of companies have the necessary GPUs to meet current and future AI demands and 39% have the capabilities to protect data in AI models with end–to–end encryption, security audits, continuous monitoring, and instant threat response.

As companies weigh the decision to build or buy AI solutions, modernizing data centres and leveraging plug-and-play AI infrastructure that evolves with their needs without adding complexity is crucial. Cisco’s AI PODS, for instance, offer infrastructure stacks tailored for specific AI use cases, integrating compute, networking, storage, and cloud management. This provides companies with a flexible starting point that can be easily adapted to meet their specific needs.

Guardrails and data governance in focus

As AI systems become more integrated into everyday life, discussions will focus on the responsible use, compliance, data protection, and anti-discrimination laws and AI quality standards.

Collaboration between the public and private sectors will be crucial to establish standards and baseline regulations that promote innovation and enhance AI safety. Global leaders will face mounting pressure to implement frameworks that improve the accountability of AI systems and address ethical and misinformation issues arising out of the use of AI, without inhibiting innovation. Companies will need to adopt responsible AI frameworks, conduct regular privacy assessments, and develop and implement a robust incident management plan to ensure judicious AI use.

Data privacy and security is another tenet of AI governance. As organizations increasingly operate across multiple jurisdictions, there will be increasing pressure on them to adopt measures that align data storage and processing with local data sovereignty laws. The next generation of privacy laws will continue to drive transparency, fairness, and accountability in spaces like data collection and use, cross-border data flows, and verifiable compliance. Companies will have to consider how their employees interact with AI systems and develop strategies to mitigate data breaches and associated risks through mock drills and continuous monitoring.

Cybersecurity moves to machine scale and networks

Networks will no longer just be used to connect. As more devices and services get connected, the risk and sophistication of attacks become greater. For example, social engineering attacks are more accessible given the amount of data that people share online with different platforms. Supply chain attacks also pose a problem, given the complicated web of technology suppliers that many businesses use in their operations. Advances in areas like quantum computing will further complicate the landscape. All of this will push cybersecurity to move at machine scale.

The network will emerge as a crucial pillar in managing workloads and serving as both the first and last line of security defence. This will become increasingly important as attacks conduct lateral movement attacks where they use one entry point to infiltrate the rest of the network to penetrate deeper into organizational systems.

AI will also transform security, assisting security teams and simplifying tool management, augmenting human insights, and automating complex workflows. Innovations that infuse security into the fabric of the network like Hypershield, architected to insert security enforcement into advanced silicon in servers and network devices, will redefine businesses’ ability to detect and respond to threats more effectively, and update and patch it all with lean teams.

The next great frontier of security involves not only securing businesses’ own four walls but also the extensive ecosystem of partners and vendors they rely on. As hyper distributed defences and federated data become the norm, companies that can leverage network will become self-defending digitally resilient enterprises.

Balancing sustainability and growth in an AI-powered era

The race to AI will continue to accelerate, leading to higher power consumption levels, which will impact carbon emissions across all scopes. By 2027, AI usage alone is predicted to use as much water as all of New Zealand. In a world where net-zero goals and carbon emission reductions target loom large, companies need to find solutions that balance sustainability goals with the growth opportunities that AI brings.

To achieve this balance, businesses will increasingly seek partners who can provide energy-efficient products and solutions or help them adopt circular business models aligned with their net-zero timelines. AI itself will play a crucial role in unlocking efficiencies for businesses. We see AI heralding a new era of energy networking, which combines software-defined networking capabilities, and an electric power system made up of direct current (DC) micro grids. This will enhance energy efficiency while delivering increased visibility, insights, and automation. Power over Ethernet is another innovative solution, delivering DC power to devices over copper ethernet cabling, which eliminates the need for separate power supplies and outlets.

Technological advancements in materials and design processes also contribute to balancing sustainability needs. Architectures like Cisco Silicon One chip exemplifies this by performing tasks faster and more efficiently with less hardware, reducing overall power consumption while minimizing electronic waste by extending device lifespans. Takeback and Reuse programs that allow companies to return hardware that has reached end-of-use will be important.

Humans and AI will co-exist

The future of work won’t be a binary choice between humans and machines; rather both will coexist to get work done. AI will evolve from just supporting tasks to forming an integral part of the future workforce, helping to address skills shortages across various roles. The pressing talent shortage in the technology sector is very real and is compounded by the ageing populations in many countries, especially so in Asia. Increased mobility of talent, and extremely diverse populations coming into the workplace will help to relieve some of those pressures.

This will also translate into benefits at work. Employees who can harness AI for their work will outperform others who do not use AI, achieving better quality of work, productivity, and efficiency. Possessing the right skillsets to leverage AI will be crucial to any technical and non-technical role. Every employee will have to upskill themselves to stay relevant.

Initiatives like the Cisco Networking Academy, which provides digital skills training including cybersecurity, are crucial in bridging the digital skills gap. As technology continues to advance, it is vital to persistently upskill, stay relevant, and leverage the latest innovations.

Conditions for a thriving workplace

Returning to the office should be a magnet, not a mandate. As we envision the future of work, it will be a tech-enabled one where job roles continue to evolve alongside technological advancements, much like the transition from fax to email and are now connected from anywhere. Work will happen in tech-enabled spaces and people will naturally seek the flexibility that technology brings to their personal lives in their work routines. This shift will raise questions around the value that the physical office will add to work.

As employees shift their mindset from coming to the office to do heads-down work to using this as an opportunity to connect, innovate and collaborate with their teams, employers need to cultivate an environment that supports this type of work.

Whether it’s about the type of work, the location it’s performed, or who it’s done by, trust is a crucial element at every stage of the process. Employers must trust that they have hired the right people for the right roles, and they will deliver the goals set for them. Likewise, employees must trust that their efforts will be recognized and rewarded by their employers, with opportunities for growth and development. Trust will become a reciprocal relationship, and the ability to foster this trust will distinguish high-performing teams and companies from the rest.