2025 Predictions for Generative AI
Thinkers360 2025 Predictions for Generative AI are member-sourced from our opt-in B2B thought leader, analyst and influencer community with 100M+ followers on social media combined. The 2025 Predictions for Generative AI are part of a series to provide actionable insights for business and technology executives.
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We asked a selection of our Thinkers360 global thought leaders, analysts and influencers about their predictions for Generative AI in 2025. We heard that as AI becomes more agentic, orchestration layers will increasingly be needed to act as an intermediary, querying the right data sources, verifying access permissions, and converting jargon-laden data into actionable information. The emergence of specialized large models, large action models, and liquid foundation models will reflect a broader trend toward more adaptable and efficient AI solutions. In addition, more AI agents performing as semi-autonomous Gen AI programs will become embedded in applications to interact with unstructured data. AI deployments will also become more human-centric, recognizing that AI without human insight and collaboration can’t deliver real value.
We also heard that as we push into 2025, AI (gen AI) will be used to both enable and improve cybersecurity and personal privacy but also be used as a weapon for hacking, intrusions, fraud, identity theft, and threats. Ethical AI will be paramount—focused on fairness, transparency, privacy and integrity to build systems people can rely on. Increasing attention will also be paid to ensure Gen AI meets environmental regulations. As organizations deal with additional legislation, such as the EU AI Act and the resulting compliance checks, governance audits and the first enforcements, we may see a slowdown in deployment.
We see these predictions as positive signs that Gen AI is becoming more productive and industrialized for enterprise deployments and is moving into the next phase of its maturity and the technology adoption lifecycle. One of our takeaways is that in 2025, enterprises should look beyond LLM expertise and start thinking more holistically about how agentic AI can transform their enterprise business processes and the set of human skills and toolsets they need to enlist to make this happen.
For the full details of each thought leader, analyst and influencer prediction, please read on to hear what they told us about their predictions for generative AI in 2025:
What are your Predictions for Generative AI in 2025?
In 2025, AI will become more agentic, moving beyond mere idea generation to actively drive business performance through action. It will also be more human-centric, recognizing that AI without human insight and collaboration can’t deliver real value. And as trust becomes the new currency in a world saturated with fakes, ethical AI will be paramount—focused on fairness, transparency, privacy and integrity to build systems people can rely on.
– Pascal BORNET, Intelligent Automation
In the realm of human-AI interaction, Generative Intelligence will excel at solving complex, real-world problems that demand significant flexibility and adaptability. This is especially crucial for AGI, as it will be capable of performing a broad range of tasks, learning from the human brain, and applying its knowledge to new situations, all while adhering to ethical principles and regulatory frameworks.
– Fatima Roumate, (PhD) President of the International Institute of Scientific Research (IISR) and Founder of the Global Network on AI and International Society GNAI&IS
In the past two years, large language models (LLMs) have revolutionized the AI landscape, showcasing their remarkable capabilities in understanding and generating human-like text. Their versatility has led to widespread adoption across industries, powering applications from chatbots to content creation. This rapid innovation cycle has not only highlighted the potential of LLMs but also paved the way for the emergence of next-generation language models tailored to specific needs and contexts.
The Rise of Specialized Language Models. As organizations seek to leverage AI for more targeted applications, specialized language models are gaining traction. These models come in various sizes—small, medium, and large—each designed to meet the specific demands of different industries and domains. For example, a small model might be optimized for customer support interactions, while a large model could be tailored for complex legal document analysis. This specialization allows businesses to harness the power of AI in ways that are most relevant to their operations, enhancing efficiency and effectiveness.
Large Action Models: Bridging the Gap. Another significant part of this trend is the development of large action models that go beyond mere text generation. These models are designed to understand and execute complex tasks, integrating various forms of input and output. This capability not only improves user experience but also enables businesses to automate workflows and make data-driven decisions more effectively. As large action models become more sophisticated, their applications will expand into areas such as process automation, decision support, and predictive analytics.
Liquid Foundation Models: The Future of Continuous Learning. One of the most exciting advancements on the horizon is the concept of liquid foundation models (LFMs). These models aim to minimize the need for extensive pretraining and enable continuous improvement without the traditional retraining processes. By leveraging a dynamic approach to learning, LFMs can adapt to new data and changing environments in real-time, making them highly responsive to the evolving needs of users. This shift represents a significant departure from the static nature of current LLMs, paving the way for more resilient and adaptable AI systems. As we move beyond traditional LLMs, the future of AI is set to be defined by specialization, action-oriented capabilities, and continuous learning.
The emergence of specialized LMs, large action models, and liquid foundation models reflects a broader trend toward more adaptable and efficient AI solutions. By embracing these innovations, organizations can unlock new possibilities for automation, decision-making, and customer engagement, ultimately transforming their operations in the process. The next phase of AI development promises to be as transformative as the last, as we explore the full potential of these next-generation models.
– Michael Fauscette, CEO & Chief Analyst at Arion Research LLC
In 2025, AI will transition from a “cool tool” to a “clever colleague”, and will bring a new set of complexities, compromises, and casualties with it. Specifically, I see 3 shifts in 2025:
1. EU AI Act will force organisations to slow down, while they invest time and resources in compliance and governance. As organisations deal with additional compliance checks, governance audits and the first enforcements, we will see a slowdown in deployment. This will give large organisations with deep pockets, an opportunity to build a defense mechanisms against the more agile movers. Expect some high-profile fines to serve as warning shots across the industry.
2. LLM Orchestration Layer: As use cases go from customer support (outward facing) to more strategic planning (CxO and Board facing), there will be a demand from AI agents to pull data from multiple, enterprise resource planning (ERP) systems and synthesize it into meaningful insights. This orchestration layer will act as an intermediary, querying the right data sources, verifying access permissions, and converting jargon-laden data into actionable information. A new market for customisable orchestration solutions will emerge.
3. AI-Fraud Drives Culture Change: In 2025, we’re likely to see a correlation emerge between workplace culture and fraud resilience. Businesses with strong hierarchical divides or a high power-distance index (PDI) will be particularly vulnerable, as employees feel too intimidated to flag dubious directives. AI-enabled fraud will continue to rise, and defending systems will not keep pace. Employee security awareness will become critical. Awareness is one part of the equation, business culture of psychological safety will have to complete the equation.
– Aarti Samani, Shreem Growth Partners
Advanced-level prompt engineering will become necessary to produce unbiased results for Gen AI Applications. More AI Agents performing as semi-autonomous Gen AI programs will be embedded in applications to interact with unstructured data. The environmental impact of Gen AI will become more noticeable, and federal and State governments will adopt environmental policies to ensure Gen AI meets environmental regulations. The use of Gen AI applications at the high school and college level will become more prevalent causing schools and school districts to develop and enforce more stringent Gen AI use policies.
– Tony Rhem, A.J. Rhem & Associates, Inc.
Privacy and Cybersecurity Battle Picks up due to Gen AI
As we push into 2025, AI (gen AI) will be used to both enable and improve cybersecurity (including networks) and personal privacy but also be used as a weapon for hacking, intrusions, fraud, identity theft, and threats.
– Stephanie Atkinson, Compass Intelligence, LLC
We will see the rise of AI agents in businesses to take over more complex tasks within and across departments. Leaders need to manage this shift as humans increasingly rely on AI.
– Andreas Welsch, Intelligence Briefing
To see the full set of predictions in the Thinkers360 Predictions Series, please visit our Predictions page. Have comments on these predictions, or predictions of your own? Please join the community at Thinkers360.com and follow us on LinkedIn, X and YouTube to share your insights!
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