Financial sector shows caution in using AI for code generation due to high operational risks

Despite the undeniable influence of artificial intelligence (AI) on modern society, there remains a sharp debate over whether its overall impact is positive or negative. Just a year or two ago, the internet was flooded with AI-generated images that quickly entered corporate advertising. Soon after, social media platforms like YouTube were filled with AI-generated thumbnails—visuals that initially attracted viewer interest but now increasingly cause audience fatigue and skepticism.

However, outside of consumer social media feeds, artificial intelligence holds significant potential to transform corporate operations, provided it is implemented strategically. In an exclusive interview with IOL, Paul Banting, co-founder of growthguru.ai, analyzed the common narrative that AI has become an overrated tool that does not deliver expected productivity growth.

Banting stated that the problem is not that AI is overrated, but that it is being judged against the wrong promise. He emphasized that productivity gains are real and supported by research. According to a McKinsey survey on AI adoption in corporations, 80% of respondents noted improved individual productivity, yet only 37% claimed that AI directly contributed to increased profit for their organization—a metric that has remained virtually unchanged over the past year.

Therefore, in Banting's view, it is more accurate to say that AI is not overrated, but fundamentally misunderstood. Leaders mistakenly assume that saved time automatically translates into revenue growth. In reality, companies must actively direct the hours freed up by AI toward achieving tangible, high-return commercial opportunities.

While most public attention naturally focuses on optimizing outdated workflows, Banting warns that task efficiency should not become the primary goal of the enterprise. Around 79% of executives expect AI to drive substantial revenue growth by 2030, compared to 40% today. Nevertheless, only 24% have a clear idea of where this future revenue will originate. The true objective, Banting explained, is using AI to identify urgent commercial gaps and capture high-value market opportunities ahead of competitors.

The Growthguru.ai platform was developed precisely to bridge this strategic gap, focusing on business development rather than general workflow automation. Instead of offering a single universal assistant, their platform utilizes specialized AI agents targeting specific commercial levers: Perky helps partners access relevant incentives, discounts, and co-financing from suppliers; Maya develops go-to-market strategies and co-marketing initiatives; Alex guides partners through certifications and supplier tiers; and Lexi tracks important enterprise updates, such as critical Microsoft platform releases.

Nevertheless, alongside the commercial potential lies a darker side—AI-enabled crime, where issues of accountability and legal liability remain unresolved. Banting argues that criminals using AI for financial fraud must be held responsible for their actions, regardless of the tools they employ. However, if proprietary or third-party enterprise AI causes operational or financial damage, the responsibility lies directly with the business that implemented it. Legal liability cannot simply be shifted to the model provider. While software developers must create secure and compliant architectures, the choice of implementation rests entirely with the enterprise. BCG confirmed this finding in its applied AI benchmark.

Trading session concluded with gains on Wall Street: the Dow Jones Industrial Average increased by 1.02%, and the expanded S&P 500 showed a rise of 0.29%, while the technology-focused Nasdaq remained unchanged, declining by 0.02%.

Patrick O'Hare from Briefing.com told AFP that many stocks outside the technology sector performed relatively well due to falling oil prices and the rotation of investment flows.

Investors are showing greater interest in more 'traditional' sectors, such as industrials, pharmaceutical laboratories, and major banks, while companies related to artificial intelligence (AI) are losing appeal.

According to O'Hare, a positive factor is that the liquidity generated from selling AI stocks remains invested on Wall Street, which prevents a mass exit from the market. He emphasized that the market continues to be in an uptrend.

Optimism is supported by company results. The defense sector closed higher after several companies reported earnings that exceeded expectations, such as RTX (+0.64%) and Northrop Grumman (+4.57%).

The drop in oil prices, linked to hopes for renewed dialogue between the US and Iran, allows companies to anticipate less pressure on costs.

Regarding AI, O'Hare noted that upcoming earnings reports from major players are accompanied by some nervousness due to fears that growth rates may prove less sustainable than forecast. He reminded that a significant part of investor expectations is based on a very high growth rate, which justifies high valuation levels and huge AI development costs, and disappointment in these expectations could lead to stock price declines, as has already been observed.