Colombia. The discussion about artificial intelligence is no longer theoretical in Colombia. With the adoption of CONPES 4144 of 2025, the country defined clear guidelines for the development, use, and governance of AI, marking a turning point for its incorporation into the public and private sectors.
In this context, as organizations advance in the maturity of their analytical capabilities, a new conversation is beginning to gain relevance at strategic levels: the convergence between artificial intelligence and quantum computing.
Quantum computing is not a faster version of traditional computing or a technology designed to replace, in the short term, the current infrastructure. It is based on principles of quantum mechanics (such as superposition and entanglement) that allow multiple solutions to be explored simultaneously. This opens up the possibility of addressing problems that are currently complex due to cost, time, or computational complexity, especially when combined with advanced analytics and AI.
What does this mean for businesses?
Globally, quantum computing is still in an early phase of development, known as NISQ, with technical limitations that prevent immediate mass adoption. For this reason, the real impact for companies is not in "migrating to quantum", but in preparing for a hybrid model, where classical computing, advanced analytics, AI and, progressively, quantum computing, play complementary roles.
According to SAS, the first use cases with business sense are concentrated in scenarios where traditional methods are beginning to show clear limits, particularly in:
● Complex optimization, such as logistics, routing, planning, and resource allocation, when the search space is highly combinatorial
● Financial modeling and risk management, in increasingly interconnected and volatile markets.
● Advanced simulation, especially in chemistry, materials, and drug discovery, where modeling interactions at the molecular level exceeds the capabilities of classical systems.
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Agentic AI today, quantum architecture tomorrow
At the same time, artificial intelligence is going through its own stage of maturity. The so-called agentic AI systems (capable of acting, deciding and adapting autonomously) are moving from pilots to core business processes. By 2026, this type of AI will be consolidated in operations, customer experience, and risk management, raising the demands on technological infrastructure and computing capacity.
For the company, it is at this point that the concept of "quantum architecture" begins to gain strength: not only quantum hardware, but the set of layers that make it viable for the business (software, applications, integration with classic systems, data governance and specialized talent) and that will allow real value to be captured as technology advances towards practical applications.
The risks that accompany the technological leap
Like any general-purpose technology, the convergence between AI and quantum computing introduces risks that must be anticipated in advance. The most visible risk is in information security, since in the future quantum computing could jeopardize the encryption systems that today protect data, transactions and communications, forcing organizations to start preparing for new digital security standards.
SAS sees a less technical but equally relevant challenge: disorderly adoption, driven by expectations rather than strategy. Recent experience with generative AI has left a clear lesson: competitive advantage does not come from adopting first, but from adopting with focus, governance, and clear value metrics.
The challenge for organizations in Colombia
In a country that is making progress in the discussion of guidelines for the development and responsible use of AI, and that is beginning to open spaces for emerging technologies from public policy, the business challenge is to take the next step with criteria. Preparing for the convergence between AI and quantum computing means strengthening the existing foundation: talent, data quality and governance, and the ability to translate analytics into real operational decisions.
Rather than a sudden disruption, the quantum leap will be a gradual process. Organizations that understand now how this evolution connects to the AI they are already deploying will be better positioned to turn that transition into a sustainable competitive advantage.
Analysis published by the analytics company SAS.
