Artificial Intelligence has officially graduated from niche technology to a core operational driver. In 2025, the AI revolution will continue to be defined by Generative AI (GenAI) and the rise of AI agents. Deloitte aptly describes AI as being “woven into the fabric of our lives”, shifting from conceptual pilot projects to tangible, scaled applications across industries. CB Insights goes a step further, identifying AI agents as a game-changer capable of mimicking and surpassing human productivity in repetitive, decision-heavy tasks.

What Are AI Agents?

AI agents are sophisticated, autonomous systems powered by machine learning and predictive analytics. Unlike earlier AI tools that respond passively to human input, these agents adapt automatically to handle intricate workflows like financial reporting, inventory management and customer engagement without human intervention.

The biggest advantage of AI agents is their ability to make decisions and identify optimal outcomes, improve accuracy and efficiency – whether it’s adjusting retail pricing strategies or recommending precise healthcare treatments. But be careful – for more complex and critical applications it’s essential that we keep an extremely close eye on how these models are adapting and why.

AI Opportunities for SMEs

For SMEs, AI presents an exciting paradox—while it offers massive productivity gains and decision-making precision, it also demands careful adoption. Research by PwC estimates AI could contribute $15.7 trillion to the global economy by 2030, with SMEs playing a critical role in that growth. Yet, concerns over high costs, technical know-how and data ethics and biases persist. Our recommendations include:

  • Start small by integrating low-cost AI tools (like CRM systems with predictive capabilities).
  • Focus on AI solutions that offer quick returns on investment, such as chatbots, analytics platforms, or automated bookkeeping software.
  • Train your team to understand and utilise AI responsibly, ensuring trust and transparency in implementation.

The Hidden Challenges of AI: Energy consumption and sustainability

The power-hungry nature of AI is a growing concern for the tech industry and beyond. The International Energy Agency (IEA) warns that data centres alone could consume 10% of global electricity by 2030, up from 2% in 2020. As advanced AI models, including GPT-4, become ubiquitous, their colossal computational demands are leading to rising energy costs and an outsized carbon footprint.

AI systems are energy-intensive because the high-performance computing involved in training advanced models requires thousands of GPUs. The explosion of cloud-based solutions – in part to store and manage all this information efficiently – necessitates massive data centres and energy intensive cooling infrastructure.

The way forward: To navigate these challenges, businesses must embrace sustainable AI practices to mitigate energy consumption and environmental impact. Transitioning to green data centres powered by renewable energy sources or adopting localised solutions like on-premise, energy-efficient micro data centres can minimise transmission losses and optimise operational efficiency. Companies should also prioritise AI frameworks designed for lower energy consumption, which reduce computational waste while maintaining performance.

If you’re an innovator tackling the challenges of energy efficiency and responsible AI consumption, we’d love to hear from you. Get in touch to find out more about how Sussex Innovation can support you on your journey.

Read our overview of the political and economic landscape of 2025 and its impact on the business world here.