In the continuous interplay of innovation and technology, Artificial Intelligence (AI) has emerged as a game-changer in many industries. An opinion, however, has been growing concerning its role in software development. While some consider AI an all-solving panacea, experts argue that its effectiveness is not absolute.

The belief in AI's unbounded potential has fueled expectations such as making developers multiply their productivity. However, as it stands, the tech sector struggles to establish a uniform metric to measure engineering productivity. The absence of quantitative data leaves us with only anecdotal evidence to support AI's impact, leading to subjective and contrasting opinions.

While the AI buzz has created a sense of apprehension because of its unquantified impact on quality, and risks like potential plagiarism, tech-driven companies are harnessing AI for its transformative potential. Companies that manage to leverage AI successfully can rapidly streamline processes, improving productivity and delivering products to market more quickly and cost-effectively.

Interestingly, a recent GitHub report revealed that developers regard AI coding tools as beneficial for improving their coding language skills and automating repetitive tasks. Another example showed ChatGPT's effectiveness in writing simple tests for trivial functions and straightforward code paths.

In conclusion, while the merits of AI in software development are undeniable, it is not the ultimate solution. It could potentially multiply an engineering team's output, but only if applied and fine-tuned properly. Even though AI-driven development is still in its nascent stage, companies that exploit this technology efficiently will likely reap benefits in the longer run. However, over-reliance without understanding its limitations could be a risky gamble.