AI predictions for 2025 highlight scalable adoption, tailored applications, and multi-modal systems as key drivers of transformation, alongside increasing focus on regulation and energy efficiency.
Copyright: cio.com – “12 AI predictions for 2025”
This year we’ve seen AI move from pilots into production use cases. In 2025, they’ll expand into fully-scaled, enterprise-wide deployments.
Generative AI has seen faster and more widespread adoption than any other technology today, with many companies already seeing ROI and scaling up use cases into wide adoption.
Vendors are adding gen AI across the board to enterprise software products, and AI developers haven’t been idle this year either. We’ve also seen the emergence of agentic AI, multi-modal AI, reasoning AI, and open-source AI projects that rival those of the biggest commercial vendors.
According to a Bank of America survey of global research analysts and strategists released in September, 2024 was the year of ROI determination, and 2025 will be the year of enterprise AI adoption.
“Over the next five to 10 years, BofA Global Research expects gen AI to catalyze an evolution in corporate efficiency and productivity that may transform the global economy, as well as our lives,” says Vanessa Cook, content strategist for Bank of America Institute.
Small language models and edge computing
Most of the attention this year and last has been on the big language models — specifically on ChatGPT in its various permutations, as well as competitors like Anthropic’s Claude and Meta’s Llama models. But for many business use cases, LLMs are overkill and are too expensive, and too slow, for practical use.
“Looking ahead to 2025, I expect small language models, specifically custom models, to become a more common solution for many businesses,” says Andrew Rabinovich, head of AI and ML at Upwork. LLMs aren’t just expensive, they’re also very broad, and not always relevant to specific industries, he says.
“Smaller models, on the other hand, are more tailored, allowing businesses to create AI systems that are precise, efficient, robust, and built around their unique needs,” he adds.[…]
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