Productivity is one of the main advantages that companies expect from AI.
IT leaders who develop IT strategies generally cite the automation of routine tasks and the simplification of content as two of their main priorities. Foundry’s search has shown that improving employee productivity was the most cited commercial objective that causes AI (48%) investment. [1]
But while businesses seek to carry out these advantages, the technological debate extends beyond data and algorithms to another crucial part of the global puzzle: underlying equipment, in particular PC IA.
In the end, the transformation of the AI needs a foundation, and part of this will be the material companies used to deploy AI.
How PC IA allow productivity gains
IA PCs are designed to manage complex algorithms and large data sets, simultaneously managing several high -demand applications.
By performing workloads on disk, IA PCs also reduce dependence on the treatment of clouds and considerably reduce latency. Applications tend to operate more easily without data moving to remote servers, allowing efficient offline work. This device treatment is designed to accelerate task completion, increase productivity and improve the user experience.
Meanwhile, independent software providers (ISV) are increasingly looking to use AI fleas in productivity solutions, taking a head of Copilot + PCS applications from Microsoft.
The power of the multitasking
When selecting an IA PC, companies must look for devices capable of performing simultaneous high performance workloads.
The Lenovo Thinkpad T14S illustrates why such a robust multitasking is important. In tests by signal65, the system – which uses an AMD Ryzen ™ AI 760 AI processor – was up to 50% faster in multi -steam scenarios combining content creation and office productivity applications compared to a competing system with the Intel Core 7 165U.[2]
PCs powered by powerful processors can manage several demanding tasks simultaneously, hierarchical processors and allocating the computing power where it is necessary and adapt in real time to the requirements of various applications.
The impact on device performance for end users is deep. For example, while a user participates in a high-intensity video conference, a PC IA can simultaneously manage the translation of documents in real time and the creation of complex content, while undertaking background processes.
Productivity propulation anywhere
Of course, users are also likely to execute these workloads in distant places as in the office. IA PCs can help in this passage to work anywhere by considerably improving the quality and efficiency of collaboration tools.
For example, features such as real -time translation and automated transcription in videoconference can improve virtual collaboration. AI capabilities can also optimize the use of bandwidth during video calls, guaranteeing clear and coherent communication.
The electrical efficiency and the battery life are essential for these distant capacities to be used at their full potential, which makes the choice of processor key again.
A device strategy ready for the future
AI should transform employee productivity and stimulate business growth. And the pioneer breed of technology is definitely activated. Foundry’s research shows that almost two -thirds of organizations (61%) are increasing AI budgets, while 87% are looking for, piloting or really deploying AI. [3]
Organizations must start working now on the creation of a robust device strategy to provide productivity advantages faster and overcome the wave of IA innovation. Here, the power and efficiency of the PC processors will be a key determinant of success. IT teams should carefully assess the technical capacities of the devices they plan to use in the coming years to maximize the potential advantages of productivity.
Learn more About AMD Pro processors for the company.
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[1] Foundry, “Ai Priority Study 2023”, 2023 –
[2] Signal65, “AMD Ryzen ™ AI Pro Processor Leadership and TCO Advantages”, February 2025 – (page 3)
[3] Foundry, “Ai Priority Study 2023”, 2023 –
