‘Once the right balance between cloud and local AI is found, organisations will find the sweet spot between cost, performance and security’: The future of AI strategy and how businesses can get the best results

As businesses across various industries increasingly adopt AI to boost productivity and efficiency, they are encountering rising token costs, integration difficulties, and heightened security risks. Initially, the focus was on experimenting with AI across different sectors, but now organisations are seeking a balance between cost, performance, and security.

Ruth Patterson, Managing Director of HP in the UK & Ireland, highlights that successful adoption of AI does not necessarily mean integrating it into every aspect of a business. Instead, they focus on practical workflows that protect data and generate tangible results. This shift in attitude towards AI token use in 2026 emphasizes the need for a strategic approach that balances cost, security, and performance.

The primary gains from AI so far have been in automating repetitive tasks, allowing employees to focus on more complex and creative work. To achieve this, organisations must provide access to the right technology and foster an environment that encourages employees to experiment with AI. However, as businesses move beyond initial experimentation, they become more disciplined in assessing the security of AI tools, their suitability for approved workflows, and the actual impact on productivity.

In scaling AI deployment, organisations must balance protecting sensitive data, managing operational costs, maintaining performance, and fostering employee trust. To achieve this, they must decide which AI workloads should be processed in the cloud and which can be executed locally. Ultimately, cloud AI and on-device AI are complementary approaches, each offering unique advantages in terms of performance, cost, and security.