Get Ready for the Quantum AI Age
Today's digital transformation strategies are influenced by advancements in cloud computing, automation, big data, and machine learning. Quantum AI offers even greater potential to address processing complexities and scalability challenges efficiently.
Puneet Agarwal, Partner at CLA Global Indus Value Consulting, examines the evolving landscape of quantum computers and the role that qubits will play in this shift in computational power.
AI experts believe 2025 will mark a major advancement in scalable quantum computing. Quantum AI, merging quantum computing with AI, offers the potential to enhance forecasting and reporting accuracy beyond current limits. This shift could impact everything from cybersecurity and encryption standards, to supporting faster product developments and even quicker taxation computations.
Testament to the progress, this February Microsoft presented the world’s first topological quantum processor. During the launch they described Majorana 1 as a breakthrough type of material which can observe and control Majorana particles to produce more reliable and scalable qubits, which are the building blocks for quantum computers.
This is mind-blowing progress that the hyperscalers have been working on for years. Although the potential for breakthrough innovation is immense, practical integration of quantum computing into financial services is likely to unfold over several phases and decades. Currently, it is already proving useful in risk modeling or in applications that requires ultra-fast processing of large, complex datasets.
Quantum AI in the real world
Generative AI has already altered our interactions with digital content. However, even here it continues to function within the limits of classical computing power.
Areas where significant Quantum AI developments are occurring include:
- Enhanced machine learning – supporting face/image recognition, predictive analysis, and quicker emergency and surveillance responses.
- Advanced optimization capabilities – detecting faults in systems and mitigating errors in industrial, logistics, healthcare, finance, and supply chain planning applications.
- Superior computational power – using qubits and quantum algorithms to analyze complex relationships and patterns in data from multiple sources simultaneously to solve problems faster and more accurately.
To reach the scale that is required to truly solve world problems, for example addressing the environmental challenges of microplastics or accelerating medical drug advances, further research into these hybrid technologies is needed states a report released in April 2025 by the Quantum Economic Development Consortium (https://quantumconsortium.org/publication/quantum-computing-and-artificial-intelligence-use-cases/).
"At this early stage, industry, academia and governments must collaborate to make the most of this opportunity," said QED-C executive director Celia Merzbacher on release of the report. QED-C also emphasized applying lessons from AI's rapid adoption, including ensuring standardized benchmarks, transparency, and privacy protections are considered as quantum computing and AI converge.
Nevertheless, the potential for hybrid Quantum AI systems remains very exciting. Being able to more accurately predict extreme weather events, optimize smart energy grids, revolutionize logistics and supply chain planning or making faster drug discoveries all require extreme simulation and predictive capabilities. These advances can only be realized by combining the capabilities of quantum computing with the learning, prediction, and optimization strengths of AI.
Prepare for industrial usefulness
The Quantum Era is not a distant future — it is pulling into stations all over the world. For those working on it in the trenches it has been an evolution years in the making. What is more exciting is it is on the verge of tipping into widespread industrial usefulness.
Quantum AI is set to redefine the very fabric of technological capability and business strategy. Commercialized cases are already imminent. Preparation should not focus on the if, but when.
Already, 80% of global banks are engaging in it. With such reliance on data, security, and optimization, financial services stands to gain immensely. Its potential could stretch from portfolio optimization to using quantum models to predict market trends. It could also detect fraudulent activities or assist with derivative valuations.
Equally, it has the potential to cause major disruptions. For example, current encryption systems could be easily compromised by the power of quantum machines, exposing sensitive data to cyber threats. For this reason, financial institutions are advised to both strengthen current systems against threats and explore quantum's offensive capabilities.
Organizations must be prepared not just to adapt but to lead. Companies that ignore quantum computing, AI acceleration and global AI disruption will struggle to stay relevant, cautions Puneet Agarwal.
"Quantum AI is not just a technological advancement or a product launch — it represents a paradigm shift. As businesses and governments face increasingly complex challenges in data processing, optimization, and predictive analysis, Quantum AI offers a transformative solution that surpasses the limits of classical computing,” reports Punnet.
Organizations that take steps now — investing in research, building strategic partnerships, and preparing their teams for upcoming changes — will be well-positioned in the future. The shift towards the Quantum Era requires forward-thinking leadership. Adopting a strategic approach will be essential to harness its value. Understanding quantum advancements early on will help determine the potential benefits in the future.
For further information
Puneet Agarwal
Partner – Government and Public Sector Advisory (GPSA)
CLA Global Indus Value Consulting
https://www.linkedin.com/in/puneet-agarwal-91136518/
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