Eric Sydell, the Chief Executive Officer of Vero AI, has shared insights on the future of artificial intelligence (AI) as organisations navigate the practical challenges of deploying AI at scale.
As the initial excitement surrounding generative AI gives way to more practical considerations, organisations are recognising the need to scale AI tools efficiently by integrating them within enterprise workflows. "Restructuring workflows to enhance rather than replace human workers, leveraging robust evaluation tools to assess AI's effectiveness, and using scientific methods to measure AI systems at scale" are vital approaches, said Sydell, looking towards 2025.
The next phase in AI development is projected to evolve through the enhancement of foundational models with specialised capabilities. The industry anticipates a shift towards models becoming more context-aware and tailored to specific sectors. "Expect genAI to become more context-aware, customized, and deeply integrated into industry workflows," Sydell predicts, "transforming advanced machine learning from a technological marvel into a practical, indispensable tool that enhances human potential across sectors."
Technological advancements termed "cognitive architectures" are set to simulate the impact that cloud computing had on making technology accessible. These scalable tools will enhance the capabilities of generative AI models in specific, practical ways, potentially eliminating hefty costs for businesses. Sydell explains, "Creative approaches to scaled genAI level the playing field, empowering small and midsize companies to innovate and strategize effectively, matching the efficiency of larger competitors."
There is also a forecasted increase in autonomous AI systems, or "agentic AI," which marry generative AI and traditional coding to autonomously complete tasks. "In 2025, we can expect this trend to accelerate, as autonomous agents become more capable and integrated into business processes," states Sydell. However, with growing autonomy in AI systems comes an increased need for oversight to mitigate potential risks to privacy and security.
Eric Sydell stresses the importance of AI literacy within organisations to seize competitive advantages. As AI becomes embedded in work processes, disparities are expected to widen, favouring businesses that harness these tools effectively. "This shift will create a rising demand for AI literacy and upskilling programs," he points out, predicting a realignment in workforce skills focused on managing and overseeing AI systems.
The regulatory environment for AI, especially in the US, is anticipated to evolve with a new political administration. The focus will be on fostering innovation without hindering technological progress, all while prioritising issues of trust and accountability. "We may see frameworks that penalize tech companies for censoring content, especially in cases of misinformation," says Sydell, acknowledging ongoing debates over free speech and content moderation. Organisations will need to emphasise responsible AI practices to maintain trust and address legal and ethical challenges posed by large language models (LLMs).
