[AI]AI in 2025: Purpose-driven models, human integration, and more

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As AI becomes increasingly embedded in our daily lives, industry leaders and experts are forecasting a transformative 2025.

From groundbreaking developments to existential challenges, AI’s evolution will continue to shape industries, change workflows, and spark deeper conversations about its implications.

For this article, AI News caught up with some of the world’s leading minds to see what they envision for the year ahead.

Smaller, purpose-driven models

Grant Shipley, Senior Director of AI at

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, predicts a shift away from valuing AI models by their sizeable parameter counts.

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“2025 will be the year when we stop using the number of parameters that models have as a metric to indicate the value of a model,” he said.  

Instead, AI will focus on specific applications. Developers will move towards chaining together smaller models in a manner akin to microservices in software development. This modular, task-based approach is likely to facilitate more efficient and bespoke applications suited to particular needs.

Open-source leading the way

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Bill Higgins, VP of watsonx Platform Engineering and Open Innovation at

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, expects open-source AI models will grow in popularity in 2025.

“Despite mounting pressure, many enterprises are still struggling to show measurable returns on their AI investments—and the high licensing fees of proprietary models is a major factor. In 2025, open-source AI solutions will emerge as a dominant force in closing this gap,” he explains.

Alongside the affordability of open-source AI models comes transparency and increased customisation potential, making them ideal for multi-cloud environments. With open-source models matching proprietary systems in power, they could offer a way for enterprises to move beyond experimentation and into scalability.

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This plays into a prediction from Nick Burling, SVP at

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, who believes that 2025 will usher in a more measured approach to AI investments. 

“Enterprises will focus on using AI strategically, ensuring that every AI initiative is justified by clear, measurable returns,” said Burling.

Cost efficiency and edge data management will become crucial, helping organisations optimise operations while keeping budgets in check.  

Augmenting human expertise

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For Jonathan Siddharth, CEO of

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, the standout feature of 2025 AI systems will be their ability to learn from human expertise at scale.

“The key advancement will come from teaching AI not just what to do, but how to approach problems with the logical reasoning that coding naturally cultivates,” he says.

Competitiveness, particularly in industries like finance and healthcare, will hinge on mastering this integration of human expertise with AI.  

Behavioural psychology will catch up

Understanding the interplay between human behaviour and AI systems is at the forefront of predictions for Niklas Mortensen, Chief Design Officer at

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“With so many examples of algorithmic bias leading to unwanted outputs – and humans being, well, humans – behavioural psychology will catch up to the AI train,” explained Mortensen.  

The solutions? Experimentation with ‘pause moments’ for human oversight and intentional balance between automation and human control in critical operations such as healthcare and transport.

Mortensen also believes personal AI assistants will finally prove their worth by meeting their long-touted potential in organising our lives efficiently and intuitively.

Bridge between physical and digital worlds

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Andy Wilson, Senior Director at

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, envisions AI becoming an indispensable part of our daily lives.

“AI will evolve from being a helpful tool to becoming an integral part of daily life and work – offering innovative ways to connect, create, and collaborate,” Wilson says.  

Mobile devices and wearables will be at the forefront of this transformation, delivering seamless AI-driven experiences.

However, Wilson warns of new questions on boundaries between personal and workplace data, spurred by such integrations.

Driving sustainability goals 

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With 2030 sustainability targets looming over companies, Kendra DeKeyrel, VP ESG & Asset Management at IBM, highlights how AI can help fill the gap.

DeKeyrel calls on organisations to adopt AI-powered technologies for managing energy consumption, lifecycle performance, and data centre strain.

“These capabilities can ultimately help progress sustainability goals overall,” she explains.

Unlocking computational power and inference

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James Ingram, VP Technology at

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, foresees a shift in computational requirements as AI scales to handle increasingly complex problems.

“The focus will move from pre-training to inference compute,” he said, highlighting the importance of real-time reasoning capabilities.

Expanding context windows will also significantly enhance how AI retains and processes information, likely surpassing human efficiency in certain domains.

Rise of agentic AI and unified data foundations

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According to Dominic Wellington, Enterprise Architect at

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, “Agentic AI marks a more flexible and creative era for AI in 2025.”

However, such systems require robust data integration because siloed information risks undermining their reliability.

Wellington anticipates that 2025 will witness advanced solutions for improving data hygiene, integrity, and lineage—all vital for enabling agentic AI to thrive.  

From hype to reality

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Jason Schern, Field CTO of

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, predicts that 2025 will be remembered as the year when truly transformative, validated generative AI solutions emerge.

“Through the fog of AI for AI’s sake noise, singular examples of truly transformative embedding of Gen AI into actual workflows will stand out,” predicts Schern.  

These domain-specific AI agents will revolutionise industrial workflows by offering tailored decision-making. Schern cited an example in which AI slashed time-consuming root cause analyses from months to mere minutes.

Deepfakes and crisis of trust

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Sophisticated generative AI threatens the authenticity of images, videos, and information, warns Siggi Stefnisson, Cyber Safety CTO at

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“Even experts may not be able to tell what’s authentic,” warns Stefnisson.

Combating this crisis requires robust digital credentials for verifying authenticity and promoting trust in increasingly blurred digital realities.

2025: Foundational shifts in the AI landscape

As multiple predictions converge, it’s clear that foundational shifts are on the horizon.

The experts that contributed to this year’s industry predictions highlight smarter applications, stronger integration with human expertise, closer alignment with sustainability goals, and heightened security. However, many also foresee significant ethical challenges.

2025 represents a crucial year: a transition from the initial excitement of AI proliferation to mature and measured adoption that promises value and a more nuanced understanding of its impact.

See also:

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