‘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

Businesses of all shapes and sizes are adopting AI to improve productivity and efficiency, but where they should be seeing improvements from this strategy, instead they’re seeing rising token costs, struggles with integrating tools, and more security risks.

As with all new technologies, adoption comes first and the procedures and governance are a few steps behind.

Experiments are taking place in almost every industry, and the lessons learned will help guide other businesses into successful adoption and AI maturity.

But employees fear replacement and sometimes spend more time questioning the results of their AI assisted work.

In the worst circumstances more work is created in trying to ensure employees trust the technology, and solving the new, unseen challenges that come with adapting an AI strategy.

AI costs and challenges in the road ahead Rising token costs are one of the biggest challenges businesses face.

Without clear ways to measure how token costs reflect performance, it’s very difficult to assess if AI spend is actually offering any performance benefits.

This is especially true when new, more powerful models are being released - and staying ahead of the competition means the accompanying, ever-increasing costs is the price of doing business.

But while employees may have just finished their training, or setting up a new workflow for one AI model, introducing the next can increase complexity and harm any new productivity gains.

There is therefore a balance to be struck between AI integration, its associated costs, and the productivity gains employees see.

Rampant spending and reckless adoption can turn an AI strategy from a business-boosting asset into a stress-inducing, trust-eroding liability.

Ruth Patterson, Managing Director, HP, UK & Ireland says that the businesses seeing the most success during this technological revolution aren’t necessarily integrating it at every turn.

Instead, they’re “applying it to practical workflows in a way that protects data and delivers real results.” I spoke to Patterson to understand the challenges businesses face in delivering an AI strategy that shows real results, and how organisations can tackle the challenges that come with adoption AI.

How are enterprise attitudes towards AI token use changing in 2026? Businesses are waking up to a simple but overlooked truth about AI: the more they use, the more it costs.