There is a new gold rush in the world of technology, and its name is Artificial Intelligence. Every organisation, from a startup to a global corporation, wants to implement its predictive models, intelligent chatbots and recommendation systems.
The public cloud, with its promise of infinite scalability and flexibility, seems the ideal place to realise these ambitions. AI is the ticket to innovation and gaining competitive advantage. Enthusiasm reigns and the possibilities seem endless. And then comes the bill.
Suddenly, the promise of a revolution turns into a headache for IT and finance departments. It turns out that training advanced models and handling millions of queries in real time generates costs that can surprise even the most experienced managers.
This scenario is becoming increasingly common. For artificial intelligence to become a true friend of business and not a financial nightmare, it needs a strategic partner. That partner is FinOps – the culture and practice of cloud-aware financial management that reconciles innovation with profitability.
Appetite grows, and with it the bills
AI has long ceased to be the domain of experiments in laboratories. It is a powerful business tool in which companies are investing huge resources. It is no surprise that more than 40 per cent of IT budgets are now being spent on expanding cloud capabilities, mainly to handle AI workloads.
Technology leaders are well aware of the challenge ahead, with almost as many (40%) specifically citing artificial intelligence as one of the main factors that will drive up IT costs over the next three years.
The problem is that AI costs are not linear. They consist of powerful and expensive graphics processing units (GPUs), the transfer and storage of gigantic data sets and the constant running of models in production mode. This complexity overlaps with the already existing problem of controlling expenditure in the cloud.
With almost all (94%) IT leaders admitting they face challenges in optimising cloud costs, and nearly half (44%) of organisations having limited visibility into their spend, adding resource-intensive AI to the equation is a simple recipe for financial disaster.
Unforeseen cost spikes are becoming the norm rather than the exception.
To the rescue of FinOps: The cost charmer in the age of AI
This is when FinOps enters the scene. It’s much more than just cost monitoring tools. It is a cultural shift that builds bridges between technology, finance and business teams. It aims to instil shared responsibility for spending in the cloud, where every engineer and developer understands the financial implications of their decisions.
In the context of artificial intelligence, the role of FinOps becomes crucial and covers three main areas:
- Forecasting: Rather than acting blindly, FinOps practices allow you to estimate the costs of AI projects before they even take off. This enables informed decisions to be made about whether a project makes business sense.
- Continuous optimisation: FinOps teams act as personal trainers for the cloud infrastructure. They identify unused or oversized resources, help select the right machine instances and take care of cost “hygiene” on a daily basis.
- Allocating and measuring value: FinOps allows every dollar spent on the cloud to be precisely allocated to a specific product, project or department. This allows the business to finally answer the fundamental question: is our investment in AI actually paying off?
The technological ‘power couple’ in practice
What does AI and FinOps collaboration look like in action? Let’s imagine a few scenarios. A data science team wants to train a new complex model. Instead of running the most expensive GPU instances on-demand, thanks to FinOps they can schedule this process for overnight hours, using much cheaper spot instances.
Another example is a model that supports recommendations in an online shop. Instead of maintaining full computing power 24/7, the systems automatically scale during peak hours and almost shut down at night, generating huge savings.
The most important aspect, however, is to link costs to real business value. With FinOps, a company can see that although the new recommendation model costs 20% more, it has simultaneously increased conversions by 35%. This turns the discussion about costs into a conversation about a strategic, measurable investment.
Sustainable innovation
Investing in AI without a solid FinOps foundation is like sailing on a rough ocean without a map and compass – an exciting but extremely risky expedition. Combining the power of AI with informed financial management is today’s new standard for creating sustainable and profitable innovations.
It is through this approach that artificial intelligence can fully realise its promise and become a reliable best friend in the development of any organisation.
