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The Generative AI Gap Year

2025 is being called a transitional year for generative AI, as businesses and governments work to address energy demands, ethical concerns, and uneven adoption

The Generative AI Gap Year

What’s happening
Deloitte’s Global TMT Predictions 2025 report describes this year as a transitional or “gap year” for generative AI and the broader tech, media, and telecom sectors. The excitement around generative AI remains high, but implementation challenges are slowing full adoption.

Key challenges holding AI back

  1. Energy and sustainability issues
    Generative AI models, especially large language models, are demanding massive amounts of energy. Some forecasts suggest data centers may consume up to 8% of national energy by 2030. Companies are exploring more sustainable solutions like liquid cooling and renewable energy sourcing.
  2. Deepfake concerns and trust gaps
    The use of generative AI for synthetic media is growing rapidly, making it harder for people to trust what they see and hear online. Deepfake incidents are rising, and the tools to detect and manage them are still catching up.
  3. Gender disparity in adoption
    Adoption of generative AI tools is not equal across all demographics. In countries like Australia, studies show men are more likely to use generative AI (around 70%) compared to women (around 40%). Closing this gap is important for inclusive innovation.
  4. Cautious use of AI agents
    Despite excitement about AI agents that can automate tasks and make decisions, most companies are only experimenting. Few are investing heavily yet, with major growth expected after 2027.

What this means for businesses
A recent survey of over 400 CIOs found that 76% view generative AI as critical for improving operations and creating new products. However, trust remains low among consumers. Fewer than half of people feel confident in AI-generated content, and many are calling for clearer labels and transparency.

The bottom line
2025 is not the year of peak generative AI growth. It is a year of preparation. Companies are working through infrastructure, regulation, ethics, and trust challenges. Those who build strong foundations now will be better positioned for the next phase of AI evolution in the coming years.

A1, 2025, design
2 min read
Jun 27, 2024
By Ugwuanyi Adaobi
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