The Boston Consulting Group (BCG) estimates that artificial intelligence (AI) could generate about $340 billion in additional annual profit for the banking industry by 2030. This figure was presented by László Juhász, managing director and senior partner at Boston Consulting Group, during his talk at the Portfolio Hitelezés 2026 conference. Juhász stressed that the real success factor is not the technology alone but the human side: he argued that 70% of success depends on people.
What banks can expect
According to the BCG executive, AI can have a notable impact on bank operations through autonomous, real-time solutions that carry significant cost-reduction potential. In lending, improvements are possible across targeting, product development and credit decisioning with AI support. As a practical consequence, processes that once took weeks could shrink to days, and in some international examples decisions on mortgage applications have been reached within hours, particularly thanks to streamlined documentation and automation.
Hype versus economic reality
Juhász urged caution regarding the hype around AI: the technology is evolving rapidly, with new developments appearing daily, and the long-term shape of the field remains hard to predict. He noted that despite the large potential, relatively few companies have so far monetized AI: at the end of last year roughly 14% of firms actually generated revenue from AI applications.
Costs, profit distribution and prompt engineering
The speaker reminded the audience that new technologies often introduce new types of costs, which must be assessed on a net basis when judging ultimate outcomes. A key open question is who will capture the AI-driven profit—whether banks will retain the gains or pass some on to customers, for example through lower fees.
Juhász also emphasized the importance of proper prompt engineering; correctly steering AI systems is essential to achieve reliable performance.
Focus and people development
The BCG leader recommended that banks concentrate on a few high-impact areas—so-called “Big Wins”—rather than dispersing attention and resources. He outlined a rough success breakdown: algorithms contribute about 10%, data about 20%, and the human element about 70%, which makes targeted, role-specific staff training on AI tools indispensable.
Juhász envisions a future composed of collaborative networks of people and AI agents: humans will carry strategic decision-making and create added value while AI provides substantial operational support. Organizations should therefore focus on tasks where they have comparative advantage and invest in focused upskilling accordingly.
Conclusion
BCG’s projection and Juhász László’s remarks suggest that AI adoption in banking can bring significant profit increases and faster processes, but the ultimate results will hinge largely on human capabilities and strategic focus. Banks need to prepare both technologically and through targeted employee development.
