In the ever-evolving landscape of modern business, artificial intelligence (AI) has transitioned from being a mere assistant to an indispensable employee that cannot be dismissed. The speed and efficiency that AI offers are now critical to success, yet many companies still cling to outdated practices, unaware of the profound changes AI has brought to intellectual labor. Some mistakenly view AI as just an alternative to Wikipedia or Google, overlooking its transformative potential, which can lead to resource wastage and a significant competitive disadvantage.
Valentin Vasilievsky, co-founder of Business Booster, discusses how white-collar workers can adapt to this new reality. Just a year ago, AI capabilities were limited, but the emergence of advanced reasoning models and tools like Deep Research has resulted in a game-changing breakthrough. Nowadays, executing intellectual tasks effectively without neural networks is nearly impossible. The focus has shifted from mere automation to investing in AI tools and training teams to harness them intensively.
The capabilities of modern neural networks are astonishing. For instance, Deep Research can analyze hundreds of sources in mere minutes, providing detailed comparisons of global brands that would have previously taken weeks and cost thousands of dollars in analyst fees.
A strategic marketing director at Business Booster faced the daunting task of analyzing extensive transcriptions from JTBD interviews with clients to identify target audience needs and validate segmentation hypotheses. Previously, this manual process consumed weeks, and the quality of analysis suffered due to the sheer volume of data and human error. However, with the use of Gemini 2.5 Pro, the landscape changed dramatically. After uploading the transcriptions and a framework for defining customer avatars, the AI provided analyzed information, structured data, and clear conclusions within minutes, marking a significant leap in analytical capability.
While the latest GPT-5 has been released, Gemini 2.5 Pro remains the preferred choice for data processing and analytics due to its exceptional performance in handling large documents with a million-token context window, ensuring accurate and unaltered results.
AI is also reshaping approaches to legal challenges, particularly in unfamiliar jurisdictions. When opening a company in Cyprus, a question arose regarding the signing of a contract by the director. A standard inquiry to ChatGPT failed to yield a comprehensive answer, while consulting an in-house lawyer could delay the process by a week as the specialist researched traditionally. The solution came through Gemini Deep Research, which effectively analyzed corporate documents and Cyprus regulations, delivering precise, justified responses in mere minutes—far quicker and more reliable than a human without specialized expertise.
The introduction of prompts for legal analysis has streamlined the resolution of slow legal inquiries, such as refunds and contract clarifications. This innovation reduces response times from hours to just 10 minutes, transforming lawyers from mere "analysts" into proactive "controllers."
Global trends further support the integration of AI into operational processes. For example, Walmart has launched an internal AI assistant designed to handle routine tasks, summarize documents, and draft client materials. This initiative is not a one-off experiment but part of a broader program to embed AI into daily operations, significantly enhancing productivity for teams in both stores and offices.
Another notable example comes from Microsoft, which, in the summer of 2025, solidified its AI-first strategy during its 50th anniversary celebrations. The focus is no longer just on implementing AI as a tool but on developing true AI agents. Whereas neural networks once only responded to simple commands like "write me a letter," they now perform complex multi-step tasks as if they were employees. Microsoft 365 Copilot can generate sales reports by autonomously gathering data from various applications, compiling reports, and creating task lists for teams.
The fundamental shift in mindset is that tasks previously assigned to lawyers, analysts, and other specialists are now primarily directed toward AI. Humans are tasked with overseeing, refining results, and utilizing the data for more complex insights. Mastering AI tools is crucial, requiring skills in prompt formulation, contextual provision, and tool operation. For example, Google’s NotebookLM serves as a personal research assistant that can analyze various uploaded sources, allowing users to ask questions, summarize information, find connections, or even generate new ideas based on collected data. Another tool, Gemini AI Studio, offers a flexible environment for creating and testing AI models.
Without the skills to leverage these and other tools, even the most powerful AI systems cannot fully realize their potential. Those who master neural networks become "cyborgs," or more competent, capable, and agile professionals. The speed at which AI operates, combined with a human equipped with these technologies, far surpasses outdated methods of information gathering and approval.
The world has irrevocably changed. Routine intellectual tasks that require little significant creativity are now primarily handled by AI, reshaping the workforce and creating new dynamics in the market. As companies increasingly adopt these technologies, those that fail to adapt may find themselves left behind in this new era of AI-driven productivity.
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