2025 is poised to be a pivotal year for technological advancement, with Artificial Intelligence (AI) poised to revolutionize industries across the globe further. Leading industry experts offer their insights into the key trends shaping the technological landscape:
The Rise of Agentic AI and Sophisticated Models
Joe Dunleavy, Global SVP & Head of AI Pod at Endava, envisions a future where Agentic AI takes center stage. “We are moving beyond passive AI systems,” Dunleavy explains, “towards AI agents that can act autonomously, learn from their environment, and adapt to changing circumstances.” This transformative shift will be particularly impactful in heavily regulated sectors such as healthcare, finance, and energy, where transparency and compliance are paramount.
“Imagine AI systems that not only automate tasks but also proactively identify and address potential issues, all while adhering to strict regulatory guidelines,” Dunleavy envisions. “This level of autonomy will revolutionize how businesses operate and interact with their customers.”
Stefan Leichenauer, VP Engineering at SandboxAQ, highlights the emergence of Large Quantitative Models (LQMs) as a significant leap forward in AI capabilities. “Unlike traditional language models that primarily process text,” Leichenauer explains, “LQMs are designed to excel in handling vast amounts of quantitative data. This empowers them to tackle complex challenges in fields like drug discovery, materials science, and financial modeling, delivering unprecedented levels of precision and data-driven insights.”
Leichenauer emphasizes that the success of these advanced models hinges on robust AI infrastructure, including high-performance computing, optimized energy management, and dedicated data centers. “Investing in cutting-edge infrastructure is not just an option, it’s necessary for organizations that want to remain competitive in the AI-powered future,” he asserts.
A More Discerning Approach to AI Investment
Omar Akar, Regional VP for META & CEE at Pure Storage, anticipates a shift in AI investment strategies in 2025. “The initial wave of AI enthusiasm has given way to a more pragmatic approach,” Akar observes. “Companies are now focusing on demonstrating tangible ROI from their AI investments.” Akar predicts a decline in investment for non-customized AI solutions, as organizations increasingly demand a return on their investments.
To achieve this, Akar believes Retrieval Augmented Generation (RAG) will gain prominence as a standardized approach for implementing AI. “RAG enhances the performance of AI models by retrieving relevant information from external knowledge sources,” Akar explains. “This not only improves the accuracy and reliability of AI-generated outputs but also mitigates the risk of ‘hallucinations’ – instances where AI models generate incorrect or misleading information.” By incorporating RAG, organizations can tailor AI solutions more effectively to specific business needs, ensuring a higher likelihood of successful implementation and achieving desired outcomes.
Data Quality and Governance: Cornerstones of AI Success
Cathy Mauzaize, President of Europe, Middle East and Africa (EMEA) at ServiceNow, emphasizes the critical role of high-quality data in driving successful AI initiatives. “Many AI projects, she points out, “falter due to inadequate data quality, hindering the model’s ability to learn and make accurate predictions.” Mauzaize advocates for a shift in focus from merely demonstrating the feasibility of AI (proof-of-concept) to proving its real-world value (proof-of-value). “This necessitates a focus on addressing genuine business challenges with real-world data,” she asserts, “ensuring that AI solutions deliver tangible benefits and drive meaningful business outcomes.”
Furthermore, Mauzaize stresses the importance of transparency and responsible data governance. “As AI systems become increasingly integrated into business operations,” she explains, “it is crucial to ensure ethical data practices, maintain transparency in how data is collected, used, and protected, and comply with relevant regulations.” Building trust with customers, partners, and employees hinges on demonstrating responsible AI practices and safeguarding data privacy. “Organizations that prioritize data ethics and transparency will not only build stronger relationships with their stakeholders but also gain a competitive advantage in the long run,” Mauzaize concludes.
Cathy Mauzaize also highlights the growing importance of CEO-level engagement in AI governance. “As AI technologies become more sophisticated and integrated into critical business functions,” she asserts, “the potential risks associated with algorithmic bias, data misuse, and reputational damage demand direct attention from the C-suite.” Effective AI governance, she argues, is not merely a technical concern but a strategic imperative. “By actively engaging in AI governance,” she explains, “CEOs can ensure that AI initiatives align with broader business objectives, mitigate potential risks, and unlock the full potential of AI while upholding ethical standards.”
Democratizing AI: The Rise of Citizen Development
Dinesh Varadharajan, Chief Product Officer at Kissflow, predicts a significant rise in citizen development in 2025. “The convergence of Low-Code/No-Code (LCNC) platforms with Generative AI is creating a powerful synergy,” Varadharajan explains. “This empowers business users with limited coding experience to build and deploy powerful applications, driving greater agility and efficiency within organizations.” By leveraging the intuitive interfaces of LCNC platforms and the creative capabilities of Generative AI, business users will be able to translate their domain expertise into innovative solutions, fostering a more democratized and agile approach to application development.
Personalization and Immersive Experiences
Dinesh Varadharajan also foresees a continued emphasis on personalization in user experiences. “Natural Language Interfaces (NLIs), voice recognition, and multi-modal interactions will become increasingly prevalent,” he predicts, “enabling users to interact with applications more naturally and intuitively.”
Composable UI components will further enhance personalization, allowing applications to dynamically adapt to individual user needs and preferences. “By leveraging design systems and micro-frontends,” Varadharajan explains, “organizations can create customized user interfaces that cater to specific user contexts, enhancing user satisfaction and engagement.”
Sustainability and Ethical Considerations
Adrian Hobbs, Chief Technology Officer at Core42, emphasizes the growing importance of sustainability and ethical considerations in the development and deployment of AI technologies. “As climate change becomes a more pressing global concern,” Hobbs observes, “the need for energy-efficient and environmentally friendly AI solutions will become increasingly critical.”
Hobbs also highlights the importance of ethical AI development, ensuring that AI systems are used responsibly and do not perpetuate or exacerbate existing biases or inequalities. “Developing and deploying AI responsibly is not just an ethical imperative,” Hobbs concludes, “it is also a business imperative. Organizations that prioritize ethical AI practices will build stronger relationships with their stakeholders and gain a competitive advantage in the long run.”
These predictions from leading industry experts paint a dynamic and exciting picture of the technological landscape in 2025. AI is poised to play a pivotal role in driving innovation, transforming industries, and shaping the future of work. As these technologies evolve, organizations must embrace responsible AI practices, prioritize data quality and governance, and foster a culture of innovation and continuous learning to realize the transformative potential of AI fully.
