It's undeniable. AI is gaining more and more traction daily, and the UK is slowly positioning itself as a leader in the market. With a robust AI workforce of more than 360,000, the country is making impressive strides. In fact, Britain boasts twice the number of AI-based organisations as any other European nation.
But while the British enthusiasm for AI is clear, it's crucial to ensure that AI adoption is tailored to each business's specific needs and the return on investment (ROI) is closely monitored. Yes, AI is already revolutionising various aspects of business operations, but implementing and profiting from it comes with its own set of challenges.
Drawing parallels between cloud computing and AI adoption reveals striking similarities, and business leaders must take note. For instance, similar to how cloud computing allows organisations to scale their computing resources on demand, AI adoption enables businesses to scale their decision-making and automation capabilities therefore saving money. However, businesses need to approach both cloud computing and AI adoption with the same level of caution, managing and monitoring each investment effectively. Organisations need to take what they have learned from their rapid cloud adoption, which has led to spiralling, unpredicted cloud bills. And this is where applying FinOps principles to AI adoption can help.
Applying FinOps principles to AI implementation
AI is weaving its way into every organisation's fabric, and businesses are being pushed to quickly build an AI strategy that will drive revenue forward and propel employee productivity to new heights. The UK saw a 449 per cent increase in AI spending across the private sector in the first quarter of 2024 compared to the same period last year. However, building a strong foundation is essential before integrating AI into business operations.
When incorporating AI into corporate activities, companies must first recognise the importance of applying FinOps principles to their AI journey. Fundamentally, FinOps focuses on cost management, resource allocation and monitoring ROI. By understanding and implementing these principles, businesses can streamline their processes, avoid errors and pave the way for successful AI adoption – without unexpected expenses.
When applying these principles to AI, companies can effectively control rising costs and maximise ROI, especially during unpredictable economic periods. This strategic planning is essential and should lay out a clear roadmap for AI integration, including identifying use cases, selecting appropriate AI tools and devising a structured implementation plan. This approach empowers organisations to navigate the challenges of AI adoption and ensures a seamless integration of technology with business objectives and an ROI.
Cost control in AI implementation
With the demand for AI solutions for business acceleration being high, the costs have also skyrocketed. According to the UK government, spending on AI technologies could surge to between £27.2 billion and £35.6 billion by the end of 2025. As such, integrating AI is likely to be a substantial investment for organisations, making effective strategies to manage and control the costs associated with AI vital.
The first step should be developing a budget and forecast for AI projects. Accurately estimating the costs involved in implementing AI initiatives will enable organisations to allocate resources more effectively and avoid unexpected expenses. Another approach businesses could take is to use cost optimisation techniques - which involve identifying opportunities to minimise expenses without compromising the quality or effectiveness of AI solutions. For instance, organisations can consider using cloud-based AI services, which offer scalability and cost efficiency compared to in-house infrastructure.
The bottom line is that all businesses want to ensure that their investments are making operations better, faster, and ideally cheaper, all while avoiding unexpected costs. To maximise the value derived from AI solutions while minimising financial risks, businesses need to have control over costs.
Monitoring ROI
A recent survey found that CIOs might be eager to scale AI, but they also acknowledge the difficulty of demonstrating an ROI. Therefore, monitoring the ROI is essential for CIOs to evaluate the success and effectiveness of their AI implementation. Developing appropriate metrics and benchmarks will allow these CIOs to measure the impact of AI on their operational performance and easily demonstrate the impact to the rest of the C-suite. It is crucial to track and analyse the effects of AI on various business functions, including customer engagement, sales growth, operational efficiency, and cost savings.
Regular performance assessments enable businesses to use data to identify areas where AI generates positive results and recognise areas that need improvement. Additionally, applying FinOps principles to monitor and manage AI-related expenses helps identify opportunities for cost savings and optimise usage. This, in turn, leads to better visibility into AI investments, evaluation of the financial impact of AI initiatives and informed decision-making to maximise ROI.
As AI continues to reshape business operations, it is crucial for organisations to carefully plan their implementation, manage costs effectively and focus on maximising the ROI of AI – and this is where applying FinOps principles can help. Developing cost-control strategies and efficiently allocating resources, businesses can use these principles to navigate the complexities of AI adoption. Ensuring a seamless integration delivers value for the organisation and its stakeholders.