TL;DR
Business leaders are shifting focus from AI adoption to demonstrating measurable value and ROI. Over 90% of organisations expect rising technology budgets with AI as a primary driver, bringing continuous costs in infrastructure, energy, and specialist talent. Success requires unified visibility across teams, hybrid cloud approaches for data control, and Technology Business Management frameworks to link IT spend directly to business outcomes.
The ROI Challenge in AI Adoption
The conversation in boardrooms has evolved from “what can AI do?” to “what value is it delivering, and at what cost?” Organisations integrating AI tools are achieving enhanced efficiency and improved business outcomes, but face a critical challenge: demonstrating tangible return on investment to justify further investment.
Many organisations lack the information needed to evaluate technology spend decisions properly. ROI metrics often operate in silos, communicated differently across finance, IT, and operations. Finance teams focus on capital versus operational expenditure, whilst IT measures utilisation rates and uptime. This disconnect means many organisations stop evaluating ROI once projects are underway, making it difficult to accurately track AI value realisation.
A unified taxonomy and shared data source is essential. When measuring AI value, it must translate into business metrics showing cost against achieved business outcomes, particularly as generative AI workloads remain notoriously compute and energy-hungry.
Managing Continuous AI Costs
Unlike past technology rollouts, AI is not a simple one-time capital investment. Data from Apptio indicates over 90% of organisations expected technology budgets to rise this year, with AI as one of the most significant spend drivers. AI brings continuous costs in IT infrastructure, energy, people, and processes. Training models and running inference requires massive compute power in energy-intensive data centres, whilst specialist AI talent remains scarce and expensive.
AI serves diverse functions including data analysis, process automation, fraud detection, and cybersecurity. Scaling these applications requires absolute clarity about costs and benefits. Leaders must distinguish between spend involved in training large foundation models versus embedding third-party services into existing processes.
Technology Business Management frameworks can help by linking IT spend directly to business outcomes. This enables leaders to spot waste, prioritise high-value projects, and prevent AI from repeating the same overspend patterns many businesses encountered with cloud adoption.
Strategic Hybrid Approaches
Data location has become one of the most pressing questions when scaling AI projects. Boards are increasingly concerned about intellectual property loss, regulatory compliance, and risks of feeding sensitive datasets into third-party systems.
Whilst cloud remains indispensable for scalability, there’s growing recognition that not every workload belongs there. Some companies are pulling specific processes back on-premises to regain predictability, strengthen compliance, and control long-term costs. A hybrid approach—balancing cloud agility with on-premises control—is becoming the default strategy.
Looking Forward
Success depends on treating AI with the same discipline as any other strategic investment. Four principles stand out: prioritising visibility into investments and project performance, taking hybrid approaches to cloud strategies, continuously monitoring and reviewing costs, and linking IT investments to measurable business outcomes including productivity gains, better decision-making, and improved customer outcomes.
The most successful companies will be those that know how to manage trade-offs, invest pragmatically, and smartly manage data. As more innovative projects emerge, technology, business, and finance leaders must partner closely to prove value and increase internal expertise, ensuring AI delivers on its transformative promise whilst maintaining financial sustainability.
Source: TechRadar Pro